UserFlow: a tool for visualizing fine-grained contextual analytics in teaching documents

Shaveen Singh; Bernd Meyer; Michael Wybrow

doi:10.1145/3341525.3387410

UserFlow: a tool for visualizing fine-grained contextual analytics in teaching documents

Shaveen Singh, Bernd Meyer, Michael Wybrow

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

2 Citations (Scopus)

Abstract

The adoption of innovative online teaching tools in Computer Science (CS) courses provides opportunities for data-informed instruction as a regular teaching practice in CS classrooms. In this paper, we present a design study for an interactive visual analytics dashboard, called UserFlow, that supports feedback collection from teaching documents and assists instructors in interpreting feedback and acting on it in a timely manner. The design study is conducted with eight domain experts comprising of four teaching instructors, two learning analytics (LA) experts and two instructional designers. UserFlow offers a set of novel visualization designs for presenting the four interleaving aspects of document engagement (i.e., annotations, document traversal path, reading/focus time and student information). We evaluated UserFlow in an undergraduate computer science course with over 700 students. Our results demonstrate the usefulness and need for such a tool for CS educators to inform teaching approaches and courseware improvement.

Original language	English
Title of host publication	Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education
Editors	Andrew Luxton-Reilly, Monica Divitini
Place of Publication	New York NY USA
Publisher	Association for Computing Machinery (ACM)
Pages	384-390
Number of pages	7
ISBN (Electronic)	9781450368742
DOIs	https://doi.org/10.1145/3341525.3387410
Publication status	Published - Jun 2020
Event	Annual Conference on Innovation and Technology in Computer Science Education 2020 - Trondheim, Norway Duration: 15 Jun 2020 → 19 Jun 2020 Conference number: 25th https://iticse.acm.org (Website) https://dl.acm.org/doi/proceedings/10.1145/3341525 (Proceedings)

Conference

Conference	Annual Conference on Innovation and Technology in Computer Science Education 2020
Abbreviated title	ITiCSE 2020
Country/Territory	Norway
City	Trondheim
Period	15/06/20 → 19/06/20
Internet address	https://iticse.acm.org (Website) https://dl.acm.org/doi/proceedings/10.1145/3341525 (Proceedings)

Keywords

analytics
annotations
dashboards
digital education
engagement

Access to Document

10.1145/3341525.3387410

Cite this

Singh, S., Meyer, B., & Wybrow, M. (2020). UserFlow: a tool for visualizing fine-grained contextual analytics in teaching documents. In A. Luxton-Reilly, & M. Divitini (Eds.), Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education (pp. 384-390). Association for Computing Machinery (ACM). https://doi.org/10.1145/3341525.3387410

Singh, Shaveen ; Meyer, Bernd ; Wybrow, Michael. / UserFlow : a tool for visualizing fine-grained contextual analytics in teaching documents. Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education. editor / Andrew Luxton-Reilly ; Monica Divitini. New York NY USA : Association for Computing Machinery (ACM), 2020. pp. 384-390

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abstract = "The adoption of innovative online teaching tools in Computer Science (CS) courses provides opportunities for data-informed instruction as a regular teaching practice in CS classrooms. In this paper, we present a design study for an interactive visual analytics dashboard, called UserFlow, that supports feedback collection from teaching documents and assists instructors in interpreting feedback and acting on it in a timely manner. The design study is conducted with eight domain experts comprising of four teaching instructors, two learning analytics (LA) experts and two instructional designers. UserFlow offers a set of novel visualization designs for presenting the four interleaving aspects of document engagement (i.e., annotations, document traversal path, reading/focus time and student information). We evaluated UserFlow in an undergraduate computer science course with over 700 students. Our results demonstrate the usefulness and need for such a tool for CS educators to inform teaching approaches and courseware improvement.",

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address = "United States of America",

note = "Annual Conference on Innovation and Technology in Computer Science Education 2020, ITiCSE 2020 ; Conference date: 15-06-2020 Through 19-06-2020",

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Singh, S , Meyer, B & Wybrow, M 2020, UserFlow: a tool for visualizing fine-grained contextual analytics in teaching documents. in A Luxton-Reilly & M Divitini (eds), Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education. Association for Computing Machinery (ACM), New York NY USA, pp. 384-390, Annual Conference on Innovation and Technology in Computer Science Education 2020, Trondheim, Norway, 15/06/20. https://doi.org/10.1145/3341525.3387410

UserFlow: a tool for visualizing fine-grained contextual analytics in teaching documents. / Singh, Shaveen ; Meyer, Bernd ; Wybrow, Michael.
Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education. ed. / Andrew Luxton-Reilly; Monica Divitini. New York NY USA: Association for Computing Machinery (ACM), 2020. p. 384-390.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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UserFlow: a tool for visualizing fine-grained contextual analytics in teaching documents

Abstract

Conference

Keywords

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