Navigation in hypermedia learning systems: Experts vs. novices

With the advancement of Web technology, hypermedia learning systems are becoming more widespread in educational settings. Hypermedia learning systems present course content with non-sequential formats, so students are required to develop learning paths by themselves. Yet, empirical evidence indicates that not all students can benefit from hypermedia learning. Research into individual differences suggests that prior knowledge has significant effects on student learning in hypermedia systems, with experts and novices showing different preferences to the use of hypermedia learning systems and requiring different levels of navigation support. It is therefore essential to develop a mechanism to help designers understand the needs of experts and novices. To address this issue, this paper presents a framework to illustrate the needs of students with different levels of prior knowledge by analyzing the findings of previous research. The overall aim of this framework is to integrate students’ prior knowledge into the design of hypermedia learning systems. Finally, implications for the design of hypermedia learning systems are discussed

Hypermedia learning and prior knowledge: Domain expertise vs. system expertise

Prior knowledge is often argued to be an important determinant in hypermedia learning, and may be thought of as including two important elements: domain expertise and system expertise. However, there has been a lack of research considering these issues together. In an attempt to address this shortcoming, this paper presents a study that examines how domain expertise and system expertise influence students’ learning performance in, and perceptions of, a hypermedia system. The results indicate that participants with lower domain knowledge show a greater improvement in their learning performance than those with higher domain knowledge. Furthermore, those who enjoy using the Web more are likely to have positive perceptions of non-linear interaction. Discussions on how to accommodate the different needs of students with varying levels of prior knowledge are provided based on the results

Investigation of the use of navigation tools in web-based learning: A data mining approach

Web-based learning is widespread in educational settings. The popularity of Web-based learning is in great measure because of its flexibility. Multiple navigation tools provided some of this flexibility. Different navigation tools offer different functions. Therefore, it is important to understand how the navigation tools are used by learners with different backgrounds, knowledge, and skills. This article presents two empirical studies in which data-mining approaches were used to analyze learners' navigation behavior. The results indicate that prior knowledge and subject content are two potential factors influencing the use of navigation tools. In addition, the lack of appropriate use of navigation tools may adversely influence learning performance. The results have been integrated into a model that can help designers develop Web-based learning programs and other Web-based applications that can be tailored to learners' needs

Navigational patterns in interactive multimedia

The central purpose of this thesis is to investigate whether users have distinct preferences for specific navigational patterns in multimedia: that is preferences for moving through multimedia. Subsidiary questions are whether users have preferences for working strategies, (the mental approach to investigating software) whether these preferences are similar for specific groups and whether these preferences are affected by the software's system and navigational design. Four groups were investigated within two ranges: children to adults, and novices to experts. The literature review revealed four different perspectives of investigating navigation: user, designer, pedagogy and human computer interaction and although this research concentrates on the first two perspectives the other two are integral and of equal importance.Two empirical studies elicited the navigational information. The first studied pairs of children undertaking set tasks in multimedia, and demonstrated that although each pair had definite preferences, each group did not utilise the full pattern range discerned from the observations, literature review and multimedia package analysis. The second study was redesigned using individual adults to ascertain the full range of preferred patterns in use. The essential element from the investigations was the wide range of variation between individuals and within groups. There was a gradual progression in their range and speed using these patterns, related to their skills, abilities and experience, and each individual could be placed along a continuum. Topologies of the multimedia packages and diagrams of the fit of the navigation patterns were included. Finally an expert panel was convened to verify the pattern range and their comments supported the new classification.The research outcomes included navigational patterns and working strategies classifications, future techniques for designers, and user methods. These will create more successful and informed multimedia, and forward developments and improvements in the design of high quality user preference software

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

Cognition in orienteering

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The influence of human factors on user's preferences of web-based applications: A data mining approach

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University on 20/12/2010.As the Web is fast becoming an integral feature in many of our daily lives, designers are faced with the challenge of designing Web-based applications for an increasingly diverse user group. In order to develop applications that successfully meet the needs of this user group, designers have to understand the influence of human factors upon users‘ needs and preferences. To address this issue, this thesis presents an investigation that analyses the influence of three human factors, including cognitive style, prior knowledge and gender differences, on users‘ preferences for Web-based applications. In particular, two applications are studied: Web search tools and Web-based instruction tools. Previous research has suggested a number of relationships between these three human factors, so this thesis was driven by three research questions. Firstly, to what extent is the similarity between the two cognitive style dimensions of Witkin‘s Field Dependence/Independence and Pask‘s Holism/Serialism? Secondly, to what extent do computer experts have the same preferences as Internet experts and computer novices have the same preferences as Internet novices? Finally, to what extent are Field Independent users, experts and males alike, and Field Dependent users, novices and females alike? As traditional statistical analysis methods would struggle to effectively capture such relationships, this thesis proposes an integrated data mining approach that combines feature selection and decision trees to effectively capture users‘ preferences. From this, a framework is developed that integrates the combined effect of the three human factors and can be used to inform system designers. The findings suggest that firstly, there are links between these three human factors. In terms of cognitive style, the relationship between Field Dependent users and Holists can be seen more clearly than the relationship between Field Independent users and Serialists. In terms of prior knowledge, although it is shown that there is a link between computer experience and Internet experience, computer experts are shown to have similar preferences to Internet novices. In terms of the relationship between all three human factors, the results of this study highlighted that the links between cognitive style and gender and between cognitive style and system experience were found to be stronger than the relationship between system experience and gender. This work contributes both theory and methodology to multiple academic communities, including human-computer interaction, information retrieval and data mining. In terms of theory, it has helped to deepen the understanding of the effects of single and multiple human factors on users‘ preferences for Web-based applications. In terms of methodology, an integrated data mining analysis approach was proposed and was shown that is able to capture users‘ preferences

Web-based interaction: A review of three important human factors

With the rapid development of information technology, the World Wide Web has been widely used in various applications, such as search engines, online learning and electronic commerce. These applications are used by a diverse population of users with heterogeneous backgrounds, in terms of their knowledge, skills, and needs. Therefore, human factors are key issues for the development of Web-based applications, leading research into human factors to grow significantly in the past decade. This paper identifies and reviews three important human factors that have been examined in existing empirical studies, including gender differences, prior knowledge, and cognitive styles. The main results from the analysis include that: (a) females have more disorientation problems than males; (b) flexible paths are more beneficial to experts while structured content is more useful to novices; and (c) Field Dependent and Field Independent users prefer to employ different search strategies. In addition to reviewing the existing empirical studies, this paper also highlights areas of future research