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Showing 1 to 15 of 138 results Save | Export
Priti Oli – ProQuest LLC, 2024
This dissertation focuses on strategies and techniques to enhance code comprehension skills among students enrolled in introductory computer science courses (CS1 and CS2). We propose a novel tutoring system, "DeepCodeTutor," designed to improve the code comprehension abilities of novices. DeepCodeTutor employs scaffolded self-explanation…
Descriptors: Reading Comprehension, Tutoring, Scaffolding (Teaching Technique), Automation
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Yousaf, Yousra; Shoaib, Muhammad; Hassan, Muhammad Awais; Habiba, Ume – Interactive Learning Environments, 2023
Learning trend has been shifted from a conventional way to a digital way in the form of E-learning, but it faces a high dropout ratio. Lack of engagement is one of the primary factors reported for this issue as the same type of course content is presented to learners despite their different background, knowledge and learning styles. Different…
Descriptors: Intelligent Tutoring Systems, Cognitive Style, Learner Engagement, Academic Achievement
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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
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Wiegand, R. Paul; Bucci, Anthony; Kumar, Amruth N.; Albert, Jennifer; Gaspar, Alessio – ACM Transactions on Computing Education, 2022
In this article, we leverage ideas from the theory of coevolutionary computation to analyze interactions of students with problems. We introduce the idea of "informatively" easy or hard concepts. Our approach is different from more traditional analyses of problem difficulty such as item analysis in the sense that we consider Pareto…
Descriptors: Concept Formation, Difficulty Level, Computer Science Education, Problem Solving
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Da Teng; Xiangyang Wang; Yanwei Xia; Yue Zhang; Lulu Tang; Qi Chen; Ruobing Zhang; Sujin Xie; Weiyong Yu – Education and Information Technologies, 2025
The swift advancement of artificial intelligence, especially large language models (LLMs), has generated novel prospects for improving educational methodologies. Nonetheless, the successful incorporation of these technologies into pedagogical methods, such as flipped classrooms, continues to pose a challenge. This study investigates the…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Flipped Classroom, Technology Uses in Education
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Xieling Chen; Haoran Xie; S. Joe Qin; Fu Lee Wang; Yinan Hou – European Journal of Education, 2025
Artificial intelligence (AI) is increasingly exploited to promote student engagement. This study combined topic modelling, keyword analysis, trend test and systematic analysis methodologies to analyse AI-supported student engagement (AIsE) studies regarding research keywords and topics, AI roles, AI systems and algorithms, methods and domains,…
Descriptors: Artificial Intelligence, Learner Engagement, Technology Uses in Education, Electronic Learning
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Sirinda Palahan – IEEE Transactions on Learning Technologies, 2025
The rise of online programming education has necessitated more effective personalized interactions, a gap that PythonPal aims to fill through its innovative learning system integrated with a chatbot. This research delves into PythonPal's potential to enhance the online learning experience, especially in contexts with high student-to-teacher ratios…
Descriptors: Programming, Computer Science Education, Artificial Intelligence, Computer Mediated Communication
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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
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Guozhu Ding; Xiangyi Shi; Shan Li – Education and Information Technologies, 2024
In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…
Descriptors: Programming, Computer Science Education, Classification, Graphs
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Vesin, Boban; Mangaroska, Katerina; Akhuseyinoglu, Kamil; Giannakos, Michail – ACM Transactions on Computing Education, 2022
Online learning systems should support students preparedness for professional practice by equipping them with the necessary skills while keeping them engaged and active. In that regard, the development of online learning systems that support students' development and engagement with programming is a challenging process. Early career computer…
Descriptors: Adaptive Testing, Online Courses, Programming, Computer Science Education
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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)
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Almotairi, Maram; Fkih, Fethi – Journal of Education and e-Learning Research, 2022
The Question answering (QA) system plays a basic role in the acquisition of information and the e-learning environment is considered to be the field that is most in need of the question-answering system to help learners ask questions in natural language and get answers in short periods of time. The main problem in this context is how to understand…
Descriptors: Semantics, Natural Language Processing, Intelligent Tutoring Systems, Ambiguity (Semantics)
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Shabrina, Preya; Mostafavi, Behrooz; Tithi, Sutapa Dey; Chi, Min; Barnes, Tiffany – International Educational Data Mining Society, 2023
Problem decomposition into sub-problems or subgoals and recomposition of the solutions to the subgoals into one complete solution is a common strategy to reduce difficulties in structured problem solving. In this study, we use a datadriven graph-mining-based method to decompose historical student solutions of logic-proof problems into Chunks. We…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Graphs, Data Analysis
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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
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Quadir, Benazir; Mostafa, Kazi; Yang, Jie Chi; Shen, Juming; Akter, Rokaya – Education and Information Technologies, 2023
This study used the ARCS approach to investigate the effects of university students' motivation, including attention, relevance, confidence, and satisfaction, to use the Programming Teaching Assistant (PTA) on their Programming Problem-Solving Skills (PPSS). Previous studies have shown that PTA features enhance learners' programming performance,…
Descriptors: Programming Languages, Computer Science Education, Problem Solving, Student Motivation
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