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Molly Domino; Bob Edmison; Stephen H. Edwards; Rifat Sabbir Mansur; Alexandra Thompson; Clifford A. Shaffer – Computer Science Education, 2025
Background and Context: Self-regulated learning (SRL) skills are critical aspect of learning to program and are predictive of academic success. Early college students often struggle to use these skills, but can improve when given targeted instruction. However, it is not yet clear what skills are best to prioritize. Objective: We seek to create a…
Descriptors: Metacognition, Programming, Computer Science Education, College Students
Yoonhee Shin; Jaewon Jung; Seohyun Choi; Bokmoon Jung – Education and Information Technologies, 2025
This study investigates the effects of metacognitive and cognitive strategies for computational thinking (CT) on managing cognitive load and enhancing problem-solving skills in collaborative programming. Four different scaffolding conditions were provided to help learners optimize cognitive load and improve their problem-solving abilities. A total…
Descriptors: Scaffolding (Teaching Technique), Mental Computation, Cognitive Processes, Difficulty Level
Yoonhee Shin; Jaewon Jung; Hyun Ji Lee – Metacognition and Learning, 2024
This study investigated the effects of concept-oriented faded in worked-out examples (WOE) and metacognitive scaffolding on learners' transfer performance and motivation in programming education. Two types of faded in WOE and metacognitive scaffolding were provided. A total of 140 participants were randomly assigned into one of four groups, with…
Descriptors: Metacognition, Concept Formation, Scaffolding (Teaching Technique), Learning Processes
Gamze Türkmen; Sinan Hopcan; Elif Polat – Journal of Learning and Teaching in Digital Age, 2024
This research explores how metacognitive strategies influence the metacognitive awareness of undergraduate students enrolled in an online flipped programming course. It specifically focuses on regulatory actions crucial for success in programming instruction and distance education settings. The primary objective is to contribute to the existing…
Descriptors: Undergraduate Students, Metacognition, Online Courses, Programming
Jhon Jairo Ramírez-Echeverry; Felipe Restrepo-Calle; Stephanie Torres Jiménez – European Journal of Education, 2025
This study investigates the self-regulated learning strategies employed by students in computer programming courses. Utilising the Questionnaire on Learning Strategies in Computer Programming (CEAPC), the research aims to identify specific strategies used by students. The findings reveal a variety of effective learning strategies, including…
Descriptors: Independent Study, Learning Strategies, Programming, Computer Science Education
Chen, Peggy P. – New Directions for Teaching and Learning, 2023
Many introductory computer science (CS) courses are intended to address the increased demand for computer literacy and the development of cross-cutting concepts and practices of computational thinking (CT). Colleges and universities offer introductory CS courses every semester toward this end. The issue is centered on how to support CT learning in…
Descriptors: Introductory Courses, Computer Science Education, Computer Literacy, Thinking Skills
Shin, Yoonhee; Jung, Jaewon; Zumbach, Joerg; Yi, Eunseon – Journal of Educational Computing Research, 2023
This study explores the effects of worked-out examples and metacognitive scaffolding on novice learners' knowledge performance, cognitive loads, and self-regulation skills in problem-solving programming. 126 undergraduate students in a computer programming fundamentals course were randomly assigned to one of four groups: (1) task performance with…
Descriptors: Problem Solving, Metacognition, Scaffolding (Teaching Technique), Programming
Li, Wei; Liu, Cheng-Ye; Tseng, Judy C. R. – Education and Information Technologies, 2023
Collaborative programming can develop computational thinking and knowledge of computational programming. However, the researchers pointed out that because students often fail to mobilize metacognition to regulate and control their cognitive activities in a cooperation, this results in poor learning effects. Especially low-achieving students need…
Descriptors: Correlation, Metacognition, Thinking Skills, Programming
Anna Y. Q. Huang; Cheng-Yan Lin; Sheng-Yi Su; Stephen J. H. Yang – British Journal of Educational Technology, 2025
Programming education often imposes a high cognitive burden on novice programmers, requiring them to master syntax, logic, and problem-solving while simultaneously managing debugging tasks. Prior knowledge is a critical factor influencing programming learning performance. A lack of foundational knowledge limits students' self-regulated learning…
Descriptors: Artificial Intelligence, Technology Uses in Education, Coding, Programming
Gabbay, Hagit; Cohen, Anat – International Educational Data Mining Society, 2023
In MOOCs for programming, Automated Testing and Feedback (ATF) systems are frequently integrated, providing learners with immediate feedback on code assignments. The analysis of the large amounts of trace data collected by these systems may provide insights into learners' patterns of utilizing the automated feedback, which is crucial for the…
Descriptors: MOOCs, Feedback (Response), Teaching Methods, Learning Strategies
Chengliang Wang; Xiaojiao Chen; Yifei Li; Pengju Wang; Haoming Wang; Yuanyuan Li – Journal of Educational Computing Research, 2025
This study explored the impact of MetaClassroom, a virtual immersive programming learning environment designed based on the three-dimensional learning progression (3DLP) concept, on students' multidimensional development. Utilizing a quasi-experimental research design, this study compared students' programming learning achievements (PLA),…
Descriptors: Programming, Computer Science Education, Metacognition, Computer Simulation
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michail – Journal of Computer Assisted Learning, 2022
Background: Problem-solving is a multidimensional and dynamic process that requires and interlinks cognitive, metacognitive, and affective dimensions of learning. However, current approaches practiced in computing education research (CER) are not sufficient to capture information beyond the basic programming process data (i.e., IDE-log data).…
Descriptors: Cognitive Processes, Psychological Patterns, Problem Solving, Programming
The Role of Task Value and Online Learning Strategies in an Introductory Computer Programming Course
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
Ouyang, Fan; Dai, Xinyu; Chen, Si – International Journal of STEM Education, 2022
Background: Instructor scaffolding is proved to be an effective means to improve collaborative learning quality, but empirical research indicates discrepancies about the effect of instructor scaffoldings on collaborative programming. Few studies have used multimodal learning analytics (MMLA) to comprehensively analyze the collaborative programming…
Descriptors: Learning Analytics, Scaffolding (Teaching Technique), Small Group Instruction, Computer Science Education
Lakshminarayanan, Srinivasan; Rao, N. J. – Cogent Education, 2021
CS1 courses are designed in Indian Institutions as a lecture course of three to four credits and one credit lab course. The issues related to curriculum design, instruction design, and students' learning manifest themselves as issues in the lab programs. This situation presents the lab instructor with an opportunity to understand and address the…
Descriptors: Computer Science Education, Teaching Methods, Programming, Programming Languages

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