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Troussas, Christos; Krouska, Akrivi; Sgouropoulou, Cleo – IEEE Transactions on Education, 2021
Contribution: This article presents the instruction of computer programming using adaptive learning activities considering students' cognitive skills based on the learning theory of the Revised Bloom Taxonomy (RBT). To achieve this, the system converts students' knowledge level to fuzzy weights, and using rule-based decision making, delivers…
Descriptors: Undergraduate Students, Intelligent Tutoring Systems, Computer Science Education, Programming
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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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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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Elvina, Elvina; Karnalim, Oscar; Ayub, Mewati; Wijanto, Maresha Caroline – Journal of Technology and Science Education, 2018
Numerous Program Visualization tools (PVs) have been developed for assisting novice students to understand their source code further. However, none of them are practical to be used in the context of completing programming laboratory task; students are required to keep switching between PV and programming workspace since PV's features are…
Descriptors: Visualization, Programming, Computer Science Education, Intelligent Tutoring Systems
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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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Tahir, Faiza; Mitrovic, Antonija; Sotardi, Valerie – Research and Practice in Technology Enhanced Learning, 2022
The practice of adding game elements to non-gaming educational environments has gained much popularity. Gamification has been shown in some studies to enhance engagement, motivation and learning outcomes in technology-supported learning environments. Although gamification research has matured, there are some shortcomings such as inconsistency in…
Descriptors: Recognition (Achievement), Credentials, Outcomes of Education, Programming Languages
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Kumar, Amruth N. – International Educational Data Mining Society, 2023
Is there a pattern in how students solve Parsons puzzles? Is there a difference between the puzzle-solving strategies of C++ and Java students? We used Markov transition matrix to answer these questions. We analyzed the solutions of introductory programming students solving Parsons puzzles involving if-else statements and while loops in C++ and…
Descriptors: Markov Processes, Puzzles, Introductory Courses, Computer Science Education
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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
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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
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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
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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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Dawar, Deepak – Information Systems Education Journal, 2022
Learning computer programming is a challenging task for most beginners. Demotivation and learned helplessness are pretty common. A novel instructional technique that leverages the value-expectancy motivational model of student learning was conceptualized by the author to counter the lack of motivation in the introductory class. The result was a…
Descriptors: Teaching Methods, Introductory Courses, Computer Science Education, Assignments
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Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology
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Conejo, Ricardo; Barros, Beatriz; Bertoa, Manuel F. – IEEE Transactions on Learning Technologies, 2019
This paper presents an innovative method to tackle the automatic evaluation of programming assignments with an approach based on well-founded assessment theories (Classical Test Theory (CTT) and Item Response Theory (IRT)) instead of heuristic assessment as in other systems. CTT and/or IRT are used to grade the results of different items of…
Descriptors: Computer Assisted Testing, Grading, Programming, Item Response Theory
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Price, Thomas W.; Dong, Yihuan; Barnes, Tiffany – International Educational Data Mining Society, 2016
Intelligent Tutoring Systems (ITSs) have shown success in the domain of programming, in part by providing customized hints and feedback to students. However, many popular novice programming environments still lack these intelligent features. This is due in part to their use of open-ended programming assignments, which are difficult to support with…
Descriptors: Intelligent Tutoring Systems, Programming, Data, Computer Science Education
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