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Phung, Tung; Cambronero, José; Gulwani, Sumit; Kohn, Tobias; Majumdarm, Rupak; Singla, Adish; Soares, Gustavo – International Educational Data Mining Society, 2023
Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for fixing syntax errors in Python programs, a key scenario in introductory programming. More concretely, given a student's buggy program, our goal is…
Descriptors: Computational Linguistics, Feedback (Response), Programming, Computer Science Education
Badrinath, Anirudhan; Wang, Frederic; Pardos, Zachary – International Educational Data Mining Society, 2021
Bayesian Knowledge Tracing, a model used for cognitive mastery estimation, has been a hallmark of adaptive learning research and an integral component of deployed intelligent tutoring systems (ITS). In this paper, we provide a brief history of knowledge tracing model research and introduce pyBKT, an accessible and computationally efficient library…
Descriptors: Models, Markov Processes, Mathematics, Intelligent Tutoring Systems
Vassoyan, Jean; Vie, Jill-Jênn – International Educational Data Mining Society, 2023
Adaptive learning is an area of educational technology that consists in delivering personalized learning experiences to address the unique needs of each learner. An important subfield of adaptive learning is learning path personalization: it aims at designing systems that recommend sequences of educational activities to maximize students' learning…
Descriptors: Reinforcement, Networks, Simulation, Educational Technology
Chrysafiadi, Konstantina; Virvou, Maria; Tsihrintzis, George A.; Hatzilygeroudis, Ioannis – Education and Information Technologies, 2023
Nowadays, the improvement of digital learning with Artificial Intelligence has attracted a lot of research, as it provides solutions for individualized education styles which are independent of place and time. This is particularly the case for computer science, as a tutoring domain, which is rapidly growing and changing and as such, learners need…
Descriptors: Foreign Countries, Undergraduate Students, Computer Science Education, Programming
Silvia García-Méndez; Francisco de Arriba-Pérez; Francisco J. González-Castaño – International Association for Development of the Information Society, 2023
Mobile learning or mLearning has become an essential tool in many fields in this digital era, among the ones educational training deserves special attention, that is, applied to both basic and higher education towards active, flexible, effective high-quality and continuous learning. However, despite the advances in Natural Language Processing…
Descriptors: Higher Education, Artificial Intelligence, Computer Software, Usability
Peiris, K. Dharini Amitha; Gallupe, R. Brent – Decision Sciences Journal of Innovative Education, 2018
Recommender-driven online learning systems (ROLS) are at the forefront of new computer-based learning. They incorporate machine learning to allow learning-by-doing, generating personalized recommendations in the process. This article describes the evaluations of a new type of online learning systems, ROLS. This evaluation was carried out in three…
Descriptors: Intelligent Tutoring Systems, Computer Science Education, Programming Languages, Conventional Instruction
Loksa, Dastyni; Margulieux, Lauren; Becker, Brett A.; Craig, Michelle; Denny, Paul; Pettit, Raymond; Prather, James – ACM Transactions on Computing Education, 2022
Metacognition and self-regulation are important skills for successful learning and have been discussed and researched extensively in the general education literature for several decades. More recently, there has been growing interest in understanding how metacognitive and self-regulatory skills contribute to student success in the context of…
Descriptors: Metacognition, Programming, Computer Science Education, Learning Processes
Weragama, Dinesha; Reye, Jim – International Journal of Artificial Intelligence in Education, 2014
Programming is a subject that many beginning students find difficult. The PHP Intelligent Tutoring System (PHP ITS) has been designed with the aim of making it easier for novices to learn the PHP language in order to develop dynamic web pages. Programming requires practice. This makes it necessary to include practical exercises in any ITS that…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Programming Languages
Rinderknecht, Christian – Informatics in Education, 2014
We survey the literature about the teaching and learning of recursive programming. After a short history of the advent of recursion in programming languages and its adoption by programmers, we present curricular approaches to recursion, including a review of textbooks and some programming methodology, as well as the functional and imperative…
Descriptors: Teaching Methods, Learning Processes, Visualization, Animation
Murray, Tom – International Journal of Artificial Intelligence in Education, 2016
Intelligent Tutoring Systems authoring tools are highly complex educational software applications used to produce highly complex software applications (i.e. ITSs). How should our assumptions about the target users (authors) impact the design of authoring tools? In this article I first reflect on the factors leading to my original 1999 article on…
Descriptors: Usability, Programming, Computer Software, Intelligent Tutoring Systems
O'Donnell, Eileen; Lawless, Séamus; Sharp, Mary; Wade, Vincent P. – International Journal of Distance Education Technologies, 2015
The realisation of personalised e-learning to suit an individual learner's diverse learning needs is a concept which has been explored for decades, at great expense, but is still not achievable by non-technical authors. This research reviews the area of personalised e-learning and notes some of the technological challenges which developers may…
Descriptors: Electronic Learning, Individualized Instruction, Programming, Authors
Sudol, Leigh Ann; Rivers, Kelly; Harris, Thomas K. – International Educational Data Mining Society, 2012
In complex problem solving domains, correct solutions are often comprised of a combination of individual components. Students usually go through several attempts, each attempt reflecting an individual solution state that can be observed during practice. Classic metrics to measure student performance over time rely on counting the number of…
Descriptors: Problem Solving, Tutors, Feedback (Response), Probability
Di Bitonto, Pierpaolo; Roselli, Teresa; Rossano, Veronica; Sinatra, Maria – International Journal of Distance Education Technologies, 2013
One of the most closely investigated topics in e-learning research has always been the effectiveness of adaptive learning environments. The technological evolutions that have dramatically changed the educational world in the last six decades have allowed ever more advanced and smarter solutions to be proposed. The focus of this paper is to depict…
Descriptors: Educational Technology, Technology Uses in Education, Computer Assisted Instruction, Artificial Intelligence
Hsiao, I.-H.; Sosnovsky, S.; Brusilovsky, P. – Journal of Computer Assisted Learning, 2010
Rapid growth of the volume of interactive questions available to the students of modern E-Learning courses placed the problem of personalized guidance on the agenda of E-Learning researchers. Without proper guidance, students frequently select too simple or too complicated problems and ended either bored or discouraged. This paper explores a…
Descriptors: Electronic Learning, Guidance, Individualized Instruction, Computer Software
Benjamin D. Nye; Arthur C. Graesser; Xiangen Hu – Grantee Submission, 2014
AutoTutor is a natural language tutoring system that has produced learning gains across multiple domains (e.g., computer literacy, physics, critical thinking). In this paper, we review the development, key research findings, and systems that have evolved from AutoTutor. First, the rationale for developing AutoTutor is outlined and the advantages…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Computer Software, Artificial Intelligence