2 research outputs found
Investigating attributes affecting the performance of WBI users
This is the post-print version of the final paper published in Computers and Education. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Numerous research studies have explored the effect of hypermedia on learners' performance using Web Based Instruction (WBI). A learner's performance is determined by their varying skills and abilities as well as various differences such as gender, cognitive style and prior knowledge. In this paper, we investigate how differences between individuals influenced learner's performance using a hypermedia system to accommodate an individual's preferences. The effect of learning performance is investigated to explore relationships between measurement attributes including gain scores (post-test minus pre-test), number of pages visited in a WBI program, and time spent on such pages. A data mining approach was used to analyze the results by comparing two clustering algorithms (K-Means and Hierarchical) with two different numbers of clusters. Individual differences had a significant impact on learner behavior in our WBI program. Additionally, we found that the relationship between attributes that measure performance played an influential role in exploring performance level; the relationship between such attributes induced rules in measuring level of a learners' performance
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Integrating multiple individual differences in web-based instruction
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.There has been an increasing focus on web-based instruction (WBI) systems which accommodate individual differences in educational environments. Many of those studies have focused on the investigation of learners’ behaviour to understand their preferences, performance and perception using hypermedia systems. In this thesis, existing studies focus extensively on performance measurement attributes such as time spent using the system by a user, gained score and number of pages visited in the system. However, there is a dearth of studies which explore the relationship between such attributes in measuring performance level. Statistical analysis and data mining techniques were used in this study. We built a WBI program based on existing designs which accommodated learner’s preferences. We evaluated the proposed system by comparing its results with related studies. Then, we investigated the impact of related individual differences on learners’ preferences, performance and perception after interacting with our WBI program.
We found that some individual differences and their combination had an impact on learners' preferences when choosing navigation tools. Consequently, it was clear that the related individual differences altered a learner’s preferences. Thus, we did further investigation to understand how multiple individual differences (Multi-ID) could affect learners’ preferences, performance and perception. We found that the Multi-ID clearly altered the learner’s preferences and performance. Thus, designers of WBI applications need to consider the combination of individual differences rather than these differences individually. Our findings also showed that attributes relationships had an impact on measuring learners’ performance level on learners with Multi-ID.
The key contribution of this study lies in the following three aspects: firstly, investigating the impact of our proposed system, using three system features in the design, on a learner’s behavior, secondly, exploring the influence of Multi-ID on a learner’s preferences, performance and perception, thirdly, combining the three measurement attributes to understand the performance level using these measuring attributes