The equalizing effect of teacher dashboards on feedback in K-12 classrooms
Open accessAbstract
Teacher dashboards provide real-time information about students’ performance and progress, which help K-12 teachers to adjust feedback to student’ specific needs during learning. Prior research indicated two problems with respect to how teachers provide feedback: (i) teachers do not always select the most effective feedback to support student’ learning and (ii) feedback is not allocated equally to students with different abilities. Specifically, process feedback is considered most effective yet is relatively scarce. In order to understand how dashboards influence the type and allocation of feedback, we compared characteristics of feedback given after dashboard consultation (dashboard-prompted feedback) to feedback triggered by teachers themselves or in response to students’ questions (human-prompted feedback) in thirty-five K-12 classrooms. Results showed that dashboards led to equal amounts of task and process feedback, while human-prompts led to much more task than process feedback and this difference was especially large for low-ability students. Hence the different types of dashboard-prompted feedback were more equally distributed among students of different ability levels. These results indicate that dashboards can have an important equalizing effect on teacher feedback practices.
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AI systems can augment teacher feedback by providing real-time data analytics and visualizations of student performance, exemplified by teacher dashboards.
“AI systems can augment teacher feedback by providing real-time data analytics and visualizations of student performance, exemplified by teacher dashboards that facilitate monitoring and assessment through visualizing relevant learner variables (Knoop-van Campen et al., 2023;Xhakaj et al., 2017).”
From Looking Beyond the Hype: Understanding the Effects of AI on Learning (2025) · cites this paper as Knoop-van Campen et al., 2023
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References 75 · Cited by 58
Research works printed but not linked: 3
- Molenaar, I., & Knoop-van Campen, C. A. N. (2017b, September). How teachers differ in using dashboards: the classroom observation app. Presented at the workshop "multimodal learning analytics across (physical and digital) spaces" at European conference on technology enhanced learning. Cham: Springer.
- ep10770698 · DOI
- Van Leeuwen, A., Teasley, S., & Wise, D., & F, A. (in press). Teacher and student facing learning analytics. In C. Lang, G. Siemens, A. F. Wise, D. Gasevic, & A. Mercernon (Eds.), Handbook of learning analytics. 2nd ed. SoLAR.
- Authors
- Knoop-van Campen, C. A. N., Wise, A., & Molenaar, I.
- Affiliations
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
- New York University (US)
- Radboud University Nijmegen (NL)
- Venue
- Interactive Learning Environments
- Publisher
- Informa UK Limited
- Published
- 2021-05-31
- Volume
- 31
- Issue
- 6
- Pages
- 3447-3463
- ISSN
- 1049-4820 (ISSN-L)
- 1744-5191
- OpenAlex
- W3170353180
- Cited by
- 58
- References
- 75
- Citations by year
- 2026: 11 · 2025: 14 · 2024: 14 · 2023: 9 · 2022: 9 · 2021: 1
- FWCI
- 14.50
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Interactive Learning Environments (publishedVersion, cc-by-nc-nd)
- Radboud Repository (Radboud University) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Funders
- Kennisnet - Doorbraakproject (405-15-823)
- Topics
- Social Sciences › Education › Student Assessment and Feedback
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- teacher dashboards, teacher feedback, process feedback, task feedback, student ability, K-12 classrooms, educational data mining, personalized learning
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