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Visualizing Self-Regulated Learner Profiles in Dashboards: Design Insights from Teachers

Authors
Paola Mejia-Domenzain,
Eva Laini,
Seyed Parsa Neshaei,
Thiemo Wambsganss,
Tanja Kaser
Date
Publisher
arXiv
Flipped Classrooms (FC) are a promising teaching strategy, where students engage with the learning material before attending face-to-face sessions. While pre-class activities are critical for course success, many students struggle to engage effectively in them due to inadequate of self-regulated learning (SRL) skills. Thus, tools enabling teachers to monitor students' SRL and provide personalized guidance have the potential to improve learning outcomes. However, existing dashboards mostly focus on aggregated information, disregarding recent work leveraging machine learning (ML) approaches that have identified comprehensive, multi-dimensional SRL behaviors. Unfortunately, the complexity of such findings makes them difficult to communicate and act on. In this paper, we follow a teacher-centered approach to study how to make thorough findings accessible to teachers. We design and implement FlippED, a dashboard for monitoring students' SRL behavior. We evaluate the usability and actionability of the tool in semi-structured interviews with ten university teachers. We find that communicating ML-based profiles spark a range of potential interventions for students and course modifications.
Study at a glance
  • Question: How can dashboards clearly present complex student learning behaviors so teachers can easily understand and act on them?
  • Setting and data: Ten university teachers.
  • Method: Tool design and semi-structured usability interviews.
Why it matters

Many students struggle in flipped classrooms due to inadequate self-regulated learning skills. However, existing dashboards mostly focus on aggregated information, making complex, multi-dimensional machine learning findings difficult to communicate and act on.

Key findings
  • In interviews with ten university teachers, sharing machine learning-based student profiles sparked a range of potential student interventions and course modifications.
  • Existing dashboards typically present aggregated information, making complex, multi-dimensional student learning behaviors difficult for educators to interpret and act on.
  • Many students struggle to engage effectively in pre-class activities within flipped classrooms because they lack adequate self-regulated learning skills.

Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.

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