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dc.contributor.authorXia, Mengen_US
dc.contributor.authorXu, Minen_US
dc.contributor.authorLin, Chuan-enen_US
dc.contributor.authorCheng, Ta Yingen_US
dc.contributor.authorQu, Huaminen_US
dc.contributor.authorMa, Xiaojuanen_US
dc.contributor.editorViola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatianaen_US
dc.date.accessioned2020-05-24T13:01:45Z
dc.date.available2020-05-24T13:01:45Z
dc.date.issued2020
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.13998
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13998
dc.description.abstractProblem-solving dynamics refers to the process of solving a series of problems over time, from which a student's cognitive skills and non-cognitive traits and behaviors can be inferred. For example, we can derive a student's learning curve (an indicator of cognitive skill) from the changes in the difficulty level of problems solved, or derive a student's self-regulation patterns (an example of non-cognitive traits and behaviors) based on the problem-solving frequency over time. Few studies provide an integrated overview of both aspects by unfolding the problem-solving process. In this paper, we present a visual analytics system named SeqDynamics that evaluates students' problem-solving dynamics from both cognitive and non-cognitive perspectives. The system visualizes the chronological sequence of learners' problem-solving behavior through a set of novel visual designs and coordinated contextual views, enabling users to compare and evaluate problem-solving dynamics on multiple scales. We present three scenarios to demonstrate the usefulness of SeqDynamics on a real-world dataset which consists of thousands of problem-solving traces. We also conduct five expert interviews to show that SeqDynamics enhances domain experts' understanding of learning behavior sequences and assists them in completing evaluation tasks efficiently.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/]
dc.subjectHuman centered computing
dc.subjectVisual analytics
dc.subjectApplied computing
dc.subjectE
dc.subjectlearning
dc.titleSeqDynamics: Visual Analytics for Evaluating Online Problem-solving Dynamicsen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersVisual Analytics for Problem Solving
dc.description.volume39
dc.description.number3
dc.identifier.doi10.1111/cgf.13998
dc.identifier.pages511-522


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  • 39-Issue 3
    EuroVis 2020 - Conference Proceedings

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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License