NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing 1 to 15 of 41 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Peng Chen; Dong Yang; Jia Zhao; Shu Yang; Jari Lavonen – Journal of Computer Assisted Learning, 2025
Background: Computational thinking (CT) refers to the ability to represent problems, design solutions and migrate solutions computationally. While previous studies have shown that self-explanation can enhance students' learning, few empirical studies have examined the effects of using different self-explanation prompts to cultivate students' CT…
Descriptors: Computation, Thinking Skills, Programming, Learning Processes
Peer reviewed Peer reviewed
Direct linkDirect link
Feng Hsu Wang – IEEE Transactions on Learning Technologies, 2024
Due to the development of deep learning technology, its application in education has received increasing attention from researchers. Intelligent agents based on deep learning technology can perform higher order intellectual tasks than ever. However, the high deployment cost of deep learning models has hindered their widespread application in…
Descriptors: Learning Processes, Models, Man Machine Systems, Cooperative Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Pavlos Toukiloglou; Stelios Xinogalos – Education and Information Technologies, 2024
Hour of Code is a widely recognized global event that aims to introduce programming to novice users and integrate computer science into education. This paper presents an analysis of the effectiveness of the support system and user interface of Minecraft Adventurer, a serious game designed for the Hour of Code global event. Although previous…
Descriptors: Novices, Programming, Coding, Computer Science Education
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Robin Samuelsson – British Journal of Educational Technology, 2025
Programming is becoming a key subject in early education globally, with surging problems of how computer science can become a subject for children of all ages and backgrounds. Problems of implementing new technologies in the old curricula have long been noted, and lately, concern over computer science education goals is often too narrow and…
Descriptors: Computer Science Education, Play, Early Childhood Education, Technology Integration
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Leonardo Silva; António Mendes; Anabela Gomes; Gabriel Fortes – ACM Transactions on Computing Education, 2024
Self-regulation of learning (SRL) is an essential ability for academic success in multiple educational contexts, including programming education. However, understanding how students regulate themselves during programming learning is still limited. This exploratory research aimed to investigate the regulatory strategies externalized by 51 students…
Descriptors: Learning Strategies, Programming, Self Management, Introductory Courses
Peer reviewed Peer reviewed
Direct linkDirect link
Linjing Wu; Xuelin Xiang; Xueyan Yang; Xuan Jin; Liang Chen; Qingtang Liu – Educational Technology Research and Development, 2025
Problem-solving strategies are crucial in learning programming. Owing to their hidden nature, traditional methods such as interviews and questionnaires cannot reflect the details and differences of problem-solving strategies in programming. This study uses the Hidden Markov Model to detect and compare the problem-solving strategies of different…
Descriptors: Markov Processes, Problem Solving, Programming, Identification
Peer reviewed Peer reviewed
Direct linkDirect link
Hui-Zhi Hu; Li-Guo Zhang; Jia-Hua Zhang; Di Zhang; Jia-Rui Xie – Education and Information Technologies, 2025
Computer Science (CS) is a vital subject in K-12 education, and acquiring proficiency in CS is essential for nurturing talent. However, current teaching practices often rely on standardized tests to evaluate academic performance, which may not offer a comprehensive and multidimensional assessment of students' competency in learning CS.…
Descriptors: Evaluation Methods, Student Evaluation, Competence, Computer Literacy
Peer reviewed Peer reviewed
Direct linkDirect link
Yu-Sheng Su; Shuwen Wang; Xiaohong Liu – Journal of Educational Computing Research, 2024
Pair programming (PP) can help improve students' computational thinking (CT), but the trajectory of CT skills and the differences between high-scoring and low-scoring students in PP are unknown and need further exploration. In this study, a total of 32 fifth graders worked on Scratch tasks in 16 pairs. The group discourse of three learning topics…
Descriptors: Epistemology, Network Analysis, Elementary School Students, Computation
Peer reviewed Peer reviewed
Direct linkDirect link
Allison S. Theobold; Megan H. Wickstrom; Stacey A. Hancock – Journal of Statistics and Data Science Education, 2024
Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…
Descriptors: Computer Science Education, Coding, Data Science, Statistics Education
Peer reviewed Peer reviewed
Direct linkDirect link
Abdullahi Yusuf; Norah Md Noor; Shamsudeen Bello – Education and Information Technologies, 2024
Studies examining students' learning behavior predominantly employed rich video data as their main source of information due to the limited knowledge of computer vision and deep learning algorithms. However, one of the challenges faced during such observation is the strenuous task of coding large amounts of video data through repeated viewings. In…
Descriptors: Learning Analytics, Student Behavior, Video Technology, Classification
Peer reviewed Peer reviewed
Direct linkDirect link
Zachary M. Savelson; Kasia Muldner – Computer Science Education, 2024
Background and Context: Productive failure (PF) is a learning paradigm that flips the order of instruction: students work on a problem, then receive a lesson. PF increases learning, but less is known about student emotions and collaboration during PF, particularly in a computer science context. Objective: To provide insight on students' emotions…
Descriptors: Student Attitudes, Psychological Patterns, Fear, Failure
Peer reviewed Peer reviewed
Direct linkDirect link
Ünal Çakiroglu; Seval Bilgi – Interactive Learning Environments, 2024
The aim of this explanatory study is to identify the causes of intrinsic cognitive load in programming process. For this purpose, a method based on two dimensions; programming knowledge types (syntactic, semantic, and strategic) and programming constructs was proposed. The proposed method was tested with high school students enrolled in Computer…
Descriptors: Cognitive Processes, Difficulty Level, Programming, Interaction
Peer reviewed Peer reviewed
Direct linkDirect link
Zhaojun Duo; Jianan Zhang; Yonggong Ren; Xiaolu Xu – Education and Information Technologies, 2025
"Self-regulated learning" (SRL) significantly impacts the process and outcome of "programming problem-solving." Studies on SRL behavioural patterns of programming students based on trace data are limited in number and lack of coverage. In this study, hence, the Hidden Markov Model (HMM) was employed to probabilistically mine…
Descriptors: Students, Programming, Problem Solving, Self Management
Previous Page | Next Page »
Pages: 1  |  2  |  3