Academic journal article Educational Technology & Society

Measuring Knowledge Elaboration Based on a Computer-Assisted Knowledge Map Analytical Approach to Collaborative Learning

Academic journal article Educational Technology & Society

Measuring Knowledge Elaboration Based on a Computer-Assisted Knowledge Map Analytical Approach to Collaborative Learning

Article excerpt

Introduction

It has been widely acknowledged that collaborative learning facilitates knowledge gains (Dillenbourg, 1999; Stahl, 2011). Moreover, elaboration is an important activity for promoting knowledge acquisition during collaborative learning activities (Denessen et al., 2008; Golanics & Nussbaum, 2008; Stegmann et al., 2012). Knowledge elaboration has been defined as organising, restructuring, interconnecting, and integrating new information with prior knowledge (Reigeluth et al., 1980; Weinstein & Mayer, 1986; Kalyuga, 2009). It can facilitate the retention of the target information (Anderson, 1983) and stimulate the reorganisation of information. Educators have pointed out that elaboration processes are necessary for meaningful learning, which emphasises the integration of new knowledge into existing knowledge (Novak, 2002; Kalyuga, 2009). The importance of elaboration is also supported by the generative model of learning put forward by Wittrock (1989), who indicated that new information should be meaningfully related to prior knowledge to generate connections between the informing information and memory representations in order to retain new information.

Researchers have further indicated that knowledge elaboration is the key factor in collaborative learning (Denessen et al., 2008). Many studies have reported that knowledge elaboration has positive effects on students' learning achievements (Van Boxtel et al., 2000; Stark et al., 2002; Hwang et al., 2007; Denessen et al., 2008; Stegmann et al., 2012). However, most previous studies measured knowledge elaboration by questionnaire (Draskovic et al., 2004), by coding think-aloud protocols (Stegmann et al., 2012), by coding discussion transcripts into different categories (Eysink & de Jong, 2012), or by assigning values of -1, 0, and 1 (Ding et al., 2011) to assess knowledge elaboration. Such coding is subjective and ignores the domain knowledge when segmenting and coding discourse data (Suthers et al., 2010; Zheng et al., 2012). Little research has been performed to determine how to measure knowledge elaboration accurately and objectively.

The present study attempts to overcome the methodological limitations in measuring knowledge elaboration. The purpose of this study is to go beyond the scope of previous studies by measuring the level of knowledge elaboration based on the knowledge map analytic approach, and by examining the relationships between the prior knowledge of a group, group performance, and knowledge elaboration. The knowledge map approach is quite different from concept mapping in terms of knowledge representation. The nodes in a knowledge map can denote symbols, concepts, principles and formulas, processes and steps, cognitive strategies, and facts and instances (Yang, 2010), while those in a concept map mainly denote concepts, facts and instances (Novak & Canas, 2006). More specially, concepts are defined as abstract objects (Laurence & Margolis, 1999), or perceived regularities or patterns in events or objects (Novak & Canas, 2006). Based on the knowledge map approach, the following research questions are investigated in this study:

* What are the indicators of knowledge elaboration from the perspective of graph theory and knowledge semantic properties?

* Does students' knowledge elaboration level positively affect their group performance?

* Is students' knowledge elaboration level positively related to their prior knowledge?

Literature review

Knowledge elaboration plays a crucial role in collaborative learning. When group members interact with one another, they need to explain large quantities of information about the learning material to others and therefore process information more deeply. Slavin et al. (2003) believed that elaboration can be achieved by explaining information to others when interacting during collaborative learning. Researchers assume that interaction with others promotes the processing of information and the modification of cognitive structures (Baker, 2003; Wibeck et al. …

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