Applying Cognitive Load Theory to Examine STEM Undergraduate Students' Experiences in An Adaptive Learning Environment: A Mixed-Methods Study. (September 2021)

• Record Type: Journal Article
• Authors: Bounajim, Dolly; Rachmatullah, Arif; Hinckle, Madeline; Mott, Bradford; Lester, James; Smith, Andy; Emerson, Andrew; Morshed Fahid, Fahmid; Tian, Xiaoyi; Wiggins, Joseph B.; Elizabeth Boyer, Kristy; Wiebe, Eric
• Is Part Of: Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Volume 65:Part 1(2021)
• Page Start: 556
• Page End: 560
• Publication Date: 2021-09
• Subjects: Human engineering -- Congresses; 620.8205
• DOI: 10.1177/1071181321651249
• Languages: English
• ISSNs: 1541-9312

Abstract

This study examined undergraduate STEM students' experiences using an online introductory computer programming learning environment equipped with an automated hint generation system. Following a convergent parallel mixed methods design, this study utilized both quantitative and qualitative data from student experiential data. Analysis by level of prior knowledge demonstrated that elements of the learning environment did not cater to their learning needs and cognitive architecture. Cognitive Load Theory was used to contextualize system elements against both higher and lower prior experience learners, ultimately pointing to a need to design better scaffolds and hints to the needs of novice CS learners.