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International Journal
of
Learning, Teaching
And
Educational Research
p-ISSN:
1694-2493
e-ISSN:
1694-2116
IJLTER.ORG
Vol.21 No.12
International Journal of Learning, Teaching and Educational Research
(IJLTER)
Vol. 21, No. 12 (December 2022)
Print version: 1694-2493
Online version: 1694-2116
IJLTER
International Journal of Learning, Teaching and Educational Research (IJLTER)
Vol. 21, No. 12
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Foreword
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VOLUME 21 NUMBER 12 December 2022
Table of Contents
Acceptance of the GeoGebra Application in Learning Circle Theorems.........................................................................1
Nxumalo Mfanasibili Philemon, Admire Chibisa, Maria Siwela Mabusela
Exploring the Impact of Enquiry-Based Instructional Strategies on Students’ Attitudes towards Biology ............. 21
Henriette Manishimwe, William Aino Shivoga, Venuste Nsengimana
Challenges to and Enablers of Women's Advancement in Academic Careers at a Selected South African
University .............................................................................................................................................................................. 44
Ifeanyi Mbukanma, Kariena Strydom
Students' Perceptions and Challenges in Learning Business English: Understanding Students’ Needs and Job
Market Requirements........................................................................................................................................................... 65
Wael Alharbi
The Role of Writing Process Components and Cognitive Components in Improving the Quality of Narrative.....88
Lati Andriani, Syihabuddin ., Andoyo Sastromiharjo, Dadang Anshori
University Students’ Experiences of the Teaching and Learning of an Acupuncture Programme: A South African
Case Study ........................................................................................................................................................................... 107
Zijing Hu, Roy Venketsamy, Janice Pellow
On-the-Job Training in Vocational College: Issue and Improvement Plan.................................................................126
Suzila Othman, Mohd Azlan Mohammad Hussain, Rafeizah Mohd Zulkifli, Mohammad Sukri Saud
Students’ Time Management, Academic Procrastination, and Performance during Online Science and
Mathematics Classes........................................................................................................................................................... 142
John Paul E. Santos, Joseph A. Villarama, Joseph P. Adsuara, Jordan F. Gundran, Aileen G. De Guzman, Evelyn M. Ben
Review of Essential Amendments in Indian Higher Education with Special Reference to COVID-19 Pandemic
and National Education Policy (NEP) 2020..................................................................................................................... 162
Afzalur Rahman
Motivation in English Learning at University: A Mixed-Methods Study Investigating the Perceptions of Different
Stakeholders*....................................................................................................................................................................... 175
Diego Ortega-Auquilla, Paul Sigüenza-Garzón, Julio Chumbay, Esteban Heras
Beyond Educational Reforms: A Review of Teacher Preparation in Tanzania........................................................... 197
Nipael Mrutu, Hamisi Nkota, Jamila Kova, Esther Kibga, Peter Kajoro, Aladini Hoka, Fredrick Mtenzi
Distinguishing between Bilingualism and Dyslexia: Views of Secondary School Teachers in Greece ................... 218
Christina Biza, Aretousa Giannakou
Exploring Business Studies Teachers’ Technology Self-Efficacy on their Technology Integration to Create
Learner-Centred Teaching Environment......................................................................................................................... 238
Nduduzo Brian Gcabashe, Nokulunga Sithabile Ndlovu
Exploring Threats to Novice Teachers’ Development in Selected Secondary Schools in South Africa................... 259
Joseph Lesiba Makhananesa, Mmalefikane Sylvia Sepeng
Exploring English Language Proficiency, English Language Problems, and English Needs Among First Year
Undergraduate Students.................................................................................................................................................... 272
Bussayarat Nithideechaiwarachok, Ornpiya Maneekanon, Thirapong Bubphada
1
©Authors
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0
International License (CC BY-NC-ND 4.0).
International Journal of Learning, Teaching and Educational Research
Vol. 21, No. 12, pp. 1-20, December 2022
https://doi.org/10.26803/ijlter.21.12.1
Received Aug 29, 2022; Revised Nov 9, 2022; Accepted Dec 12, 2022
Acceptance of the GeoGebra Application in
Learning Circle Theorems
Nxumalo Mfanasibili Philemon
University of Zululand, Faculty of Education
Department of Mathematics, Science and Technology Education
Admire Chibisa
University of Zululand, Faculty of Education
Department of Mathematics, Science and Technology Education
Maria Siwela Mabusela
University of Zululand, Faculty of Education
Department of Mathematics, Science and Technology Education
Abstract. The learning area of circle theorems is one of the most difficult
topics in geometry, resulting in low student performance. GeoGebra has
been shown in studies to enhance learners' proficiency in circle theorems.
However, pre-service teachers' use of GeoGebra is not at the expected
level in Eswathini. The adoption of an information system is reliant on its
acceptance by individuals. However, little is known regarding pre-
service teachers' use of GeoGebra to understand circle theorems. The goal
of this study was to investigate pre-service teachers' perceptions of
GeoGebra's suitability for learning circle theorems. A cross-sectional
survey design was used in this investigation, with a total of 187 pre-
service instructors as participants. The model explained 74.9% of the
variance in the acceptability of GeoGebra for learning circle theorems by
Eswatini pre-service teachers. According to the findings, task-technology
fit, system quality, system compatibility, perceived ease of use, perceived
usefulness, perceived attitude toward, and user satisfaction account for
74.9% of the variance in actual use. The study's findings revealed that
rural Eswatini pre-service teachers' reported attitude toward using the
mathematics software application GeoGebra for learning circle theorems
was the strongest direct predictor of actual use. This research shows that
pre-service teachers' views toward technology integration in education
should be positive for educational learning applications to be successfully
adopted in Eswatini teacher training institutes.
Keywords: circle theorems; GeoGebra; pre-service teachers; task-
technology fit; technology acceptance model
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1. Introduction
Geometry, as a branch of mathematics, is critical in assisting mathematicians and
students of mathematics in appreciating and comprehending the space, shape,
and orientation of numerous bodies and objects in our universe (Jin et al., 2021).
Geometry includes circle theorems, which allow "mathematicians and students of
mathematics to grasp circular space, shape, and orientation in this world" (Badu-
Domfeh, 2020, p. 1). Circle theorems are regarded as one of the most difficult
sections of Geometry, resulting in poor student performance (Kwadwo &
Asomani, 2021). According to studies (Adolphus, 2011; Erdoğan et al., 2011;
Kwadwo & Asomani, 2021), the difficulty in teaching and learning Geometry,
particularly circle theorems, results in poor learners’ performance. For this reason,
studying circle theorems, particularly in teacher training institutions, need more
creative techniques that will improve pre-service teachers' circle theorems
comprehension and skills (Amevor & Bayaga, 2021; Kwadwo & Asomani, 2021;
Tay & Wonkyi, 2018). Some of these novel ways that are recognized to aid
learners' knowledge of circle theorems include the use of educational technology,
notably the incorporation of mathematics software into the teaching and learning
of circle theorems (Amevor & Bayaga, 2021; Kovács, 2018; Tay & Wonkyi, 2018).
GeoGebra is a popular mathematics application software in the teaching and
learning of circle theorems (Adhikari, 2021; Arbain & Shukor, 2015; Tay &
Wonkyi, 2018).
Studies have shown that GeoGebra software can improve learners’ performance
in circle theorems (Adhikari, 2021; Mushipe & Ogbonnaya, 2019; Pamungkas et
al., 2020; Tay & Wonkyi, 2018; Tran & Nguyen, 2020). However, the adoption of
GeoGebra is lower than expected (Ganesan & Eu, 2020; Mutambara & Bayaga,
2020c; Nwoke & Chidi, 2020). According to Padmanathan and Jogulu (2018), the
proper deployment and use of an information system are dependent on
individuals’ acceptance.
Mutambara and Bayaga (2020c) stated in an educational context that learners' use
of educational technologies is dependent on their acceptance of these
technologies. According to the findings of Padmanathan and Jogulu (2018) and
Mutambara and Bayaga (2020c), one can conclude that the successful adoption of
GeoGebra by pre-service teachers is contingent on their acceptance of it. However,
little is understood about GeoGebra's acceptance for learning circle theorems
(Chen, 2020).
Mukamba and Makamure (2020) observed a scarcity of studies focusing on factors
that pre-service teachers consider important when accepting GeoGebra.
Additionally, Aman et al. (2020) also advocated for more research in the
acceptance of GeoGebra by pre-service teachers.
A considerable amount of research has been carried out on the use of GeoGebra
in the mathematics classroom (Aman et al., 2020; Belgheis & Kamalludeen, 2018;
Chen, 2020; Johar, 2021; Septian & Monariska, 2021; Venter, 2015). Venter (2015)
investigated in-service teachers’ acceptance of GeoGebra. Septian and Monariska
(2021) focused on what motivates learners to use GeoGebra for learning
mathematics. However, there are very few studies that have focused on factors
that influence the acceptance of GeoGebra (Aman et al., 2020; Belgheis &
Kamalludeen, 2018; Chen, 2020; Johar, 2021).
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Chen (2020) and (Johar, 2021) assessed the acceptance of GeoGebra by university
students. Aman et al. (2020) and Belgheis and Kamalludeen (2018) looked at the
factors that pre-service teachers consider important when accepting GeoGebra,
but these were all conducted in developed countries, so their generalization to
developing countries may be limited. Additionally, Mutambara and Bayaga
(2020b) called for developing countries to carry out their own acceptance of
educational technology studies, and not to follow examples in developed
countries blindly. This therefore, calls for the need for investigating the use and
acceptance of GeoGebra in a rural setting of a developing country.
Based on the preceding arguments, the purpose of this study was to examine pre-
service teachers' acceptance of GeoGebra in the learning of circle theorems. In
doing so, this study combined the technology acceptance model (TAM) and the
task-technology fit (TTF) to create a new model that predicts the acceptance of
GeoGebra for learning circle theorems.
2. Literature Review
2.1 Application of GeoGebra in the Classroom
Korenova (2017) investigated the use of GeoGebra among children between nine
and 11 years of age on their attitudes and achievements. The findings were similar
to the findings of previous studies (Sheikh Qasem, 2020; Suryani et al., 2020;
Zulnaidi et al., 2020) which revealed that GeoGebra improves learners’
performance in Geometry. Additionally, the results indicated that learners had a
positive attitude towards GeoGebra (Safrida et al., 2020). These results concur
with the findings of Boo and Leong (2016), which stated that learners were able to
express their geometric imagination and understanding of mathematical concepts
after using GeoGebra. The study's findings also demonstrated that GeoGebra can
make classroom lessons more fun and intriguing (Boo & Leong, 2016).
In a study by Safrida et al. (2020) to investigate the effect of GeoGebra on
university students’ learners’ performance in Geometry, the findings revealed a
considerable difference in learners' pre-test and post-test scores. The results
showed that GeoGebra is a useful supplement to traditional teaching. Similarly,
Baltaci and Yildiz (2015) added that GeoGebra is dynamic, easy to apply, and can
improve learners’ performance.
Another study was carried out in Zimbabwe by Mukamba and Makamure (2020)
on the effects of teaching and learning geometric transformations at Ordinary
Level. The results agree with the findings of Arbain and Shukor (2015), who found
that learners had positive attitudes towards the use of GeoGebra and had better
learning achievement using GeoGebra. Arbain and Shukor (2015) added that
GeoGebra can benefit learners’ mathematics learning and diversifying learning in
the classrooms.
2.2 Factors that Influence Pre-Service Teachers to use GeoGebra
The technology acceptance model was used by Kalogiannakis and Papadakis
(2019) to predict pre-service teachers’ acceptance of GeoGebra. Pre-service
teachers’ perceived usefulness (PU) was predicted by perceived ease of use
(PEOU) and they were both determinants of perceived attitude towards (ATT)
use (Kalogiannakis & Papadakis, 2019). The positive influence of PEOU on ATT
was also supported by Pittalis (2020), who stressed that pre-service teachers’
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attitude towards GeoGebra is affected by the effort required to learn to use it.
These results were also supported by Aman et al. (2020) and Khlaisang et al. (2019)
who together added that PU does not influence ATT only, but actual use
(USAGE). The ATT construct has a strong correlation with USAGE (Aman et al.,
2020; Mac Callum & Jeffrey, 2014). The positive attitude of pre-service teachers
towards GeoGebra reinforces USAGE
Previous studies in educational context have empirically established that TTF
positively influences both users’ attitude towards technologies and actual usage
of technologies (Alamri et al., 2020; Gan et al., 2017; McGill & Klobas, 2009).
Alamri et al. (2020), for example, discovered that TTF has a considerable impact
on students' attitude towards the usage of educational technologies. Gan et al.
(2017) noted that TTF had a substantial impact on GeoGebra usage in higher
education. McGill and Klobas (2009) reported that TTF extensively influences
both user’s ATT and USAGE. TTF was found to be affected by PEOU (Isaac et al.,
2019).
Empirical studies have shown that task-technology fit is influenced by system
quality (Aldholay et al., 2018; Isaac et al., 2019). Aldholay et al. (2018) found that
Yemen university students’ TTF is influenced by system quality. Isaac et al. (2019)
also reported that TTF is influenced by both system quality and system
compatibility. Congruent with the findings of Isaac et al. (2019), Alamri et al.
(2020) reported that both system actual usage and TTF are influenced by system
compatibility. Also, user satisfaction positively correlates with TTF (Gharbawi &
Bassam, 2016).
3. Theoretical Framework
According to the TAM, people's behavioral intention (BI) to utilize a new
information system (IS) is influenced by both its perceived usefulness (PU) and
their attitude towards it (ATT) (Davis et al., 1989). That is, a person's attitude
toward an IS Aldolic influenced by its utility and the effort required to learn how
to utilize it (Mutambara & Bayaga, 2020a). Thus, the TAM postulates that PU is
predicted by PEOU, and they are both influenced by external factors (Davis et al.,
1989). The TAM is also considered as a well-established and robust technology
acceptance theory (Chibisa et al., 2021; Mutambara & Bayaga, 2021).
Even though the TAM is considered robust in predicting technology acceptance,
other researchers have criticized the TAM (Dishaw & Strong, 1999; Venkatesh et
al., 2003). The TAM was critiqued by Venkatesh et al. (2003) for having a low
explanatory power of users' perceptions towards IS. Venkatesh et al. (2003)
suggested that adding external variables improves the TAM's explanatory power,
and this was supported by several studies (Khlaisang et al., 2019; Mutambara &
Bayaga, 2021; Pittalis, 2020). The TAM is also critiqued for its lack of task focus
when explaining the use of new technology (Dishaw & Strong, 1999).
Information technology is a tool that allows users to complete organizational tasks
(Dishaw & Strong, 1999). Furthermore, Dishaw and Strong (1999) averred that a
lack of task focus when evaluating acceptance of a new information system
contributes to mixed results in new information system evaluations. In dealing
with these weaknesses, the current study extended the TAM by adding the TTF
constructs.
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4. Conceptual Framework
The use of a hybrid TAM/TTF model was appropriate for this study, given both
separate models assessed different aspects of rural Eswatini pre-service teachers’
acceptance of GeoGebra for learning circle theorems. Most of the TAM variables
and hypotheses were retained in this new model. The TTF variables extend the
TAM by considering how the task impacts use. The current study posits that the
TTF construct influences perceived usefulness, perceived attitude towards, and
actual usage, while the TTF itself is predicted by perceived ease of use, system
quality, system compatibility, and user satisfaction. System compatibility also
influences actual usage. Error! Reference source not found.1 shows the proposed G
eoGebra acceptance hybrid model. The model constructs and hypotheses follow
thereafter.
Error! Reference source not found.1: Conceptual framework
4.1 User Satisfaction (U_SA)
This study defines user satisfaction as the intensity with which rural Eswatini pre-
service teachers find satisfaction in their individual decision to use GeoGebra to
learn circle theorems. User satisfaction is regarded as among the most important
indicators of the success of information systems (IS) (DeLone & McLean, 2016;
Gharbawi & Bassam, 2016). Studies have shown that U_SA has a positive effect
on TTF (Alamri et al., 2020; Isaac et al., 2019). This study proposed that if rural
Eswatini pre-service teachers are satisfied with GeoGebra for learning circle
theorems, they will find it (GeoGebra) fit for the task. Therefore, the hypothesis
for the construct is:
H13: Rural Eswatini pre-service teachers’ U_SA influences their TTF.
4.2 System Compatibility (COM)
The degree to which a system is technically sound, flexible, and sophisticated is
defined as system compatibility (Adeniji et al., 2018). Prior studies found
contradicting results on the effect of COM on TTF. Isaac et al. (2019) reported that
university students' system compatibility has a significant positive effect on their
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TTF. Contrary to the findings of Isaac et al. (2019), Islam and Azad (2015) revealed
that system compatibility has no effect on task technology fit. This study proposed
that if rural Eswatini pre-service teachers find GeoGebra to be technically sound,
flexible, and sophisticated, they will perceive it fit for learning circle theorems.
Therefore, the following hypotheses were proposed:
H11: Rural Eswatini pre-service teachers’ COM influences their TTF.
H1: Rural Eswatini pre-service teachers’ COM influences their USAGE.
4.3. System Quality (QUAL)
Isaac et al. (2019) defined system quality as the degree to which an individual
perceives that an IS is simple to operate, connect, and learn, as well as pleasurable
to use. Because an IS has various characteristics, such as system aspects, quality
aspects, and other technical concerns, Ali and Younes (2013) defined system
quality as a multidimensional process focused on multiple aspects. According to
Aldholay et al. (2018) and Isaac et al. (2019), system quality has a beneficial effect
on TTF. This study hypothesizes that if rural Eswatini pre-service teachers find
GeoGebra easy to use, connect, and learn, as well as entertaining to use, they will
consider it appropriate for learning circle theorems. As a result, the following
hypothesis was established:
H12: Rural Eswatini pre-service teachers’ QUAL influences their TTF.
4.4. Task-Technology Fit (TTF)
The task-technology fit model is a commonly used as a theoretical framework for
measuring the influence of information technology on performance, examining
usage impacts, and judging the match between task and technology features (Wu
& Chen, 2017). The TTF, as described by Goodhue and Thompson (1995), is a
crucial component in explaining work performance levels. It is a matter of how
the capabilities of the IS meet the tasks that the user must do. According to Wu
and Chen (2017), the view of whether a certain technology fits well with the
current values of users, its perceived usefulness, can be used to develop
perceptions of actually using the technology. Furthermore, empirical studies
show that TTF influences PU; that is, when the task-to-technology fit is better,
users perceive the technology to be more useful (Wu & Chen, 2017).
Previous studies in educational context have empirically established that TTF
positively influences both users’ attitude towards technologies and actual usage
of technologies (Alamri et al., 2020; Gan et al., 2017; McGill & Klobas, 2009). This
study proposes that if rural Eswatini pre-service teachers find GeoGebra fit for
learning circle theorems, they will realize its usefulness, have positive attitudes
towards it and will use it. It is therefore hypothesized that:
H2: Rural Eswatini pre-service teachers’ TTF influences their USAGE.
H10: Rural Eswatini pre-service teachers’ TTF influences their PU.
H6: Rural Eswatini pre-service teachers’ TTF influences their ATT.
4.5. Perceived Attitude Towards (ATT)
Venkatesh et al. (2003) defined ATT as a person's total emotional reaction to the
use of a new IS. In the current study, perceived attitude towards was defined as
the overall affective reaction of Eswatini pre-service teachers towards the use of
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GeoGebra. Prior studies have shown that pre-service teachers’ perceived attitude
towards, influence their actual use (Montrieux et al., 2014; Siyam, 2019). Siyam
(2019) emphasized the importance of managing pre-service teachers’ attitude
towards, as ATT is the best predictor of their technology adoption. Teo et al. (2009)
reported that pre-service teachers’ attitude predicts their actual usage. Similar
results were reported by Aman et al. (2020), who reported that pre-service
teachers’ actual use is influenced by their attitude. If rural Eswatini pre-service
teachers have a positive attitude towards the use of GeoGebra, they will use it for
learning circle theorems. Therefore, the hypothesis is that:
H3: Rural Eswatini pre-service teachers’ ATT influences their USAGE.
4.6. Perceived Ease of Use (PEOU)
Perceived ease of use is user’s perseption that the use of an information system
will be free of cognitive effort (Davis et al., 1989). Several studies have shown that
perceived ease of use influences pre-services teachers’ perceived usefulness
(Pittalis, 2020; Teo et al., 2015; Teo et al., 2009). The use of technology for learning
involves additional effort of learning the technology (Pittalis, 2020). This work
load increases when the technology is difficult or confusing to use (Teo et al.,
2015). Hence, the perception that it is difficult to use GeoGebra to learn circle
theorems will likely discourage rural Eswatini pre-service teachers from using it.
Studies have shown that perceived attitude is influenced by perceived ease of use
(Joo et al., 2018; Papadakis, 2018). Previous studies also show that PEOU
influences TTF (Aldholay et al., 2018; Isaac et al., 2019). If rural Eswatini pre-
service teachers found GeoGebra easy for the learning of circle theorems, then
they will have a positive attitude towards it and use it. It is therefore hypothesized
that:
H14: Rural Eswatini pre-service teachers’ PEOU influences their TTF.
H9: Rural Eswatini pre-service teachers’ PEOU influences their PU.
H7: Rural Eswatini pre-service teachers’ PEOU influences their ATT.
4.7. Perceived Usefulness (PU)
Perceived usefulness was defined in educational context as a person’s perception
that using information communication and technology will improve teaching and
learning (Mutambara & Bayaga, 2020b). Studies have shown that perceived
usefulness influences perceived attitude towards, and actual usage (Lin & Huang,
2008; Siegel, 2008; Wu & Chen, 2017). Perceived usefulness is also reported to
influence learners’ actual usage (Lin & Huang, 2008). It can be proposed that rural
Eswatini pre-service teachers’ perceived attitude towards use is influenced by
their belief that using GeoGebra for learning circle theorems will improve their
performance. Therefore, the hypotheses for the construct PU are:
H8: Rural Eswatini pre-service teachers’ PU influences their ATT.
H4: Rural Eswatini pre-service teachers’ PU influences their USAGE.
5. Methodology
5.1 Research Design
This study made use of a cross sectional survey design. A survey design provides
an accurate depiction of a population's attitudes by analyzing a subset of the
population (Creswell, 2015). A cross-sectional survey was conducted to give a
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quantitative description of the views of rural Eswatini pre-service teachers’
attitudes towards the use of GeoGebra for the learning of circle theorems.
5.2 Data collection tool
A questionnaire survey was employed to assess the utilization of GeoGebra by
rural Eswatini pre-service teachers for studying circle theorems. This
questionnaire was employed because it enabled the gathering of a significant
amount of data from rural Eswatini pre-service teachers in a short time and at a
low cost. The first section of the survey included biographic information about
rural Eswatini pre-service teachers. The second section was devoted to measuring
the conceptual model's constructs, such as TTF, PEOU, ATT, PU, U_SA, COM,
QUAL, and actual use. Items from previously validated and reliable instruments
were used to assess PEOU, ATT, and PU (Mutambara & Bayaga, 2020a). The items
TTF, U_SA, COM, QUAL, and actual use were adopted from the study of
Gharbawi and Bassam (2016). A 7-point Likert scale was used to assess these
constructs.
5.3 Participants
The participants of this study comprised of pre-service teachers studying
Mathematics at a rural Eswatini colleges. Eswatini has four teachers' colleges and
universities ( Ministry of Education and Training, 2013). Three of them are in
urban areas, while one is in a rural location (Ministry of Education and Training,
2013). As a result, the population of this study included all pre-service teachers
learning circle theorems at a rural teachers' training institution in Eswatini. All
pre-service teachers at the rural teachers' college, who were studying circle
theorems, were asked to take part in this study. There was a total of 187 pre-
service teachers chosen.
According to Hair et al. (2017), the minimal sample size for formative partial least
squares-structural equation modeling, should be 10 times the number of
indicators of the construct with the most indicators. In this study, perceived
usefulness was the construct with the most indicators (five). The minimum
predicted sample size for this investigation was 50, as per the recommendation by
Hair Jr et al. (2014). This study's actual sample size was 187, which was much
larger than the recommended 50. Most of the participants in this research were
females (53 %), while males were in the minority (47%).
5.4 Data analysis
Descriptive statistics were used to analyze the data first, and then the model was
evaluated using partial least squares–structural equation modeling. The analysis
of the model was carried out in two parts. Firstly, the measurement model was
assessed. Secondly, the structural model was evaluated.
5.5 Measurement Model
The extracted values of outer loadings, composite reliability (CR), and average
variance extracted values (AVE) are used to assess convergent validity (Hair Jr et
al., 2021; Hair Jr et al., 2017). In this study, all of the outer loadings in Table 1 and
in Figure 2 were more than the cut-off value of 0.7 as per recommendation (Hair
Jr et al., 2021; Hair Jr et al., 2017). These findings indicated that item reliability was
satisfactory. All Cronbach's alpha (CA), rho A, and CR values were more than 0.7,
indicating satisfactory internal consistency as suggested (Hair Jr et al., 2021; Hair
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Jr et al., 2017). The AVE values more than the cut off value of 0.5 were considered.
Convergent validity was confirmed with acceptable item reliability, AVE, and
internal consistency (Hair Jr et al., 2021).
Table 1: Measurement Model
Construct Indicator Loadings CA rho_A CR AVE
ATA
ATT1 0.868
0.919 0.920 0.943 0.805
ATT2 0.885
ATT3 0.918
ATT4 0.916
COMP
COMP1 0.938
0.847 0.853 0.929 0.867
COMP2 0.923
PEOU
PEOU1 0.846
0.852 0.856 0.900 0.692
PEOU2 0.853
PEOU3 0.833
PEOU4 0.795
PU
PU1 0.759
0.855 0.869 0.901 0.696
PU2 0.796
PU3 0.890
PU4 0.885
QUIL
QUIL1 0.909
0.758 0.765 0.892 0.805
QUIL2 0.885
TTF
TTF1 0.910
0.804 0.806 0.911 0.836
TTF2 0.919
USAGE
USAGE1 0.930
0.936 0.943 0.952 0.801
USAGE2 0.756
USAGE3 0.934
USAGE4 0.906
USAGE5 0.937
U_SAT
U_SAT1 0.829
0.750 0.904 0.882 0.790
U_SAT2 0.945
The Fornell-Larcker criterion is used to assess discriminant validity (Hair Jr et al.,
2017). Table 2 demonstrates that the square root of each latent variable's AVE
value was greater than the latent variable's strongest correlation with any other
latent variable, as stated by Hair Jr, et al. (2021). The findings revealed that each
construct can be distinguished from any other construct in the model.
Table 2: Fornell-Larcker criterion
ATT COMP PEOU PU QUIL TTF USAGE U_SAT
ATT 0.897
COMP 0.680 0.931
PEOU 0.427 0.510 0.832
PU 0.614 0.518 0.359 0.834
QUIL 0.607 0.574 0.525 0.610 0.897
TTF 0.669 0.762 0.463 0.483 0.532 0.915
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USAGE 0.838 0.691 0.504 0.527 0.616 0.687 0.895
U_SAT 0.383 0.228 0.166 0.497 0.461 0.349 0.309 0.889
5.6 Structural model
After the measurement model's appropriateness was confirmed, the structural
model was evaluated. The four-step structural model assessment by Hair Jr et al.
(2021) was used in this study. The first phase, according to Hair Jr et al. (2021), is
to examine the structural model for collinearity, followed by the importance and
relevance of the path coefficients, the model's explanatory power, and finally the
model's predictive power.
The variance inflation factor (VIF) values were utilized to test the measurement
model's collinearity. Table 3 shows that all the VIF values were lower than four,
indicating that the model had no collinearity issues (Hair Jr et al., 2021). The
bootstrapping approach (with 5000 subsamples) was used to determine the
relevance of the path coefficients. The results from Table 3 show that out of 14
hypotheses tested five were rejected, while nine were accepted.
The rejected hypotheses were having p-values greater than 0.05 and a t-value less
than 1.96. The rejected paths are COMP to USAGE (β = 0.102, p > 0.05), PEOU to
ATT (β = 0.086, p > 0.05), PU to USAGE (β = - 0.031, p > 0.05), PEOU to TTF (β =
0.080, p > 0.05), and QUIL to TTF (β = 0.029, p > 0.05). The nine paths which were
supported by data are TTF to PU (β = 0.403, p < 0.05), TTF to USAGE (β = 0.136,
p < 0.05), TTF to ATT (β = 0.454, p < 0.05), PU to ATT (β = 0.364, p < 0.05), COMP
to TTF (β = 0.665, p < 0.05), PEOU to USAGE (β = 0.125, p < 0.05), PEOU to PU (β
= 0.173, p < 0.05), U_SAT to TTF (β = 0.685, p < 0.05), and ATT to USAGE (β =
0.642, p < 0.05).
Table 3: Structural model
Path
Std
Beta
Std
Error
T-
Statistics
P-
Values
Decision
f-
squared
VIF
ATT -> USAGE 0.642 0.051 12.679 0.000 Accepted 0.671 2.452
COMP -> TTF 0.665 0.052 12.878 0.000 Accepted 0.708 1.640
COMP -> USAGE 0.102 0.075 1.361 0.174 Rejected 0.014 2.907
PEOU -> ATT 0.086 0.066 1.303 0.193 Rejected 0.013 1.313
PEOU -> PU 0.173 0.073 2.359 0.019 Accepted 0.031 1.273
PEOU -> TTF 0.080 0.055 1.460 0.145 Rejected 0.011 1.528
PEOU -> USAGE 0.125 0.058 2.145 0.032 Accepted 0.045 1.397
PU -> ATT 0.364 0.071 5.129 0.000 Accepted 0.225 1.345
PU -> USAGE -0.031 0.044 0.688 0.492 Rejected 0.002 1.667
QUIL -> TTF 0.029 0.071 0.413 0.680 Rejected 0.001 2.028
TTF -> ATT 0.454 0.065 6.975 0.000 Accepted 0.316 1.492
TTF -> PU 0.403 0.071 5.679 0.000 Accepted 0.172 1.273
TTF -> USAGE 0.136 0.055 2.496 0.013 Accepted 0.028 2.679
U_SAT -> TTF 0.171 0.055 3.083 0.002 Accepted 0.059 1.284
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The model's explanatory power was assessed using the coefficient of
determination (R-squared) and effect size (f-squared) values. According to Chin
(1998), R-squared values of 0.19, 0.33, and 0.67 represent a weak, moderate, and
substantial level of accuracy, respectively.
Figure 2 shows that ATT, PU, TTF, and USAGE had R-squared values of 0.564,
0.257, 0.619, and 0.749, respectively. PU's R-squared value (0.257) is considered
weak (Chin, 1998). The R-squared values of ATT and TTF were moderate, while
USAGE's R-squared value was substantial (Chin, 1998). These results show that
the total contribution of predictors; COM, PEOU, PU, QUIL, TTF, U_SAT, and
ATT on the explained variance of USAGE is 74.9%. Figure 2 shows that QUIL and
U_SAT are predictors of TTF. COM is a predictor of TTF and they both influence
USAGE. PEOU is a determinant of PU, ATT, TTF, and USAGE. ATT is influenced
by PU and TTF. PU and ATT predict USAGE.
Figure 2: Structural model
The f-squared values of 0.02, 0.15, and 0.35, according to Chin (1998), correspond
to effect sizes of small, medium, and large, respectively. The f-squared value of
PEOU to PU (0.031), TTF to USAGE (0.028), and U_SAT to TTF (0.059) are all
considered small, as seen in Table 3. TTF to PU (0.172), TTF to ATT (0.316), and
PU to ATT (0.256) all have a medium effect size while the effect size of ATT to
USAGE (0.671) and COMP to TTF (0.708) are considered large.
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The Stone-Geisser’s Q-squared statistic was used to assess the model’s predictive
power. The endogenous variables ATT, PU, TTF, and USAGE obtained Q-squared
values of 0.448, 0.173, 0.503, and 0.593, respectively. All the Q-squared values were
greater than zero, indicating that the model's predictive significance was adequate
(Hair Jr et al., 2017). This means that the predictors COMP, PEOU, PU, ATT,
PEOU, QUIL, and U SAT can be used to forecast the use of GeoGebra to teach
circle theorems to rural Eswatini pre-service teachers.
6. Discussion
The primary goal of this research was to explore the factors that influence
Eswatini pre-service teachers' acceptance of GeoGebra in the learning of circle
theorems. This has been accomplished by combining the technology acceptance
model and task technology fit. The hybrid model explained 74.9% of the variance
in Eswatini pre-service teachers' acceptance of GeoGebra in the learning of circle
theorems. This suggests that variables such as task-technology fit, system quality,
system compatibility, perceived ease of use, perceived usefulness, perceived
attitude toward, and user satisfaction accounted for 74.9% of the total variance.
All the Q-squared values were greater than zero, indicating that the model can be
used to predict Eswatini pre-service teachers' acceptance of GeoGebra in the
learning of circle theorems.
This study demonstrated that rural Eswatini pre-service teachers' perceived
attitude towards GeoGebra for learning circle theorems influences their actual
use. This is consistent with previous research (Aman et al., 2020; Eksail & Afari,
2019; Teo et al., 2009; Teo et al., 2008). This supports Mutambara and Bayaga's
(2020a) claim that increasing teachers' attitudes toward the use of technology in
learning improves its actual utilization. One probable reason for this finding is
that Eswatini pre-service teachers realized that GeoGebra can help them to
perform better on circle theorems. Furthermore, the usability of GeoGebra
promotes rural Eswatini pre-service teachers' positive attitude towards the
GeoGebra adaptive technology.
Rural Eswatini pre-service teachers’ perceived ease of use of GeoGebra for
learning circle theorems does not influence their perceived attitude towards
actual use. These findings are surprising given the body of knowledge's
widespread belief that perceived ease of use influences perceived attitude
(Mutambara & Bayaga, 2021; Sánchez-Prieto et al., 2019; Teo & Milutinovic, 2015)
and actual use (Sánchez-Prieto et al., 2019). These results were also in
contradiction with the findings of Kalogiannakis and Papadakis (2019), who
discovered that pre-service teachers' perceived ease of use influences their
perceived attitude towards the use of ICT in education. Two possible explanations
for these findings are the timing of data collection for this study and that the
survey was conducted after the pre-service teachers had completed their post-test.
This suggests that the pre-service teachers were already accustomed to the use of
GeoGebra in the learning of circle theorems, since the effect of perceived ease of
use diminishes with practice (Mutambara & Bayaga, 2020c). The survey was
conducted when the pre-service teachers had already been subjected to, and were
familiar with, GeoGebra. Additionally, rural Eswatini pre-service teachers
perceived the use of GeoGebra as simple for learning circle theorems.
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Task technology fit was found to influence actual use, perceived usefulness, and
perceived attitude towards. These results support prior studies who reported a
positive influence of task technology fit on perceived usefulness (Gharbawi &
Bassam, 2016), perceived attitude towards (Alamri et al., 2020; Gan et al., 2017),
and actual use (Glowalla & Sunyaev, 2014; Isaac et al., 2019). The ability of
GeoGebra to experiment with circles to improve cognition in circle theorems
influences the attitude of rural Eswatini pre-service teachers towards GeoGebra.
These findings suggest that the ability of GeoGebra to fit and enhance cognition
in circle theorems influenced rural Eswatini pre-service teachers' attitude towards
it and the decision to use GeoGebra. Task technology fit is a major factor in
explaining job performance levels (Goodhue & Thompson, 1995). Rural Eswatini
pre-service teachers realized that GeoGebra can improve their performance in
circle theorems, which increases their decision to use it.
Task technology fit also played a very important mediating role between actual
use and its predictors; user satisfaction and system compatibility. This finding
implies that the extent to which GeoGebra is perceived to line up with the
immediate requirements, values, and prior experiences of rural Eswatini pre-
service teachers is insufficient to directly influence the use of GeoGebra, but it
does contribute through the task technology fit.
Congruent to the findings of Kalogiannakis and Papadakis (2019) and Joo et al.
(2018), their study discovered that the perceived usefulness of GeoGebra for
learning circle theorems had a positive impact on the perceived attitude of rural
Eswatini pre-service teachers. The findings are also in line with those of Bhattarai
and Maharjan (2020), who discovered that pre-service teachers' intention to use
technology in class is influenced by their belief that it improves their performance.
A reasonable explanation for this finding is that rural Eswatini pre-service
teachers discovered that they can easily manipulate objects inside circles after
using GeoGebra when learning circle theorems. This can improve their
comprehension of circle theorems. Hence, GeoGebra's ability to improve rural
Eswatini pre-service teachers' circle theorem cognition improves their attitude
towards it.
Rural Eswatini pre-service teachers' actual use of GeoGebra for learning circle
theorems is unaffected by their perceived usefulness. These findings contradict
those of Lin and Huang (2008) and Yang (2007), who found that the utility of
technology influences its use by pre-service teachers. The findings of this study
were unexpected, given that rural Eswatini pre-service teachers had previously
used GeoGebra, and found it useful for learning circle theorems. One would
expect GeoGebra's utility to have an impact on its actual use.
6.1 Theoretical Implications
The present study adds to the existing literature in five ways. First, the study
provides empirical evidence that, despite the fact that the technology acceptance
model was developed three decades ago (Davis et al., 1989), it can still be used to
predict users’ acceptance of technology.
Second, this study confirms that adding external variables that are context related
improves the TAM's explanatory power (Venkatesh et al., 2003). In this study, the
task technology fit, system quality, system compatibility, and user satisfaction
added to the explanatory power of the TAM.
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Third, this work adds to the body of knowledge by constructing a hybrid model
for predicting the rural Eswatini pre-service teachers’ acceptance of GeoGebra by
extending the technology acceptance model. This would be a significant
contribution to the acceptance of educational technology in developing countries,
given that most researches to date were carried out in developed countries.
Fourth, the findings of the study showed that perceived attitude towards the use
of GeoGebra for learning circle theorems was the strongest direct predictor of
actual use by rural Eswatini pre-service teachers. This implies that the attitudes of
rural pre-service teachers towards GeoGebra play an important role in its actual
use to improve the cognition of circle theorems.
Fifth, the original technology acceptance model and technology task fit model
have been applied in an educational context, and they have demonstrated that the
two models can be combined to explain the actual use of technology in an
educational context. This is useful for other researchers who are interested in
developing conceptual frameworks for investigating the acceptance and use of
electronic-learning technology in their educational contexts.
6.2 Practical Contributions
This study and its results have several practical implications. First, in practice, this
research has contributed to a better understanding of the factors that can help or
hinder the successful implementation of GeoGebra for learning circle theorems in
rural Eswatini colleges. These factors can assist Eswatini teacher training
institutions, researchers, and educational learning application-developers in
creating successful educational learning applications. This is especially true in the
context of African countries and other developing countries, where the situation
in teacher education institutions is similar to that of Eswatini.
Second, this study discovered that user satisfaction and system compatibility are
good predictors of technology task fit and through this finding, it can be implied
that an educational learning application should be technically sound, flexible, and
sophisticated in order for users to want to reuse it. This discovery assists
educational learning application developers in inventing educational learning
applications that are technically sound, flexible, and sophisticated, as this will
improve their actual use.
Third, perceived attitude towards actual GeoGebra use was discovered to be the
best predictor of actual use. Additionally, perceived attitude towards use was
likewise discovered to play a critical mediating role between perceived usefulness
and actual use. This finding implies that, for educational learning applications to
be successfully implemented in Eswatini teacher training institutions, pre-service
teachers' attitude towards technology integration in education should be positive.
This discovery assists Eswatini teacher training institutions and researchers in
determining factors that influence pre-service teachers' perceived attitude
towards technology integration in education.
According to the findings of this study, perceived usefulness and technology task
fit accounts for 56.4 % of the variance in perceived attitude towards use. It is
critical for researchers to identify additional factors that influence pre-service
teachers' attitude towards technology integration, as this plays a significant role
in its actual use.
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6.3 Limitation of the study
This study was conducted at one institution of higher learning in one developing
country. Hence, the generalizability of the results may need to be applied with
caution.
7. Conclusion
The study's goal was to identify the factors that influence rural Eswatini pre-
service teachers' use of GeoGebra in learning circle theorems. The study suggested
a novel model to explain the use of GeoGebra for learning circle theorems. The
model was created by incorporating the task technology fit into the technology
acceptance model. A questionnaire was used to collect data. Partial least squares-
structural equation modeling was used to analyze the data. The model accounted
for 74.9% of the variance in rural Eswatini pre-service teachers' use of GeoGebra
for learning circle theorems. The study found that perceived attitude towards use,
perceived ease of use, and technology task fit all had a direct impact on the actual
use of GeoGebra for learning circle theorems. However, perceived usefulness was
found to have an indirect effect on actual use via the mediating effect of perceived
attitude towards use. The influence of user satisfaction and system compatibility
on actual use was mediated by the task technology fit construct. It is critical for
researchers to identify additional factors that influence pre-service teachers'
attitudes towards technology integration in teaching and learning, as this plays a
significant role in its actual use.
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©Authors
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0
International License (CC BY-NC-ND 4.0).
International Journal of Learning, Teaching and Educational Research
Vol. 21, No. 12, pp. 21-43, December 2022
https://doi.org/10.26803/ijlter.21.12.2
Received Aug 10, 2022; Revised Nov 23, 2022; Accepted Dec 17, 2022
Exploring the Impact of Enquiry-Based
Instructional Strategies on Students’ Attitudes
towards Biology
Henriette Manishimwe
African Centre of Excellence for Innovative Teaching and Learning Mathematics
and Science (ACEITLMS),
University of Rwanda College of Education (URCE), Rwamagana, Rwanda
William Aino Shivoga
Department of Biological Sciences, School of Natural Sciences, Masinde Muliro
University of Science and Technology (MMUST), Kakamega, Kenya
Venuste Nsengimana
Department of Mathematics, Science and Physical Education, School of
Education, University of Rwanda College of Education (URCE), PO BOX 55
Rwamagana, Rwanda
Abstract. Teaching methods dominated by teacher demonstration, chalk
and talk, have been attributed as the main source of negative attitudes
towards biology. This study aimed to explore the impact of enquiry-based
learning on students’ attitudes towards biology. The study comprised 228
students purposely selected from six secondary schools. Focus-roup
discussions were used to collect qualitative data with a phenomenological
design. Six groups were probed with interview questions, three on the
side of the experimental group and three on the side of the group
subjected to conventional teaching methods. The data were analysed by
using NVIVO software, and later, content analysis was employed
descriptively. The study's findings revealed an extensive impact of
enquiry-based learning on enhancing students’ attitudes towards
biology. Moreover, a remarkable commitment was identified on the side
of the experimental group, while exploring biological concepts in their
groups. Difficulties, such as insufficient laboratory activities, lack of
planning for practical laboratory skills, and the inability to grasp the
scientific names of micro-organisms were identified. Learners proposed
ways of improving teaching and learning biology, such as providing
learning resources, extra time to explore the biological content, more
laboratory practical work, access to ICT tools, field studies, and the need
for active learning methods. More support in active learning was
requested on the side of the control group. The students subjected to
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enquiry instructions improved their attitude towards biology. Further
studies can adopt in-depth interviews, in order to gain more information.
Keywords: Enquiry-based instructions; biology course;
phenomenological method; students’ attitude
1. Introduction
Teaching methods play an important role in science to promote learning
outcomes, where the attitude of learners helps students to manifest behaviours
and interests in a particular subject (Adejimi et al., 2022). Nevertheless, teaching
methods dominated by a teacher with teacher’s demonstration and chalk and talk
have been attributed to the main source of problems that affect students’ learning
outcomes, including negative attitudes towards science, including biology
(Bizimana et al., 2022).
To date, active learning methods are being recommended for teaching and
learning biology. Active learning methods are considered to be instructional
approaches that allow learners to play a part in their learning, while using
resources for knowledge construction (Lombardi et al., 2021; Harris et al., 2020).
It helps to attain the most learning outcomes; and it facilitates students’
interactions. In this regard, science education and trends that advocate the
integration of innovative teaching techniques, such as co-operative learning
methods, concept mapping, and enquiry-based learning that engages learners in
the learning process and are learner-centered (Dotimineli & Mawardi, 2021). The
benefits of implementing active teaching strategies were reported in a number of
studies. In this vein, optimal performance, high motivation, and interest in
learning biology were pointed out, among others (Chidubem & Adewunmi, 2020;
Rabgay, 2018; Erbas & Demirer, 2019; Dorfner et al., 2018). Consequently, the
attitude towards learning biology was improved.
Enquiry-based learning methods were identified as one of the instructional
strategies that reflect the active learning method (Khalaf & Zin, 2018). In this
regard, occasions are furnished for students to explore their concepts and
resources bestowed. With enquiry-based instruction, questions are posed to the
students, and time is given to find solutions with their peers by using the available
resources. Given this opportunity to grasp concepts themselves, their thinking
skills are upgraded (Kang & Keinonen, 2018). Collaboration between students is
more motivated, which produces more skills and knowledge of a particular
concept. Thus, their attitude towards learning science subjects is improved
(Manishimwe et al., 2022).
In relation to biology, the teaching and learning of biology have been
characterised by poor teaching methods dominated by the teacher (Chidubem &
Adewunmi, 2020; Kareem, 2018). Moreover, it has been marked by a lack of
resources, insufficient laboratory activities, biological terminologies, and
insufficient time cited, among others (Byukusenge et al., 2022; Island et al., 2022;
Chidubem & Adewunmi, 2020). Therefore, instructional strategies that provide
an engaging learning environment were scarce, and consequently the attitude of
students towards biology was not satisfactory. With this background, the present
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study was conceived, in order to explore the effect of active learning methods,
such as enquiry-based learning, in order to improve students’ attitudes towards
biology.
Biology is an enormous subject with different subjects, from secondary level to
university. Amidst biology lessons, microbiology is a fundamental subject that
gives basic knowledge about micro-organisms,the diseases they cause, and the
ways of prevention (Mukagihana et al., 2021). On top of that, it brings forth some
useful aspects of micro-organisms with respect to economic importance. A
number of studies have been done on microbiology teaching and learning (Cheng
et al., 2022; Mukagihana et al., 2021; Cox & Simpson, 2018). Most of them were
conducted at the university level. However, there was a deficit in the literature
about microbiology at the secondary school level. This study investigates the
effect of enquiry-based learning on improving students’ attitudes towards
biology, particularly in microbiological subjects.
Studies reported the influence of conventional teaching methods on students’
learning of biology. It was observed that poor teaching methods make biology
courses abstract; and they do not promote students’ commitment to playing any
role in the learning process (Akinbadewa & Sofowora, 2020; Harris et al., 2020).
Students became less involved in the lesson, relying on teachers’ information; and
they consider biology boring (Chidubem & Adewunmi, 2020). Consequently,
their interest in learning biology decreases, and they develop a negative attitude
towards biology. There is a need to evaluate how active learning methods, such
as enquiry methods, raise students’ commitment to exploring biological concepts
and improve students’ attitudes towards biology.
In the light of the effect of enquiry-based learning on students’ attitudes towards
science, specifically in biology, studies with mixed research methods were rare.
This research will contribute to the existing literature by evaluating the effect of
enquiry-based learning on students’ attitudes towards biology, with a focus-
group discussion to enrich the research with deep qualitative data ,which provide
detailed and accurate information. Specifically, students’ attitudes towards
biology at a higher level were less highlighted in Rwanda. The findings of this
study may be useful in disclosing the difficulties that students encountered in
learning biology and suggesting ways of improving. The study answered the
following research questions:
1) What are the effects of enquiry-based instructional strategies on students’
attitudes towards biology?
2) How was the commitment of students to exploring biological concepts?
3) What are the difficulties in learning biological concepts?
4) What are the factors that could improve the teaching and learning
of biology?
The Theoretical Framework
Basically, the teaching method is established in the constructivism theory of
learning. In the constructivist learning environment; students are engaged in the
lesson; and they play a considerable role in knowledge construction (Anagün,
2018; Fuchsova & Korenova, 2019). Teachers’ support is subsidiary to learners’
effortts during the lesson (Rogayan, 2019). In the learning process, students use
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their previous knowledge and their past experience, in order to understand any
new notions (Musengimana et al., 2022). Social constructivism underpins the
study concerning students’ learning in the social domain, as well as integrating
knowledge at the individual level (Xu & Shi, 2018).
2. The Methodology
2.1.The Research design
A qualitative phenomenological method was employed to collect the qualitative
data with focus groups. This method was chosen because it provides people’s
understanding and experience (Dahlin et al., 2012). A qualitative research
approach was employed in the study, due to the quality of the data that it displays
(Moretti et al., 2011).In this perspective, focus-group discussion was chosen
because it creates an opportunity for sharing experiences; and it suits
phenomenological research design.
2.2.The Sampling design
The population of this study comprises 1216 students studying biology at the
upper secondary-school level in senior four. The schools concerned in the study
are in Kigali City (Kicukiro district) and the southern province (Kamonyi and
Muhanga districts) of Rwanda. The selection was based on the availability of
teaching resources to compare schools with the same standards, so that the effect
of the intervention could be traced. Having mathematics, chemistry, and biology
(MCB) as subject combinations at the senior four secondary levels was also
another considered criterion for selection. Moreover, the schools to be selected
should have both male and female students. Thus, the sample size for this study
conaisted of six schools.
Since the average classroom size in one class in the selected districts in the
Rwandan context is 38, for six schools, 228 students participated in the study
(Ministry of Education, 2018). One of two schools in each district served as the
control group, while another from two schools in each district served as the
experimental group. Students to participate in the focus-group discussions were
chosen deliberately, based on students who were able to respond to the questions,
and on gender balance. Using four to eight people in a focus-group interview is
recommended. Thus, six students per class participated in this research. After one
round of interviews,the data were saturated; and we could not take any other
groups.
2.3 The Research Instrument
The instrument was made up of six open-ended questions (See Box 2.1) reflecting
students’ attitudes towards learning biology, from broad to specific questions.
The questionnaire was reviewed by experts in science education at the University
of Rwanda College of Education (URCE), in order to ensure the trustworthiness
of the instruments. Interviews scheduled were subjected to consultations with
other researchers, in order to contribute in making themes to ensure credibility.
Dependability was considered to maintain the consistency of the instrument, the
transferability for the generalisability of the findings was employed, and
conformability was thereby ensured. Questions were put to the entire group,
giving equal opportunities to all the participants to share their experiences freely.
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The first author played the role of moderator, guiding the conversation and
preventing divergence from the main objective of the conversation, and avoiding
influencing the participants’ responses, in order to ensure the confirmability of
the data collected. The research assistant took notes of the major points during the
discussions and examined the consistency of the process.
Box 1. Key Questions Used in Interviewing Students via Focus-Group
Discussions
FOCUS-GROUP DISCUSSIONS
1. What did you learn in the lesson we had last time?
2. What specifically did you like in the lesson we had last time?
3. How did the teaching methodology used in the lesson help you to learn new
things?
4. How committed were you while exploring biological concepts in groups?
5. In what ways do you think biology would help you to understand other
science subjects?
6. (a) Did you find any difficulties in learning some of the concepts in the lesson
we had?
(b) Can you tell me anything you think could help to improve the teaching
and learning of biology?
2.4. Data-collection procedures
Before the data collection, an ethical clearance certificate was given by the research
and innovation unit of the University of Rwanda - College of Education. The
purpose and procedures of the research were explained to the participants, and
they willingly agreed to participate in the study; and they signed a consent form.
The research was conducted from April to June of the 2021 school year; and the
intervention took four weeks. The purpose of the intervention was to compare the
achievements and attitudes of the students subjected to enquiry-based
instructions and the achievement and attitude of students taught by the
conventional teaching methods group. Since the achievement tests indicated poor
performance on the side of control, achievement correlates with attitude. The idea
was to determine the impact of enquiry-based instructional strategies to improve
the attitude towards biology.
For three days the workshop was conducted with the teachers of the experimental
group on the enquiry-based learning method early in April of the 2021 school
year, before embarking on microbiology teaching. On the other hand, teachers
explained the purpose of the research and delivered their biology lessons as usual.
Permission to record the discussions was requested prior to starting the
discussions. Six students per class were selected to participate in the focus-group
discussion after the teaching intervention, and gender balance was considered. A
treatment of enquiry-based learning, designed by the 5Es instructional model,
was given to the experimental group, and a conventional teaching method was on
the side of the control group. The microbiology lesson was taught to all the
groups.
On the side of the experimental group, the students were taught with enquiry-
based learning methods. The learning takes place in a social context by interacting
with their peers in their respective groups in the company of teaching and
learning materials. Gender balance was maintained, as male and female students
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participated equally in the learning process. Assessments occurred at the end of
the lesson. Consequently, students’ attitudes are polished, due to their active
participation and social interactions while acquiring knowledge. Inversely, the
control group underwent their accustomed teaching methods dominated by
teachers’ knowledge derived and summative assessment prevailed. After
intervention and achievement tests, the students from all the groups were
subjected to focus-group discussions on examining their attitudes towards
biology. These focus-group discussions were administered in the last two weeks
of June. Since it was impossible to conduct interviews with all the students of the
entire class, six students were selected from each class: three males and three
females.
2.5. Analysis and Data Presentation
The interviews were recorded and transcribed in Microsoft Word. The data were
transferred to NVIVO software for analysis. Deductive data analysis (Orodho et
al., 2016) was employed from specific observation of the students’ views to
general conclusions. The major themes were predetermined. These were
remembering what was learnt, what students liked in the lesson, the
characteristics of the method used, group-work activities, the relationship
between biology and other subjects, difficulties faced during learning, and ways
of improving. Transcripts were first imported into NVIVO files, followed by the
set-up of a coding table, based on the emerged themes and categories. The
software coded the transcripts and analysed them. Finally, content analysis was
made with major themes and their frequencies. Figure 1 shows the data entry and
outlook of NVIVO.
Figure 1. Our data in NVIVO
While Figure 1 shows our files entered in NVIVO software, Figure 2 shows an
example of the relationship of the codes extracted from the files in both the
control and the experimental groups of the students.
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Figure 2. Comparison group between control and experimental groups at school-1
Under each theme, we selected all the codes; and via the “visualised” option, we
selected chart coding by the attributed value. Under the chart-item box, we
selected the relevant codes, as well as our teaching-intervention groups under the
x-axis attribute. We obtained an unclear chart that did not clearly show the
visibility of the percentage coverage of each of the control and experimental
groups. We opened “summary” and exported the results into MS Excel 2016.
From there, we appropriately designed the relevant figures.
Table 1. Themes, extracted codes, and their references within source files
Themes Codes Files References
Remembering what was
learned
Categories of micro-organisms 3 4
Characteristics of micro-
organisms
4 8
Culturing micro-organisms 3 11
Fermentation 3 6
Genetic engineering 1 1
The negative effect of bacteria 3 6
What students liked in
the lesson
Bacteria to make yogurt 1 1
Culturing micro-organisms 6 10
Diseases caused by viruses 6 18
Group discussion 1 1
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Micro-organisms used in
agriculture
1 1
Micro-organisms used in
medicine
1 1
Using microscope 1 2
Yeast to brew alcohol 3 4
Yeast to produce pieces of
bread
1 1
Characteristics of the
method used
Group work 3 16
Laboratory 5 7
Research 3 6
Teacher demonstration 2 3
Teacher talk 2 3
Watching videos 2 3
Group-work activities Commitment 3 14
Enhancing understanding 6 13
Mutual work 3 3
Research 3 5
Room for self-expression 3 7
Self-preparedness 2 6
Self-study 3 3
Relationship between
biology and other
subjects
Keep environment 1 1
No linkage 1 2
Others 4 10
Understanding the Chemistry 5 14
Difficulties faced during
learning
Drawing 1 1
Insufficient Laboratory
activities
4 5
Scientific names 5 9
Time scarcity 2 3
Using a microscope 1 1
Ways of improvement Active learning methods 1 1
Need for field trips 1 2
Need of resources 5 13
Need for enough time 2 3
Practical work 3 7
Teacher support 1 1
3. The Results
❖ Remembering what was learnt
When students were asked what they remembered after learning microbiology,
the average percentage coverage for students in the experimental group was
higher (68%) than in the control group (32%). Students that learned with the
traditional method still remember the characteristics of micro-organisms and the
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negative effects of bacteria, while those taught with enquiry-based techniques still
remembered the categories of micro-organisms, culturing micro-organisms,
fermentation, and genetic engineering (Figure 3).
Figure 3. Average of percentage coverage by “Remembering of what was learned”
The learning was better in the experimental group than in the control group. For
instance, students taught with the traditional method testified that they learned
how micro-organisms are developed in agar-agar medium, which contains all the
nutrients responsible for the growth of bacteria. They have also seen how yeast is
grown and fermentation is made. One student said, “I also learned about viruses
and how they can live in living organisms, I have learned the characteristics that make
them living things. For example, they reproduce inside the host cells, and they cause
diseases and characteristics that make them to be non-living thing;s since they do not
reproduce outside the host cell, do not respond to stimuli, and do not feed.”
Students that learned with enquiry-based learning (EBL) said that they have seen
how bacteria can cause diseases, how bacteria can cause food spoilage, and how
gram-staining techniques can differentiate bacteria. One student ascertained, “In
microbiology study, we have seen how we can culture micro-organisms in medical
research. For example, culturing bacteria staphylococcus for searching the role of penicillin
as an antibiotic.” Another student was able to explain how micro-organisms can be
cultured. She said, “This means that they can grow by using different methods. For
example, suppose you want to grow the bacteria Tuberculosis. In that case, you can take a
sample from the sinus of the patient affected by it and culture it in a Petri dish on a medium
containing the necessary nutrients.”
Students taught with EBL were certain to describe what they had learnt One
student said, “We have learnt about bacteria in microbiology; there are Archaebacteria
and Eubacteria; the first one has special characteristics, which are different from those of
other bacteria; for example, they live in an extreme environment like living in a hot area
(the bacteria), and the second ones are normal bacteria that can be categorised by gram-
staining.” Another student said, “We learnt that some diseases are caused by micro-
organisms. For example, Entamoeba Histolytica causes Amoebiasis as its symptoms, and
0% 20% 40% 60% 80% 100% 120%
Categories of microorganisms
Characteristics of microorganisms
Culture microorganisms
Fermentation
Genetic engineering
Negative effect of bacteria
Overall
Control group Experimental group
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preventive measures are required.” Students were aware that micro-organisms could
not be seen with our eyes and that they are harmful and important to other living
things. One student said, “The chemicals which harm them limit their usefulness to
people. We have seen the application of microbiology in bread-making, and genetic
engineering; and we have seen different categories of micro-organisms, such as
algae, viruses, protozoa, and so forth.”
❖ What students liked in the lesson
Four of the nine codes revealed under the “what students liked in the lesson”
theme were depicted from experimental group-focus discussions. Two codes
were found in the control group alone (how bacteria are used to produce yoghurt
and how yeasts are used to produce bread). Both the control and the experimental
groups (cultured micro-organisms, diseases caused by viruses, and how yeast is
used to brew alcohol) shared three codes. These students liked the use of group
discussion, and the way in which micro-organisms are used in agriculture and in
medicine; and they enjoyed using the microscope. As shown in Figure 4, the
overall liking of the lesson was in favour of those learnt with the EBL technique
(experimental group students), with 58% alongside 42%.
Figure 4. Average percentage coverage by “What students liked in the lesson.”
Students are taught by traditional methods, like how yeast changes glucose into
alcohol, how they culture micro-organisms, and the lesson about diseases caused
by viruses. One student testified that he didn’t know that microbes could grow
and how they cause diseases. The following are extracts from the students:
“What I liked is the importance of bacteria and how they are used in
making yoghurt, for I like it. I knew that they decompose glucose into
lactic acid.”
“As we were studying micro-organisms, after seeing how Alexander
Fleming cultured micro-organisms and found penicillin from Penicillium
Notatum; it made me curious because I had a dream to be like him, and I
0% 20% 40% 60% 80% 100% 120%
Bacteria to make yogurt
Culture microorganisms
Diseases caused by viruses
Group discussion
Microorganisms used in agriculture
Microorganisms used in medicine
Using microscope
Yeast to brew alcohol
Yeast to produce breads
Overall
Control group Experimental group
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want to invent something which is not known; that is what I liked in that
lesson that made me interested in biology.”
Students were surprised to see micro-organisms on the door they touched. So,
they came to know that micro-organisms are everywhere. The lesson has inspired
students to know and emphasise Coronavirus; as they testified that this pandemic
is mainly found in microbiology; they have known the composition and shape of
the Coronavirus, and how it causes Covid -19, and how to prevent this infection.
Likewise, the students taught by EBL liked how micro-organisms are applied in
our daily life. For example, how they are involved in making useful products like
human insulin used to protect against diabetes. They also liked to see bacteria and
other micro-organisms that help in agriculture; since they decompose organic
matter in the soil to produce fertilisers, so that the soil can sustain growth. They
liked the sterilisation techniques used before culturing micro-organisms, such as
washing hands, cleaning working areas, and cleaning Petri dishes. Students
testified that they learned the lesson about protozoa and how they could cause
diseases; for example, they can cause malaria, which is dangerous to humans. The
following are extracts from the students:
“I liked how we can prevent diseases. I liked the topic of protozoa[ because it
teaches me about different diseases and how we can prevent them, and how those
diseases are spread. For example, we learned how Entamoeba Histolytica and
plasmodium cause diseases, and the knowledge I got from this lesson helped me to
-protect myself.”
“We did the culture of micro-organisms as in industries and other laboratories.
For me, I liked culturing micro-organisms, and we saw how they reach the stage
to grow and reach the stage where they can reproduce and infect other organisms.”
❖ Characteristics of the methosds used
Group work and watching videos were two teaching methods that the students
in the experimental group described that were used in their class. Likewise,
teacher demonstration and talk were mentioned by the students in the control
group. Research and laboratory were used in both groups, but they were
extensively used in the experimental group. The overall findings showed that the
teaching methods used were more characterised by students that learned with
EBL (56%) than those who learned by the traditional method (44%). Figure 5
visualises these results.
32
http://ijlter.org/index.php/ijlter
Figure 5. Average percentage coverage by the “Characteristics of the method used”
Ideas from students taught by traditional methods clearly show the use of
teachers’ demonstration and talk. For instance, they testified that they didn’t
know how to grow bacteria, but the teacher showed them how to grow them by
using agar-agar. Their teacher told them how to prevent Escherichia Coli from
being transmitted through faeces.
Expression of the use of the laboratory was mentioned. One student said: “For me,
a new thing I have learnt is laboratory equipment called an incubator; I didn’t know you
can put microbes in it and grow them. It is like in a refrigerator. We tested micro-
organisms in the laboratory by using a microscope; because they were too small; and
without a microscope, we could not see them.”
Students taught in the EBL method testified that group work encouraged them to
do research and present their findings. This presentation then improved their
communication skills. They said that when they were in groups, they acquired
many skills because when they join in the group, they share some skills about the
topic they are learning. Students appreciated the way they have acquired a
leadership style. One student who was representative of his group concurred that
he had to do everything to make a good presentation in front of the teacher. The
following are extracts from students:
“The method used in this unit is different from the other methods we are
used to; as just the teacher went on the blackboard giving summaries; and
the rest of the work is supposed to be done by the students. But this lesson
on microbiology was different; everybody was to put together everything
we had got. This unit involves much effort between the teacher and the
students. The teacher brings his ownis ideas, and the students bring their
own ideas, and they compare these; and perfect ideas were consequently
formed.”
“When you are not in groups, sometimes you get scared, ‘saying may I
ask this question’; but when you are in a group with your group members,
0% 20% 40% 60% 80% 100% 120%
Group work
Laboratory
Research
Teacher demonstration
Teacher talk
Watching videos
Overall
Control group Experimental group
33
http://ijlter.org/index.php/ijlter
you are free to talk to them; you won’t fear, we would ask a question; he
or she would answer, or ask the teacher; so, ithis builds confidence in us.”
Many students appreciated the research. They said they learned how to use the
internet in a study because they accessed the internet, in order to study the
lifecycles of some bacteria. They realised that the internet is not for entertainment
only; but it can also be used in class. One student concurred: “I didn’t know some
life ycles of some organisms; they helped me to get more about them, and I went to a
computer lab and we did something practical, like the lifecycle of Amoebiasis and how it’s
going through it.’ This was quite awesome; but it was enjoyable.”
❖ Group-work activities
Related to activities used in group-work, students in the experimental group said
that group work increased their commitment to engage in different activities; they
developed mutual work; as it allowed them to work together, where each one
could contribute to the task given; it allowed them to do research before
presenting their findings, they became self-prepared. They were then able to learn
by themselves (self-study). The overall group work activity (see Figure 6) was
found to be on the side of students that had learnt with EBL (81%).
Figure 6. Average of percentage coverage by “Group work activities.”
Although group-work was not extensively used in the control group; the little that
it was used, students taught by the traditional method applied to it. For instance,
one student said that her role in the group was to give an idea as a group member,
knowing that this would help all the members. Another student agreed that when
they are grouped together with others, it is better than when one is studying alone,
for we can then understand more. The following is an extract from one of the
students:
“In our group, we used groups at the beginning of the topic; then the
teacher gives us a topic, and we discussed it in our group, and everyone
in the group participates and gives his idea rs her idea about it a it, and
how he/she thinks; and thereafter the teacher comes and supplements this
as a group, in order to reach a common understanding in the whole class.”
0% 20% 40% 60% 80% 100% 120%
Commitment
Enhancing understanding
Mutual work
Research
Room for self-expression
Self-preparedness
Self-study
Overall
Control group Experimental group
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IJLTER.ORG Vol 21 No 12 December 2022

  • 1. International Journal of Learning, Teaching And Educational Research p-ISSN: 1694-2493 e-ISSN: 1694-2116 IJLTER.ORG Vol.21 No.12
  • 2. International Journal of Learning, Teaching and Educational Research (IJLTER) Vol. 21, No. 12 (December 2022) Print version: 1694-2493 Online version: 1694-2116 IJLTER International Journal of Learning, Teaching and Educational Research (IJLTER) Vol. 21, No. 12 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically those of translation, reprinting, re-use of illustrations, broadcasting, reproduction by photocopying machines or similar means, and storage in data banks. Society for Research and Knowledge Management
  • 3. International Journal of Learning, Teaching and Educational Research The International Journal of Learning, Teaching and Educational Research is a peer-reviewed open-access journal which has been established for the dissemination of state-of-the-art knowledge in the fields of learning, teaching and educational research. Aims and Objectives The main objective of this journal is to provide a platform for educators, teachers, trainers, academicians, scientists and researchers from over the world to present the results of their research activities in the following fields: innovative methodologies in learning, teaching and assessment; multimedia in digital learning; e-learning; m-learning; e-education; knowledge management; infrastructure support for online learning; virtual learning environments; open education; ICT and education; digital classrooms; blended learning; social networks and education; e- tutoring: learning management systems; educational portals, classroom management issues, educational case studies, etc. Indexing and Abstracting The International Journal of Learning, Teaching and Educational Research is indexed in Scopus since 2018. The Journal is also indexed in Google Scholar and CNKI. All articles published in IJLTER are assigned a unique DOI number.
  • 4. Foreword We are very happy to publish this issue of the International Journal of Learning, Teaching and Educational Research. The International Journal of Learning, Teaching and Educational Research is a peer-reviewed open-access journal committed to publishing high-quality articles in the field of education. Submissions may include full-length articles, case studies and innovative solutions to problems faced by students, educators and directors of educational organisations. To learn more about this journal, please visit the website http://www.ijlter.org. We are grateful to the editor-in-chief, members of the Editorial Board and the reviewers for accepting only high quality articles in this issue. We seize this opportunity to thank them for their great collaboration. The Editorial Board is composed of renowned people from across the world. Each paper is reviewed by at least two blind reviewers. We will endeavour to ensure the reputation and quality of this journal with this issue. Editors of the December 2022 Issue
  • 5. VOLUME 21 NUMBER 12 December 2022 Table of Contents Acceptance of the GeoGebra Application in Learning Circle Theorems.........................................................................1 Nxumalo Mfanasibili Philemon, Admire Chibisa, Maria Siwela Mabusela Exploring the Impact of Enquiry-Based Instructional Strategies on Students’ Attitudes towards Biology ............. 21 Henriette Manishimwe, William Aino Shivoga, Venuste Nsengimana Challenges to and Enablers of Women's Advancement in Academic Careers at a Selected South African University .............................................................................................................................................................................. 44 Ifeanyi Mbukanma, Kariena Strydom Students' Perceptions and Challenges in Learning Business English: Understanding Students’ Needs and Job Market Requirements........................................................................................................................................................... 65 Wael Alharbi The Role of Writing Process Components and Cognitive Components in Improving the Quality of Narrative.....88 Lati Andriani, Syihabuddin ., Andoyo Sastromiharjo, Dadang Anshori University Students’ Experiences of the Teaching and Learning of an Acupuncture Programme: A South African Case Study ........................................................................................................................................................................... 107 Zijing Hu, Roy Venketsamy, Janice Pellow On-the-Job Training in Vocational College: Issue and Improvement Plan.................................................................126 Suzila Othman, Mohd Azlan Mohammad Hussain, Rafeizah Mohd Zulkifli, Mohammad Sukri Saud Students’ Time Management, Academic Procrastination, and Performance during Online Science and Mathematics Classes........................................................................................................................................................... 142 John Paul E. Santos, Joseph A. Villarama, Joseph P. Adsuara, Jordan F. Gundran, Aileen G. De Guzman, Evelyn M. Ben Review of Essential Amendments in Indian Higher Education with Special Reference to COVID-19 Pandemic and National Education Policy (NEP) 2020..................................................................................................................... 162 Afzalur Rahman Motivation in English Learning at University: A Mixed-Methods Study Investigating the Perceptions of Different Stakeholders*....................................................................................................................................................................... 175 Diego Ortega-Auquilla, Paul Sigüenza-Garzón, Julio Chumbay, Esteban Heras Beyond Educational Reforms: A Review of Teacher Preparation in Tanzania........................................................... 197 Nipael Mrutu, Hamisi Nkota, Jamila Kova, Esther Kibga, Peter Kajoro, Aladini Hoka, Fredrick Mtenzi Distinguishing between Bilingualism and Dyslexia: Views of Secondary School Teachers in Greece ................... 218 Christina Biza, Aretousa Giannakou Exploring Business Studies Teachers’ Technology Self-Efficacy on their Technology Integration to Create Learner-Centred Teaching Environment......................................................................................................................... 238
  • 6. Nduduzo Brian Gcabashe, Nokulunga Sithabile Ndlovu Exploring Threats to Novice Teachers’ Development in Selected Secondary Schools in South Africa................... 259 Joseph Lesiba Makhananesa, Mmalefikane Sylvia Sepeng Exploring English Language Proficiency, English Language Problems, and English Needs Among First Year Undergraduate Students.................................................................................................................................................... 272 Bussayarat Nithideechaiwarachok, Ornpiya Maneekanon, Thirapong Bubphada
  • 7. 1 ©Authors This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). International Journal of Learning, Teaching and Educational Research Vol. 21, No. 12, pp. 1-20, December 2022 https://doi.org/10.26803/ijlter.21.12.1 Received Aug 29, 2022; Revised Nov 9, 2022; Accepted Dec 12, 2022 Acceptance of the GeoGebra Application in Learning Circle Theorems Nxumalo Mfanasibili Philemon University of Zululand, Faculty of Education Department of Mathematics, Science and Technology Education Admire Chibisa University of Zululand, Faculty of Education Department of Mathematics, Science and Technology Education Maria Siwela Mabusela University of Zululand, Faculty of Education Department of Mathematics, Science and Technology Education Abstract. The learning area of circle theorems is one of the most difficult topics in geometry, resulting in low student performance. GeoGebra has been shown in studies to enhance learners' proficiency in circle theorems. However, pre-service teachers' use of GeoGebra is not at the expected level in Eswathini. The adoption of an information system is reliant on its acceptance by individuals. However, little is known regarding pre- service teachers' use of GeoGebra to understand circle theorems. The goal of this study was to investigate pre-service teachers' perceptions of GeoGebra's suitability for learning circle theorems. A cross-sectional survey design was used in this investigation, with a total of 187 pre- service instructors as participants. The model explained 74.9% of the variance in the acceptability of GeoGebra for learning circle theorems by Eswatini pre-service teachers. According to the findings, task-technology fit, system quality, system compatibility, perceived ease of use, perceived usefulness, perceived attitude toward, and user satisfaction account for 74.9% of the variance in actual use. The study's findings revealed that rural Eswatini pre-service teachers' reported attitude toward using the mathematics software application GeoGebra for learning circle theorems was the strongest direct predictor of actual use. This research shows that pre-service teachers' views toward technology integration in education should be positive for educational learning applications to be successfully adopted in Eswatini teacher training institutes. Keywords: circle theorems; GeoGebra; pre-service teachers; task- technology fit; technology acceptance model
  • 8. 2 http://ijlter.org/index.php/ijlter 1. Introduction Geometry, as a branch of mathematics, is critical in assisting mathematicians and students of mathematics in appreciating and comprehending the space, shape, and orientation of numerous bodies and objects in our universe (Jin et al., 2021). Geometry includes circle theorems, which allow "mathematicians and students of mathematics to grasp circular space, shape, and orientation in this world" (Badu- Domfeh, 2020, p. 1). Circle theorems are regarded as one of the most difficult sections of Geometry, resulting in poor student performance (Kwadwo & Asomani, 2021). According to studies (Adolphus, 2011; Erdoğan et al., 2011; Kwadwo & Asomani, 2021), the difficulty in teaching and learning Geometry, particularly circle theorems, results in poor learners’ performance. For this reason, studying circle theorems, particularly in teacher training institutions, need more creative techniques that will improve pre-service teachers' circle theorems comprehension and skills (Amevor & Bayaga, 2021; Kwadwo & Asomani, 2021; Tay & Wonkyi, 2018). Some of these novel ways that are recognized to aid learners' knowledge of circle theorems include the use of educational technology, notably the incorporation of mathematics software into the teaching and learning of circle theorems (Amevor & Bayaga, 2021; Kovács, 2018; Tay & Wonkyi, 2018). GeoGebra is a popular mathematics application software in the teaching and learning of circle theorems (Adhikari, 2021; Arbain & Shukor, 2015; Tay & Wonkyi, 2018). Studies have shown that GeoGebra software can improve learners’ performance in circle theorems (Adhikari, 2021; Mushipe & Ogbonnaya, 2019; Pamungkas et al., 2020; Tay & Wonkyi, 2018; Tran & Nguyen, 2020). However, the adoption of GeoGebra is lower than expected (Ganesan & Eu, 2020; Mutambara & Bayaga, 2020c; Nwoke & Chidi, 2020). According to Padmanathan and Jogulu (2018), the proper deployment and use of an information system are dependent on individuals’ acceptance. Mutambara and Bayaga (2020c) stated in an educational context that learners' use of educational technologies is dependent on their acceptance of these technologies. According to the findings of Padmanathan and Jogulu (2018) and Mutambara and Bayaga (2020c), one can conclude that the successful adoption of GeoGebra by pre-service teachers is contingent on their acceptance of it. However, little is understood about GeoGebra's acceptance for learning circle theorems (Chen, 2020). Mukamba and Makamure (2020) observed a scarcity of studies focusing on factors that pre-service teachers consider important when accepting GeoGebra. Additionally, Aman et al. (2020) also advocated for more research in the acceptance of GeoGebra by pre-service teachers. A considerable amount of research has been carried out on the use of GeoGebra in the mathematics classroom (Aman et al., 2020; Belgheis & Kamalludeen, 2018; Chen, 2020; Johar, 2021; Septian & Monariska, 2021; Venter, 2015). Venter (2015) investigated in-service teachers’ acceptance of GeoGebra. Septian and Monariska (2021) focused on what motivates learners to use GeoGebra for learning mathematics. However, there are very few studies that have focused on factors that influence the acceptance of GeoGebra (Aman et al., 2020; Belgheis & Kamalludeen, 2018; Chen, 2020; Johar, 2021).
  • 9. 3 http://ijlter.org/index.php/ijlter Chen (2020) and (Johar, 2021) assessed the acceptance of GeoGebra by university students. Aman et al. (2020) and Belgheis and Kamalludeen (2018) looked at the factors that pre-service teachers consider important when accepting GeoGebra, but these were all conducted in developed countries, so their generalization to developing countries may be limited. Additionally, Mutambara and Bayaga (2020b) called for developing countries to carry out their own acceptance of educational technology studies, and not to follow examples in developed countries blindly. This therefore, calls for the need for investigating the use and acceptance of GeoGebra in a rural setting of a developing country. Based on the preceding arguments, the purpose of this study was to examine pre- service teachers' acceptance of GeoGebra in the learning of circle theorems. In doing so, this study combined the technology acceptance model (TAM) and the task-technology fit (TTF) to create a new model that predicts the acceptance of GeoGebra for learning circle theorems. 2. Literature Review 2.1 Application of GeoGebra in the Classroom Korenova (2017) investigated the use of GeoGebra among children between nine and 11 years of age on their attitudes and achievements. The findings were similar to the findings of previous studies (Sheikh Qasem, 2020; Suryani et al., 2020; Zulnaidi et al., 2020) which revealed that GeoGebra improves learners’ performance in Geometry. Additionally, the results indicated that learners had a positive attitude towards GeoGebra (Safrida et al., 2020). These results concur with the findings of Boo and Leong (2016), which stated that learners were able to express their geometric imagination and understanding of mathematical concepts after using GeoGebra. The study's findings also demonstrated that GeoGebra can make classroom lessons more fun and intriguing (Boo & Leong, 2016). In a study by Safrida et al. (2020) to investigate the effect of GeoGebra on university students’ learners’ performance in Geometry, the findings revealed a considerable difference in learners' pre-test and post-test scores. The results showed that GeoGebra is a useful supplement to traditional teaching. Similarly, Baltaci and Yildiz (2015) added that GeoGebra is dynamic, easy to apply, and can improve learners’ performance. Another study was carried out in Zimbabwe by Mukamba and Makamure (2020) on the effects of teaching and learning geometric transformations at Ordinary Level. The results agree with the findings of Arbain and Shukor (2015), who found that learners had positive attitudes towards the use of GeoGebra and had better learning achievement using GeoGebra. Arbain and Shukor (2015) added that GeoGebra can benefit learners’ mathematics learning and diversifying learning in the classrooms. 2.2 Factors that Influence Pre-Service Teachers to use GeoGebra The technology acceptance model was used by Kalogiannakis and Papadakis (2019) to predict pre-service teachers’ acceptance of GeoGebra. Pre-service teachers’ perceived usefulness (PU) was predicted by perceived ease of use (PEOU) and they were both determinants of perceived attitude towards (ATT) use (Kalogiannakis & Papadakis, 2019). The positive influence of PEOU on ATT was also supported by Pittalis (2020), who stressed that pre-service teachers’
  • 10. 4 http://ijlter.org/index.php/ijlter attitude towards GeoGebra is affected by the effort required to learn to use it. These results were also supported by Aman et al. (2020) and Khlaisang et al. (2019) who together added that PU does not influence ATT only, but actual use (USAGE). The ATT construct has a strong correlation with USAGE (Aman et al., 2020; Mac Callum & Jeffrey, 2014). The positive attitude of pre-service teachers towards GeoGebra reinforces USAGE Previous studies in educational context have empirically established that TTF positively influences both users’ attitude towards technologies and actual usage of technologies (Alamri et al., 2020; Gan et al., 2017; McGill & Klobas, 2009). Alamri et al. (2020), for example, discovered that TTF has a considerable impact on students' attitude towards the usage of educational technologies. Gan et al. (2017) noted that TTF had a substantial impact on GeoGebra usage in higher education. McGill and Klobas (2009) reported that TTF extensively influences both user’s ATT and USAGE. TTF was found to be affected by PEOU (Isaac et al., 2019). Empirical studies have shown that task-technology fit is influenced by system quality (Aldholay et al., 2018; Isaac et al., 2019). Aldholay et al. (2018) found that Yemen university students’ TTF is influenced by system quality. Isaac et al. (2019) also reported that TTF is influenced by both system quality and system compatibility. Congruent with the findings of Isaac et al. (2019), Alamri et al. (2020) reported that both system actual usage and TTF are influenced by system compatibility. Also, user satisfaction positively correlates with TTF (Gharbawi & Bassam, 2016). 3. Theoretical Framework According to the TAM, people's behavioral intention (BI) to utilize a new information system (IS) is influenced by both its perceived usefulness (PU) and their attitude towards it (ATT) (Davis et al., 1989). That is, a person's attitude toward an IS Aldolic influenced by its utility and the effort required to learn how to utilize it (Mutambara & Bayaga, 2020a). Thus, the TAM postulates that PU is predicted by PEOU, and they are both influenced by external factors (Davis et al., 1989). The TAM is also considered as a well-established and robust technology acceptance theory (Chibisa et al., 2021; Mutambara & Bayaga, 2021). Even though the TAM is considered robust in predicting technology acceptance, other researchers have criticized the TAM (Dishaw & Strong, 1999; Venkatesh et al., 2003). The TAM was critiqued by Venkatesh et al. (2003) for having a low explanatory power of users' perceptions towards IS. Venkatesh et al. (2003) suggested that adding external variables improves the TAM's explanatory power, and this was supported by several studies (Khlaisang et al., 2019; Mutambara & Bayaga, 2021; Pittalis, 2020). The TAM is also critiqued for its lack of task focus when explaining the use of new technology (Dishaw & Strong, 1999). Information technology is a tool that allows users to complete organizational tasks (Dishaw & Strong, 1999). Furthermore, Dishaw and Strong (1999) averred that a lack of task focus when evaluating acceptance of a new information system contributes to mixed results in new information system evaluations. In dealing with these weaknesses, the current study extended the TAM by adding the TTF constructs.
  • 11. 5 http://ijlter.org/index.php/ijlter 4. Conceptual Framework The use of a hybrid TAM/TTF model was appropriate for this study, given both separate models assessed different aspects of rural Eswatini pre-service teachers’ acceptance of GeoGebra for learning circle theorems. Most of the TAM variables and hypotheses were retained in this new model. The TTF variables extend the TAM by considering how the task impacts use. The current study posits that the TTF construct influences perceived usefulness, perceived attitude towards, and actual usage, while the TTF itself is predicted by perceived ease of use, system quality, system compatibility, and user satisfaction. System compatibility also influences actual usage. Error! Reference source not found.1 shows the proposed G eoGebra acceptance hybrid model. The model constructs and hypotheses follow thereafter. Error! Reference source not found.1: Conceptual framework 4.1 User Satisfaction (U_SA) This study defines user satisfaction as the intensity with which rural Eswatini pre- service teachers find satisfaction in their individual decision to use GeoGebra to learn circle theorems. User satisfaction is regarded as among the most important indicators of the success of information systems (IS) (DeLone & McLean, 2016; Gharbawi & Bassam, 2016). Studies have shown that U_SA has a positive effect on TTF (Alamri et al., 2020; Isaac et al., 2019). This study proposed that if rural Eswatini pre-service teachers are satisfied with GeoGebra for learning circle theorems, they will find it (GeoGebra) fit for the task. Therefore, the hypothesis for the construct is: H13: Rural Eswatini pre-service teachers’ U_SA influences their TTF. 4.2 System Compatibility (COM) The degree to which a system is technically sound, flexible, and sophisticated is defined as system compatibility (Adeniji et al., 2018). Prior studies found contradicting results on the effect of COM on TTF. Isaac et al. (2019) reported that university students' system compatibility has a significant positive effect on their
  • 12. 6 http://ijlter.org/index.php/ijlter TTF. Contrary to the findings of Isaac et al. (2019), Islam and Azad (2015) revealed that system compatibility has no effect on task technology fit. This study proposed that if rural Eswatini pre-service teachers find GeoGebra to be technically sound, flexible, and sophisticated, they will perceive it fit for learning circle theorems. Therefore, the following hypotheses were proposed: H11: Rural Eswatini pre-service teachers’ COM influences their TTF. H1: Rural Eswatini pre-service teachers’ COM influences their USAGE. 4.3. System Quality (QUAL) Isaac et al. (2019) defined system quality as the degree to which an individual perceives that an IS is simple to operate, connect, and learn, as well as pleasurable to use. Because an IS has various characteristics, such as system aspects, quality aspects, and other technical concerns, Ali and Younes (2013) defined system quality as a multidimensional process focused on multiple aspects. According to Aldholay et al. (2018) and Isaac et al. (2019), system quality has a beneficial effect on TTF. This study hypothesizes that if rural Eswatini pre-service teachers find GeoGebra easy to use, connect, and learn, as well as entertaining to use, they will consider it appropriate for learning circle theorems. As a result, the following hypothesis was established: H12: Rural Eswatini pre-service teachers’ QUAL influences their TTF. 4.4. Task-Technology Fit (TTF) The task-technology fit model is a commonly used as a theoretical framework for measuring the influence of information technology on performance, examining usage impacts, and judging the match between task and technology features (Wu & Chen, 2017). The TTF, as described by Goodhue and Thompson (1995), is a crucial component in explaining work performance levels. It is a matter of how the capabilities of the IS meet the tasks that the user must do. According to Wu and Chen (2017), the view of whether a certain technology fits well with the current values of users, its perceived usefulness, can be used to develop perceptions of actually using the technology. Furthermore, empirical studies show that TTF influences PU; that is, when the task-to-technology fit is better, users perceive the technology to be more useful (Wu & Chen, 2017). Previous studies in educational context have empirically established that TTF positively influences both users’ attitude towards technologies and actual usage of technologies (Alamri et al., 2020; Gan et al., 2017; McGill & Klobas, 2009). This study proposes that if rural Eswatini pre-service teachers find GeoGebra fit for learning circle theorems, they will realize its usefulness, have positive attitudes towards it and will use it. It is therefore hypothesized that: H2: Rural Eswatini pre-service teachers’ TTF influences their USAGE. H10: Rural Eswatini pre-service teachers’ TTF influences their PU. H6: Rural Eswatini pre-service teachers’ TTF influences their ATT. 4.5. Perceived Attitude Towards (ATT) Venkatesh et al. (2003) defined ATT as a person's total emotional reaction to the use of a new IS. In the current study, perceived attitude towards was defined as the overall affective reaction of Eswatini pre-service teachers towards the use of
  • 13. 7 http://ijlter.org/index.php/ijlter GeoGebra. Prior studies have shown that pre-service teachers’ perceived attitude towards, influence their actual use (Montrieux et al., 2014; Siyam, 2019). Siyam (2019) emphasized the importance of managing pre-service teachers’ attitude towards, as ATT is the best predictor of their technology adoption. Teo et al. (2009) reported that pre-service teachers’ attitude predicts their actual usage. Similar results were reported by Aman et al. (2020), who reported that pre-service teachers’ actual use is influenced by their attitude. If rural Eswatini pre-service teachers have a positive attitude towards the use of GeoGebra, they will use it for learning circle theorems. Therefore, the hypothesis is that: H3: Rural Eswatini pre-service teachers’ ATT influences their USAGE. 4.6. Perceived Ease of Use (PEOU) Perceived ease of use is user’s perseption that the use of an information system will be free of cognitive effort (Davis et al., 1989). Several studies have shown that perceived ease of use influences pre-services teachers’ perceived usefulness (Pittalis, 2020; Teo et al., 2015; Teo et al., 2009). The use of technology for learning involves additional effort of learning the technology (Pittalis, 2020). This work load increases when the technology is difficult or confusing to use (Teo et al., 2015). Hence, the perception that it is difficult to use GeoGebra to learn circle theorems will likely discourage rural Eswatini pre-service teachers from using it. Studies have shown that perceived attitude is influenced by perceived ease of use (Joo et al., 2018; Papadakis, 2018). Previous studies also show that PEOU influences TTF (Aldholay et al., 2018; Isaac et al., 2019). If rural Eswatini pre- service teachers found GeoGebra easy for the learning of circle theorems, then they will have a positive attitude towards it and use it. It is therefore hypothesized that: H14: Rural Eswatini pre-service teachers’ PEOU influences their TTF. H9: Rural Eswatini pre-service teachers’ PEOU influences their PU. H7: Rural Eswatini pre-service teachers’ PEOU influences their ATT. 4.7. Perceived Usefulness (PU) Perceived usefulness was defined in educational context as a person’s perception that using information communication and technology will improve teaching and learning (Mutambara & Bayaga, 2020b). Studies have shown that perceived usefulness influences perceived attitude towards, and actual usage (Lin & Huang, 2008; Siegel, 2008; Wu & Chen, 2017). Perceived usefulness is also reported to influence learners’ actual usage (Lin & Huang, 2008). It can be proposed that rural Eswatini pre-service teachers’ perceived attitude towards use is influenced by their belief that using GeoGebra for learning circle theorems will improve their performance. Therefore, the hypotheses for the construct PU are: H8: Rural Eswatini pre-service teachers’ PU influences their ATT. H4: Rural Eswatini pre-service teachers’ PU influences their USAGE. 5. Methodology 5.1 Research Design This study made use of a cross sectional survey design. A survey design provides an accurate depiction of a population's attitudes by analyzing a subset of the population (Creswell, 2015). A cross-sectional survey was conducted to give a
  • 14. 8 http://ijlter.org/index.php/ijlter quantitative description of the views of rural Eswatini pre-service teachers’ attitudes towards the use of GeoGebra for the learning of circle theorems. 5.2 Data collection tool A questionnaire survey was employed to assess the utilization of GeoGebra by rural Eswatini pre-service teachers for studying circle theorems. This questionnaire was employed because it enabled the gathering of a significant amount of data from rural Eswatini pre-service teachers in a short time and at a low cost. The first section of the survey included biographic information about rural Eswatini pre-service teachers. The second section was devoted to measuring the conceptual model's constructs, such as TTF, PEOU, ATT, PU, U_SA, COM, QUAL, and actual use. Items from previously validated and reliable instruments were used to assess PEOU, ATT, and PU (Mutambara & Bayaga, 2020a). The items TTF, U_SA, COM, QUAL, and actual use were adopted from the study of Gharbawi and Bassam (2016). A 7-point Likert scale was used to assess these constructs. 5.3 Participants The participants of this study comprised of pre-service teachers studying Mathematics at a rural Eswatini colleges. Eswatini has four teachers' colleges and universities ( Ministry of Education and Training, 2013). Three of them are in urban areas, while one is in a rural location (Ministry of Education and Training, 2013). As a result, the population of this study included all pre-service teachers learning circle theorems at a rural teachers' training institution in Eswatini. All pre-service teachers at the rural teachers' college, who were studying circle theorems, were asked to take part in this study. There was a total of 187 pre- service teachers chosen. According to Hair et al. (2017), the minimal sample size for formative partial least squares-structural equation modeling, should be 10 times the number of indicators of the construct with the most indicators. In this study, perceived usefulness was the construct with the most indicators (five). The minimum predicted sample size for this investigation was 50, as per the recommendation by Hair Jr et al. (2014). This study's actual sample size was 187, which was much larger than the recommended 50. Most of the participants in this research were females (53 %), while males were in the minority (47%). 5.4 Data analysis Descriptive statistics were used to analyze the data first, and then the model was evaluated using partial least squares–structural equation modeling. The analysis of the model was carried out in two parts. Firstly, the measurement model was assessed. Secondly, the structural model was evaluated. 5.5 Measurement Model The extracted values of outer loadings, composite reliability (CR), and average variance extracted values (AVE) are used to assess convergent validity (Hair Jr et al., 2021; Hair Jr et al., 2017). In this study, all of the outer loadings in Table 1 and in Figure 2 were more than the cut-off value of 0.7 as per recommendation (Hair Jr et al., 2021; Hair Jr et al., 2017). These findings indicated that item reliability was satisfactory. All Cronbach's alpha (CA), rho A, and CR values were more than 0.7, indicating satisfactory internal consistency as suggested (Hair Jr et al., 2021; Hair
  • 15. 9 http://ijlter.org/index.php/ijlter Jr et al., 2017). The AVE values more than the cut off value of 0.5 were considered. Convergent validity was confirmed with acceptable item reliability, AVE, and internal consistency (Hair Jr et al., 2021). Table 1: Measurement Model Construct Indicator Loadings CA rho_A CR AVE ATA ATT1 0.868 0.919 0.920 0.943 0.805 ATT2 0.885 ATT3 0.918 ATT4 0.916 COMP COMP1 0.938 0.847 0.853 0.929 0.867 COMP2 0.923 PEOU PEOU1 0.846 0.852 0.856 0.900 0.692 PEOU2 0.853 PEOU3 0.833 PEOU4 0.795 PU PU1 0.759 0.855 0.869 0.901 0.696 PU2 0.796 PU3 0.890 PU4 0.885 QUIL QUIL1 0.909 0.758 0.765 0.892 0.805 QUIL2 0.885 TTF TTF1 0.910 0.804 0.806 0.911 0.836 TTF2 0.919 USAGE USAGE1 0.930 0.936 0.943 0.952 0.801 USAGE2 0.756 USAGE3 0.934 USAGE4 0.906 USAGE5 0.937 U_SAT U_SAT1 0.829 0.750 0.904 0.882 0.790 U_SAT2 0.945 The Fornell-Larcker criterion is used to assess discriminant validity (Hair Jr et al., 2017). Table 2 demonstrates that the square root of each latent variable's AVE value was greater than the latent variable's strongest correlation with any other latent variable, as stated by Hair Jr, et al. (2021). The findings revealed that each construct can be distinguished from any other construct in the model. Table 2: Fornell-Larcker criterion ATT COMP PEOU PU QUIL TTF USAGE U_SAT ATT 0.897 COMP 0.680 0.931 PEOU 0.427 0.510 0.832 PU 0.614 0.518 0.359 0.834 QUIL 0.607 0.574 0.525 0.610 0.897 TTF 0.669 0.762 0.463 0.483 0.532 0.915
  • 16. 10 http://ijlter.org/index.php/ijlter USAGE 0.838 0.691 0.504 0.527 0.616 0.687 0.895 U_SAT 0.383 0.228 0.166 0.497 0.461 0.349 0.309 0.889 5.6 Structural model After the measurement model's appropriateness was confirmed, the structural model was evaluated. The four-step structural model assessment by Hair Jr et al. (2021) was used in this study. The first phase, according to Hair Jr et al. (2021), is to examine the structural model for collinearity, followed by the importance and relevance of the path coefficients, the model's explanatory power, and finally the model's predictive power. The variance inflation factor (VIF) values were utilized to test the measurement model's collinearity. Table 3 shows that all the VIF values were lower than four, indicating that the model had no collinearity issues (Hair Jr et al., 2021). The bootstrapping approach (with 5000 subsamples) was used to determine the relevance of the path coefficients. The results from Table 3 show that out of 14 hypotheses tested five were rejected, while nine were accepted. The rejected hypotheses were having p-values greater than 0.05 and a t-value less than 1.96. The rejected paths are COMP to USAGE (β = 0.102, p > 0.05), PEOU to ATT (β = 0.086, p > 0.05), PU to USAGE (β = - 0.031, p > 0.05), PEOU to TTF (β = 0.080, p > 0.05), and QUIL to TTF (β = 0.029, p > 0.05). The nine paths which were supported by data are TTF to PU (β = 0.403, p < 0.05), TTF to USAGE (β = 0.136, p < 0.05), TTF to ATT (β = 0.454, p < 0.05), PU to ATT (β = 0.364, p < 0.05), COMP to TTF (β = 0.665, p < 0.05), PEOU to USAGE (β = 0.125, p < 0.05), PEOU to PU (β = 0.173, p < 0.05), U_SAT to TTF (β = 0.685, p < 0.05), and ATT to USAGE (β = 0.642, p < 0.05). Table 3: Structural model Path Std Beta Std Error T- Statistics P- Values Decision f- squared VIF ATT -> USAGE 0.642 0.051 12.679 0.000 Accepted 0.671 2.452 COMP -> TTF 0.665 0.052 12.878 0.000 Accepted 0.708 1.640 COMP -> USAGE 0.102 0.075 1.361 0.174 Rejected 0.014 2.907 PEOU -> ATT 0.086 0.066 1.303 0.193 Rejected 0.013 1.313 PEOU -> PU 0.173 0.073 2.359 0.019 Accepted 0.031 1.273 PEOU -> TTF 0.080 0.055 1.460 0.145 Rejected 0.011 1.528 PEOU -> USAGE 0.125 0.058 2.145 0.032 Accepted 0.045 1.397 PU -> ATT 0.364 0.071 5.129 0.000 Accepted 0.225 1.345 PU -> USAGE -0.031 0.044 0.688 0.492 Rejected 0.002 1.667 QUIL -> TTF 0.029 0.071 0.413 0.680 Rejected 0.001 2.028 TTF -> ATT 0.454 0.065 6.975 0.000 Accepted 0.316 1.492 TTF -> PU 0.403 0.071 5.679 0.000 Accepted 0.172 1.273 TTF -> USAGE 0.136 0.055 2.496 0.013 Accepted 0.028 2.679 U_SAT -> TTF 0.171 0.055 3.083 0.002 Accepted 0.059 1.284
  • 17. 11 http://ijlter.org/index.php/ijlter The model's explanatory power was assessed using the coefficient of determination (R-squared) and effect size (f-squared) values. According to Chin (1998), R-squared values of 0.19, 0.33, and 0.67 represent a weak, moderate, and substantial level of accuracy, respectively. Figure 2 shows that ATT, PU, TTF, and USAGE had R-squared values of 0.564, 0.257, 0.619, and 0.749, respectively. PU's R-squared value (0.257) is considered weak (Chin, 1998). The R-squared values of ATT and TTF were moderate, while USAGE's R-squared value was substantial (Chin, 1998). These results show that the total contribution of predictors; COM, PEOU, PU, QUIL, TTF, U_SAT, and ATT on the explained variance of USAGE is 74.9%. Figure 2 shows that QUIL and U_SAT are predictors of TTF. COM is a predictor of TTF and they both influence USAGE. PEOU is a determinant of PU, ATT, TTF, and USAGE. ATT is influenced by PU and TTF. PU and ATT predict USAGE. Figure 2: Structural model The f-squared values of 0.02, 0.15, and 0.35, according to Chin (1998), correspond to effect sizes of small, medium, and large, respectively. The f-squared value of PEOU to PU (0.031), TTF to USAGE (0.028), and U_SAT to TTF (0.059) are all considered small, as seen in Table 3. TTF to PU (0.172), TTF to ATT (0.316), and PU to ATT (0.256) all have a medium effect size while the effect size of ATT to USAGE (0.671) and COMP to TTF (0.708) are considered large.
  • 18. 12 http://ijlter.org/index.php/ijlter The Stone-Geisser’s Q-squared statistic was used to assess the model’s predictive power. The endogenous variables ATT, PU, TTF, and USAGE obtained Q-squared values of 0.448, 0.173, 0.503, and 0.593, respectively. All the Q-squared values were greater than zero, indicating that the model's predictive significance was adequate (Hair Jr et al., 2017). This means that the predictors COMP, PEOU, PU, ATT, PEOU, QUIL, and U SAT can be used to forecast the use of GeoGebra to teach circle theorems to rural Eswatini pre-service teachers. 6. Discussion The primary goal of this research was to explore the factors that influence Eswatini pre-service teachers' acceptance of GeoGebra in the learning of circle theorems. This has been accomplished by combining the technology acceptance model and task technology fit. The hybrid model explained 74.9% of the variance in Eswatini pre-service teachers' acceptance of GeoGebra in the learning of circle theorems. This suggests that variables such as task-technology fit, system quality, system compatibility, perceived ease of use, perceived usefulness, perceived attitude toward, and user satisfaction accounted for 74.9% of the total variance. All the Q-squared values were greater than zero, indicating that the model can be used to predict Eswatini pre-service teachers' acceptance of GeoGebra in the learning of circle theorems. This study demonstrated that rural Eswatini pre-service teachers' perceived attitude towards GeoGebra for learning circle theorems influences their actual use. This is consistent with previous research (Aman et al., 2020; Eksail & Afari, 2019; Teo et al., 2009; Teo et al., 2008). This supports Mutambara and Bayaga's (2020a) claim that increasing teachers' attitudes toward the use of technology in learning improves its actual utilization. One probable reason for this finding is that Eswatini pre-service teachers realized that GeoGebra can help them to perform better on circle theorems. Furthermore, the usability of GeoGebra promotes rural Eswatini pre-service teachers' positive attitude towards the GeoGebra adaptive technology. Rural Eswatini pre-service teachers’ perceived ease of use of GeoGebra for learning circle theorems does not influence their perceived attitude towards actual use. These findings are surprising given the body of knowledge's widespread belief that perceived ease of use influences perceived attitude (Mutambara & Bayaga, 2021; Sánchez-Prieto et al., 2019; Teo & Milutinovic, 2015) and actual use (Sánchez-Prieto et al., 2019). These results were also in contradiction with the findings of Kalogiannakis and Papadakis (2019), who discovered that pre-service teachers' perceived ease of use influences their perceived attitude towards the use of ICT in education. Two possible explanations for these findings are the timing of data collection for this study and that the survey was conducted after the pre-service teachers had completed their post-test. This suggests that the pre-service teachers were already accustomed to the use of GeoGebra in the learning of circle theorems, since the effect of perceived ease of use diminishes with practice (Mutambara & Bayaga, 2020c). The survey was conducted when the pre-service teachers had already been subjected to, and were familiar with, GeoGebra. Additionally, rural Eswatini pre-service teachers perceived the use of GeoGebra as simple for learning circle theorems.
  • 19. 13 http://ijlter.org/index.php/ijlter Task technology fit was found to influence actual use, perceived usefulness, and perceived attitude towards. These results support prior studies who reported a positive influence of task technology fit on perceived usefulness (Gharbawi & Bassam, 2016), perceived attitude towards (Alamri et al., 2020; Gan et al., 2017), and actual use (Glowalla & Sunyaev, 2014; Isaac et al., 2019). The ability of GeoGebra to experiment with circles to improve cognition in circle theorems influences the attitude of rural Eswatini pre-service teachers towards GeoGebra. These findings suggest that the ability of GeoGebra to fit and enhance cognition in circle theorems influenced rural Eswatini pre-service teachers' attitude towards it and the decision to use GeoGebra. Task technology fit is a major factor in explaining job performance levels (Goodhue & Thompson, 1995). Rural Eswatini pre-service teachers realized that GeoGebra can improve their performance in circle theorems, which increases their decision to use it. Task technology fit also played a very important mediating role between actual use and its predictors; user satisfaction and system compatibility. This finding implies that the extent to which GeoGebra is perceived to line up with the immediate requirements, values, and prior experiences of rural Eswatini pre- service teachers is insufficient to directly influence the use of GeoGebra, but it does contribute through the task technology fit. Congruent to the findings of Kalogiannakis and Papadakis (2019) and Joo et al. (2018), their study discovered that the perceived usefulness of GeoGebra for learning circle theorems had a positive impact on the perceived attitude of rural Eswatini pre-service teachers. The findings are also in line with those of Bhattarai and Maharjan (2020), who discovered that pre-service teachers' intention to use technology in class is influenced by their belief that it improves their performance. A reasonable explanation for this finding is that rural Eswatini pre-service teachers discovered that they can easily manipulate objects inside circles after using GeoGebra when learning circle theorems. This can improve their comprehension of circle theorems. Hence, GeoGebra's ability to improve rural Eswatini pre-service teachers' circle theorem cognition improves their attitude towards it. Rural Eswatini pre-service teachers' actual use of GeoGebra for learning circle theorems is unaffected by their perceived usefulness. These findings contradict those of Lin and Huang (2008) and Yang (2007), who found that the utility of technology influences its use by pre-service teachers. The findings of this study were unexpected, given that rural Eswatini pre-service teachers had previously used GeoGebra, and found it useful for learning circle theorems. One would expect GeoGebra's utility to have an impact on its actual use. 6.1 Theoretical Implications The present study adds to the existing literature in five ways. First, the study provides empirical evidence that, despite the fact that the technology acceptance model was developed three decades ago (Davis et al., 1989), it can still be used to predict users’ acceptance of technology. Second, this study confirms that adding external variables that are context related improves the TAM's explanatory power (Venkatesh et al., 2003). In this study, the task technology fit, system quality, system compatibility, and user satisfaction added to the explanatory power of the TAM.
  • 20. 14 http://ijlter.org/index.php/ijlter Third, this work adds to the body of knowledge by constructing a hybrid model for predicting the rural Eswatini pre-service teachers’ acceptance of GeoGebra by extending the technology acceptance model. This would be a significant contribution to the acceptance of educational technology in developing countries, given that most researches to date were carried out in developed countries. Fourth, the findings of the study showed that perceived attitude towards the use of GeoGebra for learning circle theorems was the strongest direct predictor of actual use by rural Eswatini pre-service teachers. This implies that the attitudes of rural pre-service teachers towards GeoGebra play an important role in its actual use to improve the cognition of circle theorems. Fifth, the original technology acceptance model and technology task fit model have been applied in an educational context, and they have demonstrated that the two models can be combined to explain the actual use of technology in an educational context. This is useful for other researchers who are interested in developing conceptual frameworks for investigating the acceptance and use of electronic-learning technology in their educational contexts. 6.2 Practical Contributions This study and its results have several practical implications. First, in practice, this research has contributed to a better understanding of the factors that can help or hinder the successful implementation of GeoGebra for learning circle theorems in rural Eswatini colleges. These factors can assist Eswatini teacher training institutions, researchers, and educational learning application-developers in creating successful educational learning applications. This is especially true in the context of African countries and other developing countries, where the situation in teacher education institutions is similar to that of Eswatini. Second, this study discovered that user satisfaction and system compatibility are good predictors of technology task fit and through this finding, it can be implied that an educational learning application should be technically sound, flexible, and sophisticated in order for users to want to reuse it. This discovery assists educational learning application developers in inventing educational learning applications that are technically sound, flexible, and sophisticated, as this will improve their actual use. Third, perceived attitude towards actual GeoGebra use was discovered to be the best predictor of actual use. Additionally, perceived attitude towards use was likewise discovered to play a critical mediating role between perceived usefulness and actual use. This finding implies that, for educational learning applications to be successfully implemented in Eswatini teacher training institutions, pre-service teachers' attitude towards technology integration in education should be positive. This discovery assists Eswatini teacher training institutions and researchers in determining factors that influence pre-service teachers' perceived attitude towards technology integration in education. According to the findings of this study, perceived usefulness and technology task fit accounts for 56.4 % of the variance in perceived attitude towards use. It is critical for researchers to identify additional factors that influence pre-service teachers' attitude towards technology integration, as this plays a significant role in its actual use.
  • 21. 15 http://ijlter.org/index.php/ijlter 6.3 Limitation of the study This study was conducted at one institution of higher learning in one developing country. Hence, the generalizability of the results may need to be applied with caution. 7. Conclusion The study's goal was to identify the factors that influence rural Eswatini pre- service teachers' use of GeoGebra in learning circle theorems. The study suggested a novel model to explain the use of GeoGebra for learning circle theorems. The model was created by incorporating the task technology fit into the technology acceptance model. A questionnaire was used to collect data. Partial least squares- structural equation modeling was used to analyze the data. The model accounted for 74.9% of the variance in rural Eswatini pre-service teachers' use of GeoGebra for learning circle theorems. The study found that perceived attitude towards use, perceived ease of use, and technology task fit all had a direct impact on the actual use of GeoGebra for learning circle theorems. However, perceived usefulness was found to have an indirect effect on actual use via the mediating effect of perceived attitude towards use. The influence of user satisfaction and system compatibility on actual use was mediated by the task technology fit construct. It is critical for researchers to identify additional factors that influence pre-service teachers' attitudes towards technology integration in teaching and learning, as this plays a significant role in its actual use. 8. References Adeniji, S. M., Ameen, S. K., Dambatta, B., & Orilonise, R. (2018). Effect of Mastery Learning Approach on Senior School Students' Academic Performance and Retention in Circle Geometry. International Journal of Instruction, 11(4), 951-962. https://eric.ed.gov/?id=EJ1191669 Adhikari, K. P. (2021). GeoGebra integrated instruction: Effectiveness and empowerment. Siddhajyoti Interdisciplinary Journal, 2(01), 1-9. https://doi.org/10.3126/sij.v2i01.39197 Adolphus, T. (2011). Problems of teaching and learning of geometry in secondary schools in Rivers State, Nigeria. International Journal of Emerging Sciences, 1(2), 143-152. https://www.stir.ac.uk/research/hub/publication/510419 Alamri, M. M., Almaiah, M. A., & Al-Rahmi, W. M. (2020). The Role of Compatibility and Task-Technology Fit (TTF): On Social Networking Applications (SNAs) Usage as Sustainability in Higher Education. IEEE Access, 8, 161668-161681. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9186601 Aldholay, A. H., Abdullah, Z., Ramayah, T., Isaac, O., & Mutahar, A. M. (2018). Online learning usage and performance among students within public universities in Yemen. International Journal of Services and Standards, 12(2), 163-179. https://www.learntechlib.org/p/209952/ Aman, A., Prasojo, L. D., Sofwan, M., Mukminin, A., Habibi, A., & Yaqin, L. N. (2020). Factors affecting indonesian pre-service teachers’ use of m-LMS: A mix method study. International Journal of Interactive Mobile Technologies (iJIM), 14(06), 137-147. DOI: https://doi.org/10.3991/ijim.v14i06.12035 Amevor, G., & Bayaga, A. (2021). Assessing the Impact of Dynamic Software Environments (MATLAB) on Rural-Based Pre-Service Teachers' Spatial- Visualisation Skills. Contemporary Educational Technology, 13(4). https://doi.org/10.30935/cedtech/11235
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  • 27. 21 ©Authors This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). International Journal of Learning, Teaching and Educational Research Vol. 21, No. 12, pp. 21-43, December 2022 https://doi.org/10.26803/ijlter.21.12.2 Received Aug 10, 2022; Revised Nov 23, 2022; Accepted Dec 17, 2022 Exploring the Impact of Enquiry-Based Instructional Strategies on Students’ Attitudes towards Biology Henriette Manishimwe African Centre of Excellence for Innovative Teaching and Learning Mathematics and Science (ACEITLMS), University of Rwanda College of Education (URCE), Rwamagana, Rwanda William Aino Shivoga Department of Biological Sciences, School of Natural Sciences, Masinde Muliro University of Science and Technology (MMUST), Kakamega, Kenya Venuste Nsengimana Department of Mathematics, Science and Physical Education, School of Education, University of Rwanda College of Education (URCE), PO BOX 55 Rwamagana, Rwanda Abstract. Teaching methods dominated by teacher demonstration, chalk and talk, have been attributed as the main source of negative attitudes towards biology. This study aimed to explore the impact of enquiry-based learning on students’ attitudes towards biology. The study comprised 228 students purposely selected from six secondary schools. Focus-roup discussions were used to collect qualitative data with a phenomenological design. Six groups were probed with interview questions, three on the side of the experimental group and three on the side of the group subjected to conventional teaching methods. The data were analysed by using NVIVO software, and later, content analysis was employed descriptively. The study's findings revealed an extensive impact of enquiry-based learning on enhancing students’ attitudes towards biology. Moreover, a remarkable commitment was identified on the side of the experimental group, while exploring biological concepts in their groups. Difficulties, such as insufficient laboratory activities, lack of planning for practical laboratory skills, and the inability to grasp the scientific names of micro-organisms were identified. Learners proposed ways of improving teaching and learning biology, such as providing learning resources, extra time to explore the biological content, more laboratory practical work, access to ICT tools, field studies, and the need for active learning methods. More support in active learning was requested on the side of the control group. The students subjected to
  • 28. 22 http://ijlter.org/index.php/ijlter enquiry instructions improved their attitude towards biology. Further studies can adopt in-depth interviews, in order to gain more information. Keywords: Enquiry-based instructions; biology course; phenomenological method; students’ attitude 1. Introduction Teaching methods play an important role in science to promote learning outcomes, where the attitude of learners helps students to manifest behaviours and interests in a particular subject (Adejimi et al., 2022). Nevertheless, teaching methods dominated by a teacher with teacher’s demonstration and chalk and talk have been attributed to the main source of problems that affect students’ learning outcomes, including negative attitudes towards science, including biology (Bizimana et al., 2022). To date, active learning methods are being recommended for teaching and learning biology. Active learning methods are considered to be instructional approaches that allow learners to play a part in their learning, while using resources for knowledge construction (Lombardi et al., 2021; Harris et al., 2020). It helps to attain the most learning outcomes; and it facilitates students’ interactions. In this regard, science education and trends that advocate the integration of innovative teaching techniques, such as co-operative learning methods, concept mapping, and enquiry-based learning that engages learners in the learning process and are learner-centered (Dotimineli & Mawardi, 2021). The benefits of implementing active teaching strategies were reported in a number of studies. In this vein, optimal performance, high motivation, and interest in learning biology were pointed out, among others (Chidubem & Adewunmi, 2020; Rabgay, 2018; Erbas & Demirer, 2019; Dorfner et al., 2018). Consequently, the attitude towards learning biology was improved. Enquiry-based learning methods were identified as one of the instructional strategies that reflect the active learning method (Khalaf & Zin, 2018). In this regard, occasions are furnished for students to explore their concepts and resources bestowed. With enquiry-based instruction, questions are posed to the students, and time is given to find solutions with their peers by using the available resources. Given this opportunity to grasp concepts themselves, their thinking skills are upgraded (Kang & Keinonen, 2018). Collaboration between students is more motivated, which produces more skills and knowledge of a particular concept. Thus, their attitude towards learning science subjects is improved (Manishimwe et al., 2022). In relation to biology, the teaching and learning of biology have been characterised by poor teaching methods dominated by the teacher (Chidubem & Adewunmi, 2020; Kareem, 2018). Moreover, it has been marked by a lack of resources, insufficient laboratory activities, biological terminologies, and insufficient time cited, among others (Byukusenge et al., 2022; Island et al., 2022; Chidubem & Adewunmi, 2020). Therefore, instructional strategies that provide an engaging learning environment were scarce, and consequently the attitude of students towards biology was not satisfactory. With this background, the present
  • 29. 23 http://ijlter.org/index.php/ijlter study was conceived, in order to explore the effect of active learning methods, such as enquiry-based learning, in order to improve students’ attitudes towards biology. Biology is an enormous subject with different subjects, from secondary level to university. Amidst biology lessons, microbiology is a fundamental subject that gives basic knowledge about micro-organisms,the diseases they cause, and the ways of prevention (Mukagihana et al., 2021). On top of that, it brings forth some useful aspects of micro-organisms with respect to economic importance. A number of studies have been done on microbiology teaching and learning (Cheng et al., 2022; Mukagihana et al., 2021; Cox & Simpson, 2018). Most of them were conducted at the university level. However, there was a deficit in the literature about microbiology at the secondary school level. This study investigates the effect of enquiry-based learning on improving students’ attitudes towards biology, particularly in microbiological subjects. Studies reported the influence of conventional teaching methods on students’ learning of biology. It was observed that poor teaching methods make biology courses abstract; and they do not promote students’ commitment to playing any role in the learning process (Akinbadewa & Sofowora, 2020; Harris et al., 2020). Students became less involved in the lesson, relying on teachers’ information; and they consider biology boring (Chidubem & Adewunmi, 2020). Consequently, their interest in learning biology decreases, and they develop a negative attitude towards biology. There is a need to evaluate how active learning methods, such as enquiry methods, raise students’ commitment to exploring biological concepts and improve students’ attitudes towards biology. In the light of the effect of enquiry-based learning on students’ attitudes towards science, specifically in biology, studies with mixed research methods were rare. This research will contribute to the existing literature by evaluating the effect of enquiry-based learning on students’ attitudes towards biology, with a focus- group discussion to enrich the research with deep qualitative data ,which provide detailed and accurate information. Specifically, students’ attitudes towards biology at a higher level were less highlighted in Rwanda. The findings of this study may be useful in disclosing the difficulties that students encountered in learning biology and suggesting ways of improving. The study answered the following research questions: 1) What are the effects of enquiry-based instructional strategies on students’ attitudes towards biology? 2) How was the commitment of students to exploring biological concepts? 3) What are the difficulties in learning biological concepts? 4) What are the factors that could improve the teaching and learning of biology? The Theoretical Framework Basically, the teaching method is established in the constructivism theory of learning. In the constructivist learning environment; students are engaged in the lesson; and they play a considerable role in knowledge construction (Anagün, 2018; Fuchsova & Korenova, 2019). Teachers’ support is subsidiary to learners’ effortts during the lesson (Rogayan, 2019). In the learning process, students use
  • 30. 24 http://ijlter.org/index.php/ijlter their previous knowledge and their past experience, in order to understand any new notions (Musengimana et al., 2022). Social constructivism underpins the study concerning students’ learning in the social domain, as well as integrating knowledge at the individual level (Xu & Shi, 2018). 2. The Methodology 2.1.The Research design A qualitative phenomenological method was employed to collect the qualitative data with focus groups. This method was chosen because it provides people’s understanding and experience (Dahlin et al., 2012). A qualitative research approach was employed in the study, due to the quality of the data that it displays (Moretti et al., 2011).In this perspective, focus-group discussion was chosen because it creates an opportunity for sharing experiences; and it suits phenomenological research design. 2.2.The Sampling design The population of this study comprises 1216 students studying biology at the upper secondary-school level in senior four. The schools concerned in the study are in Kigali City (Kicukiro district) and the southern province (Kamonyi and Muhanga districts) of Rwanda. The selection was based on the availability of teaching resources to compare schools with the same standards, so that the effect of the intervention could be traced. Having mathematics, chemistry, and biology (MCB) as subject combinations at the senior four secondary levels was also another considered criterion for selection. Moreover, the schools to be selected should have both male and female students. Thus, the sample size for this study conaisted of six schools. Since the average classroom size in one class in the selected districts in the Rwandan context is 38, for six schools, 228 students participated in the study (Ministry of Education, 2018). One of two schools in each district served as the control group, while another from two schools in each district served as the experimental group. Students to participate in the focus-group discussions were chosen deliberately, based on students who were able to respond to the questions, and on gender balance. Using four to eight people in a focus-group interview is recommended. Thus, six students per class participated in this research. After one round of interviews,the data were saturated; and we could not take any other groups. 2.3 The Research Instrument The instrument was made up of six open-ended questions (See Box 2.1) reflecting students’ attitudes towards learning biology, from broad to specific questions. The questionnaire was reviewed by experts in science education at the University of Rwanda College of Education (URCE), in order to ensure the trustworthiness of the instruments. Interviews scheduled were subjected to consultations with other researchers, in order to contribute in making themes to ensure credibility. Dependability was considered to maintain the consistency of the instrument, the transferability for the generalisability of the findings was employed, and conformability was thereby ensured. Questions were put to the entire group, giving equal opportunities to all the participants to share their experiences freely.
  • 31. 25 http://ijlter.org/index.php/ijlter The first author played the role of moderator, guiding the conversation and preventing divergence from the main objective of the conversation, and avoiding influencing the participants’ responses, in order to ensure the confirmability of the data collected. The research assistant took notes of the major points during the discussions and examined the consistency of the process. Box 1. Key Questions Used in Interviewing Students via Focus-Group Discussions FOCUS-GROUP DISCUSSIONS 1. What did you learn in the lesson we had last time? 2. What specifically did you like in the lesson we had last time? 3. How did the teaching methodology used in the lesson help you to learn new things? 4. How committed were you while exploring biological concepts in groups? 5. In what ways do you think biology would help you to understand other science subjects? 6. (a) Did you find any difficulties in learning some of the concepts in the lesson we had? (b) Can you tell me anything you think could help to improve the teaching and learning of biology? 2.4. Data-collection procedures Before the data collection, an ethical clearance certificate was given by the research and innovation unit of the University of Rwanda - College of Education. The purpose and procedures of the research were explained to the participants, and they willingly agreed to participate in the study; and they signed a consent form. The research was conducted from April to June of the 2021 school year; and the intervention took four weeks. The purpose of the intervention was to compare the achievements and attitudes of the students subjected to enquiry-based instructions and the achievement and attitude of students taught by the conventional teaching methods group. Since the achievement tests indicated poor performance on the side of control, achievement correlates with attitude. The idea was to determine the impact of enquiry-based instructional strategies to improve the attitude towards biology. For three days the workshop was conducted with the teachers of the experimental group on the enquiry-based learning method early in April of the 2021 school year, before embarking on microbiology teaching. On the other hand, teachers explained the purpose of the research and delivered their biology lessons as usual. Permission to record the discussions was requested prior to starting the discussions. Six students per class were selected to participate in the focus-group discussion after the teaching intervention, and gender balance was considered. A treatment of enquiry-based learning, designed by the 5Es instructional model, was given to the experimental group, and a conventional teaching method was on the side of the control group. The microbiology lesson was taught to all the groups. On the side of the experimental group, the students were taught with enquiry- based learning methods. The learning takes place in a social context by interacting with their peers in their respective groups in the company of teaching and learning materials. Gender balance was maintained, as male and female students
  • 32. 26 http://ijlter.org/index.php/ijlter participated equally in the learning process. Assessments occurred at the end of the lesson. Consequently, students’ attitudes are polished, due to their active participation and social interactions while acquiring knowledge. Inversely, the control group underwent their accustomed teaching methods dominated by teachers’ knowledge derived and summative assessment prevailed. After intervention and achievement tests, the students from all the groups were subjected to focus-group discussions on examining their attitudes towards biology. These focus-group discussions were administered in the last two weeks of June. Since it was impossible to conduct interviews with all the students of the entire class, six students were selected from each class: three males and three females. 2.5. Analysis and Data Presentation The interviews were recorded and transcribed in Microsoft Word. The data were transferred to NVIVO software for analysis. Deductive data analysis (Orodho et al., 2016) was employed from specific observation of the students’ views to general conclusions. The major themes were predetermined. These were remembering what was learnt, what students liked in the lesson, the characteristics of the method used, group-work activities, the relationship between biology and other subjects, difficulties faced during learning, and ways of improving. Transcripts were first imported into NVIVO files, followed by the set-up of a coding table, based on the emerged themes and categories. The software coded the transcripts and analysed them. Finally, content analysis was made with major themes and their frequencies. Figure 1 shows the data entry and outlook of NVIVO. Figure 1. Our data in NVIVO While Figure 1 shows our files entered in NVIVO software, Figure 2 shows an example of the relationship of the codes extracted from the files in both the control and the experimental groups of the students.
  • 33. 27 http://ijlter.org/index.php/ijlter Figure 2. Comparison group between control and experimental groups at school-1 Under each theme, we selected all the codes; and via the “visualised” option, we selected chart coding by the attributed value. Under the chart-item box, we selected the relevant codes, as well as our teaching-intervention groups under the x-axis attribute. We obtained an unclear chart that did not clearly show the visibility of the percentage coverage of each of the control and experimental groups. We opened “summary” and exported the results into MS Excel 2016. From there, we appropriately designed the relevant figures. Table 1. Themes, extracted codes, and their references within source files Themes Codes Files References Remembering what was learned Categories of micro-organisms 3 4 Characteristics of micro- organisms 4 8 Culturing micro-organisms 3 11 Fermentation 3 6 Genetic engineering 1 1 The negative effect of bacteria 3 6 What students liked in the lesson Bacteria to make yogurt 1 1 Culturing micro-organisms 6 10 Diseases caused by viruses 6 18 Group discussion 1 1
  • 34. 28 http://ijlter.org/index.php/ijlter Micro-organisms used in agriculture 1 1 Micro-organisms used in medicine 1 1 Using microscope 1 2 Yeast to brew alcohol 3 4 Yeast to produce pieces of bread 1 1 Characteristics of the method used Group work 3 16 Laboratory 5 7 Research 3 6 Teacher demonstration 2 3 Teacher talk 2 3 Watching videos 2 3 Group-work activities Commitment 3 14 Enhancing understanding 6 13 Mutual work 3 3 Research 3 5 Room for self-expression 3 7 Self-preparedness 2 6 Self-study 3 3 Relationship between biology and other subjects Keep environment 1 1 No linkage 1 2 Others 4 10 Understanding the Chemistry 5 14 Difficulties faced during learning Drawing 1 1 Insufficient Laboratory activities 4 5 Scientific names 5 9 Time scarcity 2 3 Using a microscope 1 1 Ways of improvement Active learning methods 1 1 Need for field trips 1 2 Need of resources 5 13 Need for enough time 2 3 Practical work 3 7 Teacher support 1 1 3. The Results ❖ Remembering what was learnt When students were asked what they remembered after learning microbiology, the average percentage coverage for students in the experimental group was higher (68%) than in the control group (32%). Students that learned with the traditional method still remember the characteristics of micro-organisms and the
  • 35. 29 http://ijlter.org/index.php/ijlter negative effects of bacteria, while those taught with enquiry-based techniques still remembered the categories of micro-organisms, culturing micro-organisms, fermentation, and genetic engineering (Figure 3). Figure 3. Average of percentage coverage by “Remembering of what was learned” The learning was better in the experimental group than in the control group. For instance, students taught with the traditional method testified that they learned how micro-organisms are developed in agar-agar medium, which contains all the nutrients responsible for the growth of bacteria. They have also seen how yeast is grown and fermentation is made. One student said, “I also learned about viruses and how they can live in living organisms, I have learned the characteristics that make them living things. For example, they reproduce inside the host cells, and they cause diseases and characteristics that make them to be non-living thing;s since they do not reproduce outside the host cell, do not respond to stimuli, and do not feed.” Students that learned with enquiry-based learning (EBL) said that they have seen how bacteria can cause diseases, how bacteria can cause food spoilage, and how gram-staining techniques can differentiate bacteria. One student ascertained, “In microbiology study, we have seen how we can culture micro-organisms in medical research. For example, culturing bacteria staphylococcus for searching the role of penicillin as an antibiotic.” Another student was able to explain how micro-organisms can be cultured. She said, “This means that they can grow by using different methods. For example, suppose you want to grow the bacteria Tuberculosis. In that case, you can take a sample from the sinus of the patient affected by it and culture it in a Petri dish on a medium containing the necessary nutrients.” Students taught with EBL were certain to describe what they had learnt One student said, “We have learnt about bacteria in microbiology; there are Archaebacteria and Eubacteria; the first one has special characteristics, which are different from those of other bacteria; for example, they live in an extreme environment like living in a hot area (the bacteria), and the second ones are normal bacteria that can be categorised by gram- staining.” Another student said, “We learnt that some diseases are caused by micro- organisms. For example, Entamoeba Histolytica causes Amoebiasis as its symptoms, and 0% 20% 40% 60% 80% 100% 120% Categories of microorganisms Characteristics of microorganisms Culture microorganisms Fermentation Genetic engineering Negative effect of bacteria Overall Control group Experimental group
  • 36. 30 http://ijlter.org/index.php/ijlter preventive measures are required.” Students were aware that micro-organisms could not be seen with our eyes and that they are harmful and important to other living things. One student said, “The chemicals which harm them limit their usefulness to people. We have seen the application of microbiology in bread-making, and genetic engineering; and we have seen different categories of micro-organisms, such as algae, viruses, protozoa, and so forth.” ❖ What students liked in the lesson Four of the nine codes revealed under the “what students liked in the lesson” theme were depicted from experimental group-focus discussions. Two codes were found in the control group alone (how bacteria are used to produce yoghurt and how yeasts are used to produce bread). Both the control and the experimental groups (cultured micro-organisms, diseases caused by viruses, and how yeast is used to brew alcohol) shared three codes. These students liked the use of group discussion, and the way in which micro-organisms are used in agriculture and in medicine; and they enjoyed using the microscope. As shown in Figure 4, the overall liking of the lesson was in favour of those learnt with the EBL technique (experimental group students), with 58% alongside 42%. Figure 4. Average percentage coverage by “What students liked in the lesson.” Students are taught by traditional methods, like how yeast changes glucose into alcohol, how they culture micro-organisms, and the lesson about diseases caused by viruses. One student testified that he didn’t know that microbes could grow and how they cause diseases. The following are extracts from the students: “What I liked is the importance of bacteria and how they are used in making yoghurt, for I like it. I knew that they decompose glucose into lactic acid.” “As we were studying micro-organisms, after seeing how Alexander Fleming cultured micro-organisms and found penicillin from Penicillium Notatum; it made me curious because I had a dream to be like him, and I 0% 20% 40% 60% 80% 100% 120% Bacteria to make yogurt Culture microorganisms Diseases caused by viruses Group discussion Microorganisms used in agriculture Microorganisms used in medicine Using microscope Yeast to brew alcohol Yeast to produce breads Overall Control group Experimental group
  • 37. 31 http://ijlter.org/index.php/ijlter want to invent something which is not known; that is what I liked in that lesson that made me interested in biology.” Students were surprised to see micro-organisms on the door they touched. So, they came to know that micro-organisms are everywhere. The lesson has inspired students to know and emphasise Coronavirus; as they testified that this pandemic is mainly found in microbiology; they have known the composition and shape of the Coronavirus, and how it causes Covid -19, and how to prevent this infection. Likewise, the students taught by EBL liked how micro-organisms are applied in our daily life. For example, how they are involved in making useful products like human insulin used to protect against diabetes. They also liked to see bacteria and other micro-organisms that help in agriculture; since they decompose organic matter in the soil to produce fertilisers, so that the soil can sustain growth. They liked the sterilisation techniques used before culturing micro-organisms, such as washing hands, cleaning working areas, and cleaning Petri dishes. Students testified that they learned the lesson about protozoa and how they could cause diseases; for example, they can cause malaria, which is dangerous to humans. The following are extracts from the students: “I liked how we can prevent diseases. I liked the topic of protozoa[ because it teaches me about different diseases and how we can prevent them, and how those diseases are spread. For example, we learned how Entamoeba Histolytica and plasmodium cause diseases, and the knowledge I got from this lesson helped me to -protect myself.” “We did the culture of micro-organisms as in industries and other laboratories. For me, I liked culturing micro-organisms, and we saw how they reach the stage to grow and reach the stage where they can reproduce and infect other organisms.” ❖ Characteristics of the methosds used Group work and watching videos were two teaching methods that the students in the experimental group described that were used in their class. Likewise, teacher demonstration and talk were mentioned by the students in the control group. Research and laboratory were used in both groups, but they were extensively used in the experimental group. The overall findings showed that the teaching methods used were more characterised by students that learned with EBL (56%) than those who learned by the traditional method (44%). Figure 5 visualises these results.
  • 38. 32 http://ijlter.org/index.php/ijlter Figure 5. Average percentage coverage by the “Characteristics of the method used” Ideas from students taught by traditional methods clearly show the use of teachers’ demonstration and talk. For instance, they testified that they didn’t know how to grow bacteria, but the teacher showed them how to grow them by using agar-agar. Their teacher told them how to prevent Escherichia Coli from being transmitted through faeces. Expression of the use of the laboratory was mentioned. One student said: “For me, a new thing I have learnt is laboratory equipment called an incubator; I didn’t know you can put microbes in it and grow them. It is like in a refrigerator. We tested micro- organisms in the laboratory by using a microscope; because they were too small; and without a microscope, we could not see them.” Students taught in the EBL method testified that group work encouraged them to do research and present their findings. This presentation then improved their communication skills. They said that when they were in groups, they acquired many skills because when they join in the group, they share some skills about the topic they are learning. Students appreciated the way they have acquired a leadership style. One student who was representative of his group concurred that he had to do everything to make a good presentation in front of the teacher. The following are extracts from students: “The method used in this unit is different from the other methods we are used to; as just the teacher went on the blackboard giving summaries; and the rest of the work is supposed to be done by the students. But this lesson on microbiology was different; everybody was to put together everything we had got. This unit involves much effort between the teacher and the students. The teacher brings his ownis ideas, and the students bring their own ideas, and they compare these; and perfect ideas were consequently formed.” “When you are not in groups, sometimes you get scared, ‘saying may I ask this question’; but when you are in a group with your group members, 0% 20% 40% 60% 80% 100% 120% Group work Laboratory Research Teacher demonstration Teacher talk Watching videos Overall Control group Experimental group
  • 39. 33 http://ijlter.org/index.php/ijlter you are free to talk to them; you won’t fear, we would ask a question; he or she would answer, or ask the teacher; so, ithis builds confidence in us.” Many students appreciated the research. They said they learned how to use the internet in a study because they accessed the internet, in order to study the lifecycles of some bacteria. They realised that the internet is not for entertainment only; but it can also be used in class. One student concurred: “I didn’t know some life ycles of some organisms; they helped me to get more about them, and I went to a computer lab and we did something practical, like the lifecycle of Amoebiasis and how it’s going through it.’ This was quite awesome; but it was enjoyable.” ❖ Group-work activities Related to activities used in group-work, students in the experimental group said that group work increased their commitment to engage in different activities; they developed mutual work; as it allowed them to work together, where each one could contribute to the task given; it allowed them to do research before presenting their findings, they became self-prepared. They were then able to learn by themselves (self-study). The overall group work activity (see Figure 6) was found to be on the side of students that had learnt with EBL (81%). Figure 6. Average of percentage coverage by “Group work activities.” Although group-work was not extensively used in the control group; the little that it was used, students taught by the traditional method applied to it. For instance, one student said that her role in the group was to give an idea as a group member, knowing that this would help all the members. Another student agreed that when they are grouped together with others, it is better than when one is studying alone, for we can then understand more. The following is an extract from one of the students: “In our group, we used groups at the beginning of the topic; then the teacher gives us a topic, and we discussed it in our group, and everyone in the group participates and gives his idea rs her idea about it a it, and how he/she thinks; and thereafter the teacher comes and supplements this as a group, in order to reach a common understanding in the whole class.” 0% 20% 40% 60% 80% 100% 120% Commitment Enhancing understanding Mutual work Research Room for self-expression Self-preparedness Self-study Overall Control group Experimental group