Social Comparison in MOOCs

Choi, Heeryung; Dowell, Nia; Brooks, Christopher; Teasley, Stephanie D.

doi:10.1145/3303772.3303773

Cited by 5 publications

(1 citation statement)

References 30 publications

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“…Notably, the pairs with different second languages collaborated more (average turns per minute) and communicated more (average utterances) during the divergent thinking tasks. Considering the effect of socioeconomic status (SES) on peer feedback, Choi, Dowell, Brooks, and Teasley (2019) find that learners from high-SES nations in massive open online courses (MOOCs) are likely to give learners from low-income countries less formal and more emotional feedback, but offered more formal and less emotional feedback to learners from medium-income countries. Gender can also be related to learners' interaction patterns, particularly communication.…”

Section: Relationship Between Students and Contentmentioning

confidence: 99%

Collaboration Analytics Need More Comprehensive Models and Methods: An Opinion Paper

Han

Krieger

Greiff

2021

JLA

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As technology advances, learning analytics is expanding to include students’ collaboration settings. Despite their increasing application in practice, some types of analytics might not fully capture the comprehensive educational contexts in which students’ collaboration takes place (e.g., when data is collected and processed without predefined models, which forces users to make conclusions without sufficient contextual information). Furthermore, existing definitions and perspectives on collaboration analytics are incongruent. In light of these circumstances, this opinion paper takes a collaborative classroom setting as context and explores relevant comprehensive models for collaboration analytics. Specifically, this paper is based on Pei-Ling Tan and Koh’s ecological lens (2017, Situating learning analytics pedagogically: Towards an ecological lens. Learning: Research and Practice, 3(1), 1–11. https://doi.org/10.1080/23735082.2017.1305661), which illustrates the co-emergence of three interactions among students, teachers, and content interwoven with time. Moreover, this paper suggests several factors to consider in each interaction when executing collaboration analytics. Agendas and recommendations for future research are also presented.

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Section: Relationship Between Students and Contentmentioning

confidence: 99%

Collaboration Analytics Need More Comprehensive Models and Methods: An Opinion Paper

Han

Krieger

Greiff

2021

JLA

View full text Add to dashboard Cite

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Learning Analytics for Peer Assessment: A Scoping Review

Misiejuk

Wasson

2023

Social Interaction in Learning and Development

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Learning analytics is a maturing field that analyses educational data to gain new insights and improve learning. Peer assessment is an assessment technique in which students provide feedback to one another. To date, there have been no reviews examining how learning analytics is used to facilitate peer assessment. This scoping review addresses this gap and provides an overview of the role of learning analytics in understanding peer assessment, the peer assessment challenges addressed by learning analytics, and insights into peer assessment. The 27 papers in the review highlight a diverse landscape of research integrating automated assessment and visualizations into peer assessment activities, applying novel data analysis methods to peer assessment data, evaluating different types of peer assessment, or examining new research questions, such as those regarding student interaction or self-regulation during peer assessment activities.

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Impact of social comparison on perceived online academic futility: A perspective from parents

et al. 2022

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In response to the wide-ranging concern of online academic futility, the current study aimed to explore the independent variables and mediating variable from a novel perspective of parents during COVID-19. Based on the social comparison theory and the control-value theory of achievement emotions, social comparison and tutoring anxiety were incorporated into an integrated model as predictors and mediator, respectively. A total of 300 parents completed an online survey. The results of the structural equation modeling indicated that upward social comparison and downward social comparison were both positively related to tutoring anxiety, which in turn positively predicted perceived online academic futility. Notably, tutoring anxiety played a significant mediating role in the association between different social comparison and perceived online academic futility. These results highlight the consistent predictive effect of upward social comparison and downward social comparison on perceived online academic futility, shedding light on the roles of tutoring anxiety in explaining the relationship from parental perspectives.

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Social Comparison in MOOCs

Cited by 5 publications

References 30 publications

Collaboration Analytics Need More Comprehensive Models and Methods: An Opinion Paper

Collaboration Analytics Need More Comprehensive Models and Methods: An Opinion Paper

Learning Analytics for Peer Assessment: A Scoping Review

Impact of social comparison on perceived online academic futility: A perspective from parents

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