Do excellent engineers approach their studies strategically?: A quantitative study of students' approaches to learning in computer science education
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
This thesis is about students’ approaches to learning (SAL) in computer science education. Since the initial development of SAL instruments and inventories in the 70’s, they have been used as a means to understand students’ approaches to learning better, as well as to measure and predict academic achievement (such as retention, grades and credits taken) and other correlating factors. It is an instrument to measure a student’s study strategies – not how “good” a student is.
A Swedish short version of Approaches and Study Skills Inventory for Students (ASSIST) was used to gather information on whether we, through context and content, encouraged sustainable study behaviour among our students. ASSIST was used in two distinct situations: 1) Evaluation and evolvement of an online programming course design, and 2) Engineering education in media technology and computer science in a campus environment where approaches to learning has been evaluated and studied over time during the five year long programmes. Repeated measurements have been analysed against factors predicting academic achievement, and have been evaluated on a cohort level (not individual) in order to clarify patterns rather than individual characteristics.
Significant for both projects was that a surface approach to learning correlated negatively with retention. Students who adopted a combination of deep and strategic approach to learning performed better in terms of grades, ECTS credits completed and perceived value of the education. As part of developmental tools it can be beneficial to use ASSIST at a group level in order to see what kind of approach a course design or a programme supports among the students.
Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016.
TRITA-CSC-A, ISSN 1653-5723 ; 26
Approaches to learning, computer science engineering education, Computing education research, online learning
Human Computer Interaction
Research subject Human-computer Interaction
IdentifiersURN: urn:nbn:se:kth:diva-194208ISBN: 978-91-7729-156-6OAI: oai:DiVA.org:kth-194208DiVA: diva2:1040034
2016-11-18, F3, Lindstedtsvägen 26, Stockholm, 13:15 (English)
Pears, Arnold, Associate Professor
Bälter, Olle, Associate ProfessorHrastinski, Stefan, ProfessorCleveland-Innes, Martha, ProfessorThorbiörnson, Johan, PhD
QC 201610282016-10-282016-10-192016-11-01Bibliographically approved
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