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Shao-Heng Ko; Kristin Stephens-Martinez – ACM Transactions on Computing Education, 2025
Background: Academic help-seeking benefits students' achievement, but existing literature either studies important factors in students' selection of all help resources via self-reported surveys or studies their help-seeking behavior in one or two separate help resources via actual help-seeking records. Little is known about whether computing…
Descriptors: Computer Science Education, College Students, Help Seeking, Student Behavior
Gao, Zhikai; Erickson, Bradley; Xu, Yiqiao; Lynch, Collin; Heckman, Sarah; Barnes, Tiffany – International Educational Data Mining Society, 2022
In computer science education timely help seeking during large programming projects is essential for student success. Help-seeking in typical courses happens in office hours and through online forums. In this research, we analyze students coding activities and help requests to understand the interaction between these activities. We collected…
Descriptors: Computer Science Education, College Students, Programming, Coding
Karnalim, Oscar; Simon; Chivers, William; Panca, Billy Susanto – ACM Transactions on Computing Education, 2022
To help address programming plagiarism and collusion, students should be informed about acceptable practices and about program similarity, both coincidental and non-coincidental. However, current approaches are usually manual, brief, and delivered well before students are in a situation where they might commit academic misconduct. This article…
Descriptors: Computer Science Education, Programming, Plagiarism, Formative Evaluation
Dan Sun; Chee-Kit Looi; Yan Li; Chengcong Zhu; Caifeng Zhu; Miaoting Cheng – Educational Technology Research and Development, 2024
In the current era where computational literacy holds significant relevance, a growing number of schools across the globe have placed emphasis on K-12 programming education. This field of education primarily comprises two distinct modalities--the block-based programming modality (BPM) and the text-based programming modality (TPM). Previous…
Descriptors: Programming, Student Behavior, Thinking Skills, Computation
Dan Sun; Chengcong Zhu; Fan Xu; Yan Li; Fan Ouyang; Miaoting Cheng – Journal of Educational Computing Research, 2024
Although previous research has provided some insights into the effects of block-based and text-based programming modalities, there is a dearth of a detailed, multi-dimensional analysis of the transition process from different introductory programming modalities to professional programming learning. This study employed a quasi-experimental design…
Descriptors: Programming, Secondary School Students, Computation, Thinking Skills
Yin-Rong Zhang; Zhong-Mei Han; Tao He; Chang-Qin Huang; Fan Jiang; Gang Yang; Xue-Mei Wu – Journal of Computer Assisted Learning, 2025
Background: Collaborative programming is important and challenging for K12 students. Scaffolding is a vital method to support students' collaborative programming learning. However, conventional scaffolding that does not fade may lead students to become overly dependent, resulting in unsatisfactory programming performance. Objectives: This study…
Descriptors: Middle School Students, Grade 8, Scaffolding (Teaching Technique), Programming
Morales-Trujillo, Miguel Ehecatl; Galster, Matthias; Gilson, Fabian; Mathews, Moffat – IEEE Transactions on Education, 2022
Background: Peer evaluation in software engineering (SE) project courses enhances the learning experience of students. It also helps instructors monitor and assess both teams and individual students. Peer evaluations might influence the way individual students and teams work; therefore, the quality of the peer evaluations should be tracked through…
Descriptors: Undergraduate Students, Computer Software, Programming, Peer Evaluation
Hopcan, Sinan; Polat, Elif; Albayrak, Ebru – Journal of Educational Computing Research, 2022
The pair programming approach is used to overcome the difficulties of the programming process in education environments. In this study, the interaction sequences during the paired programming of preservice teachers was investigated. Lag sequential analysis were used to explore students' behavioral patterns in pair programming. The participants of…
Descriptors: Cooperative Learning, Student Behavior, Programming, Computer Science Education
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
Kim, ChanMin; Vasconcelos, Lucas; Belland, Brian R.; Umutlu, Duygu; Gleasman, Cory – International Journal of Educational Technology in Higher Education, 2022
It is critical to teach all learners to program and think through programming. But to do so requires that early childhood teacher candidates learn to teach computer science. This in turn requires novel pedagogy that can both help such teachers learn the needed skills, but also provide a model for their future teaching. In this study, we examined…
Descriptors: Programming, Error Correction, Student Behavior, Early Childhood Teachers
Gabbay, Hagit; Cohen, Anat – International Educational Data Mining Society, 2022
The challenge of learning programming in a MOOC is twofold: acquiring programming skills and learning online, independently. Automated testing and feedback systems, often offered in programming courses, may scaffold MOOC learners by providing immediate feedback and unlimited re-submissions of code assignments. However, research still lacks…
Descriptors: Automation, Feedback (Response), Student Behavior, MOOCs
Qian Fu; Wenjing Tang; Yafeng Zheng; Haotian Ma; Tianlong Zhong – Interactive Learning Environments, 2024
In this study, a predictive model is constructed to analyze learners' performance in programming tasks using data of programming behavioral events and behavioral sequences. First, this study identifies behavioral events from log data and applies lag sequence analysis to extract behavioral sequences that reflect learners' programming strategies.…
Descriptors: Predictor Variables, Psychological Patterns, Programming, Self Management
Yukiko Maruyama – International Association for Development of the Information Society, 2022
The increased focus on computational thinking has led to the acceptance of computer programming as one of the ways of teaching computational thinking. In 2020, Japan introduced programming education in elementary schools. To understand the current situation of parental involvement at the beginning of programming education, this study aimed to know…
Descriptors: Parent Participation, Programming, Computer Science Education, Thinking Skills
Denis Zhidkikh; Ville Heilala; Charlotte Van Petegem; Peter Dawyndt; Miitta Jarvinen; Sami Viitanen; Bram De Wever; Bart Mesuere; Vesa Lappalainen; Lauri Kettunen; Raija Hämäläinen – Journal of Learning Analytics, 2024
Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…
Descriptors: Learning Analytics, Prediction, School Holding Power, Academic Achievement
Kristina Litherland; Anders Kluge – Computer Science Education, 2024
Background and Context: We explore the potential for understanding the processes involved in students' programming based on studying their behaviour and dialogue with each other and "conversations" with their programs. Objective: Our aim is to explore how a perspective of inquiry can be used as a point of departure for insights into how…
Descriptors: Programming, Programming Languages, Secondary School Students, Computer Science Education