Using Learning Analytics to Improve Engagement, Learning, and Design of Massive Open Online Courses

Autor: Tim A. Cavanagh, Karina Riggs, David Santandreu Calonge, Mariam Aman Shah
Rok vydání: 2019
Předmět:
DOI: 10.4018/978-1-5225-7470-5.ch004
Popis: Academic research in the past decade has indicated that using data and analyzing learning in curriculum design decisions can lead to improved student performance and student success. As learning in many instances has evolved into the flexible format online, anywhere at any time, learning analytics could potentially provide impactful insights into student engagement in massive open online courses (MOOCs). These may contribute to early identification of “at risk” participants and provide MOOC facilitators, educators, and learning designers with insights on how to provide effective interventions to ensure participants meet the course learning outcomes and encourage retention and completion of a MOOC. This chapter uses the essential human biology MOOC within the Australian AdelaideX initiative to implement learning analytics to investigate and compare demographics of participants, patterns of navigation including participation and engagement for passers and non-passers in two iterations of the MOOC, one instructor-led, and second self-paced.
Databáze: OpenAIRE