Unfolding knowledge co-construction processes through social annotation and online collaborative writing with text mining techniques
Keywords:social annotation, collaborative writing, knowledge co-construction, semantic network analysis
Despite the positive claims on the pedagogical use of social annotation and online collaborative writing tools discussed in the literature, most of the findings are derived from interviews or self-reported survey data. Very few studies probed deep into the learning processes and examined students’ digital traces and the artefacts they co-construct. In this study, we employed semantic network analysis techniques to examine how the use of a social annotation tool (Diigo) coupled with an online collaborative writing (Google Docs) affects students’ learning outcomes. The results indicate that the use of Diigo coupled with Google Docs helps enhance student engagement in the collaborative process and that the concept connectivity and quality of the text co-constructed by each group using Diigo coupled with Google Docs is significantly higher than those using Moodle’s forum. In addition, the level of collaboration within a group correlates positively with the number of vertices with high lexical relevancy identified in the semantic network of the text co-constructed by each group.
Implications for practice and policy:
- Undergraduate students can use Diigo coupled with Google Docs to enhance their collaborative work.
- Course leaders could use Diigo coupled with Google Docs to support learning activities, such as flipped learning or collaborative inquiry learning, in which students are required to engage in close reading and the co-construction of artefacts.
- Course instructors could consider using semantic measures such as the number of clusters and betweenness centrality to assess the quality of students’ co-constructed artefacts.
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Copyright (c) 2021 Sandy C Li, Tony K. H. Lai
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