TY - GEN
T1 - Learning Styles and On-Line Learning Analytics
T2 - 25th International Conference on Human-Computer Interaction, HCII 2023
AU - Lang, Michael
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/7/1
Y1 - 2023/7/1
N2 - This paper presents an analysis of student behaviour on a Learning Management System (LMS), as observed by means of learning analytics, and compares this against expected behaviour, as put forward by the Honey & Mumford Learning Styles Model (H&M LSM). The H&M Learning Styles Questionnaire (LSQ) was administered on-line to a class of 211 postgraduate students at an Irish university. A response rate of 25% was achieved, yielding 52 usable responses. Descriptive statistical analysis and hierarchical clustering was performed on the data, discovering ten clusters of learning styles, eight of which were distinct and could be quite clearly identified. The most common learning style found was ‘Reflector’ or variants thereof. Evidence of the existence of the ‘Pragmatist’, ‘Activist’ and ‘Theorist’ learning styles was also discovered. Overall, the study found sufficient evidence to suggest that the H&M LSM is a reasonable predictor of student behaviour on a LMS, notwithstanding its flaws and shortcomings.
AB - This paper presents an analysis of student behaviour on a Learning Management System (LMS), as observed by means of learning analytics, and compares this against expected behaviour, as put forward by the Honey & Mumford Learning Styles Model (H&M LSM). The H&M Learning Styles Questionnaire (LSQ) was administered on-line to a class of 211 postgraduate students at an Irish university. A response rate of 25% was achieved, yielding 52 usable responses. Descriptive statistical analysis and hierarchical clustering was performed on the data, discovering ten clusters of learning styles, eight of which were distinct and could be quite clearly identified. The most common learning style found was ‘Reflector’ or variants thereof. Evidence of the existence of the ‘Pragmatist’, ‘Activist’ and ‘Theorist’ learning styles was also discovered. Overall, the study found sufficient evidence to suggest that the H&M LSM is a reasonable predictor of student behaviour on a LMS, notwithstanding its flaws and shortcomings.
KW - Learning Management Systems (LMS)
KW - Learning styles
KW - hierarchical cluster analysis
KW - learning analytics
UR - https://www.scopus.com/pages/publications/85178509259
U2 - 10.1007/978-3-031-48060-7_12
DO - 10.1007/978-3-031-48060-7_12
M3 - Conference Publication
SN - 9783031480591
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 154
EP - 166
BT - HCI International 2023 – Late Breaking Papers - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings
A2 - Zaphiris, Panayiotis
A2 - Ioannou, Andri
A2 - Ioannou, Andri
A2 - Sottilare, Robert A.
A2 - Schwarz, Jessica
A2 - Fui-Hoon Nah, Fiona
A2 - Siau, Keng
A2 - Wei, June
A2 - Salvendy, Gavriel
PB - Springer Science and Business Media Deutschland GmbH
CY - Copenhagen, Denmark
Y2 - 23 July 2023 through 28 July 2023
ER -
