The relationship of e-learner’s self-regulatory efficacy and perception of e-learning environmental quality of Jong-Ki Lee & Woo-kyu Lee. This slide was used for critical presentation in Educational Psychology subject at CCNU. Author: Chinun Boonroungrut ชื่อ-นามสกุล: ชินัณ บุญเรืองรัตน์ E-mail: b.chinun@gmail.com

1. THE RELATIONSHIP OF E-
LEARNER’S SELF-REGULATORY
EFFICACY AND PERCEPTION OF
E-LEARNING ENVIRONMENTAL
QUALITY
Presented by:
Alemayehu E., Chinun B. and Kflezgi O.
Central China Normal University
Researchers:
Jong-Ki Lee,
Woong-Kyu Lee

2. DOWNLOAD HERE
The original article and handouts is available online.
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https://pan.baidu.com/s/1skZ9yTf

3. COMPUTERS IN HUMAN
BEHAVIOR
Journal Published on 2008 Vol.24, 32 - 47
SSCI Impact factor: 1.344 (2008), 2.88
(2015)

4. RESEARCHERS
Jong-Ki Lee
School of Business Administration,
Kyungpook National University,
Republic of Korea
Woong-Kyu Lee
School of Business Administration,
Daegu University,
Republic of Korea

5. INTRODUCTION Backgrounds & theories

6. IT BACKGROUNDS:
E-Learning
Internet Technology Web-based Applications
Why is E-Learning
User increasing in
2008?

7. WHAT HAPPENED IN 2008:
“BACK TO THE FUTURE”
Beginning time of
the digital world

8. BACKGROUNDS:
E-learning
System Provider
E-Learning
End User
as Self-Directed
Learning
●
The System’s User Satisfaction
The Quality of the Information
●
The Learning Environment
The Study Ability
The Learner’s Regulatory
●
Academic Achievement (degree or
diploma)

9. INFORMATION SYSTEM
SUCCESS MODEL:
DeLone & McLean’ s ISS model (1992)

10. INFORMATION SYSTEM
SUCCESS MODEL:
DeLone & McLean ’ s an intergrated ISS model (2003)

11. RESEARCH MODEL Questions and Hypothesis

12. QUESTIONS:
Based on DeLone & McLean ISS Model (2003)
Are there some relations between
Self-Regulatory Efficacy (SRE)
And ISS Model variables ?

13. RESEARCH MODEL
The Model is divided into 3 main parts to generate hypothesis.
Satisfaction and Academic Performance
Self-regulatory Efficacy (Moderating Variable)
Quality of e-Learning Environment

14. RESEARCH MODEL
FRAMEWORK

15. HYPOTHESIS:
H1: Satisfaction of e-Learning Environment (+ ➤) Academic Performance
H2: Ease of Use LMS (+ ➤) Satisfaction of e-Learning
Environment
H3: Usefulness of Use LMS (+ ➤) Satisfaction of e-Learning
Environment
H4: Ease of Use LMS (+ ➤) Usefulness of Use LMS
H5: Service of Quality (+ ➤) Satisfaction of e-Learning
Environment
H6: Information Representational Quality (+ ➤) Satisfaction of e-Learning
Environment
H7: Information Contextual Quality (+ ➤) Satisfaction of e-Learning

16. MODERATING VARIABLE
HYPOTHESIS:
Researchers Studied
Self-regulatory Efficacy in
higher learner VS lower Learner
To define their relations
Based on ISS Model

17. MODERATING VARIABLE
HYPOTHESIS:
H1a: SRE in > on SA → PA
H2a: SRE in > on PEOU → SA
H3a: SRE in > on PU → SA
H5a: SRE in > on SQ → SA
H6a: SRE in > on IRQ → SA
H7a: SRE in > on ICQ → SA
Note: higher Lower
group group

18. METHODOLOGY Population and Method

19. ◉ Cross Sectional Study (2004)
◉ 37-item Likert’s 5 Points Scale Questionnaire
◉ Studied Population:
Students Students enrolled 225
Daegu University e-Learning course
Participants
RESEARCH METHODOLOGY
▶ ▶

20. DEMOGRAPHY
W: 102 M:123
1st: 3 2nd: 39
3rd: 62 4th:
121
Culture Social Sci Science Engineer
Physic
74 95 16 32 8
e-Ever: 102 e-
Never:123

21. RESULTS Key findings

22. RELIABILITY
Reliability
Stability or consistency of the measurement
Cronbach’s coefficient alpha (Muijs, 2004:73)

23. RELIABILITY:

24. RELIABILITY:

25. VALIDITY
Validity
It means to what extent an instrument measures
what it intends to measure (Cohen, et al.,
2000:105).
The main purpose of validity is to enhance the
accuracy of the findings by avoiding or
controlling the confounding variables

26. DEMOGRAPHIC ATTRIBUTES:
Used AVE with Cronbach ⍺

27. AVE
Advertising Value Equivalency
is a measure that has been used in the public relations industry to
'measure' the benefit to a client from media coverage of a PR
campaign.
AVE's would commonly measure the size of the coverage gained, its
placement and calculate what the equivalent amount of space, if paid
for as advertising, would cost.

28. Used Correlation Coefficient of construct and AVE
The suggested measure model is estimated as a good discriminate validity because the AVE value is
higher than the correlation coefficient of other constructs as shown in the Table.

29. DATA ANALYSIS
 PLS (Partial Least Square)
It fits multiple response variables in a single model. Because PLS regression models
the response variables in a multivariate way, the results can differ significantly from
those calculated for the response variables individually.
You should model multiple responses in a single PLS regression model only when
they are correlated.

30. PLS ANALYSIS OF FULL MODEL

31. PLS ANALYSIS OF SRE’S LOWER
GROUP

32. PLS ANALYSIS OF SRE’S HIGHER GROUP

33. PLS ANALYSIS OF SRE’S LOWER GROUP AND
HIGHER GROUP
Groups AP SA
SRE’s LG of e-learners 12.7% 60.9%
SRE’s HG of e-learners 16.7% 48.9%

34. GROUP ANALYSIS OF SRE

35. STATISTICAL HYPOTHESIS
REJECTIONS:

36. DISCUSSION Consideration by augment

37. CONCLUSION & SUGGESTION
◉ A New model of ISS + SRE
= One of Human Services to e-learner
◉ Quality of System =
LMS + Quality of Assessment of Interaction Information and System
◉ Confirmation that SRE’s higher learner
has high self-study and perceived learning strategy.

38. CRITICAL REVIEW Strength and weakness

39. E-LEARNING PROVIDERS:
FROM 2008-2016

40. STRENGTHS
-The researcher continually works on e-Learning and
many articles related e-learning are published.
-Studied Samples are in the normal distribution; not differences
between genders.
-e-Learning allows flexible learner-centered education provides
inter-disciplinary approach

41. WEAKNESS
- In the Article the number of students, who took an analysis
questionnaire, is not clearly defined.
-To make the reader understand, the source of number indicated in
Tables should be provided
•
The 4th hypotheses correlation has error. Which is LMS to LMS. So, we suggested to
be correlated with PU.
• In our group discussion we agreed the Topic had to be written e-Learners’ instead of
e-Learner’s

43. EDUCATION = FUTURE So enjoy it!

44. REFERENCES:
Dabbagh, N., & Kitsantas, A. (2012). Personal Learning Environments, social media, and self-
regulated learning: A natural formula for connecting formal and informal learning. The Internet and
higher education, 15(1), 3-8.
Gómez-Aguilar, D. A., Hernández-García, Á., García-Peñalvo, F. J., & Therón, R. (2015). Tap into
visual analysis of customization of grouping of activities in eLearning. Computers in Human
Behavior, 47, 60-67.
Kuo, Y.-C., Walker, A. E., Schroder, K. E., & Belland, B. R. (2014). Interaction, Internet self-efficacy,
and self-regulated learning as predictors of student satisfaction in online education courses. The
Internet and higher education, 20, 35-50.
Lee, J.-K., & Lee, W.-K. (2008). The relationship of e-Learner’s self-regulatory efficacy and
perception of e-Learning environmental quality. Computers in Human Behavior, 24(1), 32-47.

45. REFERENCES:
Onete, B., Vasile, V., & Teodorescu, I. (2016). APPLYING CRM TECHNIQUES IN ENHANCING
eLEARNING. Paper presented at the The International Scientific Conference eLearning and
Software for Education.
Sklar, E. S. (1976). The Possessive apostrophe: the development and decline of a crooked mark.
College English, 38(2), 175-183.