Abstract
Adaptive learning systems (ALSs) aim to provide an efficient, effective and customised learning experience for students by dynamically adapting learning content to suit their individual abilities or preferences. Despite consistent evidence of their effectiveness and success in improving student learning over the past three decades, the actual impact and adoption of ALSs in education remain restricted to mostly research projects. In this paper, we provide a brief overview of reflections and lessons learned from developing and piloting an ALS in a course on relational databases. While our focus has been on adaptive learning, many of the presented lessons are also applicable to the development and adoption of educational tools and technologies in general. Our aim is to provide insight for other instructors, educational researchers and developers that are interested in adopting ALSs or are involved in the implementation of educational tools and technologies.
Original language | English |
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Title of host publication | Proceedings of the 51st ACM Technical Symposium on Computer Science Education |
Editors | Sarah Heckman, Pamela Cutter, Alvaro Monge |
Place of Publication | New York NY USA |
Publisher | Association for Computing Machinery (ACM) |
Pages | 58-64 |
Number of pages | 7 |
ISBN (Electronic) | 9781450367936 |
DOIs | |
Publication status | Published - 2020 |
Event | ACM Technical Symposium on Computer Science Education (SIGCSE) 2020 - Portland, United States of America Duration: 11 Mar 2020 → 14 Mar 2020 Conference number: 51st https://sigcse2020.sigcse.org https://dl.acm.org/doi/proceedings/10.1145/3328778 (Proceedings) |
Conference
Conference | ACM Technical Symposium on Computer Science Education (SIGCSE) 2020 |
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Abbreviated title | SIGCSE 2020 |
Country/Territory | United States of America |
City | Portland |
Period | 11/03/20 → 14/03/20 |
Internet address |
Keywords
- Adaptive learning systems
- Crowdsourcing
- Educational technologies