This study focuses on analyzing interaction patterns in educational web forums, which are crucial indicators of learning quality. Social network analysis (SNA) is increasingly used to study these patterns by examining the interrelationships between individuals, offering a comprehensive view of group performance. Traditionally, SNA data is derived from server log files, based on the assumption that this data accurately reflects online interactions. This study challenges this assumption by comparing the conventional structural method for detecting posting addressees with an approach enriched by semantic coding. Results indicate that the new semantic coding schema identifies more addressees and includes a greater number of postings in the SNA adjacency matrix, enhancing the understanding of actual communication flows.
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Manca, Stefania, Manuela Delfino, and Elvis Mazzoni. "Coding procedures to analyse interaction patterns in educational web forums." Journal of computer assisted learning 25.2 (2009): 189-200.
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