Students' misconceptions and other difficulties in introductory programming: A literature review

Y Qian, J Lehman - ACM Transactions on Computing Education (TOCE), 2017 - dl.acm.org
Efforts to improve computer science education are underway, and teachers of computer
science are challenged in introductory programming courses to help learners develop their …

Text mining in education

R Ferreira‐Mello, M André, A Pinheiro… - … : Data Mining and …, 2019 - Wiley Online Library
The explosive growth of online education environments is generating a massive volume of
data, specially in text format from forums, chats, social networks, assessments, essays …

Learning gain differences between ChatGPT and human tutor generated algebra hints

ZA Pardos, S Bhandari - arXiv preprint arXiv:2302.06871, 2023 - arxiv.org
Large Language Models (LLMs), such as ChatGPT, are quickly advancing AI to the frontiers
of practical consumer use and leading industries to re-evaluate how they allocate resources …

Educational data mining: a review of the state of the art

C Romero, S Ventura - … on Systems, Man, and Cybernetics, Part …, 2010 - ieeexplore.ieee.org
Educational data mining (EDM) is an emerging interdisciplinary research area that deals
with the development of methods to explore data originating in an educational context. EDM …

[HTML][HTML] Data-driven hint generation in vast solution spaces: a self-improving python programming tutor

K Rivers, KR Koedinger - International Journal of Artificial Intelligence in …, 2017 - Springer
To provide personalized help to students who are working on code-writing problems, we
introduce a data-driven tutoring system, ITAP (Intelligent Teaching Assistant for …

Axis: Generating explanations at scale with learnersourcing and machine learning

JJ Williams, J Kim, A Rafferty, S Maldonado… - Proceedings of the third …, 2016 - dl.acm.org
While explanations may help people learn by providing information about why an answer is
correct, many problems on online platforms lack high-quality explanations. This paper …

Big data comes to school: Implications for learning, assessment, and research

B Cope, M Kalantzis - Aera Open, 2016 - journals.sagepub.com
The prospect of “big data” at once evokes optimistic views of an information-rich future and
concerns about surveillance that adversely impacts our personal and private lives. This …

[PDF][PDF] Offline policy evaluation across representations with applications to educational games.

T Mandel, YE Liu, S Levine, E Brunskill… - AAMAS, 2014 - grail.cs.washington.edu
Consider an autonomous teacher agent trying to adaptively sequence material to best keep
a student engaged, or a medical agent trying to help suggest treatments to maximize patient …

Next-term student performance prediction: A recommender systems approach

M Sweeney, H Rangwala, J Lester, A Johri - arXiv preprint arXiv …, 2016 - arxiv.org
An enduring issue in higher education is student retention to successful graduation. National
statistics indicate that most higher education institutions have four-year degree completion …

New potentials for data-driven intelligent tutoring system development and optimization

KR Koedinger, E Brunskill, RSJ Baker, EA McLaughlin… - AI Magazine, 2013 - ojs.aaai.org
Increasing widespread use of educational technologies is producing vast amounts of data.
Such data can be used to help advance our understanding of student learning and enable …