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Yingbin Zhang; Yafei Ye; Luc Paquette; Yibo Wang; Xiaoyong Hu – Journal of Computer Assisted Learning, 2024
Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an…
Descriptors: Learning Analytics, Learning Processes, Test Reliability, Psychometrics
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Xu, Weiqi; Wu, Yajuan; Ouyang, Fan – International Journal of Educational Technology in Higher Education, 2023
Pair programming (PP), as a mode of collaborative problem solving (CPS) in computer programming education, asks two students work in a pair to co-construct knowledge and solve problems. Considering the complex multimodality of pair programming caused by students' discourses, behaviors, and socio-emotions, it is of critical importance to examine…
Descriptors: Cooperative Learning, Problem Solving, Computer Science Education, Programming
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Ayesha Sohail; Huma Akram – Pedagogical Research, 2025
The ability to properly evaluate one's own academic progress has long been considered a predictor of academic success. However, its distinctive role in the context of computational mathematics remains underexplored. Grounded in social cognitive theory, this study investigates the critical role of self-regulated learning (SRL) strategies in…
Descriptors: Undergraduate Students, Mathematics Education, Mathematics Achievement, Self Evaluation (Individuals)
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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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Paola Iannone; Athina Thoma – International Journal of Mathematical Education in Science and Technology, 2024
Programming is becoming increasingly common in mathematics degrees as it is a desirable skill for new graduates. However, research shows that its use is mostly restricted to computational or modelling tasks. This paper reports a study on students' perceptions of and difficulties with Lean, an interactive theorem prover introduced as part of a…
Descriptors: Programming, Mathematics Instruction, Computer Science Education, Student Attitudes
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Amaya, Edna Johanna Chaparro; Restrepo-Calle, Felipe; Ramírez-Echeverry, Jhon J. – Journal of Information Technology Education: Research, 2023
Aim/Purpose: This article proposes a framework based on a sequential explanatory mixed-methods design in the learning analytics domain to enhance the models used to support the success of the learning process and the learner. The framework consists of three main phases: (1) quantitative data analysis; (2) qualitative data analysis; and (3)…
Descriptors: Learning Analytics, Guidelines, Student Attitudes, Learning Processes
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Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Informatics in Education, 2023
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student…
Descriptors: Prior Learning, Programming, Computer Science Education, Markov Processes
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Yun Huang; Christian Dieter Schunn; Julio Guerra; Peter L. Brusilovsky – ACM Transactions on Computing Education, 2024
Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills--a…
Descriptors: Programming, Computer Science Education, Error Patterns, Classification
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Menon, Pratibha – Information Systems Education Journal, 2022
The autonomy and flexibility that online learning contents provide students in a traditional face-to-face course require them to pick up newer strategies for regulating their learning process. This study focuses on identifying how students' self-reported traits of self-regulated learning may relate to the task value of the learning contents of an…
Descriptors: Learning Strategies, Programming, Computer Science Education, Metacognition
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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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Shi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation
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Malik, Sohail Iqbal; Tawafak, Ragad M.; Shakir, Mohanaad – International Journal of Information and Communication Technology Education, 2021
A teaching approach plays an important role in teaching and learning process of an introductory programming (IP) course. The teaching approach should focus on different programming skills required by novice programmers. In this study, we introduced the teaching and learning approach based on an ADRI (Approach, Deployment, Result, Improvement)…
Descriptors: Computer Science Education, Programming, Teaching Methods, Learning Processes
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Sbaraglia, Marco; Lodi, Michael; Martini, Simone – Informatics in Education, 2021
Introductory programming courses (CS1) are difficult for novices. Inspired by "Problem solving followed by instruction" and "Productive Failure" approaches, we define an original "necessity-driven" learning design. Students are put in an apparently well-known situation, but this time they miss an essential ingredient…
Descriptors: Programming, Introductory Courses, Computer Science Education, Programming Languages
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Umapathy, Karthikeyan; Ritzhaupt, Albert D.; Xu, Zhen – Journal of Educational Computing Research, 2020
The purpose of this research was to examine college students' conceptions of learning computer science and approaches to learning computer science and to examine the relationships among these two important constructs and possible moderating factors. Student data (N = 193) were collected using the conceptions of learning computer science and the…
Descriptors: Computer Science Education, Prior Learning, Learning Motivation, Programming
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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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