Academic journal article Educational Technology & Society

Measuring and Visualizing Group Knowledge Elaboration in Online Collaborative Discussions

Academic journal article Educational Technology & Society

Measuring and Visualizing Group Knowledge Elaboration in Online Collaborative Discussions

Article excerpt

Introduction

In collaborative learning environments, online discussion is an important activity that engages learners in asking questions, articulating their thoughts, explaining and justifying their opinions, and sharing ideas and resources, all of which contribute to meaningful collaborative learning (Li et al., 2009). Knowledge elaboration, as an integral part of online discussion, refers to how learners organize, restructure, interconnect, and integrate knowledge (Reigeluth et al., 1980; Kalyuga, 2009; Gleaves & Walker, 2013), thereby promoting knowledge acquisition and knowledge retention (Anderson, 1983; Denessen et al., 2008; Golanics & Nussbaum, 2008; Stegmann et al., 2012; Zheng et al., 2015).

Researchers have reported that knowledge elaboration has positive effects on group problem-solving (Eryilmaz et al., 2013) and student achievement (Van et al., 2000; Stark et al., 2002; Hwang et al., 2007). However, most previous studies analyzed knowledge elaboration through qualitative manual coding, which involves subjective judgment, and the reliability of dialog analysis schemes also remains a contentious issue (Pilkington, 2001). Because this method is time-intensive and conducted post-event, the information obtained does not offer opportunities for real-time feedback to enhance evaluation, reflection, awareness, and adaptation of collaborative learning (Kumar et al., 2010). Besides, the analysis results are meaningful mainly for researchers; it is difficult for teachers to interpret the data and to provide timely intervention or assistance during students' collaborative discussions (Xing et al., 2015). Visual representation based on automatic analysis can translate learner-generated data into an accessible visible form that highlights important features, including commonalities and anomalies. Such analysis has been considered as a key to gaining insight into the learning process and providing a basis to better monitor and evaluate students' learning (Papamitsiou & Economides, 2015). Nevertheless, among the studies on knowledge elaboration, very little research has been conducted on visualization support based on automatic analysis.

Therefore, this study proposes an automatic analysis method to measure the level of groups' knowledge elaboration in terms of three indicators: coverage, activation, and equitability. Taking the method as a basis, an interactive web-based tool is developed to provide a multidimensional view of students' knowledge elaboration. The tool allows teachers to have an in-depth understanding of students' acquisition of the target knowledge in a convenient manner, enabling teachers to monitor student's discussion process and provide adequate feedback on students' learning.

Literature review

Knowledge elaboration and measurement

Knowledge elaboration positively affects knowledge acquisition, which is an important determinant of students' satisfaction and motivation (Draskovic et al., 2004). Many researchers have explored the significant roles of knowledge elaboration in online discussion. For instance, after comparing the elaboration differences in four different instructional approaches in multimedia learning environments, Eysink and de Jong (2012) concluded that elaboration is the key process explaining differences in learning outcomes. As for the factors affecting knowledge elaboration, Stegmann et al. (2012) found that the depth of learners' cognitive elaboration is positively related to both the domain-specific knowledge acquisition and the formal quality of their own argumentation. Paus et al. (2012) also confirmed that elaborating domain-specific concepts can activate processes conducive to learning and promote individual learning outcomes in online discourse.

To study the nature of online group learning, most researchers have adopted a qualitative approach to measure knowledge elaboration. Through discourse analysis, Daradoumis and Marques (2002) investigated how distribution of cognition is transformed and becomes common to all group members in an online collaborative problem-solving situation. …

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