Adaptive Instruction: A Case Study of Gamified Practice and Testing in a Large Introductory Psychology Course
Document Type
Conference Proceeding
Publication Date
11-22-2022
Department
Department of Cognitive and Learning Sciences
Abstract
Understanding what methods are effective for learning in large lectures continues to be an important research goal and examining factors that support the use of adaptive systems in these large lectures is needed. In this case study, students from a large lecture class (n = 223) used an adaptive instructional system to cover 39 learning modules over 14 weeks. The weekly adaptive system gamified practice and ensured students distributed their studying before each exam. Using a mixed-methods approach in the context of the ICAP framework, student experience using the system was examined. Results indicated that the majority of students found the gamified activities useful for learning the material initially. The adaptive system helped students diagnose what concepts they knew and did not know, provided an additional way to review module topics, and provided additional testing of the material. However, the system did not help students know when they had studied enough. Overall students’ exam performance in the course benefited from the addition of the active practice and gamified testing, and the strategies students used are important for future adaptive instructional system design.
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
9783031221309
Recommended Citation
Veinott, E.
(2022).
Adaptive Instruction: A Case Study of Gamified Practice and Testing in a Large Introductory Psychology Course.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
13517 LNCS, 455-467.
http://doi.org/10.1007/978-3-031-22131-6_34
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/16764