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

The relationship between web enjoyment and student perceptions and learning using a web-based tutorial

Web enjoyment has been regarded as a component of system experience. However, there has been little targeted research considering the role of web enjoyment alone in student learning using web-based systems. To address this gap, this study aims to examine the influence of web enjoyment on learning performance and perceptions by controlling system experience as a variable in the study. 74 students participated in the study, using a web-based tutorial covering subject matter in the area of 'Computation and algorithms'. Their learning performance was assessed with a pre-test and a post-test and their learning perceptions were evaluated with a questionnaire. The results indicated that there are positive relationships between the levels of web enjoyment and perceived usefulness and non-linear navigation for users with similar, significant levels of system experience. The implications of these findings in relation to web-based learning are explored and ways in which the needs of students who report different levels of web enjoyment might be met 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

The role of unit evaluation, learning and culture dimensions related to student cognitive style in hypermedia learning

Recent developments in learning technologies such as hypermedia are\ud becoming widespread and offer significant contributions to improving the delivery\ud of learning and teaching materials. A key factor in the development of hypermedia\ud learning systems is cognitive style (CS) as it relates to users‟ information\ud processing habits, representing individual users‟ typical modes of perceiving,\ud thinking, remembering and problem solving.\ud \ud \ud \ud \ud A total of 97 students from Australian (45) and Malaysian (52) universities\ud participated in a survey. Five types of predictor variables were investigated with\ud the CS: (i) three learning dimensions; (ii) five culture dimensions; (iii) evaluation\ud of units; (iv) demographics of students; and (v) country in which students studied.\ud Both multiple regression models and tree-based regression were used to analyse\ud the direct effect of the five types of predictor variables, and the interactions within\ud each type of predictor variable. When comparing both models, tree-based\ud regression outperformed the generalized linear model in this study. The research\ud findings indicate that unit evaluation is the primary variable to determine students‟\ud CS. A secondary variable is learning dimension and, among the three dimensions,\ud only nonlinear learning and learner control dimensions have an effect on students‟\ud CS. The last variable is culture and, among the five culture dimensions, only\ud power distance, long term orientation, and individualism have effects on students‟\ud CS. Neither demographics nor country have an effect on students‟ CS.\ud These overall findings suggest that traditional unit evaluation, students‟\ud preference for learning dimensions (such as linear vs non-linear), level of learner\ud control and culture orientation must be taken into consideration in order to enrich\ud students‟ quality of education. This enrichment includes motivating students to\ud acquire subject matter through individualized instruction when designing,\ud developing and delivering educational resources

Analytics and complexity: learning and leading for the future

There is growing interest in the application of learning analytics to manage, inform and improve learning and teaching within higher education. In particular, learning analytics is seen as enabling data-driven decision making as universities are seeking to respond a range of significant challenges that are reshaping the higher education landscape. Experience over four years with a project exploring the use of learning analytics to improve learning and teaching at a particular university has, however, revealed a much more complex reality that potentially limits the value of some analytics-based strategies. This paper uses this experience with over 80,000 students across three learning management systems, combined with literature from complex adaptive systems and learning analytics to identify the source and nature of these limitations along with a suggested path forward

Rethinking Security Incident Response: The Integration of Agile Principles

In today's globally networked environment, information security incidents can inflict staggering financial losses on organizations. Industry reports indicate that fundamental problems exist with the application of current linear plan-driven security incident response approaches being applied in many organizations. Researchers argue that traditional approaches value containment and eradication over incident learning. While previous security incident response research focused on best practice development, linear plan-driven approaches and the technical aspects of security incident response, very little research investigates the integration of agile principles and practices into the security incident response process. This paper proposes that the integration of disciplined agile principles and practices into the security incident response process is a practical solution to strengthening an organization's security incident response posture.Comment: Paper presented at the 20th Americas Conference on Information Systems (AMCIS 2014), Savannah, Georgi

Browsing while reading: effects of instructional design and learners' prior knowledge

One of the key reasons that multimedia, and particularly hypertext systems, are gaining in importance is that they inspire hopes of optimizing learners' processes of knowledge construction. The present study is concerned with the respective influence of individual learner variables (i.e. particularly domain‐specific prior knowledge) on the use of different design attributes. Thirty‐six university students worked through a hierarchically structured two‐part hypertext about the psychology of memory under two experimental browsing conditions (reduced versus free browsing). Results show that deeper‐level comprehension (i.e. structural knowledge) was predicted by the interaction of experimental condition and prior knowledge, but that simply retaining facts was not. Participants with low prior knowledge performed better on the comprehension test if they had worked on the version with reduced access. Moreover, the version with reduced access helped to reduce feelings of disorientation. The measure of disorientation also appeared to be closely linked with the individual's computer experience, self‐concept of computer ability and subject‐related interest. The main implications for educational practice relate to the design of an adaptive multimedia and hypertext learning system and the successful learning with it

Land re-use, complexity and actor-networks: a framework for research

This paper will present a conceptual framework for the examination of land redevelopment based on a complex systems/networks approach. As Alvin Toffler insightfully noted, modern scientific enquiry has become exceptionally good at splitting problems into pieces but has forgotten how to put the pieces back together. Twenty-five years after his remarks, governments and corporations faced with the requirements of sustainability are struggling to promote an ‘integrated’ or ‘holistic’ approach to tackling problems. Despite the talk, both practice and research provide few platforms that allow for ‘joined up’ thinking and action. With socio-economic phenomena, such as land redevelopment, promising prospects open up when we assume that their constituents can make up complex systems whose emergent properties are more than the sum of the parts and whose behaviour is inherently difficult to predict. A review of previous research shows that it has mainly focused on idealised, ‘mechanical’ views of property development processes that fail to recognise in full the relationships between actors, the structures created and their emergent qualities. When reality failed to live up to the expectations of these theoretical constructs then somebody had to be blamed for it: planners, developers, politicians. However, from a ‘synthetic’ point of view the agents and networks involved in property development can be seen as constituents of structures that perform complex processes. These structures interact, forming new more complex structures and networks. Redevelopment then can be conceptualised as a process of transformation: a complex system, a ‘dissipative’ structure involving developers, planners, landowners, state agencies etc., unlocks the potential of previously used sites, transforms space towards a higher order of complexity and ‘consumes’ but also ‘creates’ different forms of capital in the process. Analysis of network relations point toward the ‘dualism’ of structure and agency in these processes of system transformation and change. Insights from actor network theory can be conjoined with notions of complexity and chaos to build an understanding of the ways in which actors actively seek to shape these structures and systems, whilst at the same time are recursively shaped by them in their strategies and actions. This approach transcends the blame game and allows for inter-disciplinary inputs to be placed within a broader explanatory framework that does away with many past dichotomies. Better understanding of the interactions between actors and the emergent qualities of the networks they form can improve our comprehension of the complex socio-spatial phenomena that redevelopment comprises. The insights that this framework provides when applied in UK institutional investment into redevelopment are considered to be significant