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Ronit Shmallo; Adi Katz – Computer Science Education, 2024
Background and Context: Gender research shows that women are better at reading comprehension. Other studies indicate a lower tendency in women to choose STEM professions. Since data modeling requires reading skills and also belongs in the areas of information systems and computer science (STEM professions), these findings provoked our curiosity.…
Descriptors: Gender Differences, Transfer of Training, Databases, Models
Hao, Xiaoxin; Xu, Zhiyi; Guo, Mingyue; Hu, Yuzheng; Geng, Fengji – International Journal of STEM Education, 2023
Background: Coding has become an integral part of STEM education. However, novice learners face difficulties in processing codes within embedded structures (also termed nested structures). This study aimed to investigate the cognitive mechanism underlying the processing of embedded coding structures based on hierarchical complexity theory, which…
Descriptors: Cognitive Processes, Difficulty Level, Programming, Computer Science Education
Miedema, Daphne; Fletcher, George; Aivaloglou, Efthimia – ACM Transactions on Computing Education, 2023
Prior studies in the Computer Science education literature have illustrated that novices make many mistakes in composing SQL queries. Query formulation proves to be difficult for students. Only recently, some headway was made towards understanding why SQL leads to so many mistakes, by uncovering student misconceptions. In this article, we shed new…
Descriptors: Computer Science Education, Novices, Misconceptions, Programming Languages
Coto, Mayela; Mora, Sonia; Grass, Beatriz; Murillo-Morera, Juan – Computer Science Education, 2022
Background and context: Emotions are ubiquitous in academic settings and affect learning strategies, motivation to persevere, and academic outcomes, however they have not figured prominently in research on learning to program at the university level. Objective: To summarize the current knowledge available on the effect of emotions on students…
Descriptors: Programming, Computer Science Education, Psychological Patterns, Emotional Response
Heinsen Egan, Matthew; McDonald, Chris – Computer Science Education, 2021
Background and Context: Students learning the C programming language struggle to debug, and to understand the runtime behaviour of, their programs. Objective: We examine a tool that combines several novice-focused error detection, program visualization, and debugging techniques, to investigate which features students use in real study sessions,…
Descriptors: Computer Science Education, Programming Languages, Programming, Novices
Zhizezhang Gao; Haochen Yan; Jiaqi Liu; Xiao Zhang; Yuxiang Lin; Yingzhi Zhang; Xia Sun; Jun Feng – International Journal of STEM Education, 2025
Background: With the increasing interdisciplinarity between computer science (CS) and other fields, a growing number of non-CS students are embracing programming. However, there is a gap in research concerning differences in programming learning between CS and non-CS students. Previous studies predominantly relied on outcome-based assessments,…
Descriptors: Computer Science Education, Mathematics Education, Novices, Programming
Tsabari, Stav; Segal, Avi; Gal, Kobi – International Educational Data Mining Society, 2023
Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…
Descriptors: College Students, Computer Science Education, Programming, Error Patterns
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
Iqbal Malik, Sohail; Mathew, Roy; Tawafak, Ragad M.; Alfarsi, Ghaliya – E-Learning and Digital Media, 2021
Algorithmic thinking is considered as one of the important steps toward learning to code for novices in programming education. In this study, algorithmic thinking was promoted by introducing a Problem Analysis Algorithmic Model (PAAM) in an Algorithms and Programming 1 (AP) course. A web-based application is developed to offer the PAAM model in…
Descriptors: Web Based Instruction, Models, Computer Science Education, Programming
Rashkovits, Rami; Lavy, Ilana – Journal of Information Technology Education: Innovations in Practice, 2020
Aim/Purpose: Multi-threaded software design is considered to be difficult, especially to novice programmers. In this study, we explored how students cope with a task that its solution requires a multi-threaded architecture to achieve optimal runtime. Background: An efficient exploit of multicore processors architecture requires computer programs…
Descriptors: Computer Software, Novices, Programming, Difficulty Level
Turkmen, Gamze; Caner, Sonay – Turkish Online Journal of Distance Education, 2020
This study aims to provide a comprehensive and in-depth investigation of the debugging process in programming teaching in terms of cognitive and metacognitive aspects, based on programming students who demonstrate low, medium, and high programming performance and to propose instructional strategies for scaffolding novice learners in an effective…
Descriptors: Programming, Novices, Electronic Learning, Troubleshooting
Flores, Rejeenald M.; Rodrigo, Ma. Mercedes T. – Journal of Educational Computing Research, 2020
Wheel-spinning refers to the failure to master a skill in a timely manner or after a considerable number of practice opportunities. Several past studies have developed wheel-spinning models in the areas of Mathematics and Physics. However, no models have been made for the context of novice programming. The purpose of this study was to develop…
Descriptors: Mastery Learning, Novices, Programming, Computer Science Education
Wu, Bian; Hu, Yiling; Ruis, A. R.; Wang, Minhong – Journal of Computer Assisted Learning, 2019
Computational thinking (CT), the ability to devise computational solutions for real-life problems, has received growing attention from both educators and researchers. To better improve university students' CT competence, collaborative programming is regarded as an effective learning approach. However, how novice programmers develop CT competence…
Descriptors: Thinking Skills, Problem Solving, Teaching Methods, College Students
Mathew, Roy; Malik, Sohail Iqbal; Tawafak, Ragad Moufaq – Informatics in Education, 2019
Problem solving skills are considered an important component in learning to program in an introductory programming (IP) course for novices. This study introduced a PROSOLVE game to enhance problem solving skills of novice programmers in the introductory programming course. The game is based on pseudo-code technique. A survey was employed to…
Descriptors: Problem Solving, Skill Development, Educational Games, Game Based Learning
Mao, Ye; Zhi, Rui; Khoshnevisan, Farzaneh; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2019
Early prediction of student difficulty during long-duration learning activities allows a tutoring system to intervene by providing needed support, such as a hint, or by alerting an instructor. To be effective, these predictions must come early and be highly accurate, but such predictions are difficult for open-ended programming problems. In this…
Descriptors: Difficulty Level, Learning Activities, Prediction, Programming
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