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A Correlation Study: The effect of online quality on students’ learning outcome and attrition By Dr. Joselina Cheng and Dr. Lisa Miller By Dr. Joselina Cheng and Dr. Lisa Miller
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Problem Statement online courses is that they undermined course content, quality, and design, affecting student learning outcomes and course completion
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Purpose Statement This quantitative research study explores the relationship between online course quality and online student learning outcomes and the relationship between online course quality and online student attrition at UCO for the fall semester of 2007.
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Research Questions (RQ) RQ1: What is the relationship between online course quality and online student learning outcomes? RQ2: What is the relationship between online course quality and online student attrition?
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Research Question #1
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Research Question #2
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Research Hypotheses H a 1: There is a relationship between online course quality and online student learning outcomes. H a 2: There is a relationship between online course quality and online student attrition. Methodology
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Findings for Hypotheses
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Methodology Research Design: Quantitative Method: Correlation Time Dimension: Cross-Sectional (fall 2007 Semester) Location: University of Central Oklahoma (UCO) Population/Sample: Students of certified online courses at UCO
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Limitations/Delimitation Small Sample Size One Higher Education Institution One Semester Geographic Boundary
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Research Significance Traditional universities are no longer protected by geographic service due to intensive competition from virtual universities. Stakeholders of traditional universities can gain insights from the study to provide quality online education to sustain long-term competitiveness.
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Recommendations Strategic leadership Institutional sponsorship 24 * 7 help desk 24 * 7 help desk Supportive policies Supportive policies Learning organization Multi-tier development for online students’ and faculties’ preparedness – ie: time management, webCT training, multimedia-based learning modules to address learning styles. Multi-tier development for online students’ and faculties’ preparedness – ie: time management, webCT training, multimedia-based learning modules to address learning styles. Double-loop learning process – revise the feedback mechanism and measures to detect students’ e- learning obstacles Double-loop learning process – revise the feedback mechanism and measures to detect students’ e- learning obstacles
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Future Studies Repeat the study with larger sample size Extend the study with a longer timeframe. Further analysis by breaking down “total withdrawals” to the following: Student factors - Never attend class, job change, lack of technical competency, lack of time management Student factors - Never attend class, job change, lack of technical competency, lack of time management Faculty factors – Disorganized, lack of timely feedbacks, etc. Faculty factors – Disorganized, lack of timely feedbacks, etc. Institutional factors – Lack of IT support, lack of training, lack of technological infrastructure Institutional factors – Lack of IT support, lack of training, lack of technological infrastructure
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Q & A For demo of Virtual Tutor, please refer to Dr. Cheng’s website – http://www.busn.ucok.edu/jcheng/index.htm
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References Cao, J. (2005). Learning with Virtual Mentors: How to make e-learning interactive and effective? The University of Arizona, AAT 3176282. Zhang, D. (2004). Virtual Mentor and the lab system – toward building an interactive, personalized, and intelligent e-learning environment. The Journal of Computer Information Systems. Spring 2004, 44 (3) 35-43.
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