Single or Multi-page Learning Analytics Dashboards? Relationships Between Teachers’ Cognitive Load and Visualisation Literacy

Pozdniakov, Stanislav; Martinez-Maldonado, Roberto; Tsai, Yi-Shan; Srivastava, Namrata; Liu, Yuchen; Gasevic, Dragan

doi:10.1007/978-3-031-42682-7_23

Cited by 3 publications

(1 citation statement)

References 39 publications

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“…This step towards more transparency is signicant, yet there are many other issues in the adoption and use of these approaches in practice that relate to ethical considerations [1], socio-cultural factors of the education system [11], as well as psycho-physiological factors of individual teachers e.g. cognitive load [34] which all require further investigations.…”

Section: Discussionmentioning

confidence: 99%

Harnessing Transparent Learning Analytics for Individualized Support through Auto-detection of Engagement in Face-to-Face Collaborative Learning

Zhou,

Suraworachet,

Cukurova

2024

Proceedings of the 14th Learning Analytics and Knowledge Conference

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Using learning analytics to investigate and support collaborative learning has been explored for many years. Recently, automated approaches with various articial intelligence approaches have provided promising results for modelling and predicting student engagement and performance in collaborative learning tasks. However, due to the lack of transparency and interpretability caused by the use of "black box" approaches in learning analytics design and implementation, guidance for teaching and learning practice may become a challenge. On the one hand, the black box created by machine learning algorithms and models prevents users from obtaining educationally meaningful learning and teaching suggestions. On the other hand, focusing on group and cohort level analysis only can make it dicult to provide specic support for individual students working in collaborative groups. This paper proposes a transparent approach to automatically detect student's individual engagement in the process of collaboration. The results show that the proposed approach can reect student's individual engagement and can be used as an indicator to distinguish students with dierent collaborative learning challenges (cognitive, behavioural and emotional) and learning outcomes. The potential of the proposed collaboration analytics approach for scaolding collaborative learning practice in face-to-face contexts is discussed and future research suggestions are provided. CCS CONCEPTS• Applied computing ! Education; Collaborative learning; • Human-centered computing ! Collaborative and social computing; Empirical studies in collaborative and social computing.

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Section: Discussionmentioning

confidence: 99%

Harnessing Transparent Learning Analytics for Individualized Support through Auto-detection of Engagement in Face-to-Face Collaborative Learning

Zhou,

Suraworachet,

Cukurova

2024

Proceedings of the 14th Learning Analytics and Knowledge Conference

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Bibliographic coupling networks of global research on data literacy by documents, sources and authors

Nwagwu

2024

Journal of Librarianship and Information Science

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This study was carried out to visualise the interconnectedness among research works in the field of Data Literacy documents, Sources and Authors, Identify clusters, nodes and key connections to understand the structural patterns within Data Literacy scholarly literature and determine the most influential and highly-cited papers, authors and journals within the bibliographic coupling networks. We specified the syntax ‘DATA LITERACY’. While it is obvious that there may be studies that have addressed this subject using other syntax, ‘Data Literacy’ will yield an appropriately representative sample of keywords in the area. The findings offer valuable insights into the landscape of research on data literacy, particularly in terms of the interconnections and influences among various scholarly works. Several discussions can be carried out based on these findings. The analysis identifies key documents that have significantly contributed to the development of research on data literacy. The analysis of publication years of identified documents offers insights into the temporal evolution of research on data literacy. This helps reveal shifts in research emphasis over time and highlights emerging areas of interest within the field.

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Mapping Bibliographic Coupling Network of Global Research on Data Literacy by Institutions and Countries

Nwagwu

2024

Preprint

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Single or Multi-page Learning Analytics Dashboards? Relationships Between Teachers’ Cognitive Load and Visualisation Literacy

Cited by 3 publications

References 39 publications

Harnessing Transparent Learning Analytics for Individualized Support through Auto-detection of Engagement in Face-to-Face Collaborative Learning

Harnessing Transparent Learning Analytics for Individualized Support through Auto-detection of Engagement in Face-to-Face Collaborative Learning

Bibliographic coupling networks of global research on data literacy by documents, sources and authors

Mapping Bibliographic Coupling Network of Global Research on Data Literacy by Institutions and Countries

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