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Why do students reply? Uncovering the socio-semantic entanglement in web annotation activities

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Abstract

Web annotation environments are widely used in education based on the premise that student interaction in these environments benefits individual and group learning. However, there is little research on factors driving student interaction in web annotation activities. In this study we asked: What dynamics could explain social interaction among students in web annotation activities in college classrooms? Recognizing the mediated nature of social interaction in web annotation, we hypothesized that student interaction is driven by multiple factors including previous relational events and semantic features of annotation content. Following a novel network analysis method named relational event modeling, we analyzed a rich dataset from four online classes. Results indicated annotation popularity was initially predictive of student replies, meaning popular annotation threads were more likely to attract new replies. However, this effect nearly diminished when adding thread-level semantic cohesion to the model, indicating an significant role played by semantic cohesion in attracting new responses. This paper makes important progress towards modeling social interaction in digital environments as a dynamic, mediated phenomenon. This study contributes empirical insights into web annotation and calls for future work to investigate social interaction as a dynamic network phenomenon.

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Data Availability

The datasets analysed during the current study are available from the corresponding author on reasonable request. R scripts used for data analysis can be found online at https://osf.io/b2p97/.

Notes

  1. We applied two pre-trained word embedding models, word2vec negative sampling and Glove; those two models yielded cohesion measures that are highly correlated (\(\textit{r} > 0.98\)). The models presented then used word2vec-based cohesion measures.

  2. For the threads made with no reference text, we included a binary missing label variable in modeling to capture any noticeable patterns caused by those cases.

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  1. Graduate School of Education, University of Pennsylvania, Philadelphia, PA, 19104, USA

    Bodong Chen

  2. College of Education and Human Development, University of Minnesota, Minneapolis, MN, 55455, USA

    Bodong Chen & Zixi Chen

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  1. Bodong Chen
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Correspondence to Bodong Chen.

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Chen, B., Chen, Z. Why do students reply? Uncovering the socio-semantic entanglement in web annotation activities. Educ Inf Technol (2023). https://doi.org/10.1007/s10639-023-12187-5

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