Abstract

A key concern for most institutions and instructors is whether students are satisfied with their learning experience. However, relatively few studies have unpacked what the key drivers for learner satisfaction are in blended and online courses. Using logistical regression modelling, learner satisfaction data of 62,986 learners in 401 undergraduate blended and online modules was analyzed. The data included over 200 potential explanatory variables based on learner and module learning design characteristics. Findings indicate that learning design has a strong and significant impact on overall satisfaction for both new and continuing learners. Learners who are more satisfied with the quality of teaching materials, assessment strategies, and workload are more satisfied with the overall learning experience. Furthermore, long-term goals of learners (i.e., qualifications and relevance of modules with learners' professional careers) are important predictors of learner satisfaction. Individual learner characteristics are mostly insignificant, indicating that despite a wide diversity of learners studying at the Open University, UK, the underlying learning experiences are similar. Future research should focus on how learning design changes can enhance the learning experiences of students.

Citation

Li, N., Marsh, V. & Rienties, B. (2016). Modelling and Managing Learner Satisfaction: Use of Learner Feedback to Enhance Blended and Online Learning Experience. Decision Sciences Journal of Innovative Education, 14(2), 216-242. Retrieved March 26, 2023 from https://www.learntechlib.org/p/194962/.

This record was imported from ERIC on January 10, 2019. [Original Record]

ERIC is sponsored by the Institute of Education Sciences (IES) of the U.S. Department of Education.

Copyright for this record is held by the content creator. For more details see ERIC's copyright policy.

Keywords

• blended learning
• Educational Quality
• Educational Strategies
• electronic learning
• Feedback (Response)
• Foreign Countries
• instructional design
• instructional materials
• Learning Experience
• Learning Modules
• open universities
• Predictor Variables
• Regression (Statistics)
• Satisfaction
• student attitudes
• Student Characteristics
• student evaluation
• undergraduate students