A Dashboard to Support Teachers During Students’ Self-paced AI-Supported Problem-Solving Practice
Open accessIntegrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
AI provided dashboards tailored for administrators, special education teachers, and parents for better monitoring of student performance.
“Artificial Intelligence also provided dashboards tailored for administrators, special education teachers, and parents for better monitoring of student performance (Aleven et al., 2022).”
From The Future of Artificial Intelligence in Special Education Technology (2023) · cites this paper as Aleven et al., 2022
Cites
Knowledge tracing: Modeling the acquisition of procedural knowledge
Corbett, A. T., & Anderson, J. R. (1995) · User Modelling and User-Adapted Interaction · doi:10.1007/bf01099821 · Cited by 2,324 · see citing works
VanLEHN, K. (2011) · Educational Psychologist · doi:10.1080/00461520.2011.611369 · Cited by 2,323 · see citing works
Cognitive Tutor: Applied research in mathematics education
RITTER, S., Anderson, J. R., Koedinger, K. R., & Corbett, A. T. (2007) · Psychonomic Bulletin & Review · doi:10.3758/bf03194060 · Cited by 495 · see citing works
The Cambridge Handbook of Multimedia Learning
Jarodzka, H. M., Mayer, R. E., & Fiorella, L. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108894333 · Cited by 454 · see citing works
Effectiveness of Cognitive Tutor Algebra I at Scale
Pane, J. F., Griffin, B. A., McCaffrey, D. F., & Karam, R. (2014) · Educational Evaluation and Policy Analysis · doi:10.3102/0162373713507480 · Cited by 317 · cited 3× · see citing works
“The current work targets contexts in which students engage in self-paced, personalized learning with AI-based tutoring software, by now a common occurrence in K-12 in the US and elsewhere [16, 23].”
BackgroundWang, S., Christensen, C., Cui, W., Tong, R., Yarnall, L., Shear, L., & Feng, M. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2020.1808794 · Cited by 277 · see citing works
Help seeking, learning and contingent tutoring
Wood, H., & Wood, D. (1999) · Computers & Education · doi:10.1016/s0360-1315(99)00030-5 · Cited by 275 · see citing works
Arroyo, I., Woolf, B. P., Burelson, W., Muldner, K., Rai, D., & Tai, M. (2014) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-014-0023-y · Cited by 263 · see citing works
Student Learning Benefits of a Mixed-Reality Teacher Awareness Tool in AI-Enhanced Classrooms
Holstein, K., McLaren, B. M., & Aleven, V. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-93843-1_12 · Cited by 235 · see citing works
Self-citationHolstein, K., McLaren, B. M., & Aleven, V. (2019) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-23204-7_14 · Cited by 189 · see citing works
Self-citationAhuja, K., Kim, D., Xhakaj, F., Varga, V., Xie, A., Zhang, S., Townsend, J. E., Harrison, C., Ogan, A., & Agarwal, Y. (2019) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3351229 · Cited by 146 · see citing works
Example-Tracing Tutors: Intelligent Tutor Development for Non-programmers
Aleven, V., McLaren, B. M., Sewall, J., van Velsen, M., Popescu, O., Demi, S., Ringenberg, M. A., & Koedinger, K. R. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-015-0088-2 · Cited by 139 · see citing works
Self-citationXhakaj, F., Aleven, V., & McLaren, B. M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66610-5_23 · Cited by 81 · see citing works
Self-citationHow Mastery Learning Works at Scale
RITTER, S., Yudelson, M. V., Fancsali, S. E., & Berman, S. R. (2016) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/2876034.2876039 · Cited by 78 · see citing works
Speed Dating: Providing a Menu of Possible Futures
Zimmerman, J., & Forlizzi, J. (2017) · She ji · doi:10.1016/j.sheji.2017.08.003 · Cited by 76 · see citing works
The TA Framework: Designing Real-time Teaching Augmentation for K-12 Classrooms
An, P., Holstein, K., d'Anjou, B., Eggen, B., & Bakker, S. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376277 · Cited by 69 · cited 1× · see citing works
“This work has resulted in novel tools and insight into how best to design these kinds of tools [1, 2, 4, 9, 13, 14, 16, 25].”
BackgroundThe equalizing effect of teacher dashboards on feedback in K-12 classrooms
Knoop-van Campen, C. A. N., Wise, A., & Molenaar, I. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2021.1931346 · Cited by 58 · see citing works
Recent Meta-reviews and Meta–analyses of AIED Systems
du Boulay, B. (2015) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-015-0060-1 · Cited by 46 · see citing works
Estimating the Effect of Web-Based Homework
Kim, K. N., Heffernan, N. T., Heffernan, C., Goldman, S. R., Pellegrino, J. W., & Goldstein, D. S. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39112-5_122 · Cited by 35 · see citing works
Olsen, J. K., Rummel, N., & Aleven, V. (2020) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-020-00228-w · Cited by 34 · see citing works
Self-citationAffective Teacher Tools: Affective Class Report Card and Dashboard
Gupta, A., Menon, N., Lee, W., Rebelsky, W., Allessio, D., Murray, T., Woolf, B. P., Whitehill, J., & Arroyo, I. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-78292-4_15 · Cited by 7 · see citing works
A Framework to Guide Educational Technology Studies in the Evolving Classroom Research Environment
Nagashima, T., Yadav, G., & Aleven, V. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-86436-1_16 · Cited by 4 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Human-centred learning analytics and AI in education: A systematic literature review
Alfredo, R., Echeverria, V., Jin, Y., Yan, L., Swiecki, Z., Gašević, D., & Martinez-Maldonado, R. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100215 · Cited by 281 · see citing works
The Future of Artificial Intelligence in Special Education Technology
Marino, M. T., Vasquez, E., Dieker, L., Basham, J., & Blackorby, J. (2023) · Journal of Special Education Technology · doi:10.1177/01626434231165977 · Cited by 142 · see citing works
Mikeladze, T., Meijer, P. C., & Verhoeff, R. P. (2024) · European Journal of Education · doi:10.1111/ejed.12663 · Cited by 136 · see citing works
Chen, R., Lee, V. R., & G Lee, M. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13350-w · Cited by 43 · see citing works
“Others viewed the revolution as a customizable tutoring system; educational technology organizations, like Khan Academy, immediately began work to attempt to develop that (Aleven et al., 2022; Mohamed et al., 2024; Yu & Chauhan, 2024).”
Echeverría, V., Yang, K. B., Lawrence, L., Rummel, N., & Aleven, V. (2023) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2023.3248155 · Cited by 36 · see citing works
Self-citationEmpowering Education Through Teacher-Technology Collaboration
Luo, Z., & Wang, Y. (2024) · Journal of Organizational and End User Computing · doi:10.4018/joeuc.358455 · Cited by 15 · see citing works
Use of Learning Analytics in K–12 Mathematics Education
Rundquist, R., Holmberg, K., Rack, J. P., Mohseni, Z. A., & Masiello, I. (2024) · Journal of Learning Analytics · doi:10.18608/jla.2024.8299 · Cited by 9 · see citing works
Barthakur, A., Marrone, R. L., Esnaashari, S., Kovanović, V., & Dawson, S. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70021 · Cited by 4 · see citing works
A Systematic Review of Studies on Decision-Making Systems for Teaching and Learning in K-12
Barthakur, A., Marrone, R. L., Esnaashari, S., Kovanović, V., & Dawson, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72315-5_4 · Cited by 1 · see citing works
A Basic Toolkit for Instructional Design by AI in Elementary Level Teaching
Türkmen, G., & Özdoğan, S. S. (2025) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-6527-4.ch001 · Cited by 1 · see citing works
Enhancing Teacher Support in Learning Technologies: A Human-Centered Approach with WearableLearning
Poh, A., Shi, Y., Castro, F. E. V., & Arroyo, I. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-99264-3_7 · Cited by 1 · see citing works
Python’s Contribution to Artificial Intelligence in Education: A state-of-the-art review
Papadimitriou, A. (2025) · Journal of Future Artificial Intelligence and Technologies · doi:10.62411/faith.3048-3719-267 · Cited by 1 · see citing works
Essel, D. D. (2026) · Advances in Mobile Learning Educational Research · doi:10.25082/amler.2026.02.003 · Cited by 1 · see citing works
Involving Teachers in the Data-Driven Improvement of Intelligent Tutors: A Prototyping Study
Xia, M., Zhao, X., Sun, D., Huang, Y., Sewall, J., & Aleven, V. A. W. M. M. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-36272-9_28 · Cited by 1 · see citing works
Self-citationOnline and Self-Paced Learning Using AI
(2024) · Advances in higher education and professional development book series · doi:10.4018/979-8-3693-4074-5.ch009 · Cited by 1 · see citing works
Da teoria à prática em sala de aula
Jaques, P. A. (2023) · Tecnologias Sociedade e Conhecimento · doi:10.20396/tsc.v10i2.18382 · Cited by 2 · see citing works
Kragten, M., Hoogma, T., & Bert Bredeweg, A. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72315-5_15
Tracing the Evolution of Autism Mathematics Learning: A Bibliometric Analysis
Ang, P. S., Maat, S. M., & Rosli, R. (2025) · European Journal of Educational Research · doi:10.12973/eu-jer.14.3.961
Understanding Students’ Nuanced Views on AI-Supported Classroom Learning Through Perspective Taking
Nagashima, T., Vincoli, M., Scholz, N., & Su, M. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-98414-3_2
Self-citationBednorz, D., & Neumann, K. (2026) · Educational communications and technology: issues and innovations · doi:10.1007/978-3-032-06823-1_10
Rasheed, Q. U. A. (2026) · Leadership and Policy in Schools · doi:10.1080/15700763.2026.2640592 · Cited by 3 · see citing works
Reconstructing the Role of Pre-Service Teachers in the Age of Artificial Intelligence
Yuan, L., Razak, R. A., Kamsin, A., Chen, L., & Xu, X. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-8027-8.ch006
Thierfelder, B., Spilski, J., Löber, J., Lachmann, T., & Bleistein, T. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29596-5_36
Syam, R. R. (2025) · Asia Conference on Cognitive Engineering and Intelligent Interaction (CEII) · doi:10.1109/ceii67787.2025.00034
Extending Instrumental Orchestration for AI-Mediated Mathematics Classrooms: The AISIO FrameworkPreprint
Kim, H.-J., Trouche, L., & Noh, Y. H. (2026) · Research Square · doi:10.21203/rs.3.rs-11019531/v1
Sun, C., Major, L., Daltry, R., Obradovic, L., & Friedberg, A. (2026) · Educational Technology Research and Development · doi:10.1007/s11423-026-10703-1 · Cited by 1 · see citing works
Dosage and Dialogue: Understanding Human Support in Hybrid Human-AI Math Tutoring
Gao, G., Gurung, A., Thomas, D. R., Kamikazi, M. C. A., Borchers, C., Gatz, E. E., Gupta, S., Fancsali, S. E., RITTER, S., Branstetter, L., et al. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-37979-5_15
Financial Literacy–Generative AI-Powered Learning
Vodenska, I., & Chitkushev, L. T. (2026) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-032-33123-6_9
- Authors
- Aleven, V., Blankestijn, J., Lawrence, L., Nagashima, T., & Taatgen, N.
- Affiliations
- Carnegie Mellon University (US)
- University of Groningen (NL)
- Utah State University (US)
- Corresponding author
- Aleven, Vincent
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2022
- Pages
- 16-30
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W4294768153
- Cited by
- 28
- References
- 22
- Citations by year
- 2026: 9 · 2025: 8 · 2024: 7 · 2023: 4
- FWCI
- 2.63
- Type
- conference paper
- Language
- en
- Open access
- green
- research.rug.nl
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- Digital Commons - USU (Utah State University) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
- Keywords
- teacher dashboards, self-paced learning, real-time analytics, classroom monitoring, junior high school teachers, K-12 education, personalized student support, remote classrooms
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
