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20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
20080223 Lasvegas Conference Presentation
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20080223 Lasvegas Conference Presentation

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Presentation Source at Las Vegas Conference in February 23, 2008

Presentation Source at Las Vegas Conference in February 23, 2008

Published in: Education, Business, Technology
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    • 1. “ The effects of LMS quality and e-learner’s characteristics regarding e-learner’s scholastic performance: A proposal for e-learning success model 2 ” ASBBS 15 th International Conference Feb. 21-24, 2008 Imperial Palace Hotel, Lasvegas, USA. Jong-Ki Lee (Research Professor, Kyungpook National University, South Korea) [email_address] http://LMS4U.kr
    • 2. Contents <ul><li>IIS Model transition </li></ul><ul><li>e-Learner </li></ul><ul><li>Research model </li></ul><ul><li>PLS Analysis </li></ul><ul><li>Discussion </li></ul><ul><li>Contribution </li></ul>
    • 3. Theoretical background <ul><li>Research purpose </li></ul><ul><ul><li>Suggest model of e-Learning effectiveness </li></ul></ul><ul><li>Theoretical background </li></ul><ul><ul><li>Information system theory </li></ul></ul><ul><ul><ul><li>TAM </li></ul></ul></ul><ul><ul><ul><li>ISS Model </li></ul></ul></ul><ul><ul><li>Education engineering theory </li></ul></ul><ul><ul><ul><li>Constructivism education </li></ul></ul></ul><ul><ul><li>others </li></ul></ul><ul><ul><ul><li>Empathy & self-regulatory efficacy </li></ul></ul></ul>
    • 4. ISS Model transition D&M IS Success Model, 1992 Updated D&M IS Success Model, 2003 Seddon & Kiew Model, 1997 Pitt et al. Model, 1995 System quality Information quality use User satisfaction Individual impact Organizational impact Service quality System quality Information quality use User satisfaction Individual benefit Service quality PEOU Information quality Perceived usefulness User satisfaction System quality Information quality use User satisfaction Individual impact Organizational impact
    • 5. Application of ISS Learning content quality Interaction service quality LMS quality Learning environment Satisfaction IT Adapted SERVQUAL Contextual quality Representational quality IT Adapted SERVQUAL IT Adapted SERVQUAL satisfaction
    • 6. e-Learner <ul><li>Learning achievement ability </li></ul><ul><ul><li>Self-directed learning </li></ul></ul><ul><ul><ul><li>e-Learner attend active learning process and promote self inner changes </li></ul></ul></ul><ul><ul><ul><li>The teacher in SDL remains available as an assistance and guide of learning; not as a unilateral knowledge source and messenger (Hwang, 1999). </li></ul></ul></ul><ul><ul><li>Self-regulated learning strategy </li></ul></ul><ul><ul><ul><li>The learner must make constant efforts to sustain learning motivation (Zimmerman, 1990). </li></ul></ul></ul><ul><ul><ul><li>e-Learning strategy is needed for self-directed learning and needed instructional design strategy based on self-directed learning. </li></ul></ul></ul><ul><li>Self-regulatory efficacy </li></ul><ul><li>Empathy </li></ul>
    • 7. Research model IQ SVC SQ EMP SA RR SRS H8 H7 H6 H4 H2 SRE ESP H1 H3 H5 SA: e-learner’s satisfaction on LMS SQ: system quality on LMS SVC: service quality on interaction IQ: information quality on LMS EMP: e-learner’s empathy SRE: self-regulatory efficacy SRS: self-regulated learning strategy ESP: e-learner’s expected performance RR: real record performance
    • 8. Hypothesis <ul><li>H1: A learner's satisfaction with LMS will be positively related to the e-learner’s expected performance. </li></ul><ul><li>H2: A learner's self-regulated learning strategy in e-Learning will be positively related to the e-learner’s expected performance. </li></ul><ul><li>H3: A learner's self-regulatory efficacy in e-Learning will be positively related to the e-learner’s expected performance. </li></ul><ul><li>H4: A learner's empathy will be positively related to the e-learner’s self-regulatory efficacy. </li></ul><ul><li>H5: A learner's expected performance will be positively related to the e-learner’s real record performance. </li></ul>
    • 9. Hypothesis 2 <ul><li>H6: The system quality of a learning management system will be positively related to the e-learner’s satisfaction. </li></ul><ul><li>H7: A learner's assessment of the service quality of interaction between a professor and learner will be positively related to the e-learner’s satisfaction. </li></ul><ul><li>H8: A learner's assessment of content quality will be positively related to the e-learner’s satisfaction. </li></ul>
    • 10. Methodology <ul><li>Empirical Research </li></ul><ul><li>Research contents </li></ul><ul><ul><li>Objectives: Daegu University & Hansung Digital University cyber lectures, 4 subjects, 341 students’ questionnaire (41 items) </li></ul></ul><ul><ul><li>Scale: Likert-5 point Scale </li></ul></ul><ul><li>Analysis: PLS method </li></ul>
    • 11. PLS analysis <ul><li>Indicator is fit to formative indicator </li></ul><ul><li>Be suited to Initial model stage </li></ul><ul><li>It is not strict with sample size, residual distribution. </li></ul><ul><li>Research construct is fit to use PLS </li></ul>
    • 12. Scale Mehrabian & Epstein (1972 ) 6 EMP Real Record 1 RR Wang(2003) 3 SA Zimmerman & Martines-Pons (1988) 4 SRS Kim and Park (2001 ) 4 SRE Kettinger & Lee(1997) 4 SVC Lee et al.(2002) 7 IQ DeLone & McLean (1992) 4 SQ Researcher item Variable
    • 13. Demographics table 2. Convergent validity analysis 0.6 2 Etc. 5.0 17 Art and physical 11.4 39 Engineering 8.5 29 Natural science 34.3 117 Social science 40.2 137 Cultural science Major 33.1 113 Senior 25.2 86 Junior 27.0 92 Sophomore 14.7 50 Freshman Grade 0.6 2 50 and above 0.9 3 45-49 0.6 2 40-44 0.9 3 35-39 2.3 8 30-34 31.1 106 25-29 63.6 217 20-24 Age 38.7 132 Female 61.3 209 Male Gender Percent(%) Frequency Item
    • 14. Demographics (2) table 2. Convergent validity analysis 1.2 4 15 hours and above 5.9 20 7-14 hours 32.3 110 3-6 hours 52.5 179 1-2 hours 8.2 28 Less than 1 hour Computer use time (1day) 1.5 5 8 subjects and above 6.5 22 6-7 subjects 3.8 13 4-5 subjects 35.8 122 2-3 subjects 52.5 179 1 subject Courses taken during e-Learning career 1.8 6 6 times and above 10.6 36 4-5 times 42.8 146 2-3 times 44.9 153 First E-Learning career Percent(%) Frequency Item
    • 15. Demographics (3) table 2. Convergent validity analysis 15.5 53 University graduation 7.3 25 College graduation 7.6 26 University dropout 68.3 233 High school graduation 1.2 4 Middle school graduation Degree 4.4 15 8 hours and above 7.9 27 5-7 hour 29.3 100 3-4 hour 55.4 189 1-2 hour 2.9 10 Less than 1 hour e-Learning time (1 week) Percent(%) Frequency Item
    • 16. Convergent validity table 2. Convergent validity analysis 0.888 0.642 0.915 EMP 0.748 0.571 0.842 SRE 0.815 0.644 0.878 SRS 0.948 0.856 0.960 ESP 0.780 0.574 0.842 SQ 0.923 0.677 0.936 SVC 0.892 0.583 0.907 IQ 0.861 0.679 0.893 SA Cronbach α AVE Composite reliability Construct
    • 17. Correlation coefficient of construct and AVE Symmetrical value is square root of AVE 1.000 0.053 0.179 0.260 0.356 0.139 0.197 0.140 0.255 RR 0.801 0.494 0.456 0.395 0.383 0.525 0.448 0.465 EMP 0.755 0.598 0.489 0.402 0.427 0.443 0.448 SRE 0.802 0.489 0.361 0.421 0.425 0.442 SRS 0.952 0.367 0.445 0.427 0.541 ESP 0.757 0.612 0.623 0.542 SQ 0.822 0.648 0.667 SVC 0.763 0.624 IQ 0.824 SA RR EMP SRE SRS ESP SQ SVC IQ SA Variable
    • 18.  
    • 19. Discussion <ul><li>All hypothesis is accepted. </li></ul><ul><li>Motivation problem </li></ul><ul><ul><li>E-learner’s voluntary motivation is very important variable </li></ul></ul><ul><ul><li>Many students are used to web based Information system. </li></ul></ul><ul><li>Satisfaction on LMS is important to expected performance </li></ul><ul><li>E-learner’s empathy effect on self-regulatory efficacy for e-learning performance </li></ul><ul><li>Self-regulatory efficacy is important variable to e-learning performance </li></ul><ul><li>Self-regulated learning strategy is also important variable to e-learning performance </li></ul><ul><li>We must upgrade e-professor’s service quality on LMS </li></ul>
    • 20. Contribution <ul><li>Theoretical contribution </li></ul><ul><ul><li>Suggestion of interdisciplinary model(IS, Education engineering) </li></ul></ul><ul><ul><li>Service quality is measured by interaction </li></ul></ul><ul><ul><li>Confirm self-regulated learning strategy as important variable in e-learning </li></ul></ul><ul><ul><li>Confirm SRE as important variable in e-learning </li></ul></ul><ul><ul><li>Confirm empathy as important variable in e-learning performance </li></ul></ul><ul><li>Practical contribution </li></ul><ul><ul><li>Divided e-Learning into learning contents and LMS </li></ul></ul><ul><ul><li>Needed customizing to self-regulated learning strategy </li></ul></ul><ul><ul><li>Needed customizing to self-regulatory efficacy </li></ul></ul><ul><ul><li>Needed customizing to e-learner’s empathy in e-learning </li></ul></ul>
    • 21. Limitation of Research <ul><li>Research of various sample </li></ul><ul><ul><li>Various subject </li></ul></ul><ul><ul><li>Various organization and student. </li></ul></ul>
    • 22. <ul><li>Thank You. </li></ul><ul><li>Have a good time... </li></ul>

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