Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/12374
Title: The effect of individual difference on learning performance using web-based instruction
Authors: Counsell, S
Alhajri, R
Liu, X
Keywords: Web-based instruction;Individual differences;Performance
Issue Date: 2013
Citation: 10th World Conference on Computers in Education (WCCE 2013), Torun, Poland, (2- 5 July 2013)
Abstract: Web-Based Instruction (WBI) brings a number of benefits to individuals requiring a combination of specific learning patterns and program structure. In this paper, we propose a WBI program which suits individual differences through an existing framework and which facilitates learning by accommodating learner preferences. In particular, we make advances in three key aspects. Firstly, we study three important individual differences (gender, cognitive style and prior knowledge) as well as their interactions in the resulting learning performances. Secondly, we combined three attributes to measure performance (gain score, number of visited pages and time spent on these pages) of the three interacting individual differences. Thirdly, we in-vestigate system features (navigation tools, additional support and content structure) to see how they can help users acquire information to meet their individual needs, resulting in an improvement in the learning performance. Two studies are presented; in one, we compare results from our program with previous studies thus evaluating its design. In the other, a data mining approach is used to investigate the effect of individual differences and how that could influence learner performance. Results indicate that performance can be affected by individual differences’ behaviour. Additionally, we found that the relationship between individual differences had an even higher impact on learners’ performance. The combined performance measurement attributes give a better understanding of how learners performed.
URI: http://edu.rsei.umk.pl/wcce2013/?q=node/59
http://bura.brunel.ac.uk/handle/2438/12374
ISBN: 978-83-231-3090-1
Appears in Collections:Dept of Computer Science Research Papers

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