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

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2 Citations (Scopus)


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 languageEnglish
Title of host publicationProceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education
EditorsAndrew Luxton-Reilly, Monica Divitini
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages7
ISBN (Electronic)9781450368742
Publication statusPublished - Jun 2020
EventAnnual Conference on Innovation and Technology in Computer Science Education 2020 - Trondheim, Norway
Duration: 15 Jun 202019 Jun 2020
Conference number: 25th (Website) (Proceedings)


ConferenceAnnual Conference on Innovation and Technology in Computer Science Education 2020
Abbreviated titleITiCSE 2020
Internet address


  • analytics
  • annotations
  • dashboards
  • digital education
  • engagement

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