Cognitive tools, individual differences, and group processing as mediating factors in a hypermedia environment

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Abstract

Much research exists on how problem-solving in hypermedia is assisted through the use of navigational aids. However, as hypermedia becomes more pedagogically rich, the structural characteristics of hypermedia no longer serve merely as navigational aids, but often as cognitive tools. When cognitive tools are embedded in problem-solving hypermedia environments, the objective is the continuous active manipulation of cognitive tools in the problem space in order to gather information, test hypotheses, and develop a solution. The purpose of this study was to investigate cognitive tools, individual differences, and group processing as mediating factors when learners were engaged in problem-solving in a hypermedia environment. We specifically examined group patterns of cognitive tool use to determine in what ways the group patterns of tool use may affect students’ individual performance and experience of the problem-solving process. The findings provided some evidence to support a more contextual approach to individual cognition and learning; and emphasized the notion that a system of instructional variables interact to create optimal conditions for learning.

Introduction

Hypermedia technology has come to secure a more central role in learning after several generations of its ancestors (e.g. drill and practice computer based instruction) provided supplemental instruction (Bangert-Drowns & Pyke, 2001; Cunningham, Duffy, & Knuth, 1993). Recently research has turned its attention to how problem-solving in hypermedia is assisted through the use of such structural characteristics as navigation tools (Beasley & Waugh, 1995; Beasley & Waugh, 1997; Boechler & Dawson, 2002; Calvi, 1997; Chiu & Wang, 2000; Dabbagh, 2002; Dias & Sousa, 1997) and interface design in general (Chen & Chai, 2002; Saxena, Kothari, Jain, & Khurana, 2002). Given recent theoretical, pedagogical, and technological advances in the area of hypermedia the question we must continue to ask regarding hypermedia design is not “Does learner attitude and performance improve?” but “Under what conditions do learners develop a stronger knowledge of content and fulfill educational experience as they navigate a hypermedia environment?” (Hannafin & Land, 1997; Land, 2000; Park & Hannafin, 1993).

Problem-solving in general, and hypermedia problem-solving in particular, is a delicate interaction between problem variations, those representations provided within the problem space, and individual differences (Jonassen, 2000). As Jonassen states, “problem-solving requires some activity-based manipulation of the problem space We cannot act without thinking or think without acting in some way” (p. 4). According to Dillon and Vaughn (1997), “comprehension is not something ‘other than’ navigation, some form of task that is independent of the process of moving through the information space” (p. 99). Theoretically, the structural and semantic properties of hypermedia are inseparable for the learner as she performs a problem-solving task in a hypermedia environment. The ways in which a learner navigates a hypermedia environment and her meaning making co-exist and co-determine each other. A student cannot navigate a hypermedia environment without learning something. However, a study by Dillon and Gabbard (1998) revealed that the learning outcomes of educational hypermedia are minimal. It appears as if comprehension is independent of navigation. Apparently students are navigating such environments quite well, and yet in the process learning little. What can hypermedia designers do to address this issue?

Section snippets

Cognitive tools

As educational theory and research continues to inform hypermedia design, these learning environments are becoming more pedagogically rich. In order to combat the “navigation without comprehension” issue, a design technique is for learners to navigate hypermedia by using the tools embedded in these virtual environments. In other words, the hypertextual capabilities of hypermedia environments, although they theoretically mimic the way knowledge is structured in human memory, do not in and of

Individual differences

As researchers are reflecting on and beginning to empirically examine how specific kinds of computer tools affect learning processes and outcomes, they consistently acknowledge that the magnitude of such processes and outcomes often relies on students’ desire to exert cognitive effort (Kozma, 1987; Pea, 1985; Salomon, 1993; Salomon et al., 1991). A central tenet of learning is that the greater the amount of mental effort exerted during knowledge acquisition, the more accessible the knowledge is

Group processing

Individual differences have been elicited as just one mediating factor among a variety of mediating factors when one takes a more contextual approach to individual cognition and learning (Pea, 1993; Salomon, 1993). Considering that hypermedia learning environments are often also a collaborative enterprise, the question arises as to the extent to which individual attitude and performance is normalized in such tool-rich and group-mediated learning environments. In an effort to identify optimal

Purpose of the study

The purpose of this study was to investigate how such mediating factors as cognitive tools, individual differences, and group processing affect students’ ability to learn in a problem-based hypermedia learning environment. Research has examined differences in individual tool use patterns and the problem-solving process (Liu & Bera, 2004). However, no research has examined group tool use patterns in relation to individual performance. Therefore, we were interested in examining group patterns of

Participants and context

Participants were 164 sixth graders from a middle school in a mid-sized southwestern city. Most students had used computer programs such as games and word processing programs prior to the study. Two experienced science teachers, though novice computer users, taught the sixth grades science classes. They went through a two-day training workshop, during which the philosophy and different attributes of the student-centered hypermedia learning environment for use in this research were discussed in

Types of tool-using groups

Interpretation of the appropriate cluster solution should be based on parsimony (Aldenderfer & Blashfield, 1984). To determine the number of clusters to extract, we used the information presented in the agglomeration schedule to graph a scree-plot, a graph of the distance between the clusters by the number of clusters (Barab et al., 1997). Greater distances between clusters indicate dissimilar clusters are being merged. Smaller distances between clusters indicate relatively similar clusters are

Discussion

The analyses on group tool use patterns indicated three distinctive patterns of tool use by the groups: a Low Frequency of Access cluster, an Average Frequency of Access cluster, and a High Frequency of Access cluster. We used students’ individual performance on the science knowledge test, in connection with frequency of access to the tools, to assist us in the interpretation of the three emergent clusters. Given the three types of tool-use groups, the results showed that the while the groups

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