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IJLTER.ORG Vol 20 No 6 June 2021

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The sudden shift from physical classroom education towards emergency remote teaching (ERT) in higher education during the unprecedented global pandemic caused an abrupt change in the learning environment for students and educators alike. The disruptive overnight change and conversion of entire courses to emergency remote teaching caused concern for not only educators, but also students that had little time to adapt to the new circumstances. While the embedment of technologies in the classroom is not a new concept, this quantitative research expands a case study that sought to examine the perceived satisfaction of undergraduate students with the emerging paradigm of ERT. Responses based on empirical data (n=450) as well as secondary data (n=219) were analyzed to conclude that, in particular, younger freshmen students struggled more with online emergency remote teaching than their older peers. Furthermore, the study identified numerous similarities between both data samples. The current research informs educators about student perceptions and preferences during these extraordinary circumstances of uncertain duration. Furthermore, the paper concludes with recommendations that aim to provide institutions and educators with practical guidance on how to tackle the outlined issues.

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International Journal
of
Learning, Teaching
And
Educational Research
p-ISSN:
1694-2493
e-ISSN:
1694-2116
IJLTER.ORG
Vol.20 No.6
International Journal of Learning, Teaching and Educational Research
(IJLTER)
Vol. 20, No. 6 (June 2021)
Print version: 1694-2493
Online version: 1694-2116
IJLTER
International Journal of Learning, Teaching and Educational Research (IJLTER)
Vol. 20, No. 6
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
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.
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 June 2021 Issue
VOLUME 20 NUMBER 6 June 2021
Table of Contents
Perceived Satisfaction of Emergency Remote Teaching: More Evidence from Thailand..............................................1
Kevin Fuchs
An Emergency Shift to e-Learning in Health Professions Education: A Comparative Study of Perspectives
between Students and Instructors ......................................................................................................................................16
Afrah Almuwais, Samiah Alqabbani, Nada Benajiba, Fatmah Almoayad
Impulsing the Development of Students' Competency Related to Mathematical Thinking and Reasoning through
Teaching Straight-Line Equations.......................................................................................................................................38
Bui Phuong Uyen, Lu Kim Ngan, Nguyen Phuong Thao, Duong Huu Tong
Exploring Effective Practices in Managing Distance Learning for Teaching Art and Design in Bahrain................. 66
Sama'a Al Hashimi
Improving Novice Students’ Computational Thinking Skills by Problem-Solving and Metacognitive Techniques
.................................................................................................................................................................................................88
Nor Hasbiah Ubaidullah, Zulkifley Mohamed, Jamilah Hamid, Suliana Sulaiman, Rahmah Lob Yussof
Examining Saudi Students’ Perceptions on the Use of the Blackboard Platform during the COVID-19 Pandemic
............................................................................................................................................................................................... 109
Elham Alzain
A Bibliometric Analysis of Blended Learning in Higher Education: Perception, Achievement and Engagement
............................................................................................................................................................................................... 126
Arumugam Raman, Raamani Thannimalai, Yahya Don, Mohan Rathakrishnan
The Role of Nurturing Technopreneurship Education and Building University Students’ Entrepreneurial
Mindsets and Skill Sets in Fostering Digital Innovation and Augmenting the Tech Start-Up Ecosystem in Bahrain
............................................................................................................................................................................................... 152
Sama'a Al Hashimi, Yasmina Zaki, Ameena Al Muwali, Nasser Mahdi
British National Corpus in English Language Teaching of University Students....................................................... 174
Nataliia Bober, Yan Kapranov, Anna Kukarina, Tetiana Tron, Tamara Nasalevych
Emerging Trends in Metaphoric Images of Curriculum Reform Implementation in Schools: A Critical Literature
Review.................................................................................................................................................................................. 194
Godsend T. Chimbi, Loyiso C. Jita
Is Decentralisation a Suitable Response to Improve South African Rural Education?.............................................. 211
Kevin Teise, Emma Barnett
Qualitative Content Analysis of Teachers’ Perceptions and Experiences in Using Blended Learning during the
COVID-19 Pandemic .......................................................................................................................................................... 225
Kenneth Ian Talosig Batac, Jonnedel Azucena Baquiran, Casper Boongaling Agaton
Teachers’ Perceptions of the Role of Entrepreneurship Education in the Career Choice Decision-Making of
Business Studies Learners in Gauteng South Africa ...................................................................................................... 244
Oluwakemi B. Ajayi
The Common Thinking Styles Based on the Mental Self-Government Theory Among Saudi University Students
According to Gender, Academic Achievement and Extracurricular Activities.......................................................... 258
Ali Tared Aldossari, Mahmoud Moh'd Ali Abu Jadou
Pre-service Science Teachers’ Integration of Constructivist Ideas in the Lecture Method........................................ 277
Rose Atieno Mutende, Rosemary K. Imonje, Winston Akala
Implementation of the Social Component of Higher Education: Bottom-up Approach........................................... 299
Alla A. Marushkevych, Iryna M. Zvarych, Natalia M. Lavrychenko, Liudmyla Ya. Biriuk, Olha M. Zaitseva
The Effects of Using a Case Study Method for Environmental Education..................................................................319
Sergii D. Rudyshyn, Inna A. Stakhova, Nataliia H. Sharata, Tetiana V. Berezovska, Tetiana P. Kravchenko
Exploring Vocational High School Students’ Entrepreneurial Intention: Preliminary Study ..................................341
Darma Rika Swaramarinda, Badrul Isa, Norhayati Mohd Yusof, Mohd Ali Bahari Abdul Kadir
School Support Received and the Challenges Encountered in Distance Learning Education by Filipino Teachers
during the Covid-19 Pandemic ......................................................................................................................................... 360
Angelito Palma Bautista Jr., Doris Gelvoligaya Bleza, Cielito Bernardino Buhain, Dianne Morta Balibrea
The Role of Teacher Educators in Curriculum Reforms in Lesotho Schools .............................................................. 386
Julia Chere-Masopha, Tebello Tlali, Tankie Khalanyane, Edith Sebatane
The Development of Digital Competences for University Tourism Teachers ............................................................ 403
Derling José Mendoza Velazco, Magda Francisca Cejas Martínez, Mercedes Navarro Cejas, María Hipatia Delgado Demera,
Silvia Marieta Aldaz Hernández

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IJLTER.ORG Vol 20 No 6 June 2021

  • 1. International Journal of Learning, Teaching And Educational Research p-ISSN: 1694-2493 e-ISSN: 1694-2116 IJLTER.ORG Vol.20 No.6
  • 2. International Journal of Learning, Teaching and Educational Research (IJLTER) Vol. 20, No. 6 (June 2021) Print version: 1694-2493 Online version: 1694-2116 IJLTER International Journal of Learning, Teaching and Educational Research (IJLTER) Vol. 20, No. 6 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 June 2021 Issue
  • 5. VOLUME 20 NUMBER 6 June 2021 Table of Contents Perceived Satisfaction of Emergency Remote Teaching: More Evidence from Thailand..............................................1 Kevin Fuchs An Emergency Shift to e-Learning in Health Professions Education: A Comparative Study of Perspectives between Students and Instructors ......................................................................................................................................16 Afrah Almuwais, Samiah Alqabbani, Nada Benajiba, Fatmah Almoayad Impulsing the Development of Students' Competency Related to Mathematical Thinking and Reasoning through Teaching Straight-Line Equations.......................................................................................................................................38 Bui Phuong Uyen, Lu Kim Ngan, Nguyen Phuong Thao, Duong Huu Tong Exploring Effective Practices in Managing Distance Learning for Teaching Art and Design in Bahrain................. 66 Sama'a Al Hashimi Improving Novice Students’ Computational Thinking Skills by Problem-Solving and Metacognitive Techniques .................................................................................................................................................................................................88 Nor Hasbiah Ubaidullah, Zulkifley Mohamed, Jamilah Hamid, Suliana Sulaiman, Rahmah Lob Yussof Examining Saudi Students’ Perceptions on the Use of the Blackboard Platform during the COVID-19 Pandemic ............................................................................................................................................................................................... 109 Elham Alzain A Bibliometric Analysis of Blended Learning in Higher Education: Perception, Achievement and Engagement ............................................................................................................................................................................................... 126 Arumugam Raman, Raamani Thannimalai, Yahya Don, Mohan Rathakrishnan The Role of Nurturing Technopreneurship Education and Building University Students’ Entrepreneurial Mindsets and Skill Sets in Fostering Digital Innovation and Augmenting the Tech Start-Up Ecosystem in Bahrain ............................................................................................................................................................................................... 152 Sama'a Al Hashimi, Yasmina Zaki, Ameena Al Muwali, Nasser Mahdi British National Corpus in English Language Teaching of University Students....................................................... 174 Nataliia Bober, Yan Kapranov, Anna Kukarina, Tetiana Tron, Tamara Nasalevych Emerging Trends in Metaphoric Images of Curriculum Reform Implementation in Schools: A Critical Literature Review.................................................................................................................................................................................. 194 Godsend T. Chimbi, Loyiso C. Jita Is Decentralisation a Suitable Response to Improve South African Rural Education?.............................................. 211 Kevin Teise, Emma Barnett Qualitative Content Analysis of Teachers’ Perceptions and Experiences in Using Blended Learning during the COVID-19 Pandemic .......................................................................................................................................................... 225 Kenneth Ian Talosig Batac, Jonnedel Azucena Baquiran, Casper Boongaling Agaton
  • 6. Teachers’ Perceptions of the Role of Entrepreneurship Education in the Career Choice Decision-Making of Business Studies Learners in Gauteng South Africa ...................................................................................................... 244 Oluwakemi B. Ajayi The Common Thinking Styles Based on the Mental Self-Government Theory Among Saudi University Students According to Gender, Academic Achievement and Extracurricular Activities.......................................................... 258 Ali Tared Aldossari, Mahmoud Moh'd Ali Abu Jadou Pre-service Science Teachers’ Integration of Constructivist Ideas in the Lecture Method........................................ 277 Rose Atieno Mutende, Rosemary K. Imonje, Winston Akala Implementation of the Social Component of Higher Education: Bottom-up Approach........................................... 299 Alla A. Marushkevych, Iryna M. Zvarych, Natalia M. Lavrychenko, Liudmyla Ya. Biriuk, Olha M. Zaitseva The Effects of Using a Case Study Method for Environmental Education..................................................................319 Sergii D. Rudyshyn, Inna A. Stakhova, Nataliia H. Sharata, Tetiana V. Berezovska, Tetiana P. Kravchenko Exploring Vocational High School Students’ Entrepreneurial Intention: Preliminary Study ..................................341 Darma Rika Swaramarinda, Badrul Isa, Norhayati Mohd Yusof, Mohd Ali Bahari Abdul Kadir School Support Received and the Challenges Encountered in Distance Learning Education by Filipino Teachers during the Covid-19 Pandemic ......................................................................................................................................... 360 Angelito Palma Bautista Jr., Doris Gelvoligaya Bleza, Cielito Bernardino Buhain, Dianne Morta Balibrea The Role of Teacher Educators in Curriculum Reforms in Lesotho Schools .............................................................. 386 Julia Chere-Masopha, Tebello Tlali, Tankie Khalanyane, Edith Sebatane The Development of Digital Competences for University Tourism Teachers ............................................................ 403 Derling José Mendoza Velazco, Magda Francisca Cejas Martínez, Mercedes Navarro Cejas, María Hipatia Delgado Demera, Silvia Marieta Aldaz Hernández
  • 7. 1 ©Author 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. 20, No. 6, pp. 1-15, June 2021 https://doi.org/10.26803/ijlter.20.6.1 Perceived Satisfaction of Emergency Remote Teaching: More Evidence from Thailand Kevin Fuchs Prince of Songkla University, Phuket, Thailand https://orcid.org/0000-0003-3253-5133 Abstract. The sudden shift from physical classroom education towards emergency remote teaching (ERT) in higher education during the unprecedented global pandemic caused an abrupt change in the learning environment for students and educators alike. The disruptive overnight change and conversion of entire courses to emergency remote teaching caused concern for not only educators, but also students that had little time to adapt to the new circumstances. While the embedment of technologies in the classroom is not a new concept, this quantitative research expands a case study that sought to examine the perceived satisfaction of undergraduate students with the emerging paradigm of ERT. Responses based on empirical data (n=450) as well as secondary data (n=219) were analyzed to conclude that, in particular, younger freshmen students struggled more with online emergency remote teaching than their older peers. Furthermore, the study identified numerous similarities between both data samples. The current research informs educators about student perceptions and preferences during these extraordinary circumstances of uncertain duration. Furthermore, the paper concludes with recommendations that aim to provide institutions and educators with practical guidance on how to tackle the outlined issues. Keywords: Emergency remote teaching; Technology-enhanced learning; Thailand; Online learning; Higher education 1. Introduction The universality of information technology has been influencing almost all aspects of our lives: the way we work, interact with others, process data into information, analyze and share information, entertain ourselves, and enjoy tourism (Palvia et al., 2018). Due to the threat of COVID-19, universities are facing decisions about how to continue teaching and learning while keeping their faculty, staff, and students safe from a public health emergency that is moving fast and is not well understood. Many institutions have opted to cancel all face-to-face classes, including lab-based classes and seminars. They have mandated that faculties move their courses online to help prevent the spread of
  • 8. 2 http://ijlter.org/index.php/ijlter the virus that causes COVID-19 (Fuchs, 2021a). This unprecedented situation created an entirely new phenomenon: due to the severe nature of the virus, entire curricula were moved to online education overnight. The challenge herein was not limited to the educators, who found themselves in a situation of needing to teach their entire syllabus online, but also extended to the students, who needed to adapt to a new learning environment instantaneously (Whalen, 2020). As a response to the global education crisis, online emergency remote teaching has been put into practice. It is a complex process that requires careful planning, designing, and determination of aims in order to create an effective learning ecology (Themelis & Sime, 2020). The temptation to compare online learning to face-to-face instruction in these circumstances will be great. Online learning carries a stigma of being lower in quality than face-to-face learning, despite research showing otherwise. These hurried moves online by so many institutions at once could seal the perception of online learning as a weak option when, in truth, nobody making the transition to online teaching under these circumstances will truly be designed to take full advantage of the affordances and possibilities of the online format (Hodges et al., 2020). This paper is an expansion of an earlier study done by Fuchs and Karrila (2021) that sought to examine the perceived satisfaction of students in higher education concerning emergency remote teaching amid COVID-19 in Thailand. Fuchs and Karrila (2021) identified that most undergraduate students prefer a traditional on-site classroom arrangement, but were satisfied with the alternative ERT that was delivered fully online. The study highlighted that the students perceived knowledge, friendliness, and patience as the most important characteristics of their lecturer in these circumstances. However, the limited sample size from the previous study (n=219) would not suffice to generalize the results to a larger population, nor allow for validation in different geographical parts of Thailand. This paper therefore aims to expand on the original research setting and to meet the following research objectives: 1) To seek validation of previous research results through an increased sample size 2) To identify whether the perceived satisfaction from undergraduate students varies in a different geographical setting 3) To recognize a similarity or dissimilarity between specific factors based on geographical location, i.e. in Northeastern vs. Southern Thailand Moreover, the research was guided by the following research question: “How do undergraduate students in Northeastern Thailand perceive satisfaction with the emerging paradigm of emergency remote teaching during COVID-19?” 2. Literature Review 2.1. Online learning in higher education The COVID-19 has resulted in schools shut all across the world. As a result, education has changed dramatically, with the distinctive rise of e-learning, whereby teaching is undertaken remotely and on digital platforms. As shown in a previous study, effective time management was the second-highest-rated
  • 9. 3 http://ijlter.org/index.php/ijlter advantage of online education, with students having more freedom to control their time and not being constrained by predetermined schedules (Martin et al., 2020). Another study found that, depending on the teaching methods used, the ability to use multiple virtual classrooms at the same time could improve student interest and involvement, allowing for smaller group discussions during online lectures (Fuchs, 2021b). Furthermore, a combination of time and location versatility was claimed as one of the key advantages of online education. The benefit of place and time flexibility works both ways, allowing students and educators to choose the best work environment for them. Additionally, time saved by eliminating a daily commute can be spent in more study time, increasing the likelihood of success. The variety of digital resources that can be incorporated into the virtual classroom was mentioned as another advantage of online education. According to Downes (2019) in his Connectivism-based educational theory, the online medium provided an opportunity and experience to connect with students from various disciplines, backgrounds, and cultures (Downes, 2019). Since the early 2000s, the paradigm of online education has changed radically. Most notably, the Internet is connecting an ever-increasing number of people all over the world. According to the United Nations nearly 4.68 billion people will have access to the Internet in the year 2020. This figure reflects roughly 58 percent of the world's population, so it is no wonder that online education is growing in tandem. 2.2. Challenges and opportunities related to online education Earlier research by Fuchs and Karrila (2021), Sun and Chen (2016), Kyne and Thompson (2020), Delnoij et al. (2020), and Fuchs (2021c) claim that online education has numerous advantages, including the ability to study remotely without having to engage in a daily rush hour in metropolitan areas. Furthermore, another advantage listed was timely and frequent feedback from the course instructor through digital evaluations and electronic communication (Kyne & Thompson, 2020). Other advantages of online education include the multi-media experience in a well-designed virtual classroom with various technical elements (Fuchs, 2021c). Moreover, of course, there were monetary benefits resulting from reduced costs and, therefore, lower tuition fees for participating students (Sun & Chen, 2016). Online education and technology-enhanced education are certainly not new concepts; they have been around for quite some time. However, rising curiosity has ignited a big trend in these fields (Sun & Chen, 2016; Kyne & Thompson, 2020). Educators were searching for a way to do some of their teachings online, or at the very least incorporate technology into their classrooms (Fuchs, 2021b; Fuchs, 2021c). The pedagogy of active learning, in particular, has intensified the movement toward technology-enhanced education, which has the benefits of increased student participation, improved learning outcomes, and, as a result, higher retention rates (Delnoij et al., 2020). However, many of the outlined benefits are not transferable to the paradigm of emergency remote teaching in a crisis, wherein this emerging paradigm carries its own set of distinguishing characteristics.
  • 10. 4 http://ijlter.org/index.php/ijlter 2.3. The emerging paradigm of ERT As a result of crises, emergency remote teaching (ERT) is a temporary transition in instructional delivery to an alternative delivery model, wherein it is implied that teaching is carried out entirely online. It was also stated that online education has been studied for decades, with a consensus on the elements that do not contribute proportionally to the efficacy of online education. These characteristics include but were not limited to modality, pacing, student- instructor ratio, pedagogy, the role of assessment, the instructor’s role, the student’s role, communication channels, and sources of feedback. These characteristics will invariably be evident in an effective ERT class. The lack of time available for educators to change their instructional materials – in the event of a last-minute switch from classroom to online – may potentially indicate an unsuitable learning atmosphere for students. Kyne and Thompson (2020) conducted a case study that described many challenges faced by students during their fully online semester. Completing lab- based tasks, navigating Moodle (LMS), and engaging with online content were among them. If the course content is not carefully and intentionally designed, “undergraduate students claim a lack of socialization with peers and low engagement with the course materials” as primary reasons for their dissatisfaction, according to a similar study (Fuchs, 2021a). Furthermore, Wilcox and Vignal (2020) discovered that the two most common difficulties students faced as a result of ERT were (1) course inception and (2) learning environment. The most frequently mentioned issue in the above group was unreliable Internet access that hindered the students' learning experience. Participants said the learning process was uncomfortable and unpleasant, according to Gelles et al. (2020). Although there are many benefits and opportunities in the online education paradigm, it should be recognized that it is not without its difficulties and flaws. Certainly, lack of student engagement (Fuchs, 2021c), willingness to meet learning results (Zlatkin-Troitschanskaia et al., 2016), and involvement of low-performing students (Fay & Zavattaro, 2016) were all difficulties found in previous studies. However, given the existence of the substantial changes that emergency remote teaching could entail, there is the potential for a new set of challenges to arise. 2.4. Defining students satisfaction Satisfaction is a euphoric feeling that occurs when a person's needs and desires have been met (Suikkanen, 2011). It is a state of mind of a person that has achieved or perceived a result that has exceeded their expectations (Busacca & Padula, 2015). As a result, satisfaction can be described as an experience of receiving expected results. In related research, satisfaction is often portrayed as the positive difference between the perceived importance and the perceived performance of an attribute or action (Muhsin et al., 2020). In other words, satisfaction refers to the satisfaction or dissatisfaction experienced as a result of contrasting perceived results to expectations (Suikkanen, 2011; Padula, 2015). Generally, students are satisfied when the perceived performance of a specific service or action outranks the perceived expectation of the same service/action.
  • 11. 5 http://ijlter.org/index.php/ijlter When a person perceives that service encountered as good, they will be satisfied. When the perceived performance of the service or action is below the perceived expectation, then that person would be dissatisfied with the result: Satisfaction (S) = Perceived Importance (I) – Perceived Performance (P). The measurement of a student's educational experiences leads to a short-term disposition of satisfaction. It is the product and effect of an educational system and is a positive indicator of student loyalty (Weerasinghe & Fernando, 2017; Muhsin et al., 2020). In conclusion, student satisfaction can be understood as a function of the relative level of experiences and perceived performance concerning educational services during the study period (Suikkanen, 2011; Padula, 2015; Weerasinghe & Fernando, 2017). 3. Methodology 3.1. Sample The data were collected from undergraduate students of all years who were enrolled in a full-time degree program. The sample included degree programs that relate to Business and Management studies. After screening the collected data, a total of 38 responses were discarded. The discarded responses included 13 from another Faculty (i.e. Faculty of Science). Moreover, 8 responses from international exchange students were excluded. However, responses from international degree students were included in the analysis. Finally, 17 inconclusive/incomplete responses were discarded. Table 1: Socio-demographic characteristics of the participants Characteristics University A1 University B2 Gender Male 58 26% 125 28% Female 159 73% 325 72% Prefer not to say 2 1% - 0% Total 219 100% 445 100% Year of study Year 1 50 23% 79 18% Year 2 83 38% 208 46% Year 3 43 20% 76 17% Year 4 32 14% 68 15% Year 5 or above 11 5% 19 4% Total 219 100% 445 100% Age range 18 years old or below 6 3% 7 2% 19 – 20 years old 122 56% 285 63% 21 – 22 years old 68 31% 114 25% 23 – 24 years old 16 7% 30 7% 25 years old or above 7 3% 14 3% Total 219 100% 445 100% 1Secondary Data obtained from University A in Southern Thailand (n=219) 2Empirical Data obtained from University B in Northeastern Thailand (n=450)
  • 12. 6 http://ijlter.org/index.php/ijlter An overall sample size (n=669) was included as a population sample for the data analysis. The confidence level of accurate sampling was estimated at 95% (p<0.05) and, based on the total student enrollment and sample size that were included, the margin of error was quantified at 4.40%. Based on eligible responses, the representative demographic profile in Table 1 and 2 summarizes the respondents’ gender, year of study, age range (all in Table 1), nationality, and preferred mode of study (in Table 2). Table 2: Socio-demographic characteristics of the participants Characteristics University A1 University B2 Nationality Thai 184 84% 360 80% Foreign 35 16% 90 20% Total 219 100% 445 100% Preferred study mode Virtual classroom 54 25% 117 26% Traditional classroom 165 75% 333 74% Total 219 100% 445 100% 1Secondary Data obtained from University A in Southern Thailand (n=219) 2Empirical Data obtained from University B in Northeastern Thailand (n=450) 3.2. Research instrument Convenience sampling was used to collect the data through a bilingual (Thai and English) self-administered digital survey (e-survey). The e-survey was split into three sections containing a total of 27 questions and was adapted from an earlier case study (Fuchs & Karrila, 2021). The students were recruited on-site to voluntarily participate in the data collection. Furthermore, the students were prompted for assistance to further distribute the survey amongst their peers. The first section sought to collect data on the participant’s socio-demographic profile. Table 3: Summary of survey items No. Item 1. The teacher begins the class with a review of the previous class 2. The teacher presents the material in an interesting and engaging way 3. The teacher presents the material in an organized and coherent way 4. The teacher is knowledgeable about the content of the course 5. The teacher is friendly and patient with the students 6. The course material is well and professionally prepared 7. The course material is easy to access in the LMS 8. Students are engaged to actively participate in the discussion 9. I am learning something which I consider valuable 10. I am finding the course challenging and stimulating
  • 13. 7 http://ijlter.org/index.php/ijlter The second and third sections contained ten (10) items each, wherein the participants were able to express their views on a 5-point Likert-type scale with pre-coded responses for Not Important At All (1), Not Very Important (2), Somewhat Important (3), Very Important (4), and Extremely Important (5) in the second section. Similarly, the third section had pre-coded Likert-type responses for Not At All Satisfied (1), Not Very Satisfied (2), Somewhat Satisfied (3), Very Satisfied (4), and Extremely Satisfied (5). Otherwise, the items in the second and third sections were similar in terms of comparing the perceived importance and performance for each item (Table 3). The structure and content of the administered e-survey were examined for validity by three university lecturers and tested with ten students for comprehension of the survey. These preliminary examinations yielded minor revisions to enhance the clarity of the survey. 3.3. Survey administration The secondary data were taken from an earlier study conducted by Fuchs and Karrila (2021) and were collected in the first quarter of 2021 at a large higher educational institution in southern Thailand. They were collected amid a countrywide ERT policy as a result of the imminent spread of COVID-19. Hereafter, this sample is referred to as University A (n1=219). The empirical data were collected in the second quarter of 2021 at a large higher educational institution in northeastern Thailand and the survey accepted responses for a duration of 96 hours before it was closed for new responses. It was collected in the aftermath of a countrywide ERT policy that was implemented and effectively replaced traditional face-to-face teaching. Henceforth, the sample is referred to as University B (n2=450). Both institutions are the largest universities in terms of size (i.e. student enrollment and curricula offered) and recognition in the respective areas. Furthermore, they are characterized as government-run institutions of higher education targeting students from middle-class households. 3.4. Data analysis The survey data were examined using JASP and software to obtain an average value (Mean), standard deviation (SD), minimum value (Min), maximum value (Max), the proportion of the data (i.e., a fraction of cases without missing data), and distribution of data for each item. Independent T-tests were performed to determine if there was a significant difference between the means of University A and University B. The data analysis and findings are discussed and interpreted in later sections of this paper. 4. Results and Discussion The results from the empirical data collection and secondary data sample are presented in two separate sections that allow for chronologic analysis and presentation. The first section presents the demographic profiling that was conducted to identify similarities or dissimilarities between the samples based on gender, age range, year of study, nationality, or preferred mode of study.
  • 14. 8 http://ijlter.org/index.php/ijlter The second section presents the mean values of both samples for each attribute and allows for comparison of the results and analysis of student satisfaction with emergency remote teaching. Moreover, the variance from each attribute between the first and second samples was calculated and independent t-tests were performed from both samples to determine whether there was a statistically significant difference between the means in both samples. 4.1. Demographic profiling of both sample groups The socio-demographic profile, consisting of gender, age range, year of study, and nationality, was included in a rigorous cross-analysis wherein different mean ratings based on gender or year of study were detected. However, the results do not suggest a statistical significance or relevance that would further provide value concerning the perceived satisfaction of students with emergency remote teaching in Thailand. However, one particular criterion yielded a noteworthy result. The enclosed graphic (Fig. 1) shows the preferred mode of study based on 17 totally different socio-demographic filters that were applied. Figure 1: Demographic profiling about the students preferred mode of studying The blue bar signifies the percentage of students that prefer a traditional classroom setting instead of emergency remote teaching, wherein the red bar indicates the percentage of students that prefer emergency remote teaching to a traditional on-site classroom arrangement. To draw a baseline for comparison, 13 of the 17 attributes that were examined yielded a similar proportional response, wherein 74% of students prefer the traditional classroom and 26% prefer the virtual classroom during ERT (No. 1). The majority of socio- demographic filters validate this sentiment with a relatively small standard deviation of not more than 2%. However, based on the 17 filters that were applied, four particular settings yielded noteworthy results. Namely, these are: 26% 25% 28% 25% 26% 8% 24% 29% 30% 24% 16% 27% 25% 28% 43% 24% 34% Total Female Male University A University B 18 or younger 19-20 years 21-22 years 23-24 years 25 or above Year 1 Year 2 Year 3 Year 4 Year 5+ Thai Foreign No. 1 No. 2 No. 3 No. 4 No. 5 No. 6 No. 7 No. 8 No. 9 No. 10 No. 11 No. 12 No. 13 No. 14 No. 15 No. 16 No. 17 Traditional Classroom Virtual Classroom
  • 15. 9 http://ijlter.org/index.php/ijlter No. 6 (18 or younger), No. 11 (Year 1), No. 15 (Year 5+), and No. 17 (Foreign). The first three findings indicate opposing views of the respective groups of participants. The students aged “18 years or younger” expressed their preference toward the traditional classroom environment with 92%, whereas only 8% of that same group prefer the virtual classroom as part of emergency remote teaching (No. 6). A similar notion is shared amongst the first-year students, wherein 84% prefer the traditional classroom and 16% prefer the virtual classroom (No. 11). Generally, the students are aged 17-19 years old in their first year of undergraduate studies. A possible hypothesis therefore derives that freshmen students aged 18 years or younger have a strong preference toward the traditional classroom environment. Another case study suggests that female students in particular struggle with virtual classrooms and claim “lack of socialization, peer interaction and technological challenges” as the main difficulties (Fuchs, 2021a). Students in their fifth year (and above) expressed an opposing sentiment concerning the preferred mode of study. While 92% of first-year students prefer the traditional classroom (No. 6), only 57% of their older peers share that same sentiment (No. 15). A possible explanation for these opposing views could be that freshmen students eagerly wait to commence their study experience upon high school graduation, wherein students in their final years of study are already more independent and have shifted their focus toward work-life-balance rather than study experience, as claimed in a case study by Yamada and Yamada (2018). Lastly, another notable deviation from the baseline result (No. 1) was the result recorded from foreign degree students (No. 17). 66% of foreign degree students prefer the traditional classroom, whereas 34% of them prefer the virtual classroom. While about two-thirds still favor an on-site arrangement, the result deviates by 8% from the baseline and is even 10% less compared to their Thai peers (No. 16). Trower and Lehmann (2017) suggest that personal development, immersion into a new culture, and learning a new language are amongst the top reasons for students to study abroad. Thus, a negative deviation from the baseline result suggests a rather contradictory result from these findings and offers room for further research in the future. 4.2. Importance-performance analysis The three highest mean ratings concerning the perceived importance of the attributes (Table 4) at University A are No. 4 (4.37), No. 5 (4.27), and No. 7 (4.13). On the other hand, at University B the following three attributes received the highest mean rating from the participants: No. 5 (4.18), No. 2 (4.17), and No. 4 (4.14). Similar to the results from University A, the participants at University B valued two identical attributes in their top three of most important attributes during ERT. Namely, these are “The teacher is knowledgeable about the content of the course (No. 4)” as well as “The teacher is friendly and patient about the content of the course (No.5)”. Both attributes directly address the virtues of the lecturer, as students perceive being knowledgeable, friendly, and patient as the most important characteristics at both institutions. Respectively, the weighted mean ratings from both institutions rank almost identically with No. 4 (4.22) and
  • 16. 10 http://ijlter.org/index.php/ijlter No. 5 (4.21) as the most important attributes during emergency remote teaching. Contrary to the most important attributes, the participants at University A rated item No. 1 (3.73) and No. 10 (3.58) as the least important attributes. Table 4: Comparison of importance ratings No.1 University A University B Total Mean SD Mean SD Mean SD 1 3.73 0.99 4.02 1.02 3.93 1.02 2 4.03 1.01 4.17 0.98 4.12 0.99 3 4.05 0.92 4.05 0.98 4.05 0.96 4 4.37 0.89 4.14 0.99 4.22 0.97 5 4.27 0.96 4.18 1.02 4.21 1.00 6 4.12 0.99 4.11 1.01 4.11 1.00 7 4.13 1.03 4.11 1.01 4.12 1.02 8 3.98 0.95 3.91 1.08 3.93 1.04 9 3.95 0.98 4.07 1.02 4.03 1.01 10 3.58 1.24 4.00 1.06 3.87 1.14 1Ratings obtained from a Likert-type five points scale ranging from lowest rating to highest rating, i.e. Not Important At All (1), Not Very Important (2), Somewhat Important (3), Very Important (4), and Extremely Important (5). Although these two attributes also rank in the bottom three for participants from University B, the lowest mean rating was given to No. 8 (3.91), which asked the participants about the importance of the statement “students are engaged to actively participate in the discussion”. Evaluating the totality of both samples, it can be concluded that the lowest to highest mean rating ranges from 3.87 (No 10.) to 4.22 (No. 4), which indicates relatively high importance for all ten attributes. Furthermore, the findings from the first sample taken at University A were affirmed with the second sample from University B, with the virtues of the lecturer perceived by the students as the most important characteristics. Table 5: Comparison of performance ratings No.1 University A University B Total Mean SD Mean SD Mean SD 1 3.52 0.99 3.92 1.05 3.79 1.05 2 3.62 1.04 3.80 1.04 3.74 1.04 3 3.79 1.00 3.81 1.04 3.81 1.03 4 4.12 0.96 3.82 1.08 3.92 1.05 5 4.05 0.94 3.76 1.01 3.85 1.00 6 3.84 0.98 3.63 1.08 3.70 1.05 7 3.87 1.00 3.73 1.01 3.77 1.01 8 3.81 0.96 3.83 1.03 3.82 1.01 9 3.76 1.01 3.90 1.00 3.86 1.01 10 3.54 1.20 3.87 1.03 3.76 1.09 1Ratings obtained from a Likert-type five points scale ranging from lowest rating to highest rating, i.e. Not At All Satisfied (1), Not Very Satisfied (2), Somewhat Satisfied (3), Very Satisfied (4), and Extremely Satisfied (5).
  • 17. 11 http://ijlter.org/index.php/ijlter In addition to the attributes that received the lowest and highest mean ratings about perceived importance, Table 5 indicates the perceived performance of the same ten attributes per educational institution. The three highest-rated attributes about perceived performance at University A are No. 4 (4.12), No. 5 (4.05), and No. 7 (3.87). The results recorded from participants at University B differ in terms of mean value, ranking, and mean value variance. Firstly, it can be noted that the range for the mean value is relatively narrow. The lowest to highest value range is from 3.63 (No. 6) to 3.92 (No. 1). Moreover, the highest-rated attributes about perceived performance are No. 1 (3.92), No. 9 (3.90), and No. 10 (3.87), indicating that students at University B place more emphasis on the perceived performance for a review of the previous class at the beginning of their lecture (No. 1) and being able to learn something valuable (No. 9). Notably, the lowest-rated attributes from the first sample at University A correspond to No. 1 (3.52) and No. 9 (3.54), which were the highest-ranked at University B. In summary, it can be noted that there is an agreement between both institutions that the virtues and personal traits of the lecturer are perceived as the most important attributes during emergency remote teaching. Attributes that correspond to the lecturers’ friendliness, patience, or knowledge are rated higher than, for example, the need for a stimulating or challenging course (Table 6). Table 6. Comparison of importance-performance ratings (n=669) No. Importance rating1 Performance rating2 Mean SD Mean SD 1 3.52 0.99 3.92 1.05 2 3.62 1.04 3.80 1.04 3 3.79 1.00 3.81 1.04 4 4.12 0.96 3.82 1.08 5 4.05 0.94 3.76 1.01 6 3.84 0.98 3.63 1.08 7 3.87 1.00 3.73 1.01 8 3.81 0.96 3.83 1.03 9 3.76 1.01 3.90 1.00 10 3.54 1.20 3.87 1.03 Furthermore, while there is a relative agreement about the attributes perceived as most important during emergency remote teaching, there is a discrepancy amongst both institutions about perceived performance during emergency remote teaching. The latter result is probably less surprising, considering that the performance of an online class is largely dependent on the individual lecturer, as well as how the institution manages the ERT. However, it can be noted that participants from both institutions are generally satisfied with the perceived performance during ERT. The attributes related to perceived performance for both institutions range from the lowest at 3.70 (No. 6) to the highest at 3.92 (No. 4). Also, the result is less surprising as the lowest-ranked attribute is item No. 6, about professionally prepared course material. This is understandable given the short notice to
  • 18. 12 http://ijlter.org/index.php/ijlter convert educational material from traditional classroom teaching into an online environment, as earlier stated by Hodges et al. (2020). The underlying factors are not clear for the survey items that resulted in very low comparative p-values, as summarized in Table 7, based on the analysis conducted. Table 7: Comparison and Independent T-Test’s No. Mean1 Mean2 Variance t-value p-value Importance 1 3.73 4.02 -0.29 -3.5379 <.001 2 4.03 4.17 -0.14 -1.6520 0.099 3 4.05 4.05 ±0.00 0.1027 0.918 4 4.37 4.14 0.23 2.8501 0.005 5 4.27 4.18 0.09 1.0329 0.302 6 4.12 4.11 0.01 0.0919 0.927 7 4.13 4.11 0.02 0.2802 0.779 8 3.98 3.91 0.07 0.8214a 0.412 9 3.95 4.07 -0.12 -1.4389 0.151 10 3.58 4.00 -0.42 -4.5389a <.001 Performance 1 3.52 3.92 -0.40 -4.684 <.001 2 3.62 3.80 -0.18 -2.071 0.039 3 3.79 3.81 -0.02 -0.223 0.824 4 4.12 3.82 0.30 3.419 <.001 5 4.05 3.76 0.29 3.608a <.001 6 3.84 3.63 0.21 2.343a 0.019 7 3.87 3.73 0.14 1.696 0.090 8 3.81 3.83 -0.02 -0.194 0.846 9 3.76 3.90 -0.14 -1.739 0.082 10 3.54 3.87 -0.33 -3.744a <.001 1Sample taken from University A; 2Sample taken from University B aLevene’s test is significant (p < .05), suggesting a violation of the assumption of equal variances. 5. Conclusion and Future Works It was the aim of the study to seek validation of previous research results through an increased sample size and to identify whether the perceived satisfaction from undergraduate students varies in a different geographical setting. Everyone involved in the temporary but sudden shift toward virtual learning must recognize that these crises cause disturbances for students, staff, and educators alike. While the coronavirus pandemic will hopefully soon be a distant memory, we should not simply return to our pre-virus teaching and learning practices and ignoring valuable lessons learned from ERT. There are a few noteworthy findings from this study that outline where the educator’s emphasis could be placed in a sudden and disruptive move toward virtual teaching. Both data samples suggest an agreement amongst the attributes that students value most and deem as most important in a time when educators struggle to fulfill similar expectations as in the on-site traditional classroom
  • 19. 13 http://ijlter.org/index.php/ijlter arrangement. Furthermore, the study revealed that Thai undergraduate students’ perceived performance is generally ranked lower than their perceived expectations, although it should be noted that the perceived satisfaction yielded an overall good result at both institutions. Moreover, emphasis and more attention should be given to younger undergraduate students in their first year of study who struggle more with virtual classrooms than their older peers. Lastly, limitations offer an opportunity for future research; while the authors tried to mitigate possible limitations as far as possible, it is significant to point out that the settings in which the results were collected are geographically limited to the northeastern and southern region of Thailand and not generalizable to a larger population. Furthermore, the demographic profiling of students offers opportunities for future research to quantitatively validate the results and possibly generalize the findings to a larger population. 6. Acknowledgments 6.1. Conflict of interest The author would like to declare no potential conflicts of interest concerning the research, authorship, or publication of this article. 6.2. Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. 6.3. Funding The Faculty of Hospitality and Tourism, Prince of Songkla University funded the project under the Fast Track Data Collection Grant [Contract No. FHT 6400002]. Any opinions or conclusions expressed in this paper are solely the intellectual result of the author(s) and do not reflect the viewpoint of the Faculty or University. 6.4. Recognition The author would like to thank the participants that contributed to the research project by answering the questionnaire. 7. References Busacca, B., & Padula, G. (2005). Understanding the relationship between attribute performance and overall satisfaction: Theory, measurement and implications. Marketing Intelligence & Planning, 23(6), 543-561. https://doi.org/10.1108/02634500510624110 Delnoij, L. E., Dirkx, K. J., Janssen, J. P., & Martens, R. L. (2020). Predicting and resolving non-completion in higher (online) education–a literature review. Educational Research Review, 29, 100313. https://doi.org/10.1016/j.edurev.2020.100313 Downes, S. (2019). Recent work in connectivism. European Journal of Open, Distance and E- Learning (EURODL), 22(2), 112-131. Fay, D. L., & Zavattaro, S. M. (2016). Branding and isomorphism: The case of higher education. Public Administration Review, 76(5), 805-815. https://doi.org/10.1111/puar.12626 Fuchs K., & Karrila S. (2021). The Perceived Satisfaction with Emergency Remote Teaching (ERT) amidst COVID-19: An Exploratory Case Study in Higher
  • 20. 14 http://ijlter.org/index.php/ijlter Education. The Education and Science Journal, 23(5), 116-130. https://doi.org/10.17853/1994-5639-2021-5-116-130 Fuchs, K. (2021a). Advances in Tourism Education: A Qualitative Inquiry about Emergency Remote Teaching in Higher Education. Journal of Environmental Management and Tourism, 12(2), 538-543. https://doi.org/10.14505//jemt.v12.2(50).23 Fuchs, K. (2021b). Evaluating The Technology-Enhanced Flipped Classroom Through The Students’ Eye: A Case Study. Proceedings of The 3rd International Conference on Research in Education 2021 (vol. 1, pp. 25-33). https://doi.org/10.6084/m9.figshare.14173622 Fuchs, K. (2021c). Preparing Students for Success in a Changing World: The Role of Virtual Whiteboards in the Modern Classroom. Education Quarterly Reviews, 4(1), 151-158. https://doi.org/10.31014/aior.1993.04.01.182 Gelles L. A., Lord S. M., Hoople G. D., Chen D. A., & Mejia J. A. (2020). Compassionate flexibility and self-discipline: Student adaptation to emergency remote teaching in an integrated engineering energy course during COVID-19. Education Sciences, 10(11), 304. https://doi.org/10.3390/educsci10110304 Hodges, C., Moore, S., Lockee, B., Trust, T., & Bond, A. (2020). The difference between emergency remote teaching and online learning. Educause Review, 27, 1-12. Kyne S. H., & Thompson C. D. (2020). The COVID Cohort: Student transition to university in the face of a global pandemic. Journal of Chemical Education, 97(9), 3381–3385. https://doi.org/10.1021/acs.jchemed.0c00769 Martin, F., Stamper, B., & Flowers, C. (2020). Examining Student Perception of Readiness for Online Learning: Importance and Confidence. Online Learning, 24(2), 38-58. Muhsin, S., Nurkhin, A., Pramusinto, H., Afsari, N., & Arham, A. F. (2020). The relationship of good university governance and student satisfaction. International Journal of Higher Education, 9(1). 1-10. https://doi.org/10.5430/ijhe.v9n1p1 Palvia, S., Aeron, P., Gupta, P., Mahapatra, D., Parida, R., Rosner, R., & Sindhi, S. (2018). Online education: Worldwide status, challenges, trends, and implications. Journal of Global Information Technology Management, 21(4), 233-241. https://doi.org/10.1080/1097198X.2018.1542262 Suikkanen, J. (2011). An improved whole life satisfaction theory of happiness. International Journal of Wellbeing, 1(1), 149-166. https://doi.org/10.5502/ijw.v1i1.6 Sun, A., & Chen, X. (2016). Online education and its effective practice: A research review. Journal of Information Technology Education, 15(1), 157-190. Retrieved from http://informingscience.org/publications/3502 Themelis, C., & Sime, J. A. (2020). From Video-Conferencing to Holoportation and Haptics: How Emerging Technologies Can Enhance Presence in Online Education? Emerging Technologies and Pedagogies in the Curriculum, 261-276. https://doi.org/10.1007/978-981-15-0618-5_16 Trower, H., & Lehmann, W. (2017). Strategic escapes: Negotiating motivations of personal growth and instrumental benefits in the decision to study abroad. British Educational Research Journal, 43(2), 275-289. https://doi.org/10.1002/berj.3258 Weerasinghe, I. S., & Fernando, R. L. (2017). Students' Satisfaction in Higher Education. American Journal of Educational Research, 5(5), 533-539. http://pubs.sciepub.com/education/5/5/9 Whalen, J. (2020). Should teachers be trained in emergency remote teaching? Lessons learned from the COVID-19 pandemic. Journal of Technology and Teacher Education, 28(2), 189-199. https://www.learntechlib.org/primary/p/215995
  • 21. 15 http://ijlter.org/index.php/ijlter Wilcox, B., & Vignal, M. (2020). Recommendations for emergency remote teaching based on the student experience. The Physics Teacher, 58(1), 374. https://doi.org/10.1119/10.0001828 Yamada, A., & Yamada, R. (2018). The new movement of active learning in Japanese higher education: the analysis of active learning case in Japanese graduate programs. In Active Learning-Beyond the Future, 1(4), 1-16. https://doi.org/10.5772/intechopen.80836 Zlatkin-Troitschanskaia, O., Pant, H. A., & Coates, H. (2016). Assessing student learning outcomes in higher education: Challenges and international perspectives. Assessment & Evaluation in Higher Education, 41(5), 655-661. https://doi.org/10.1080/02602938.2016.1169501
  • 22. 16 ©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. 20, No. 6, pp. 16-37, June 2021 https://doi.org/10.26803/ijlter.20.6.2 An Emergency Shift to e-Learning in Health Professions Education: A Comparative Study of Perspectives between Students and Instructors Afrah Almuwais Department of Rehabilitation Sciences, College of Health and Rehabilitation Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia https://orcid.org/0000-0002-2774-868X Samiah Alqabbani Department of Rehabilitation Sciences, College of Health and Rehabilitation Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia https://orcid.org/0000-0003-4495-5047 Nada Benajiba Department of Basic Health Sciences, Deanship of Preparatory Year, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia https://orcid.org/0000-0002-5533-7626 Fatmah Almoayad* Department of Health Sciences, College of Health and Rehabilitation Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia https://orcid.org/0000-0002-8424-5229 Abstract. This is a cross-sectional study which assessed the readiness to shift to e-learning in correlation with perceived effectiveness and satisfaction following the sudden shift caused by the coronavirus disease 2019 (COVID-19) pandemic among students and instructors. The study compared perspectives between instructors (n = 47) and students (n = 254) at the College of Health and Rehabilitation Sciences (CHRS) at Princess Nourah bint Abdulrahman University (PNU; Riyadh, Kingdom of Saudi Arabia). Data were collected using an online questionnaire using convenient sampling method. The results showed a high level of readiness to shift to e-learning among instructors and students, as well as a positive correlation between perceived effectiveness and satisfaction. However, instructors showed a higher satisfaction level and perceived this shift to be effective more than students. This experience offers a reasonable foundation for any future plans to implement e-learning in health professions education and maximise its benefits without *Corresponding author: Fatmah Almoayad; Email: ftm.myd@gmail.com
  • 23. 17 http://ijlter.org/index.php/ijlter compromising the practical and clinical training provided via face-to-face learning. Further studies are needed to explore e-learning experiences a year after this shift, when educational institutions are expected to have clearer plans and have better prepared for e-learning. In addition, effect of e-learning shift on clinical training outcomes for different health professions is also recommended. Keywords: e-learning; COVID-19; health professions; Saudi Arabia 1. Introduction Since the beginning of the 21st century, e-learning has been progressively integrated within higher education systems worldwide (Aljaber, 2018; Hiltz & Turoff, 2005). In Saudi Arabia, health colleges have participated in the e-learning movement and many have embedded blended teaching strategies that combine face-to-face learning with e-learning (Sajid et al., 2016; Zakaria et al., 2013). While an extensive body of literature discusses several types of e-learning – such as distance learning, blended learning and mobile learning – attempts to confirm their effectiveness have been inconclusive in international research, specifically in studies of e-learning in Saudi Arabia (Rajab, 2018). Nevertheless, blended learning has shown effectiveness vis-à-vis skill and knowledge acquisition in health professions education (Liu, et al 2016). Moreover, growing evidence suggests that advances in virtual simulation are benefitting health profession training (Pottle, 2019; Skochelak & Stack, 2017). 1.1 The Importance of Preparedness in e-Learning As the literature suggests, providing proper and effective e-learning requires advanced planning (Nasiri et al., 2014; Rice & McKendree, 2014). e-Learning infrastructure and support have been indicated as crucial to successful e-learning experiences (Naveed et al., 2017). This importance was clearly demonstrated when education shifted abruptly to e-learning in the early months of the coronavirus disease 2019 (COVID-19) pandemic. During this time, the existence of the required infrastructures and preparedness to accommodate this shift to e-learning demonstrated a significant positive impact on the learning process’s continuation. Countries with excellent and complete infrastructure were better able to resume the teaching process with minimal or no interruptions (Marinoni et al., 2020). Meanwhile, poor internet connections and a lack of preparedness (such as a lack of electronic devices) were found to present significant obstacles for both students and instructors during this emergency shift to e-learning (Maatuk et al., 2021). Additionally, the literature showed that satisfaction with e-learning is a key factor for the success of e-learning experiences themselves (Bolliger, 2004; Liaw et al., 2007). Al-Samarraie et al. (2018) investigated a unified perception of students’ and instructors’ satisfaction with an e-learning system, demonstrating that steadily maintained satisfaction with e- learning indicates a successful continuation of e-learning. Thus, instructors’ ability to utilise a learning management system is influenced by their satisfaction levels (Yengin et al., 2011). On the other hand, students’ online readiness had a mediated influence on learning perceptions and course satisfaction (Wei & Chou, 2020). Gopal et al. (2021) revealed that students’ satisfaction positively influenced
  • 24. 18 http://ijlter.org/index.php/ijlter their performance during online education as a result of the pandemic-related lockdown. Moreover, both students’ and instructors’ satisfaction influenced their motivation in an online environment (Bolliger & Wasilik, 2009). A previous study was conducted by Alqabbani et al. (2020) to assess the readiness to shift to online learning at Princess Nourah bint Abdulrahman University’s (PNU; Riyadh, Kingdom of Saudi Arabia). It found an excellent existing infrastructure and a high level of readiness among instructors at the university. This study’s findings also revealed that satisfaction was positively correlated with perceived effectiveness during the complete shift to e-learning. While this correlation indicated a positive shift experience at the institution, students and instructors at the College of Health and Rehabilitation Sciences (CHRS) within PNU – which offers thirteen allied health speciality programmes (PNU, 2020) – might have had a different experience. This potential difference is due to the nature of learning, which requires hands-on practice to master clinical skills. The unplanned, sudden shift to online learning led to changes in not only theoretical teaching but also practical and clinical training, which have been replaced by videos, online simulation, case study reports and online discussions. As a result, the shift to e-learning might influence both the learning process and learning outcomes (Huang, 2010; Luhanga, 2018; Parandeh et al., 2015). Therefore, assessing satisfaction with e-learning provides insights for educational institutions on identifying areas of improvement in online learning (Bolliger, 2004; Liaw et al., 2007). 1.2 Students’ and Instructors’ Complementarity in the Learning Process While exploring the unique learning experience during a shift to e-learning is interesting, such investigations can only allow insights via analyses of perceptions’ complementarity between students (as learners) and instructors (as teachers) since exploring both learners’ and teachers’ perspectives can provide comprehensive evaluations of the e-learning experience as one entity (Khan, 2005). Instructors have been very clearly established to represent half of the crucial learning experience via the teaching process for which they are responsible. The other half of the learning experience is based on students’ learning process (Ellaway & Masters, 2008). Hence, both halves of this experience (those of instructors and teachers) are complementary, and their harmony is essential to the learning process. Mishra et al. (2020) examined both students’ and teachers’ perceptions of the online learning experience during the COVID-19 pandemic. Their findings revealed that the main factor causing instructors’ better motivation compared to students is a belief that online education can proficiently deliver intended learning outcomes. Students, however, reported less interest in and attention to online classes as a new, unfamiliar teaching mode. However, as the literature suggests, while learners report preferences regarding their learning styles, they also tend to adapt their learning to the available teaching strategies, based on the context and motivations (Entwistle, 1997). Recently, Motte-Signoret et al. (2021) indicated that both medical students and their instructors perceived e-learning as a suitable alternative medical education delivery method during the pandemic.
  • 25. 19 http://ijlter.org/index.php/ijlter At the beginning of the COVID-19 pandemic, many academic researchers were interested in studying the emergency shift to e-learning. In this regard, most published studies have highlighted the sudden shift’s influence on e-learning’s effectiveness. Hence, in addition to analysing this experience, the present study also compares this experience from the perspectives of both students and teachers affiliated with a health college (including 13 different specialities). Furthermore, it emphasises some key factors’ importance in determining e-learning’s effectiveness under the pandemic’s unexpected circumstances. Thus, existing e- learning infrastructures and support prior to the COVID-19 pandemic’s lockdown-related emergency shift to e-learning, an indicator of readiness for e- learning, and perceived satisfaction among students and teachers, were analysed as possible factors influencing the shift’s perceived effectiveness. The study’s results were, therefore, expected to provide insights into the complexity of this e- learning’s effectiveness and the necessary considerations of the above-mentioned factors to promote this e-learning as education systems are currently projected to further integration of e-learning in the coming years. The present study’s researchers hypothesised that students and instructors would harbour different perspectives regarding readiness, satisfaction and perceived effectiveness during this shift. Thus, the authors’ null hypothesis was that students and instructors would demonstrate similar readiness, satisfaction and perceived effectiveness as a result of this shift. 1.3 Conceptual Framework This research adopted the cognitive theory of learning, which holds that learning is affected by both intrinsic and extrinsic factors (Janelli, 2018). In the field of e- learning teaching strategies, cognitive overload, motivation levels and real-life situations are all considered essential factors that affect the learning process (Mödritscher, 2006). In this research context, e-learning was imposed suddenly. The authors sought to explain the supporting environment that contributed to the success of any e-learning experience through a conceptual framework (Figure 1). As the literature has discussed, an appropriate e-learning infrastructure with adequate support significantly affects the continuation and successful achievement of the e-learning process. Thus, ensuring a sufficient level of readiness (preparedness) for both students and instructors positively influences satisfaction levels and, consequently, achieves reasonable levels of perceived e- learning effectiveness. The presence of all these elements simultaneously would ensure overall success in a shift to e-learning. Thus, through its mode of learning, the current research obtained insights into the factors that contribute to e- learning’s continuation.
  • 26. 20 http://ijlter.org/index.php/ijlter Figure 1: Conceptual framework of the e-learning experience 2. Methods 2.1 Design A comparative analytic study was conducted during May 2020. Participants were recruited using a convenient sampling technique. This method was the most efficient method possible, especially during the lockdown period. Questionnaires were available electronically via Microsoft Forms and distributed via the CHRS e- mail lists. To facilitate the dissemination of the study’s information and requests to affiliated students, instructors and administrative staff, the CHRS had developed and annually updated a specific e-mail list for each of the above- mentioned categories. Hence, the two e-mail lists corresponding, respectively, to instructors and students were used to solicit participation in this study after consent was obtained from all participants. The email was sent twice to each person on the e-mail lists the first time as an invitation to participate in the study and the second time as a gentle reminder to encourage further participation. The emails directed to students were sent from the official email address of the Vice- Deanship of Student Affairs. Meanwhile, the emails directed to instructors were sent from the official email address of the Vice-Deanship of Academic Affairs. The lists’ inclusion criteria were instructors and students who were actively engaged in learning or teaching during the semester when the sudden shift to e-learning occurred. The study sample comprised 47 of 66 instructors and 254 of 720 students at the CHRS. The survey rates were 35% and 71% among students and instructors, respectively. However, note that prospective participants’ ability to submit answers was deactivated soon after the survey met its required representative numbers of participants, which were n = 45 (of 66) for instructors and n = 251 for students. These values were calculated based on a confidence level of 95% and a margin of error of ± 5%. Ethical approval (IRB Log Number 20-0162) was obtained
  • 27. 21 http://ijlter.org/index.php/ijlter from the institutional review board at PNU before this research was conducted. Participation in the study was voluntary. Anonymity and confidentiality were maintained, and consent to participate was obtained from participants at the beginning of the study’s questionnaires. 2.2 Research Instruments Two questionnaires were designed for this project’s data collection. The first questionnaire was directed towards instructors (Appendix 1) while the second questionnaire was directed towards students (Appendix 2). The questionnaires were adapted from a previous study that had been conducted by the present research team (Alqabbani et al., 2020) with some adjustments to suit the current study’s aim. The two questionnaires comprised four similar sections, including general characteristics, the readiness to shift to e-learning, the perceived effectiveness of learning or teaching after the shift to e-learning and satisfaction with this shift. Since the study aimed to compare instructors’ perspectives and students’ perspectives, the questionnaires’ three latter sections were designed to measure the same parameters; therefore, they comprised the same questions. However, the term “teaching” was applied to instructors, and the term “learning” was applied to students. The sections are described in detail in the following four paragraphs. Section 1 comprised three questions for instructors and four questions for students. For instructors, this section collected data about academic rank, years of teaching experience and numbers of courses taught. For students, the collected data were grade point averages (GPAs), levels of study, academic levels and programmes of study. Section 2 contained five questions to measure the readiness to switch to e-learning by assessing experiences with e-learning platforms, as well as the feasibility and accessibility of e-learning platforms prior to the COVID-19 pandemic. These questions focused on whether instructors and students had electronic devices, proper internet access and diverse ways to interact with each other—including both face-to-face and telecommunication methods—in addition to questions about the use of different BlackBoard BB features. Each answer that reflected the use of e-learning platforms or a supporting atmosphere was given a readiness score of 1. The total readiness score was calculated by adding the values of the scores for each question. The maximum readiness score was 9, and the minimum readiness score was 0. Section 3 comprised a total of 14 questions to evaluate how both instructors and students perceived e-learning experiences’ effectiveness after the pandemic- related shift. These questions pertained to e-learning experiences and quality, the extent to which e-learning supported independent learning and helped achieve goals, students’ motivation, communication between students and instructors, time management and organisation. A five-point Likert scale (Likert, 1932) was employed in which the highest score, 5, indicated strongly agree, a score of 4 indicated agree, a score of 3 indicated neutral, a score of 2 indicated disagree and the lowest score, 1, indicated strongly disagree.
  • 28. 22 http://ijlter.org/index.php/ijlter Section 4 comprised five questions to assess satisfaction levels among students and instructions regarding their learning or teaching experiences after the shift to e-learning. These questions pertaining to satisfaction assessed overall experiences related to teaching or learning, the clarity of remote teaching or learning instructions, the accessibility of remote teaching or learning materials, the simplicity of remote teaching or learning tools and the support or feedback received during remote teaching or learning. The scale was also based on a five- point Likert scale (Likert, 1932) in which the highest score of, 5, indicated very satisfied, a score of 4 indicated satisfied, a score of 3 indicated neutral, a score of 2 indicated unsatisfied and the lowest score, 1, indicated not at all satisfied. The internal consistency of the questionnaires’ reliability was tested using Cronbach’s α, as described by Bolarinwa (2015). The obtained α value was equal for instructors and students, as follows: perceived e-learning effectiveness (14 questions; 0.85, 0.88) and satisfaction (five questions; 0.78, 0.79). These values showed that the questionnaire’s reliability was good, indicating that the items effectively measured the same aspects. Additionally, the questionnaires were piloted with 10% of the study’s respective samples. This pilot approach involved testing the questionnaires on a smaller scale with a sample of the study population before their distribution. This step was crucial since it helped ensure that the questionnaires adequately measured the items for which they were designed and that respondents provided feedback. Respondents’ feedback was requested on the appropriateness, length and wording of the questionnaires and the instructions, as well as the questions’ adequacy, as recommended by Marshall (2005). 2.3 Statistical Analysis The collected data were analysed using Statistical Package for Social Sciences software (SPSS version 22). Descriptive statistics were used to present the results in frequencies and percentages. Normal data distribution was assessed using Kolmogorov-Smirnov and Shapiro-Wilk tests. An independent t-test was conducted to evaluate differences in means between instructors and students. For instructors, Pearson’s correlation coefficient was applied to determine the correlation among teaching experience, academic rank, the readiness to shift to e- learning, the perceived effectiveness of teaching after the shift to e-learning and satisfaction with e-learning. For students, to assess the correlation among GPAs, academic levels, the readiness to switch to e-learning, the perceived effectiveness of learning and satisfaction with the shift to e-learning, Pearson’s correlation coefficient was used. The statistical significance for these analyses was set to p ≤ 0.05. 3. Results 3.1 General Characteristics In total, 47 instructors and 254 students participated in this study. Of the participating instructors, 65.9% had more than five years of teaching experience and 80.9% had a PhD. The numbers of courses taught by the instructors were two and three, representing 34% and 31.9% of participating instructors, respectively. The majority of participating students were enrolled in courses at the Rehabilitation Sciences department (35.8%) or Health Sciences department
  • 29. 23 http://ijlter.org/index.php/ijlter (45.3%). Most students (95.5%) had an excellent (> 4.5) or very good (3.75–4.4) GPA (Table 1). Table 1. Characteristics of the study sample % n Instructors (n = 47) Academic rank Teaching assistant 10.6 5 Lecturer 8.5 4 Assistant professor 61.7 29 Associate professor 14.9 7 Professor 4.3 2 Teaching experience (years) 0–2 19.1 9 3–5 14.9 7 6–10 34.0 16 > 10 31.9 15 Number of courses taught 1 19.1 9 2 34.0 16 3 31.9 15 4 6.4 3 5 8.5 4 Students (n = 254) Department Rehabilitation Sciences 35.8 91 Health Sciences 45.3 115 Communication Sciences 8.7 22 Radiology Sciences 10.2 26 GPA* Excellent (> 4.5) 41.3 105 Very good (3.75–4.4) 50.4 128 Good (2.5–3.74) 5.5 14 Poor (< 2.5) 0.0 0 Academic level 3–4 31.9 81 5–6 25.2 64 7–8 31.1 79 9–10 5.9 15 11–12 5.9 15 *GPA: Grade point average. 3.2 The Readiness to Shift to e-Learning Vis-à-vis their readiness to shift to e-learning, all participating instructors (100%) and the majority of participating students (97.6%) reported that they owned electronic devices. Additionally, 93.6% of instructors and 94.5% of students reported having proper internet access. Students and instructors seemed to use
  • 30. 24 http://ijlter.org/index.php/ijlter similar ways to interact, including office hours, emails, Telegram, WhatsApp and communication during lectures, and no significant differences were reported in this regard (p > 0.05). Therefore, the authors’ null hypothesis was verified. In contrast, the use of BB was significantly higher (more than twice as high) among instructors (61.7%) compared to students (29.9%); p < 0.00001. However, an analysis of BB use features suggested that students used certain features more than instructors, particularly assignments, virtual classes and quizzes or exams (p = 0.01, p = 0.00022 and p < 0.00001, respectively). The use of discussion boards and the uploading of course materials were almost equal among students and instructors since no significant difference was found in these regards (p > 0.05). The calculated overall mean readiness scores showed that the obtained values were equal to 6.2 ± 1.9 for instructors and 6.5 ± 1.5 for students. The difference between the overall mean readiness scores was not significant between instructors and students (p = 0.187) (Table 2). This finding shows that instructors and students at the CHRS were equally prepared for the sudden shift to e-learning as a result of the COVID-19 pandemic. Table 2: Frequency (in percentages; n) of students’ and instructors’ interactions and readiness Instructors (n = 47) Students (n = 254) p-value Electronic device 100 (47) 97.6 (248) 0.29 Proper internet 93.6 (44) 94.5 (240) 0.81 Interaction Office hours 87.2 (41) 77.6 (197) 0.13 Email 93.6 (44) 90.6 (230) 0.49 BB 61.7 (29) 29.9 (76) < 0.00001 Telegram 6.4 (3) 7.5 (19) 0.78 WhatsApp 42.6 (20) 40.6 (103) 0.79 Lectures only 19.1 (9) 18.9 (48) 0.96 Blackboard features Virtual classes 23.4 (11) 52.8 (134) 0.00022 Discussion board 51.1 (24) 44.9 (114) 0.44 Quizzes or exams 42.6 (20) 73.6 (187) < 0.00001 Uploading course materials 85.1 (40) 83.9 (213) 0.83 Submitting assignments 72.3 (34) 87.0 (221) 0.01 Overall readiness 6.2 ± 1.9 6.5 ± 1.5 0.187 Z-score 3.3 Satisfaction Table 3 summarises the study’s results regarding satisfaction with e-learning among instructors and students at the CHRS. The highest score was obtained for accessibility of e-learning materials for both instructors (4.3 ± 0.7) and students (4.0 ± 1.0). Meanwhile, the lowest score was obtained for e-learning experience for instructors (3.7 ± 1.1) and students (3.4 ± 1.1). A similar low score was obtained for students in support or feedback received during e-learning (3.4 ± 1.3). For all questions related to satisfaction, the average scores for instructors exceeded the corresponding scores for students. Hence, the differences were significant for e- learning experience and clarity of e-learning instructions between the two groups (p = 0.048 and p = 0.011, respectively). Consequently, the mean score for overall satisfaction with e-learning was significantly higher for instructors than students
  • 31. 25 http://ijlter.org/index.php/ijlter (4.1 ± .0.6 versus 3.7 ± 0.8; p < 0.001). Therefore, the authors’ null hypothesis was rejected. These results demonstrate that, unlike the readiness to shift to e-learning (which was similar between the study’s two populations), instructors were more satisfied with their e-learning experiences than students. Table 3: Satisfaction with e-learning among instructors and students at the College of Health and Rehabilitation Sciences: Mean ± SD Instructors (n = 47) Students (n = 254) p-value Overall satisfaction 4.1 ± 0.6 3.7 ± 0.8 < 0.001 e-Learning experience 3.7 ± 1.1 3.4 ± 1.1 0.048 Clarity of e-learning instructions 4.0 ± 0.9 3.6 ± 1.1 0.011 Accessibility of e-learning materials 4.3 ± 0.7 4.0 ± 1.0 0.057 Simplicity of e-learning tools 4.2 ± 0.7 3.9 ± 1.1 0.251 Support or feedback received during e- learning 4.1 ± 0.9 3.4 ± 1.3 0.685 P-values were calculated using an independent t-test. 5 = very satisfied. 1 = not at all satisfied. 3.4 Perceived Effectiveness Table 4 presents the study’s results regarding the perceived effectiveness of learning or teaching after the pandemic-related e-learning shift among both instructors and students. For both instructors and students, the lowest mean scores obtained pertained to shifting to e-learning is more enjoyable than face-to-face learning at 2.1 ± 1.1 and 2.3 ± 1.3, respectively. The highest score was obtained for shifting to e-learning introduced me to different online applications, which helped my teaching/learning, at 4.4 ± 0.7 for instructors and 3.5 ± 0.8 for students. The score for shifting to e-learning helped students become independent learners was significantly higher among students (p = 0.037). The mean scores of the perception-related items were higher for instructors than students. Among instructors, the average scores for seven items were significantly higher (p < 0.05) than students’ corresponding scores: shifting to e-learning gave me a positive teaching or learning experience; improved the quality of my teaching or learning; helped me be better organised; introduced me to different online applications, which helped my teaching or learning; introduced me to a variety of new assessment methods; a good motivation for teaching or learning; and helps deliver or explain the subject’s material well. The authors’ null hypothesis was rejected since the overall average score for instructors’ perceived teaching experiences exceeded the mean score for students’ perceived learning (3.3 ± .0.6 versus 2.9 ± .0.6; p < 0.001) (Table 4). This finding indicates that instructors had better e-learning experiences than students. Table 4: The perceived effectiveness of learning or teaching after the shift to e- learning among instructors and students at the College of Health and Rehabilitation Sciences: Mean ± SD Instructors (n = 47) Students (n = 254) p-value Overall perceived effectiveness of shifting to e- learning 3.3 ± 0.6 3.0 ± 0.6 < 0.001* It gave me a positive teaching/learning experience. 3.7 ± 0.9 2.8 ± 1.0 < 0.001* It improved the quality of my teaching/learning. 3.1 ± 0.9 2.5 ± 1.0 < 0.001* It helped me be better organised. 3.2 ± 0.9 2.9 ± 1.0 0.04*
  • 32. 26 http://ijlter.org/index.php/ijlter It improved the communication between students and instructors. 3.2 ± 1.0 3.1 ± 0.9 0.34 It helped students become independent learners. 3.3 ± 1.1 3.7 ± 0.7 0.037* It helped me work at my own speed. 3.6 ± 1.1 3.6 ± 0.7 0.787 It enabled me to achieve course learning outcomes. 2.9 ± 1.1 2.9 ± 1.1 0.978 It introduced me to different online applications, which helped my teaching or learning. 4.4 ± 0.7 3.5 ± 0.8 < 0.001* It introduced me to a variety of new assessment methods, which affected my teaching or learning in positively. 4.0 ± 1.0 3.1 ± 1.0 < 0.001* It helped me manage my time more effectively. 3.3 ± 1.0 3.1 ± 1.2 0.209 Remote learning is a good motivation for teaching or learning. 4.0 ± 0.8 2.6 ± 1.0 < 0.001* Remote learning helps deliver or explain the subject’s material well. 3.1 ± 1.0 2.5 ± 1.1 0.001* Remote learning is more enjoyable than face-to-face learning. 2.1 ± 1.1 2.3 ± 1.3 0.358 It made me prefer to teach more courses via remote learning. 2.6 ± 1.1 2.8 ± 1.2 0.251 P-values were calculated using an independent t-test. 5 = strongly agree. 1 = strongly disagree. 3.5 Correlations between e-Learning Readiness, Satisfaction and Perceived Effectiveness Table 5 and Table 6 summarise the correlations between the different parameters investigated for students and instructors, respectively. Pearson’s correlation coefficient revealed a strong positive correlation between satisfaction with perceived teaching or learning experiences after the shift to e-learning and the perceived effectiveness of learning or teaching for students (r = 0.68, p < 0.001), as well as a moderate correlation for instructors (r = 0.38, p = 0.008). The readiness to switch to e-learning was weakly correlated with satisfaction for students only (r = 0.217, p < 0.001). Instructors’ academic rank exhibited a moderate correlation with such readiness (r = 0.468, p = 0.001) and perceived effectiveness (r = 0.340, p = 0.019). Interestingly, for both students and instructors, the perceived effectiveness of learning or teaching after the shift to e-learning significantly correlated with e- learning satisfaction, unlike the readiness to switch to e-learning. This finding might indicate satisfaction’s importance as a principal factor in the learning process’s success. Table 5: Correlation between the different parameters investigated among College of Health and Rehabilitation Sciences instructors (n = 47) Teaching experience Academic rank Readiness Perceived effectiveness Satisfaction Teaching experience 1 0.265 0.255 -0.149 0.105 Academic rank — 1 0.468** 0.340* 0.246 Readiness — — 1 0.085 0.11 Perceived effectiveness — — — 1 0.383** Satisfaction — — — — 1 Correlations were calculated using Pearson’s test; * p < 0.05 and ** p < 0.01
  • 33. 27 http://ijlter.org/index.php/ijlter Table 6: Correlation between the different parameters investigated among College of Health and Rehabilitation Sciences students (n = 254) GPA Academic level Readiness Perceived effectiveness Satisfaction GPA 1 -0.085 0.019 -0.03 -0.121 Academic level — 1 0.045 0.028 -0.068 Readiness — — 1 0.682** 0.108 Perceived effectiveness — — — 1 0.217** Satisfaction — — — — 1 Correlations were calculated using the Pearson’s correlation coefficient; ** p < 0.01. 6. Discussion This study aimed to provide an understanding of experiences related to the pandemic-related abrupt shift to e-learning from the perspectives of both teachers and students, assessing how readiness may affect these experiences. The study’s findings revealed a high level of readiness to shift to e-learning among both instructors and students, as well as a positive correlation between perceived effectiveness and satisfaction. However, instructors showed significantly higher satisfaction levels (p < 0.001) and perceived this experience to be more effective than students had done. Based on the study’s conceptual framework, these results indicate that a high level of readiness among students and instructors—which led to satisfaction— correlates with the shift to e-learning’s perceived effectiveness. Both students and instructors agreed that e-learning provided an opportunity to work at their own pace, manage their time more effectively and improve their interactions. The shift to e-learning introduced instructors to a variety of previously not employed online applications with which to communicate with students. Thus, this expansion of the communication tools applied during e-learning improved interactions between instructors and their students. Such interactions enhance students’ engagement and satisfaction with online courses, as the literature has previously shown (Beaudoin et al., 2009; Dixson, 2010). Moreover, students and instructors harboured similar perspectives on the effectiveness of time management and work pacing. e-Learning offers flexible teaching and learning opportunities for more self-directed learning (Albarrak, 2011). Although e- learning forces instructors to work outside their comfort zones, instructors expressed high satisfaction levels. Instructors were more satisfied with their e- learning experiences than students, which may have been due to BB’s regular training and the accessible technical support provided by the university to all faculty members (Alqabbani et al., 2020). Additionally, Maatuk et al. (2021) explained that lower satisfaction levels among students had resulted from the increased workload caused by e-learning. This influence could be particularly present during the emergency shift to e-learning because of the COVID-19 pandemic. Thus, as cognitive load theorists have suggested, instructors should consider the amount of work they assign their students and divide information into chunks so that their students can have more effective learning experiences (Van Merrienboer & Ayres, 2005). Congruent results by Sørebø and Sørebø (2008) indicated that instructors’ perceived usefulness of e-learning and satisfaction are
  • 34. 28 http://ijlter.org/index.php/ijlter useful in introducing appropriate elements for successful planning to achieve effective e-learning. The current study’s results indicate that e-learning helped students become independent learners, showing that students’ autonomy and responsibility vis-à- vis their learning increased after the shift to e-learning. Consistent with this finding, Joo et al. (2011) and Yang and Cao (2013) concluded that learners’ realisation of their e-learning responsibilities predicted learning flows and steadiness, as well as success. Additionally, e-learning facilitates the achievement of learning outcomes and learners’ development, supporting students’ autonomy (Algahtani, 2011). However, Lawrence (2018) claimed that students’ evaluations of their learning’s effectiveness have provided invalid data, and Lawrence considered such evaluations a poor measurement of learning effectiveness. This claim was supported by a meta-analysis showing no significant correlation between students’ teaching evaluations and learning (Uttl et al., 2017). Interestingly, despite students’ low perception of effectiveness, they considered e-learning useful in increasing their autonomy and responsibility vis-à-vis their learning, which is a sign of successful learning (Joo et al., 2011; Yang & Cao, 2013). In Saudi Arabia, e-learning started suddenly during the middle of the second semester of the 2019–2020 academic year, without any prior planning, in response to the COVID-19 pandemic-related lockdowns. Yet, advanced planning and infrastructure are key determinants of successful e-learning (Algahtani, 2011; Aljaber, 2018; Edwards & McKinnell, 2007; Nasiri et al., 2014; Rice & McKendree, 2014). Negative attitudes were observed among both students and instructors in terms of preferring face-to-face learning and not enjoying e-learning. While the sudden shift to e-learning was expected to influence e-learning’s effectiveness, this impact was more apparent among students than instructors since students harboured lower perceptions of e-learning’s effectiveness. A possible explanation for this difference is courses’ clinical and practical nature, which Corter et al. (2011) by confirming that students’ motivations were higher among a hands-on group than at simulation distance laboratory. Additionally, some studies have suggested that e-learning may be avoided since it cannot replace face-to-face learning, especially in medical education (Albarrak, 2011; Rajab, 2018), given medical academics’ independent and conservative nature (Lane, 2007). Another explanation could be the difficulty of achieving intended learning outcomes, which led to improper planning for a complete e-learning mode since courses were designed to be delivered in a traditional mode. Moreover, students’ experience of the shift to e-learning were found to be negative. Hence, their introduction to new assessment methods could be more stressful since they were not trained in these methods; only 29.9% of students had used BB before the studied shift to e-learning. After this shift, classic assessment methods changed to electronic alternatives and a new grade distribution occurred. Therefore, the lack of preparation at both the technical level and the psychological level—as well as concerns about lower grades—could have contributed to this negative perception. Furthermore, the overall increase in anxiety during the COVID-19 pandemic could also have influenced learning (Almoayad et al., 2020; Cao et al., 2020; Gallagher & Schleyer, 2020; Saddik et al.,
  • 35. 29 http://ijlter.org/index.php/ijlter 2020). Students were also found not to have fully understood e-learning course material, marking a significant difference from instructors’ perception. This finding could be associated with students’ preference for face-to-face learning over e-learning and a lack of enjoyment, as previously discussed. Additionally, regarding the nature of health-profession courses, students were suddenly introduced to various substitutes to clinical training—such as simulated and recorded cases—which are effective in health professions education (Albarrak, 2011). Bao (2020) claimed that instructors should break down e-learning material and adopt a modular teaching method to increase students’ involvement in e- learning. The current study has shown that students and instructors were ready to shift to e-learning, demonstrating satisfaction with the support provided, which led to a positive perception of this shift. However, a lack of planning was highlighted in the negative perceptions among learners and teachers. The continued use of traditional methods of teaching, assessing and learning among both teachers and learners—without proper modulation for e-learning—could explain e-learning’s perceived failure to help achieve intended learning outcomes. Thus, given the lack of clarity about education’s future and the expected extension of e-learning, and to promote successful e-learning experiences in health professions education, both instructors and students must adopt new teaching and learning approaches and share their decisions regarding the e-learning planning process. This approach is essential to overcome gaps among the main education stakeholders, especially in different healthcare specialities, which may require various educational strategies and learning styles. 6.1 Limitations Although this study explored e-learning-related perceptions among health professions instructors and students, it did not differentiate between specialities vis-à-vis the nature of clinical courses taught through e-learning. Moreover, the clinical and practical training conducted after the shift to e-learning using online alternatives, such as simulation, were not tested for their effectiveness. The other limitation of this study is the convenient sampling technique used during the project’s data collection. While the study’s findings cannot be generalised, they could nonetheless serve as a basis for adequate planning to develop a complete, successful e-learning model in medical education. 7. Conclusion This study aimed to assess the level of readiness for e-learning, perceived effectiveness and satisfaction regarding e-learning experiences among both students and instructors at a college with courses in 13 health professions during the COVID-19 pandemic. The results showed that the readiness to shift to e- learning was high among both students and instructors, positively correlating with satisfaction—which, in turn, positively correlated with perceived effectiveness. The study’s main findings are that e-learning provided similar opportunities for both students and instructors at the CHRS to work at their own pace, manage their time more effectively and improve their interactions. On the other hand, the sudden shift to e-learning was not enjoyable, and it did not help students or instructors achieve course learning outcomes; both groups would
  • 36. 30 http://ijlter.org/index.php/ijlter have preferred to have more courses delivered via face-to-face learning. Throughout these findings, respondents’ experiences highlighted proper planning’s importance to e-learning. However, a complete e-learning mode might not be suitable for all aspects of health professions education—especially not for courses that require practical skills. By analysing both positive and negative e- learning perceptions during experiences after the sudden shift to e-learning among instructors and students at the CHRS, this study also recommended planning for a blended learning approach integrating face-to-face learning and e- learning to best achieve intended learning outcomes. One of this study’s main recommendations is to plan for e-learning. Utilising different approaches and teaching strategies and considering dividing information into chunks and tasks to avoid overloading students, is recommended to obtain greater benefits from the shift to e-learning during the COVID-19 pandemic, such as better time management and increased independence. Strategies such as team-based learning or flipped classes may be more enjoyable for both teachers and learners during e- learning. Additionally, some assessment methods—such as open-book exams and oral exams—may be more suitable for e-learning than traditional assessment methods. Moreover, blended learning could be suitable to address intended learning outcomes and increase motivation during clinical and practical training while maintaining e-learning’s benefits. Based on this study, the authors recommend further research exploring the e-learning shift’s effect on clinical training outcomes for different health professions. Studies on e-learning experiences a year after this shift, when educational institutions are expected to have clearer plans and have better prepared for e-learning, are also recommended. Acknowledgements This research was funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University through the Fast-track Research Funding Program. Declaration of Interest Statement The authors declare no conflicts of interest. 8. References Al-Samarraie, H., Teng, B. K., Alzahrani, A. I., & Alalwan, N. (2018). E-learning continuance satisfaction in higher education: a unified perspective from instructors and students. Studies in higher education, 43(11), 2003-2019. https://doi.org/10.1080/03075079.2017.1298088 Albarrak, A. (2011). E-learning in medical education and blended learning approach. learning, 13, 14-20. https://www.semanticscholar.org/paper/E-learning-in- Medical-Education-and-Blended- Albarrak/6f7fac687fe689a4166bf1eab385eebcf3b12ab7 Algahtani, A. (2011). Evaluating the E ectiveness of the E-learning Experience in Some Universities in Saudi Arabia from Male Students' Perceptions Durham University]. Durham, UK. http://etheses.dur.ac.uk/3215/ Aljaber, A. (2018). E-learning policy in Saudi Arabia: Challenges and successes. Research in Comparative and International Education, 13(1), 176-194. https://doi.org/10.1177/1745499918764147
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