1. Predictive Modeling of ICT Usage Behaviour among Business Education
Teachers in Tertiary Colleges
of Northwestern Nigeria
Faculty of Educational Studies
Dauda Dansarki
ISIYAKU
Ass. Prof. Dr
Ahmad Fauzi
Mohd Ayub
Dr. Suhaida
Abdulkadir

2. Faculty of Educational Studies
ICTs have taken
over the world –
especially the
regions of the
developed
countries
Background Information
Of the 4.3b
people that don’t
have access to
internet,90% are
from the regions
of developing
countries
No debate -
Teachers
MUST USE
ICTs
Only 28% of
the population
of Nigeria
have access
to Internet

3. Faculty of Educational Studies
ADF, GIA
(1999)
NPIT, (2000)
“Use IT”
Background Information
COAN
ITAN
ISPN
ZINOX
OMATEK
NPIT
Funded by
NITDEF
NRI - WEF by
(2013)
113th
Out of 144

4. Faculty of Educational Studies
Background Information
LII, SII, NII, GIIDBI
ICTs for
Schools
Train the
Trainer
ICTs in
GOs/NGOs

5. Faculty of Educational Studies
Problem Statement
COAN,
ITAN
ZINOX
OMATEK
NRI - WEF by
(2013)
113th
Out of 144
Teachers Use
of ICTs in
Nigeria is
very low
Nigeria still
ranks very
backward
in ICT
adoption
for
education
Unskilled
manpower,
poor funding,
usage of
obsolete
technologies

6. Faculty of Educational Studies
Problem Statement
COAN,
ITAN
ZINOX
OMATEK
NRI - WEF by
(2013)
113th
Out of 144
Lack of ICT
Facilities in
the Nigerian
educational
scenario
ICT Research
initiatives
from Nigeria
are rare
Nigerian
teachers buy
and use ICTs
out of their
own volition

7. To propose a MODEL to
Explain and predict teachers’
ICT usage behaviour on the basis of the
interrelationships of SN, JR, CSE, FC & PE,
(exogenous variables) and
PEOU, PU, ATT, BI & USE (endogenous variables),
in consistence with the assumptions of TRA, TPB &
TAM.
Purpose of the Study

8. Faculty of Educational Studies
Objectives of the Study
COAN,
ITAN
ZINOX
OMATEK
NRI - WEF by
(2013)
113th
Out of 144
Objective Research Questions/Hypotheses
Statistical
Analysis
Objective
1
To describe the types of ICT tools used in the classroom by teachers in tertiary colleges
of Northwestern Nigeria
RQ1 What are the types of ICT tools used in the classroom by teachers in tertiary colleges of
Northwestern Nigeria? Descriptive
Objective
2
To describe the responses of teachers on each of the variables of interest in the study,
namely: subjective norm, job relevance, computer self-efficacy, perceptions of
facilitating conditions, perceived enjoyment, perceived ease of use, perceived
usefulness, attitude towards technology, behavioural intention and ICT usage
behaviour.
RQ2 What are the mean ratings of the responses of teachers on their perceptions of the
expectations of others towards their usage of ICTs in the classroom?
Descriptive
RQ3 What are the mean ratings of the responses of teachers on their perceptions of the relevance
of ICTs to their jobs?
Descriptive
RQ4 What are the mean ratings of the responses of teachers on their perceptions of their abilities
of using computers for purpose of classroom instructions? Descriptive
RQ5 What are the mean ratings of the responses of teachers on their perceptions of the adequacy
of ICT facilities provided in business education faculties of colleges of education in
Northwestern Nigeria?
Descriptive
RQ6 What are the mean ratings of the responses of teachers on their perceptions of the fun they
derive from using ICTs for classroom purpose?
Descriptive

9. Faculty of Educational Studies
Objectives of the Study
COAN,
ITAN
ZINOX
OMATEK
NRI - WEF by
(2013)
113th
Out of 144
Objective Research Questions/Hypotheses
Statistical
Analysis
RQ7 What are the means ratings of the responses of teachers on their perceptions of how easy it
is to use ICTs for classroom purposes?
Descriptive
RQ8 What are the means ratings of the responses of teachers on their perceptions of the
usefulness of ICTs for classroom purposes?
Descriptive
RQ9 What are the means ratings of the responses of teachers on their attitudes towards
technology?
Descriptive
RQ10 What are the means ratings of the responses of teachers on their behavioural intentions
towards using ICTs for classroom purposes?
Descriptive
RQ11 What are the means ratings of the responses of teachers on their perceptions of the
frequency with which they use ICTs for classroom purposes?
Descriptive
RQ12 What are the means ratings of the responses of teachers on their perceptions of the
frequency with which they use ICTs for classroom purposes and the volume of work they do
with the ICTs for the same purpose?
Descriptive
Objective
3
To determine the direct effect of subjective norm and perceived enjoyment on
behavioural intention.
Ha1
Subjective Norm has a direct significant effect on Intention to use ICTs. SEM

10. Objectives of the Study
Objective Research Questions/Hypotheses
Statistical
Analysis
Ha6
Perceived Enjoyment has a direct significant effect on Intention to Use ICTs SEM
Objective
4
To determine the direct effect of job relevance, computer self-efficacy and perceived
ease of use on perceived usefulness.
Ha2
Job Relevance has a direct significant effect on Perceived Usefulness of ICTs. SEM
Ha3
Computer Self Efficacy has a direct significant effect on Perceived Usefulness of ICTs SEM
Ha7
Perceived Ease of Use of ICTs has a direct significant effect on Perceived Usefulness of
ICTs
SEM
Objective
5
To determine the direct effect of computer self-efficacy and facilitating conditions on
perceived ease of use.
Ha4 Computer Self Efficacy has a direct significant effect on Perceived Ease of Use of ICTs SEM
Ha5 Perception of Facilitating Conditions has a direct significant effect on Perceived Ease Use of
ICTs
SEM

11. Objectives of the Study
Objective Research Questions/Hypotheses
Statistical
Analysis
Objective
6
To determine the direct effect of perceived usefulness and perceived ease of use on
attitude towards technology.
Ha8
Perceived Usefulness of ICTs has a direct significant effect on ICT Attitude. SEM
Ha9 Perceived Ease of Use of ICTs has a direct significant effect on ICT Attitude. SEM
Objective
7
To determine the direct effect of attitude towards technology on behavioural intention.
Ha10 Attitude towards technology has a direct significant effect on Intention to Use ICTs SEM
Objective
8
To determine the direct effect of behavioural intention on ICT usage behaviour.
Ha11 Intention to Use ICTs has a direct significant effect on Actual ICT Usage SEM
Objective
9
To predict the fitness of the model of the study in explain ICT usage behaviour among
business education teachers in tertiary colleges of Northwestern Nigeria.

12. Faculty of Educational Studies
Operational Definitions
COAN,
ITAN
ZINOX
OMATEK
o extent to which teachers perceive that they are
expected to use ICTs in the classroom.
Subjective
Norm (SN)
o degree to which teachers believe that ICTs are
applicable to their instructional purposes
Job
Relevance
(JR)
o teachers’ judgment of their capabilities in using ICTs
for classroom functions.
Computer Self
Efficacy (CSE)

13. Faculty of Educational Studies
Operational Definitions
COAN,
ITAN
ZINOX
OMATEK
o degree to which teachers believe that they are
supported with ICTs to facilitate their classroom
functions.
Facilitating
Conditions
(FC)
o extent to which teachers perceive that using
ICTs in the classroom is enjoyable.
Perceived
Enjoyment
(PE)
o degree to which teachers believe that using ICTs for
classroom purposes will be easy for them
Perceived
Ease Of Use
(PEOU)

14. Faculty of Educational Studies
Operational Definitions
COAN,
ITAN
ZINOX
OMATEK
o teachers’ assessment of how ICTs are useful and
productive to them for classroom purposes
Perceived
Usefulness
(PU)
o extent to which teachers exhibit favourable or
unfavourable dispositions toward usage of
technology in facilitating classroom
instructions.
Attitude
Towards
Technology
(ATT)
o degree to which teachers are determined and
intended to use ICTs in the classroom.
Behavioural
Intention (BI)
ICT Usage
Behaviour
(USE)
o frequency with which teachers use ICTs and the
volume of the tasks they perform with these ICTs for
classroom purposes.

15. Faculty of Educational Studies
COAN,
ITAN
ZINOX
OMATEK

16. Beliefs &
Evaluati
ons
Attitude
toward
behavio
r
Normati
ve
Beliefs
Subjecti
ve
Norm
Behavio
ral
Intentio
n
Actual
Behavio
ur
Theory of Reasoned Action
(Fishbein & Ajzen, 1975)
Theories

17. Theory of Planned Behaviour
(Ajzen, 1985)
Theories
ATTITUDE
TOWARD
BEHAVIOR
SUBJECTIVE
NORM
PERCEIVED
BEHAVIORAL
CONTROL
BEHAVIOU
RAL
INTENTION
BEHAVIOU
RAL
PERFORMA
NCE

18. Theories
Technology Acceptance Model (TAM)
(Davis, 1989)
Perceived
Usefulness
Perceived
Ease of Use
System UseExternal
Factors

19. Theories
Technology Acceptance Model (TAM) 3
(Venkatesh & Bala, 2008)

20. COAN,
ITAN
ZINOX
OMATEK
Theoretical Framework
Theoretical
Framework
TRA
ATT
SN
BI
USE
TAM
SN
JR
FC
CSE
PE
PU
OU
ATT
BI
USE
TPB
ATT
SN
BI
USE

21. Faculty of Educational Studies
COAN,
ITAN
ZINOX
OMATEK
Conceptual Framework

22. Faculty of Educational Studies
Literature Review
COAN,
ITAN
ZINOX
OMATEK
Venkatesh et al., 2003; Ho, Poorisat, Neo, & Detenber,
2014; Oye, Iahad, & Rahim, 2014; López-Nicolás et al.,
2008; Echeng & Usoro, 2014
Subjective
Norm (SN)
Venkatesh & Davis, 2000; Ezeani & Akpotohwo,
2014; Kim, 2008; Egbri, 2012; Ezeani & Akpotohwo,
2014; Alharbi & Drew, 2014
Job
Relevance
(JR)
Compeau & Higgins, 1995; Agarwal & Teo, Lee, Chai,
and Wong; 2009; Igbaria and Iivari, 1995; Karahanna,
2000; Venkatesh & Bala, 2008.
Computer Self
Efficacy (CSE)

23. Faculty of Educational Studies
Literature Review
COAN,
ITAN
ZINOX
OMATEK
Thompson et al., 1991; Asogwa & Eze, 2013; David,
2012; Ololube, 2014; Prasad et al., 2015; Teo, 2011;
Venkatesh et al., 2003; Olasina & Mutula, 2014.
Facilitating
Conditions
(FC)
Verkasalo, López-Nicolás, Molina-Castillo, &
Bouwman, 2010; Venkatesh, 2000; Davis, Bagozzi,
& Warshaw, 1992; Van der Heijden 2004
Perceived
Enjoyment
(PE)
Davis et al., 1989; Igbaria, Iivari, & Maragahh, 1995;
Anandarajan et al., 2002; Alharbi and Drew, 2014;
Venkatesh and Morris, 2000.
Perceived
Ease Of Use
(PEOU)

24. Faculty of Educational Studies
Literature Review
COAN,
ITAN
ZINOX
OMATEK
Pynoo and van Braak, 2014; Davis, 1989, Anandarajan
et al., 2002; Teo, 2011; Schepers & Wetzels, 2007
Perceived
Usefulness
(PU)
Eagly Alice & Chaiken, 1998; Adewole-Odeshi, 2014;
Thompson et al., 1991; Smith, Caputi, & Rawstorne,
2000; Wilkinson and Schilt; 2008; Mohd, Mokhtar,
Wong, & Tarmizi, 2010; Valtonen et al., 2015). .
Attitude
Towards
Technology
(ATT)
Davis et al., 1989; Pynoo and van Braak, 2014; Kim, 2008;
Teo, 2011; Schepers & Wetzels, 2007; López-Nicolás et
al., 2008; Echeng & Usoro, 2014; Oye et al., 2011.
Behavioural
Intention (BI)
ICT Usage
Behaviour
(USE)
Angel, 2013; Kim, 2008; Agudo-Peregrina, Hernández-
García, & Pascual-Miguel, 2014; Turner, Kitchenham,
Brereton, Charters, and Budgen (2010; Onwuagboke,
Singh, & Fook, 2015.

25. Faculty of Educational Studies
Literature Review
COAN,
ITAN
ZINOX
OMATEK
• Schepers & Wetzels, 2007;
• López-Nicolás et al., 2008;
• Echeng & Usoro, 2014;
• Oye et al., 2011 & Teo, 2011)
SN → BI (H1)
• Ezeani & Akpotohwo, (2014)
• Venkatesh & Davis, (2000)
• Alharbi & Drew, (2014).
JR → PU (H2)
• Teo et al. (2009),
• Agarwal & Karahanna (2000)
• Cheok & Wong, (2015) CSE → PU (H3)
• Igbaria and Iivari (1995)
• Venkatesh and Bala (2008)
• (Teo et al., 2009
• (Merhi, 2015).
CSE → PEOU (H4)

26. Faculty of Educational Studies
Literature Review
COAN,
ITAN
ZINOX
OMATEK
• Olasina and Mutula (2014)
• Teo et al. (2008)
• Teo et al. (2009),
FC PEOU(H5)
• Atkinson & Kydd (1997)
• Van der Heijden (2004),
• Verkasalo et al., (2010), Merhi, (2015)
PE → BI(H6)
• Anandarajan et al. (2002),
• Venkatesh and Morris (2000)
• (Merhi, 2015)
PEOU → PU(H7)
• Teo et al. (2008),
• Pynoo and van Braak (2014)
PU → ATT(H8)
→

27. Faculty of Educational Studies
Literature Review
COAN,
ITAN
ZINOX
OMATEK
• Bajaj and Nidumolu (1998),
• Schepers &Wetzels (2007), PEOU → ATT (H9)
• Teo (2011)
• Alharbi and Drew (2014)
• Pynoo and van Braak (2014)
• (Adewole-Odeshi, 2014)
ATT → BI(H10)
• Kim (2008)
• Bagozzi (2007)
• Pynoo and van Braak (2014)
BI → USE (H11)

28. Faculty of Educational Studies
COAN,
ITAN
ZINOX
OMATEK
Methodology

29. Faculty of Educational Studies
COAN,
ITAN
ZINOX
OMATEK
Research Design:
Survey Study
Population : 363 Business Education Teachers
Sample: 157 (Cochran, 1977)
40% added =
(Salkind, 2010) 220
(Bentler & Chou, 1987)
Type of survey:
Field Trip
Location :
Northwestern Nigeria
(Educationally and technologically disoriented (Kolawole,
Omobitan, & Yaqub, 2015; Ukiwo, 2007

30. COAN,
ITAN
ZINOX
OMATEK
State
Names of Tertiary
Colleges
Pop of Bus.
Edu
Teachers
Sample of
Bus. Edu
Teachers
Kano
FCE (T) Bichi 29 21 21
FCE Kano 20 11
SRCOE Kano 32 24
Jigawa JSCOE Gumel 30 8 22
Katsina
FCE Katsina 45 32
IKCOE Dutsinama Nil 12 Nil
Kaduna
FCE Zaria 45 28
KSCOE Kafanchan 39 30 26
JCOE Kaduna 32 27
Sokoto SSCOE Sokoto 37 10 27
Kebbi AACOE Argungu 36 9 24
Zamfara
ZSCOE Maru Nil Nil
FCE (T) Gusau 38 10 27
Total 383 269
Proportionate Stratified Sampling

31. COAN,
ITAN
ZINOX
OMATEK
State
Names of Tertiary
Colleges
Pop of Bus.
Edu
Teachers
% for
Samp &
Pop
Sample of
Bus. Edu
Teachers
Kano
FCE (T) Bichi 29 21 18
FCE Kano 20 8
SRCOE Kano 32 20
Jigawa JSCOE Gumel 30 8 18
Katsina
FCE Katsina 45 26
IKCOE Dutsinama Nil 12 Nil
Kaduna
FCE Zaria 45 23
KSCOE Kafanchan 39 30 21
JCOE Kaduna 32 22
Sokoto SSCOE Sokoto 37 10 22
Kebbi AACOE Argungu 36 9 20
Zamfara
ZSCOE Maru Nil Nil
FCE (T) Gusau 38 10 22
Total 383 220
Proportionate Stratified Sampling

32. COAN,
ITAN
ZINOX
OMATEK
Section Components Items Source
Part A Demographic Items
Basic Demographic Information
ICT Usage Demographic Information:
(a) ICT Peripherals for Class Interactions
(b) ICT Tools for Virtual Interactions
(c) ICT Tools for Research
(d) ICT Tools for Mindmap & Brainstorm
(e) ICT Tools for Content Creation
(f) ICT Tools for Content Sharing
5
11
11
11
11
11
11
Self-developed
Self-developed
Self-developed
Self-developed
Self-developed
Self-developed
Self-developed
Part B
73 Items
Constructs Items
Section I Subjective Norm (SN)
Job Relevance (JR)
Computer Self-Efficacy (CSE)
7
6
7
Venkatesh et al. 2003
Venkatesh & Bala, 2008
Henry & Stone, 1997, 1999
Section II Facilitating Conditions (FC)
Perceived Enjoyment (PE)
6
6
Venkatesh &Davis1996
Venkatesh & Bala, 2008
Section III Perceived Ease Of Use (PEOU)
Perceived Usefulness (PU)
6
7
Venkatesh & Bala, 2008
Venkatesh & Davis, 2000
Section IV Attitude Towards Technology (ATT)
Behavioural Intention (BI)
7
7
Teo, 2010; 2011; Venkatesh et al., 2003
Cheun, et al., 2002Oye et al., 2012
Section VA ICT Use Frequency (USE) 7 Kim, 2008Venkatesh & Bala, 2008
Section VB ICT Use Volume (USE) 7 Kim, 2008Venkatesh & Bala, 2008
Instrumentation
Instru
Questi
(73 i

33. COAN,
ITAN
ZINOX
OMATEK
Pilot Test
S/N Construct
Number of
Items
Cronbach’s
Alpha Coefficient
For Pilot Study (n=30)
1 Subjective Norm 7 .692
2 Job Relevance 6 .512
3 Computer Self-Efficacy 7 .897
4 Facilitating Conditions 7 .726
5 Perceived Enjoyment 6 .806
6 Perceived Ease Of Use 7 .765
7 Perceived Usefulness 7 .740
8
Attitude Towards
Technology
6 .673
9 Behavioural Intention 7 .722
10 Usage Behaviour 14 .943
Average .750

34. COAN,
ITAN
ZINOX
OMATEK
Reliability
S/N Construct
Number of
Items
Cronbach’s
Alpha Coefficient
For Final Study (n=212)
1 Subjective Norm 7 .917
2 Job Relevance 6 .809
3 Computer Self-Efficacy 7 .845
4 Facilitating Conditions 7 .808
5 Perceived Enjoyment 6 .826
6 Perceived Ease Of Use 7 .875
7 Perceived Usefulness 7 .836
8
Attitude Towards
Technology
6 .813
9 Behavioural Intention 7 .879
10 Usage Behaviour 14 .926
Average .853
212
Teachers

35. COAN,
ITAN
ZINOX
OMATEK
Validity
S/N Construct
Number of
Items
Construct Reliability
(n=212)
1 Subjective Norm 7 .921
2 Job Relevance 6 .782
3 Computer Self-Efficacy 7 .804
4 Facilitating Conditions 7 .921
5 Perceived Enjoyment 6 .879
6 Perceived Ease Of Use 7 .898
7 Perceived Usefulness 7 .828
8
Attitude Towards
Technology
6 .798
9 Behavioural Intention 7 .907
10 Usage Behaviour 14 .894
Average .871
Validated by
Experts

36. COAN,
ITAN
ZINOX
OMATEK
Results & Findings

37. Data Analyses
S/N Gender Category f %
1 Females 78 36.8
2 Males 134 63.2
Gender Demographics

38. Data Analyses
S/N Age Category f %
1 26-33years 22 10.4
2 34-40 years 69 32.5
3 41-47 years 64 30.2
4 48-54 years 43 20.3
5 55-63 years 14 6.6
M=42.58; SD=7.49
Age Demographics

39. Data Analyses
S/N Work Experience f %
1 2-8 years 99 46.7
2 9-14 years 44 20.8
3 15-20 years 42 19.8
4 21-26 years 20 9.4
5 27-33 years 7 3.3
M=11.37; SD=7.38
Work Experience

40. Data Analyses
S/N Status Category f %
1 Assistant Lecturer/Instructor 42 19.8
2 Lecturer/Instructor 72 34.0
3 Senior Lecturer/Instructor 56 26.4
4 Principal Lecturer/Instructor 26 12.3
5 Chief Lecturer/Instructor 16 7.5
M=2.54; SD=1.16
Official Status

41. Data Analyses
S/N Qualifications f %
1 Ordinary Certs - -
2 NCE/OND - -
3 Degree/HND 107 50.5
4 Masters 99 46.7
5 PhD 6 2.8
M=3.52; SD=0.56
Educational Background

42. COAN,
ITAN
ZINOX
OMATEK
Overall Mean for ICT Tools Used
Items
% Mean for Non
Users
% Mean for
Users
IICT Peripherals for Classroom Interactions
72.5% 27.5%
IICT Tools for Virtual Interactions 90.8% 9.2%
IICT Tools for Research 90.6% 9.4%
IICT Tools for Mind-mapping & Brainstorming 95.6% 4.4%
IICT Tools for Content Creation 91.8% 8.2%
IICT Tools for Content Sharing 90.6% 9.4%

43. COAN,
ITAN
ZINOX
OMATEK
Overall Mean for Constructs
Variable/Construct
Number of
Items
Mean SD
Subjective Norm 7 3.59 0.75
Job Relevance 6 4.36 0.60
Computer Self Efficacy 7 3.36 0.70
Facilitating Conditions 6 2.71 0.62
Perceived Enjoyment 6 4.13 0.66
Perceived Ease Of Use 7 3.60 0.87
Perceived Usefulness 7 4.18 0.54
Attitude Towards Technology 6 3.98 0.65
Behavioural Intention 7 4.51 0.57
Usage Behaviour 14 3.33 0.96
Average Mean & SD 3.78 0.69

44. COAN,
ITAN
ZINOX
OMATEK
Findings: Descriptive Statistics
Most Common ICT
tools are desktop and
laptop computers
Teachers use Google
Scholar and YouTube
platforms above all
other tools

45. COAN,
ITAN
ZINOX
OMATEK
Findings: Descriptive Statistics
Teachers use ICTs out
of their own volition
Teachers perceive
that ICTs are relevant
to their jobs
Teachers perceptions
of their abilities for
using ICTs is low

46. COAN,
ITAN
ZINOX
OMATEK
Findings: Descriptive Statistics
ICT facilities are
very inadequate
for teachers
Teachers perceive
that ICTs are
enjoyable
Teachers perceive
that ICTs are not
easy to use

47. COAN,
ITAN
ZINOX
OMATEK
Findings: Descriptive Statistics
Teachers perceive
that ICTs are
useful for their
jobs
Teachers have
positive attitudes
towards using
ICTs
Teachers
intention
to use technology
is very high
Teachers use of
ICTs is below
average

48. COAN,
ITAN
ZINOX
OMATEK
Findings: Structural Equation Modelling
STEP 1
• Defining Individual Constructs
STEP 2 • Developing the Overall Measurement Model
STEP 3
• Designing a Study to Produce Empirical Result
STEP 4
• Assessing Measurement Model Validity
STEP 5
• Specifying the Structural Model
STEP 6
• Assessing Structural Model Validity

49. COAN,
ITAN
ZINOX
OMATEK
Data Analyses: Structural Equation Modelling
Subjective Norm ( 7 items  4 items)

50. COAN,
ITAN
ZINOX
OMATEK
Data Analyses: Structural Equation Modelling
Job Relevance (6 items  4 items)

51. COAN,
ITAN
ZINOX
OMATEK
Data Analyses: Structural Equation Modelling
Computer Self Efficacy (7 items  4 items)

52. COAN,
ITAN
ZINOX
OMATEK
Data Analyses: Structural Equation Modelling
Facilitating Conditions( 6 items  4 items)

53. COAN,
ITAN
ZINOX
OMATEK
Data Analyses: Structural Equation Modelling
Perceived Enjoyment (6 items  4 items)

54. COAN,
ITAN
ZINOX
OMATEK
Data Analyses: Structural Equation Modelling
Perceived Ease Of Use (7 items  4 items)

55. COAN,
ITAN
ZINOX
OMATEK
Data Analyses: Structural Equation Modelling
Perceived Usefulness ( 7 items  4 items)

56. COAN,
ITAN
ZINOX
OMATEK
Data Analyses: Structural Equation Modelling
Attitude Toward Technology (6 items  4 items)

57. COAN,
ITAN
ZINOX
OMATEK
Data Analyses: Structural Equation Modelling
Behavioural Intention ( 7 items  4 items)

58. COAN,
ITAN
ZINOX
OMATEK
Data Analyses: Structural Equation Modelling
ICT Usage Behaviour ( 14 items  6 items)

59. Data Analyses: SEM
Measurement Model
Fit Indices
Index
Value
Recmd
Value
Results
TLI 0.936 >0.90 Good Fit
CFI 0.947 >0.90 Good Fit
IFI 0.948 <0.90 Good Fit
RMSEA 0.054 <0.08 Good Fit
Chisq/df 1.623 <5.00 Good Fit
Model has good fit indices
Indicating internal consistency &valid path coefficients)

60. Data Analyses: SEM
Convergent Validity
• >.50 or
• >.70 (Hair et al, 2010)
Factor
loading
• >0.5 (Hair
et al, 2010)
AVE
• >0.7 (Hair et al, 2010)
CR
o 3 different methods were used to test convergent validity

61. Construct Item Factor Loading AVE (≥0.5) CR(≥0.7)
Subjective Norm SN4 0.96 0.941 0.980
SN6 0.99
SN7 0.96
Job Relevance JR1 0.93 0.923 0.960
JR5 0.99
Computer Self-Efficacy CSE1_R 0.80 0.579 0.804
CSE3_R 0.64
CSE7 0.82
Facilitating Conditions FC3_R 0.91 0.718 0.881
FC4_R 0.94
FC5 0.64
Perceived Enjoyment PE1 0.93 0.697 0.873
PE2 0.82
PE6_R 0.74
Measurement Model

62. Construct Item Factor Loading AVE (≥0.5) CR(≥0.7)
Perceived Ease Of Use PEOU1_R 0.93 0.840 0.940
PEOU3 0.92
PEOU4 0.90
Perceived Usefulness PU3_R 0.72 0.560 0.838
PU4 0.74
PU5 0.81
PU6 0.73
Attitude towards
Technology
ATT3 0.71 0.616 0.758
ATT5 0.82
Behavioural Intention BI2 0.85 0.888 0.959
BI4 0.99
BI5 0.98
ICT Usage Behaviour USE2 0.71 0.546 0.857
USE4 0.70
USE10 0.75
USE11 0.74
USE13 0.79
Measurement Model

63. Structural Model

64. Paths b S.E. C.R. P-Level
Paths
Coef.
(beta)
Results
SN → BI .010 .031 .336 .737 .016 Not Supported
JR → PU .302 .065 4.655 *** .327 Supported
CSE → PU .326 .057 5.707 *** .488 Supported
CSE → PEOU .138 .080 1.710 .087 .135 Not Supported
FC → PEOU -.056 .064 -.868 .385 -.064 Not Supported
PE → BI .619 .049 12.698 *** .724 Supported
PEOU → PU -.071 .045 -1.567 .117 -.109 Not Supported
PU → ATT .714 .122 5.865 *** .709 Supported
PEOU → ATT .011 .041 .269 .788 .017 Not Supported
ATT → BI .191 .060 3.200 .001 .172 Supported
BI → USE .102 .099 1.031 .303 .078 Not Supported
Hypotheses Test

65. Structural Model with New Paths

66. Paths b S.E. C.R. P-Level
Paths
Coef.
(beta)
Results
SN → ATT .093 .036 2.552 .011 .156 Supported
PE → PU .241 .074 3.273 .001 .318 Supported
CSE → USE .437 .085 5.108 *** .447 Supported
FC → USE .122 .055 2.233 .026 .151 Supported
ATT → USE .423 .124 3.427 *** .303 Supported
New Paths

67. OverallStructuralModelSummary

68. Faculty of Educational Studies
Conclusions
COAN,
ITAN
ZINOX
OMATEK
Endogenous Variable Estimate Percentage
Perceived Ease of Use .020 20
Perceived Usefulness .380 38
Attitude Towards Technology .502 50.2
Behavioural Intention .613 61.3
ICT Usage Behaviour .006 10
Explained Variance (Squared Multiple Correlations)- 1st Model)

69. Faculty of Educational Studies
Conclusions
COAN,
ITAN
ZINOX
OMATEK
Endogenous Variable Estimate Percentage
Perceived Ease of Use .021 20.1
Perceived Usefulness .424 42.4
Attitude Towards Technology .524 52.4
Behavioural Intention .630 63%
ICT Usage Behaviour .403 40.3
Explained Variance (Squared Multiple Correlations)- 2nd Model)

70. Faculty of Educational Studies
Conclusions
COAN,
ITAN
ZINOX
OMATEK
The proposed model has satisfied all the goodness of
fit indices criteria and it has parsimony in explaining ICT
usage behaviour
The proposed model without the new paths has
explained only about 10% of the variance in Teachers
ICT usage behaviour
The proposed model with the new paths has explained
about 40.3% of the variance in Teachers ICT usage
behaviour

71. Faculty of Educational Studies
Conclusions
COAN,
ITAN
ZINOX
OMATEK
In both models, business teachers behavioural
intention has highly contributed to their ICT usage
behaviour, however ICT usage was low
Perceived enjoyment, perceived usefulness and
computer self efficacy are the predictor factors with
greater weights and strengths as compared to other
predictor factors in the model
Lack of facilities might hinder teachers from using
ICTs even though they have good attitudes and
intentions to use them

72. Faculty of Educational Studies
Implications
COAN,
ITAN
ZINOX
OMATEK
The study is supportive to the propositions of TRA TPB
and TAM
Teachers secure and use ICTs out of their volition, school
authorities provide the tools specify that teachers are
expected to use them
Teachers who perceive that they are capable of using
ICTs use them without first understanding the
application areas of the tools thereby underutilizing
the tools

73. Faculty of Educational Studies
Implications
COAN,
ITAN
ZINOX
OMATEK
Train the teacher
programs should be
reinforced to
improve teachers’
computer efficacy
Teachers should use
more smart &
mobile technologies
to connect on the go
Teachers use virtual
platforms to ensure
that teaching doesn’t
end in the classroom
Teachers should
utilize research tools
like poll everywhere,
survey monkey to
directly connect with
targets
ICT
infrastructures
should be
greatly
improved in
schools

74. Faculty of Educational Studies
Recommendations
COAN,
ITAN
ZINOX
OMATEK
Further studies should
try to employ the
experimental
approach and attempt
to observe or
interview technology
acceptance behaviour Further research may
consider the role of
compulsory or voluntary
standards in ensuring that
teachers use ICTs in the
classroom
Further studies
should try to
cover larger
populations and
samples

76. Dansarki, I. D., Ayub, A. F. M., & Kadir S.,(2013), Utilizing information
communication technologies for facilitating business education instructions in
Nigeria. Proceedings of Graduate Research in Education Seminar(GREduc) , pp
213-221, Universiti Putra Malaysia

77. Isiyaku, D. D., Ayub, A. F. M., & Kadir, S. A. (2014). Modelling ICT usage behaviour in
business education faculties of tertiary colleges in Nigeria. Paper presented at the
Australian Academy of Business and Social Sciences Conference 2014 (in partnership of
the Journal of Developing Areas - USA), Kuala Lumpur, Malaysia.

78. Faculty of Educational Studies
COAN,
ITAN
ZINOX
OMATEK
Dansarki, I. D., Ayub, A. F. M., & Kadir, S. A. (2015). Hypothetical prediction of ICT usage behaviour among business education
teachers in Nigerian colleges of education. Australian Journal of Sustainable Business and Society, 1(2).

79. Faculty of Educational Studies
COAN,
ITAN
ZINOX
OMATEK
Dansarki, I. D., Ayub, A. F. M., & Kadir, S. A. (2015). ICT Tools Utilized by Business Education
Teachers in Tertiary Colleges of a Developing Country. 3rd International Conference on
Educational Research and Practice. Proposed paper

80. Faculty of Educational Studies
COAN,
ITAN
ZINOX
OMATEK

81. Faculty of Educational Studies
COAN,
ITAN
ZINOX
OMATEK