CoChat
Sign Up
Cited by 55

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

OATutor: An Open-source Adaptive Tutoring System and Curated Content Library for Learning Sciences Research

Pardos, Zachary A., Tang, Matthew, Anastasopoulos, Ioannis, Sheel, Shreya K., Zhang, Ethan·2023·Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
DOI 10.1145/3544548.3581574
Open this paper in CoChat — free account

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/3544548.3581574

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Show all 6 references

Research works printed but not linked: 47

  1. Vincent Aleven and Kenneth R Koedinger. 2013. Knowledge component (KC) approaches to learner modeling. Design Recommendations for Intelligent Tutoring Systems 1 (2013), 165–182.
  2. 10.1007/11774303_7 · DOI
  3. 10.1007/s40593-015-0089-1 · DOI
  4. John R Anderson, Albert T Corbett, Kenneth R Koedinger, and Ray Pelletier. 1995. Cognitive tutors: Lessons learned. The journal of the learning sciences 4, 2 (1995), 167–207.
  5. Anirudhan Badrinath, Frederic Wang, and Zachary Pardos. 2021. pyBKT: An Accessible Python Library of Bayesian Knowledge Tracing Models. In Proceedings of the 14th International Conference on Educational Data Mining. 468–474.
  6. 10.1016/j.sbspro.2015.01.685 · DOI · Paper page
  7. Sameer Bhatnagar, Amal Zouaq, Michel C Desmarais, and Elizabeth Charles. 2020. Learnersourcing Quality Assessment of Explanations for Peer Instruction. In European Conference on Technology Enhanced Learning. Springer, 144–157.
  8. Paul De Bra, David Smits, Kees van der Sluijs, Alexandra I Cristea, Jonathan Foss, Christian Glahn, and Christina M Steiner. 2013. GRAPPLE: Learning management systems meet adaptive learning environments. In Intelligent and adaptive educational-learning systems. Springer, 133–160.
  9. Hao Cen, Kenneth R Koedinger, and Brian Junker. 2007. Is Over Practice Necessary?-Improving Learning Efficiency with the Cognitive Tutor through Educational Data Mining.Frontiers in artificial intelligence and applications 158 (2007), 511.
  10. 10.1007/978-3-030-52240-7_13 · DOI · Paper page
  11. 10.1145/332040.332412 · DOI
  12. Albert T Corbett and John R Anderson. 1994. Knowledge tracing: Modeling the acquisition of procedural knowledge. User modeling and user-adapted interaction 4, 4 (1994), 253–278.
  13. 10.1007/s10459-009-9162-6 · DOI
  14. 10.1177/0165551512437638 · DOI
  15. Mingyu Feng, Neil Heffernan, and Joseph E Beck. 2009. Using learning decomposition to analyze instructional effectiveness in the ASSISTment system. In Proceedings of the 14th International Conference Artificial Intelligence in Education. IOS Press, 523–530.
  16. 10.3102/0091732X20903304 · DOI
  17. Ilya M Goldin, Kenneth R Koedinger, and Vincent Aleven. 2012. Learner Differences in Hint Processing. In Proceedings of the 5th International Conference on Educational Data Mining. ERIC, 73–80.
  18. Cristina Heffernan, Neil Heffernan, Ashish Maharjan, Leena Razzaq, Prawal Shrestha, and Xing Wei. 2009. Are Worked Examples an Effective Feedback Mechanism During Problem Solving?. In Proceedings of the 31st Annual Meeting of the Cognitive Science Society. 1294–1299.
  19. Bryan Hobbs. 2013. Improving Educational Content–A Web-based Intelligent Tutoring System with Support for Teacher Collaboration. Ph. D. Dissertation. Worcester Polytechnic Institute.
  20. 10.1007/978-1-4939-0378-8_4 · DOI
  21. Sally Johnstone. 2005. Forum on the Impact of Open Courseware for Higher Education in Developing Countries–Final Report. Education Quarterly 3(2005), 15–18.
  22. David Kabugo. 2020. Utilizing Open Education Resources to Enhance Students’ Learning Outcomes during the COVID-19 Schools Lockdown: A Case of Using Kolibri by Selected Government Schools in Uganda.Journal of Learning for Development 7, 3 (2020), 447–458.
  23. Juho Kim. 2015. Learnersourcing: improving learning with collective learner activity. Ph. D. Dissertation. Massachusetts Institute of Technology.
  24. Ryung S Kim, Rob Weitz, Neil T Heffernan, and Nathan Krach. 2009. Tutored problem solving vs.“pure” worked examples. In Proceedings of the 31st Annual Meeting of the Cognitive Science Society. 3121–3126.
  25. 10.1145/1357054.1357127 · DOI
  26. Kenneth R Koedinger, Albert T Corbett, and Charles Perfetti. 2012. The Knowledge-Learning-Instruction framework: Bridging the science-practice chasm to enhance robust student learning. Cognitive science 36, 5 (2012), 757–798.
  27. Kenneth R Koedinger, Ryan SJ d Baker, Kyle Cunningham, Alida Skogsholm, Brett Leber, and John Stamper. 2010. A Data Repository for the EDM Community: The PSLC DataShop. In Handbook of Educational Data Mining. CRC Press, 65–78.
  28. Timothy Shin Heng Mak and Albert Lam. 2022. Two-Stage Auction Mechanism for Long-Term Participation in Crowdsourcing. arXiv preprint arXiv:2202.10064(2022). · arXiv
  29. 10.1145/1868358.1868363 · DOI
  30. 10.5555/1734243.1734246 · DOI
  31. Andrew McGregor Olney. 2009. GnuTutor: An open source intelligent tutoring system based on AutoTutor. In 2009 AAAI Fall Symposium Series.
  32. 10.1145/2702123.2702580 · DOI
  33. 10.1007/s10758-015-9268-2 · DOI
  34. 10.1145/3386527.3405912 · DOI
  35. 10.19173/irrodl.v16i4.2381 · DOI
  36. Darrell Porcello and Sherry Hsi. 2013. Crowdsourcing and curating online education resources. Science 341, 6143 (2013), 240–241.
  37. 10.1145/3430895.3460130 · DOI
  38. 10.1007/11774303_63 · DOI
  39. 10.1109/TLT.2009.23 · DOI
  40. Steven Ritter, Thomas K Harris, Tristan Nixon, Daniel Dickison, R Charles Murray, and Brendon Towle. 2009. Reducing the Knowledge Tracing Space.. In Proceedings of the 2nd International Conference on Educational Data Mining. 151–160.
  41. 10.1145/3491140.3528277 · DOI
  42. 10.18608/jla.2016.32.16 · DOI
  43. Robert G. Taylor, A. Smith, Samuel P. Leeman-Munk, Bradford W. Mott, and James C. Lester. 2014. Towards ITS Authoring Tools for Domain Experts. In IntelliMedia Group.
  44. 10.1111/ejed.12019 · DOI
  45. Terrence E Turner, Michael A Macasek, Goss Nuzzo-Jones, Neil T Heffernan, and Kenneth R Koedinger. 2005. The Assistment Builder: A Rapid Development Tool for ITS.. In Proceedings of the 12th International Conference on Artificial Intelligence in Education. 929–931.
  46. Daniel Weitekamp Erik Harpstead and Ken R. Koedinger. 2020. An Interaction Design for Machine Teaching to Develop AI Tutors. ACM 1–11. https://doi.org/10.1145/3313831.3376226 · DOI
  47. 10.1145/1240624.1240704 · DOI

Cited by

Sorted by citations

See all 55

Metadata

Authors
Pardos, Z. A., Tang, M., Anastasopoulos, I., Sheel, S. K., & Zhang, E.
Venue
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2023-04-19
Pages
1-17
DOI
10.1145/3544548.3581574
Cited by
55
References
6
Licence
creativecommons.org/licenses/by-nc-nd/4.0/ (vor)

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