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Jesper Dannath; Alina Deriyeva; Benjamin Paaßen – International Educational Data Mining Society, 2025
Research on the effectiveness of Intelligent Tutoring Systems (ITSs) suggests that automatic hint generation has the best effect on learning outcomes when hints are provided on the level of intermediate steps. However, ITSs for programming tasks face the challenge to decide on the granularity of steps for feedback, since it is not a priori clear…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Undergraduate Students
Maciej Pankiewicz; Yang Shi; Ryan S. Baker – International Educational Data Mining Society, 2025
Knowledge Tracing (KT) models predicting student performance in intelligent tutoring systems have been successfully deployed in several educational domains. However, their usage in open-ended programming problems poses multiple challenges due to the complexity of the programming code and a complex interplay between syntax and logic requirements…
Descriptors: Algorithms, Artificial Intelligence, Models, Intelligent Tutoring Systems
Milos Ilic; Goran Kekovic; Vladimir Mikic; Katerina Mangaroska; Lazar Kopanja; Boban Vesin – IEEE Transactions on Learning Technologies, 2024
In recent years, there has been an increasing trend of utilizing artificial intelligence (AI) methodologies over traditional statistical methods for predicting student performance in e-learning contexts. Notably, many researchers have adopted AI techniques without conducting a comprehensive investigation into the most appropriate and accurate…
Descriptors: Artificial Intelligence, Academic Achievement, Prediction, Programming
Maximiliano Paredes-Velasco; Isaac Lozano-Osorio; Diana Perez-Marin; Liliana Patricia Santacruz-Valencia – IEEE Transactions on Learning Technologies, 2024
Teaching programming is a topic that has generated a high level of interest among researchers in recent decades. In particular, multiple approaches to teaching visual programming have been explored, from the use of tools such as Scratch, robots, unplugged programming, or activities for the development of computational thinking. Despite the wide…
Descriptors: Visual Aids, Programming, Intelligent Tutoring Systems, Computer Oriented Programs
Sychev, Oleg; Penskoy, Nikita; Anikin, Anton; Denisov, Mikhail; Prokudin, Artem – Education Sciences, 2021
Intelligent tutoring systems have become increasingly common in assisting students but are often aimed at isolated subject-domain tasks without creating a scaffolding system from lower- to higher-level cognitive skills, with low-level skills often neglected. We designed and developed an intelligent tutoring system, CompPrehension, which aims to…
Descriptors: Intelligent Tutoring Systems, Comprehension, Undergraduate Students, Computer Science Education
David Roldan-Alvarez; Francisco J. Mesa – IEEE Transactions on Education, 2024
Artificial intelligence (AI) in programming teaching is something that still has to be explored, since in this area assessment tools that allow grading the students work are the most common ones, but there are not many tools aimed toward providing feedback to the students in the process of creating their program. In this work a small sized…
Descriptors: Intelligent Tutoring Systems, Grading, Artificial Intelligence, Feedback (Response)
Xuanyan Zhong; Zehui Zhan – Interactive Technology and Smart Education, 2025
Purpose: The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners' computational thinking. Design/methodology/approach: By…
Descriptors: Intelligent Tutoring Systems, Computer Science Education, Programming, Independent Study
Caitlin Mills, Editor; Giora Alexandron, Editor; Davide Taibi, Editor; Giosuè Lo Bosco, Editor; Luc Paquette, Editor – International Educational Data Mining Society, 2025
The University of Palermo is proud to host the 18th International Conference on Educational Data Mining (EDM) in Palermo, Italy, from July 20 to July 23, 2025. EDM is the annual flagship conference of the International Educational Data Mining Society. This year's theme is "New Goals, New Measurements, New Incentives to Learn." The theme…
Descriptors: Artificial Intelligence, Data Analysis, Computer Science Education, Technology Uses in Education
Carlos Sandoval-Medina; Carlos Argelio Arévalo-Mercado; Estela Lizbeth Muñoz-Andrade; Jaime Muñoz-Arteaga – Journal of Information Systems Education, 2024
Learning basic programming concepts in computer science-related fields poses a challenge for students, to the extent that it becomes an academic-social problem, resulting in high failure and dropout rates. Proposed solutions to the problem can be found in the literature, such as the development of new programming languages and environments, the…
Descriptors: Cognitive Ability, Computer Science Education, Programming, Instructional Materials
Hongxin Yan; Fuhua Lin; Kinshuk – Canadian Journal of Learning and Technology, 2024
Online higher education provides exceptional flexibility in learning but demands high self-regulated learning skills. The deficiency of self-regulated learning skills in many students highlights the need for support. This study introduces a confidence-based adaptive practicing system as an intelligent assessment and tutoring solution to enhance…
Descriptors: Self Management, Online Courses, Intelligent Tutoring Systems, Technology Uses in Education
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
Xu, Jia; Wei, Tingting; Lv, Pin – International Educational Data Mining Society, 2022
In an Intelligent Tutoring System (ITS), problem (or question) difficulty is one of the most critical parameters, directly impacting problem design, test paper organization, result analysis, and even the fairness guarantee. However, it is very difficult to evaluate the problem difficulty by organized pre-tests or by expertise, because these…
Descriptors: Prediction, Programming, Natural Language Processing, Databases
Priti Oli; Rabin Banjade; Arun Balajiee Lekshmi Narayanan; Peter Brusilovsky; Vasile Rus – Grantee Submission, 2023
Self-efficacy, or the belief in one's ability to accomplish a task or achieve a goal, can significantly influence the effectiveness of various instructional methods to induce learning gains. The importance of self-efficacy is particularly pronounced in complex subjects like Computer Science, where students with high self-efficacy are more likely…
Descriptors: Computer Science Education, College Students, Self Efficacy, Programming
Grubišic, Ani; Žitko, Branko; Stankov, Slavomir – Journal of Technology and Science Education, 2020
In intelligent e-learning systems that adapt a learning and teaching process to student knowledge, it is important to adapt the system as quickly as possible. However, adaptation is not possible until the student model is initialized. In this paper, a new approach to student model initialization using domain knowledge representative subset is…
Descriptors: Electronic Learning, Educational Technology, Models, Intelligent Tutoring Systems
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

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