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Interest in Educational Data and Barriers to Data Use Among Massive Open Online Course Instructors
Maya Usher1, Arnon Hershkovitz1
1Department of Mathematics, Science, and Technology Education, School of Education, Tel Aviv University, 6997801 Tel Aviv, Israel.
Journal of Science Education and Technology
|August 15, 2022
Summary
Higher education instructors are interested in educational data from Massive Open Online Courses (MOOCs), particularly for understanding student interactions and resource issues. Key barriers to data use include lack of customization, real-time access, data literacy, and institutional support.
Area of Science:
- Educational Technology
- Higher Education Pedagogy
- Data Science in Education
Background:
- Instructors use educational data for student assessment and instructional decisions.
- Massive Open Online Courses (MOOCs) provide rich, automatically gathered educational data.
- Understanding instructor perspectives on data-driven instruction in MOOCs is crucial but limited.
Purpose of the Study:
- To investigate higher education MOOC instructors' interest in educational data.
- To identify perceived barriers instructors face when using MOOC data for decision-making.
Main Methods:
- Qualitative research approach.
- Semi-structured interviews conducted with MOOC instructors from four Israeli public universities.
Main Results:
- Instructors showed significant interest in data concerning learner social interactions and MOOC resource problems.
- Primary barriers identified were lack of customized data, real-time data access, data literacy, and insufficient institutional support.
Conclusions:
- MOOC instructors desire specific data insights to enhance their teaching.
- Addressing barriers through professional development and improved institutional support is essential for effective data-driven instruction in MOOCs.
Keywords:
Data-driven decision-makingHigher educationInstructor perceptionsMassive open online courses (MOOCs)Online teachingMore Related Videos
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