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Icy Zhang; Yunqi Jia; Xiaoxuan Cheng; Ji Y. Son; James W. Stigler – Journal of Educational Computing Research, 2025
Although programming is often learned through formal instruction or self-paced tutorials, informal learning, for example, through publicly available online documentation, is also a significant resource for skill development among novices. However, many novices struggle to extract useful information from documentation. This work aims to answer two…
Descriptors: Programming, Novices, Informal Education, Documentation
Camilo Vieira; Andrea Vásquez; Federico Meza; Roxana Quintero-Manes; Pedro Godoy – ACM Transactions on Computing Education, 2024
Currently, there is little evidence about how non-English-speaking students learn computer programming. For example, there are few validated assessment instruments to measure the development of programming skills, especially for the Spanish-speaking population. Having valid assessment instruments is essential to identify the difficulties of the…
Descriptors: Programming, Spanish Speaking, Translation, Test Validity
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
Toukiloglou, Pavlos; Xinogalos, Stelios – Journal of Educational Computing Research, 2023
Serious games are a growing field in academic research and they are considered an effective tool for education. Game-based learning invokes motivation and engagement in students resulting in effective instructional outcomes. An essential aspect of a serious game is the method of support for presenting the teaching material and providing feedback.…
Descriptors: Educational Games, Programming, Sequential Learning, Cognitive Processes
Sigal Levy; Yelena Stukalin; Nili Guttmann-Beck – Teaching Statistics: An International Journal for Teachers, 2024
Probability theory has extensive applications across various domains, such as statistics, computer science, and finance. In probability education, students are introduced to fundamental principles which may include mathematical topics such as combinatorics and symmetric sample spaces. Students pursuing degrees in computer science possess a robust…
Descriptors: Programming, Probability, Mathematics Skills, Computer Science Education
Renske Weeda; Sjaak Smetsers; Erik Barendsen – Computer Science Education, 2024
Background and Context: Multiple studies report that experienced instructors lack consensus on the difficulty of programming tasks for novices. However, adequately gauging task difficulty is needed for alignment: to select and structure tasks in order to assess what students can and cannot do. Objective: The aim of this study was to examine…
Descriptors: Novices, Coding, Programming, Computer Science Education
Pelánek, Radek; Effenberger, Tomáš – Computer Science Education, 2022
Background and Context: Block-based programming is a popular approach to teaching introductory programming. Block-based programming often works in the context of microworlds, where students solve specific puzzles. It is used, for example, within the Hour of Code event, which targets millions of students. Objective: To identify design guidelines…
Descriptors: Programming, Computer Science Education, Puzzles, Problem Solving
Moresi, Marco; Gomez, Marcos J.; Benotti, Luciana – IEEE Transactions on Learning Technologies, 2021
Based on hundreds of thousands of hours of data about how students learn in massive open online courses, educational machine learning promises to help students who are learning to code. However, in most classrooms, students and assignments do not have enough historical data for feeding these data hungry algorithms. Previous work on predicting…
Descriptors: Prediction, Difficulty Level, Programming, Online Courses
Arthur William Fodouop Kouam – Discover Education, 2024
This study investigates the effectiveness of Intelligent Tutoring Systems (ITS) in supporting students with varying levels of programming experience. Through a mixed-methods research design, the study explores the impact of ITS on student performance, adaptability to different skill levels, and best practices for utilizing ITS in heterogeneous…
Descriptors: Intelligent Tutoring Systems, Instructional Effectiveness, Programming, Skill Development
Liu, Cheng-Ye; Li, Wei; Huang, Ji-Yi; Lei, Lu-Yuan; Zhang, Pei-Rou – Journal of Computer Assisted Learning, 2023
Background: Socially shared regulation is a vital factor that affects students' collaborative programming performance. However, students' weak group metacognitive skills or inability to adopt shared regulation mechanisms lead to unsatisfactory collaborative programming learning. Objectives: This study proposes an approach to support socially…
Descriptors: Cooperative Learning, Programming, Academic Achievement, Metacognition
Moon, Hyunchang; Cheon, Jongphil; Kwon, Kyungbin – International Journal of Computer Science Education in Schools, 2022
To help novice learners overcome the obstacles of learning computational thinking (CT) through programming, it is vital to identify difficult CT components. This study aimed to determine the computational concepts and practices that learners may have difficulties acquiring and discuss how programming instructions should be designed to facilitate…
Descriptors: Difficulty Level, Computation, Thinking Skills, Programming
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
Saso Koceski; Natasa Koceska; Limonka Koceva Lazarova; Marija Miteva; Biljana Zlatanovska – Journal of Technology and Science Education, 2025
This study aims to evaluate ChatGPT's capabilities in certain numerical analysis problem: solving ordinary differential equations. The methodology which is developed in order to conduct this research takes into account the following mathematical abilities (defined according to National Centre for Education Statistics): Conceptual Understanding,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Number Concepts, Problem Solving
Brown, Neil C. C.; Weill-Tessier, Pierre; Sekula, Maksymilian; Costache, Alexandra-Lucia; Kölling, Michael – ACM Transactions on Computing Education, 2023
Objectives: Java is a popular programming language for use in computing education, but it is difficult to get a wide picture of the issues that it presents for novices; most studies look only at the types or frequency of errors. In this observational study, we aim to learn how novices use different features of the Java language. Participants:…
Descriptors: Novices, Programming, Programming Languages, Data
Václav Dobiáš; Václav Šimandl; Jirí Vanícek – Informatics in Education, 2024
The paper discusses an alternative method of assessing the difficulty of pupils' programming tasks to determine their age appropriateness. Building a program takes the form of its successive iterations. Thus, it is possible to monitor the number of times such a program was built by the solver. The variance of the number of program builds can be…
Descriptors: Difficulty Level, Computer Science Education, Programming, Task Analysis