Author:

Keywords:

itec, iMinds

Abstract:

In computer-based learning environments (CBLEs) the use of support, also referred to as tools, has resulted not only problematic but complex, as well. Research has pointed out that –if learners decide to use the tools- how the tools are used affects the tools functionality and hence performance (Elen & Clarebout, 2006). In addition, tool use seems to be affected by a number of variables related to the tools themselves and to their users (learners). Considering the conditions of Perkins (1985), the framework of Winne (2006) and the tool use phases of Iiyoshi and Hannafin (1998), this Ph.D. dissertation first investigates the effects of tool use on performance in an effort to analyze the tools functionality. Tool use is analyzed from a quantitative (time & frequency) and a qualitative perspective. Second, the impact of prior knowledge, metacognitive (self-regulation and perceptions) and motivational (goal-orientation and self-efficacy) learner-related variables are explored. Third, the influence of tool-related variables, namely tool delivery mode (embedded vs. non-embedded tools), tool advice (explanation of the tool functionality vs. no explanation of the tool functionality) and tool type (cognitive tools: knowledge organization tool (semi-structured concept map) and a knowledge generation tool (adjunct question)) on tool use is examined. The mutual interaction between learner and tool-related variables on tool use is also studied. Furthermore, in line with the cognitive meditational paradigm (Doyle, 1980; Winne, 1982; Winne & Marx, 1983) and the Technology Acceptance Model (TAM) (Davis, Bagozzi, & Warshaw, 1989) special attention is paid to the role of perceptions as mediators of tool use (see Chapter 1). Firstly, an exploratory study was conducted. This study consisted of a psychomotor task with two tools (a functional and a less functional one). The results indicated that learners were not capable of identifying the most functional tool, that the selection of tools may be influenced by the perceived functionality of the tools, and that the tool use complexity is not only inherent to CBLEs. These findings set the platform and baseline for the following three studies (Chapter 2). Studies 1, 2 and 3 were set in a CBLE. The CBLE task consisted of studying an instructional text from a computer screen. The studies followed a 2 x 2 experimental pre-test post-test design. The conditions differed with respect to the tool delivery mode and tool advice. There were two embedded conditions, one with explanation of the tool functionality and one without; and two non-embedded conditions, one with explanation of the tool functionality and one without. Studies 2 and 3 included a control condition with no tools nor explanation of the tool functionality. Additionally, each of the studies employed a different tool. Study 1 employed a knowledge generation tool in the form of five adjunct questions. Study 2 employed a knowledge organization tool in the form of five semi-structured concept maps. Study 3 employed multiple tools: five adjunct questions and five semi-structured concept maps. Study 1 revealed that embedded tools influenced positively quantity of tool use (time) and negatively quality of tool use. Moreover, partial effects of explained tool functionality were found. There were significant interactions of mastery avoidance and condition on quality of tool use. Performance approach influenced quality of tool use positively and self-efficacy negatively influenced quantity of tool use (frequency). Only time spent on tools affected performance. The mediation analysis indicated that self-efficacy was mediated by perceived usability which in turn influenced perceived functionality. Neither perceived functionality nor perceived usability had a significant impact on tool use (Chapter 3). The results from Study 2 were discussed with respect to experienced learners’ role on tool use. Although no differences among conditions and performance were found, results revealed that the self-regulation skill of organization and the explained tool functionality affected the time spent on the tools negatively, while the self-regulation skill of elaboration and perceived tool usability showed a positive effect. Time spent on the tools influenced performance positively but frequency of tool use influenced performance negatively. The mediation analysis showed a significant positive relationship between perceived usability and perceived functionality. Whereas perceived usability had a positive influence on the quantity of tool use, which positively influenced performance; perceived functionality had a negative influence on quantity of tool use. Self-efficacy showed a relationship with perceived usability. The effects on the mediation analysis differed among conditions (Chapter 4). In Study 3, the findings indicated that the tool type impacted tool use and performance. High levels of performance avoidance affected negatively the time spent on concept maps; critical thinking showed a positive influence on the time spent on adjunct questions; perceived usability of adjunct questions showed a negative influence on time spent on adjunct questions. Only the time spent on adjunct questions had a positive and significant effect on performance and embedded conditions spent more time on the tools (Chapter 5). In addition, the experimental conditions outperformed the control condition. The general discussions and conclusion of this dissertation are discussed in terms of their limitations, implications and suggestions for further research on tool use (Chapter 6).