research-article

PathViewer: Visualizing Pathways through Student Data

Authors:

Walker M. White,

Erik AndersenAuthors Info & Claims

CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

Pages 960 - 964

https://doi.org/10.1145/3025453.3025819

Published: 02 May 2017 Publication History

Abstract

Analysis of student data is critical for improving education. In particular, educators need to understand what approaches their students are taking to solve a problem. However, identifying student strategies and discovering areas of confusion is difficult because an educator may not know what queries to ask or what patterns to look for in the data. In this paper, we present a visualization tool, PathViewer, to model the paths that students follow when solving a problem. PathViewer leverages ideas from flow diagrams and natural language processing to visualize the sequences of intermediate steps that students take. Using PathViewer, we analyzed how several students solved a Python assignment, discovering interesting and unexpected patterns. Our results suggest that PathViewer can allow educators to quickly identify areas of interest, drill down into specific areas, and identify student approaches to the problem as well as misconceptions they may have.

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Cited By

Shi CHu YWang SMa SZheng CMa XLuo Q(2023)RetroLens: A Human-AI Collaborative System for Multi-step Retrosynthetic Route PlanningProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581469(1-20)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581469
Shen LShen ELuo YYang XHu XZhang XTai ZWang J(2023)Towards Natural Language Interfaces for Data Visualization: A SurveyIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.314800729:6(3121-3144)Online publication date: 1-Jun-2023
https://doi.org/10.1109/TVCG.2022.3148007
Tsung SWei HLi HWang YXia MQu HKizilcec RDavis KOchoa X(2022)BlockLens: Visual Analytics of Student Coding Behaviors in Block-Based Programming EnvironmentsProceedings of the Ninth ACM Conference on Learning @ Scale10.1145/3491140.3528298(299-303)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1145/3491140.3528298
Show More Cited By

Index Terms

PathViewer: Visualizing Pathways through Student Data
1. Human-centered computing

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cover image ACM Conferences

CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

May 2017

7138 pages

ISBN:9781450346559

DOI:10.1145/3025453

General Chairs:
Gloria Mark
University of California Irvine
,
Susan Fussell
Cornell University
,
Program Chairs:
Cliff Lampe
University of Michigan
,
m.c. schraefel
University of Southampton
,
Juan Pablo Hourcade
University of Iowa
,
Caroline Appert
Université Paris-Sud
,
Daniel Wigdor
University of Toronto

Copyright © 2017 ACM.

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Published: 02 May 2017

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CHI '17: CHI Conference on Human Factors in Computing Systems

May 6 - 11, 2017

Colorado, Denver, USA

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CHI '17 Paper Acceptance Rate 600 of 2,400 submissions, 25%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

Shi CHu YWang SMa SZheng CMa XLuo Q(2023)RetroLens: A Human-AI Collaborative System for Multi-step Retrosynthetic Route PlanningProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581469(1-20)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581469
Shen LShen ELuo YYang XHu XZhang XTai ZWang J(2023)Towards Natural Language Interfaces for Data Visualization: A SurveyIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.314800729:6(3121-3144)Online publication date: 1-Jun-2023
https://doi.org/10.1109/TVCG.2022.3148007
Tsung SWei HLi HWang YXia MQu HKizilcec RDavis KOchoa X(2022)BlockLens: Visual Analytics of Student Coding Behaviors in Block-Based Programming EnvironmentsProceedings of the Ninth ACM Conference on Learning @ Scale10.1145/3491140.3528298(299-303)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1145/3491140.3528298
Kui XLiu NLiu QLiu JZeng XZhang C(2022)A survey of visual analytics techniques for online educationVisual Informatics10.1016/j.visinf.2022.07.0046:4(67-77)Online publication date: Dec-2022
https://doi.org/10.1016/j.visinf.2022.07.004
Xia MVelumani RWang YQu HMa X(2021)QLens: Visual Analytics of MUlti-step Problem-solving Behaviors for Improving Question DesignIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.303033727:2(870-880)Online publication date: Feb-2021
https://doi.org/10.1109/TVCG.2020.3030337
Javvaji NHarteveld CSeif El-Nasr MMirza-Babaei PMcArthur VVanden Abeele VBirk M(2020)Understanding Player Patterns by Combining Knowledge-Based Data Abstraction with Interactive VisualizationProceedings of the Annual Symposium on Computer-Human Interaction in Play10.1145/3410404.3414257(254-266)Online publication date: 2-Nov-2020
https://dl.acm.org/doi/10.1145/3410404.3414257
Garcia CMeincheim AFaria Junior EDallagassa MSato DCarvalho DSantos EScalabrin E(2019)Process mining techniques and applications – A systematic mapping studyExpert Systems with Applications: An International Journal10.1016/j.eswa.2019.05.003133:C(260-295)Online publication date: 1-Nov-2019
https://dl.acm.org/doi/10.1016/j.eswa.2019.05.003
Chang MGuillain LJung HHare VKim JAgrawala MMandryk RHancock MPerry MCox A(2018)RecipeScapeProceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3174025(1-12)Online publication date: 21-Apr-2018
https://dl.acm.org/doi/10.1145/3173574.3174025

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