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Fu, Qian; Zheng, Yafeng; Zhang, Mengyao; Zheng, Lanqin; Zhou, Junyi; Xie, Bochao – Educational Technology Research and Development, 2023
Providing appropriate feedback is important when learning to program. However, it is still unclear how different feedback strategies affect learning outcomes in programming. This study designed four different two-step programming feedback strategies and explored their impact on novice programmers' academic achievement, learning motivations, and…
Descriptors: Feedback (Response), Academic Achievement, Novices, Programming
Jaewon Jung; Yoonhee Shin; HaeJin Chung; Mik Fanguy – Journal of Computing in Higher Education, 2025
This study investigated the effects of pre-training types on cognitive load, self-efficacy, and problem-solving in computer programming. Pre-training was provided to help learners acquire schemas related to problem-solving strategies. 84 undergraduate students were randomly assigned to one of three groups and each group received three different…
Descriptors: Training, Cognitive Processes, Difficulty Level, Self Efficacy
Menon, Pratibha – Journal of Information Systems Education, 2023
This paper introduces a teaching process to develop students' problem-solving and programming efficacy in an introductory computer programming course. The proposed teaching practice provides step-by-step guidelines on using worked-out examples of code to demonstrate the applications of programming concepts. These coding demonstrations explicitly…
Descriptors: Introductory Courses, Programming, Computer Science Education, Feedback (Response)
Mahatanankoon, Pruthikrai; Wolf, James – Information Systems Education Journal, 2021
Learning a computer programming language is typically one of the basic requirements of being an information technology (IT) major. While other studies previously investigate computer programming self-efficacy and grit, their relationships between "shallow" and "deep" learning (Miller et al., 1996) have not been thoroughly…
Descriptors: Cognitive Processes, Learning Strategies, Introductory Courses, Computer Science Education
Peidi Gu; Zui Cheng; Cheng Miaoting; John Poggio; Yan Dong – Journal of Computer Assisted Learning, 2025
Background: Today, the importance of STEM (Science, Technology, Engineering and Mathematics) education and training is widely recognised and accepted. Computer programming courses have become essential in higher education to nurture students' programming, analysis and computational skills, which are vital for success in all STEM fields and areas.…
Descriptors: Active Learning, Student Projects, Individualized Instruction, Student Motivation
Güler Yavuz Temel; Julia Barenthien; Thore Padubrin – Education and Information Technologies, 2025
The integration of different technologies for formative assessment activities into the classroom is very important for the effectiveness of learning and teaching processes. This study is an experimental study in which the student teachers designed jupyter notebooks as formative assessment activities for specified aims and subject contents. For…
Descriptors: Computer Software, Formative Evaluation, Student Teachers, Student Teacher Attitudes
Pruthikrai Mahatanankoon; James R. Wolf – Journal of Information Systems Education, 2025
Advances in information and communication technologies (ICT) coupled with artificial intelligence have made computer programming skills indispensable for IT majors and for an increasing number of other science, technology, engineering, and mathematics (STEM) disciplines. Like any hands-on skill, mastering computer programming requires dedicated…
Descriptors: Measures (Individuals), Programming, Undergraduate Students, Computer Science Education
Xue Ran; Zhigang Li; Yalin Yang – SAGE Open, 2025
Against the backdrop of the deep integration of chatbots into education, this study, based on Self-Determination Theory (SDT) and the UTAUT model, constructed a model of factors influencing college students' self-directed learning ability in programming. Through a review of existing literature, six key determinants were identified: learning…
Descriptors: Programming, College Students, Independent Study, Artificial Intelligence
Chun-Yen Tsai; Yun-An Chen; Fu-Pei Hsieh; Min-Hsiung Chuang; Chien-Liang Lin – Journal of Educational Computing Research, 2024
In higher education, it is challenging to cultivate non-computer science majors' programming concepts. This study used the GAME model (gamification, assessment, modeling, and enquiry) in a programming education course to enhance undergraduates' self-efficacy and performance of basic programming concepts. There were 83 undergraduates taking part in…
Descriptors: Programming, Undergraduate Students, Self Efficacy, Gamification
Chiu, Po-Sheng; Zhong, Hua-Xu; Lai, Chin-Feng – Innovations in Education and Teaching International, 2023
In recent years, flipping classrooms has become a popular topic of discussion. However, few previous studies have focused on the effect of the flow experience on programming self-efficacy. To address this gap, the present researchers developed a model that included six research hypotheses. The study applied a flipped classroom model to a…
Descriptors: Flipped Classroom, Programming, Self Efficacy, College Students
Lin, Guan-Yu; Liao, Yi-Wen; Su, Zhi-Yuan; Wang, Yu-Min; Wang, Yi-Shun – Education and Information Technologies, 2023
This study attempts to: (a) investigate whether positive and negative emotions mediate the pathways linking self-efficacy for learning programming with effort and persistence in undergraduates' learning Scratch programming combining with a programmable hardware platform (i.e., Arduino), and (b) assess the effect of academic major (i.e.,…
Descriptors: Undergraduate Students, Academic Persistence, Programming, Self Efficacy
Hao-Chiang Koong Lin; Chun-Hsiung Tseng; Nian-Shing Chen – Educational Technology & Society, 2025
In recent years, learning programming has been a challenge for both learners and educators. How to enhance student engagement and learning outcomes has been a significant concern for researchers. This study examines the effects of AI-based pedagogical agents on students' learning experiences in programming courses, focusing on web game development…
Descriptors: Programming, Learner Engagement, Self Efficacy, Artificial Intelligence
Dennis Tay – Journal of Statistics and Data Science Education, 2024
Data analytics and programming skills are increasingly important in the humanities, especially in disciplines like linguistics due to the rapid growth of natural language processing (NLP) technologies. However, attitudes and perceptions of students as novice learners, and the attendant pedagogical implications, remain underexplored. This article…
Descriptors: Data Analysis, Programming, Linguistics, Graduate Students
Wen-shuang Fu; Jia-hua Zhang; Di Zhang; Tian-tian Li; Min Lan; Na-na Liu – Journal of Educational Computing Research, 2025
Cognitive ability is closely associated with the acquisition of programming skills, and enhancing learners' cognitive ability is a crucial factor in improving the efficacy of programming education. Adaptive feedback strategies can provide learners with personalized support based on their learning context, which helps to stimulate their interest…
Descriptors: Feedback (Response), Cognitive Ability, Programming, Computer Science Education
Tianxiao Yang; Jongpil Cheon – Computer Science Education, 2025
Background and context: There were few studies indicating if students' computational thinking (CT) self-efficacy and their CT performance were aligned with each other. Objectives: The study was to investigate if there was a discrepancy between students' CT self-efficacy and their CT performance. Method: Involving 104 non-CS undergraduate students…
Descriptors: Self Efficacy, Computer Science Education, Prediction, Teacher Expectations of Students

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