Publication Date
In 2025 | 36 |
Since 2024 | 134 |
Since 2021 (last 5 years) | 487 |
Since 2016 (last 10 years) | 800 |
Since 2006 (last 20 years) | 1185 |
Descriptor
Source
Author
Bers, Marina Umaschi | 6 |
Cavus, Nadire | 6 |
Xinogalos, Stelios | 6 |
Barnes, Tiffany | 5 |
Ibrahim, Dogan | 5 |
Mannila, Linda | 5 |
Dan Sun | 4 |
Frydenberg, Mark | 4 |
Laakso, Mikko-Jussi | 4 |
Resnick, Mitchel | 4 |
Sullivan, Amanda | 4 |
More ▼ |
Publication Type
Education Level
Location
Turkey | 36 |
Taiwan | 28 |
China | 18 |
Germany | 18 |
United Kingdom | 18 |
Australia | 16 |
Spain | 16 |
Canada | 11 |
Finland | 11 |
Brazil | 10 |
Cyprus | 10 |
More ▼ |
Laws, Policies, & Programs
Americans with Disabilities… | 1 |
Telecommunications Act 1996 | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Meets WWC Standards with or without Reservations | 2 |
Erdem-Kara, Basak – International Journal of Assessment Tools in Education, 2019
Computer adaptive testing is an important research field in educational measurement, and simulation studies play a critically important role in CAT development and evaluation. Both Monte Carlo and Post Hoc simulations are frequently used in CAT studies in order to investigate the effects of different factors on test efficiency and to compare…
Descriptors: Computer Assisted Testing, Adaptive Testing, Programming Languages, Monte Carlo Methods
Phung, Tung; Cambronero, José; Gulwani, Sumit; Kohn, Tobias; Majumdarm, Rupak; Singla, Adish; Soares, Gustavo – International Educational Data Mining Society, 2023
Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for fixing syntax errors in Python programs, a key scenario in introductory programming. More concretely, given a student's buggy program, our goal is…
Descriptors: Computational Linguistics, Feedback (Response), Programming, Computer Science Education
Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Informatics in Education, 2023
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student…
Descriptors: Prior Learning, Programming, Computer Science Education, Markov Processes
Holman, Justin O.; Hacherl, Allie – Journal of Statistics and Data Science Education, 2023
It has become increasingly important for future business professionals to understand statistical computing methods as data science has gained widespread use in contemporary organizational decision processes in recent years. Used by scores of academics and practitioners in a variety of fields, Monte Carlo simulation is one of the most broadly…
Descriptors: Teaching Methods, Monte Carlo Methods, Programming Languages, Statistics Education
Margulieux, Lauren; Parker, Miranda C.; Cetin Uzun, Gozde; Cohen, Jonathan D. – Journal of Technology and Teacher Education, 2023
Educators across disciplines are implementing lessons and activities that integrate computing concepts into their curriculum to broaden participation in computing. Out of myriad important introductory computing skills, it is unknown which--and to what extent--these concepts are included in these integrated experiences, especially when compared to…
Descriptors: Programming, Programming Languages, Computer Science Education, Age Differences
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
Taipalus, Toni; Seppänen, Ville – ACM Transactions on Computing Education, 2020
Structured Query Language (SQL) skills are crucial in software engineering and computer science. However, teaching SQL effectively requires both pedagogical skill and considerable knowledge of the language. Educators and scholars have proposed numerous considerations for the betterment of SQL education, yet these considerations may be too numerous…
Descriptors: Programming Languages, Computer Science Education, Literature Reviews, Learning Activities
Fuentes, Pablo; Camarero, Cristobal; Herreros, David; Mateev, Vladimir; Vallejo, Fernando; Martinez, Carmen – IEEE Transactions on Learning Technologies, 2022
Understanding the architecture of a processor can be uninteresting and deterring for computer science students, since low-level details of computer architecture are often perceived to lack real-world impact. These courses typically have a strong practical component where students learn the fundamentals of the computer architecture and the handling…
Descriptors: Computer Science Education, Computer System Design, Programming Languages, Fatigue (Biology)
Gozukucuk, Meral; Gunbas, Nilgun – Journal of Education, 2022
The purpose of this study is to contribute to preservice teachers' technological pedagogical content knowledge (TPACK). For this purpose, preservice teachers (n = 8) learned visual programming language, designed technology-based reading activities, and observed students completing these activities. A case study approach was employed, and…
Descriptors: Preservice Teachers, Technological Literacy, Pedagogical Content Knowledge, Programming Languages
Saatcioglu, Fatima Munevver; Atar, Hakan Yavuz – International Journal of Assessment Tools in Education, 2022
This study aims to examine the effects of mixture item response theory (IRT) models on item parameter estimation and classification accuracy under different conditions. The manipulated variables of the simulation study are set as mixture IRT models (Rasch, 2PL, 3PL); sample size (600, 1000); the number of items (10, 30); the number of latent…
Descriptors: Accuracy, Classification, Item Response Theory, Programming Languages
Jiang, Bo; Zhao, Wei; Gu, Xiaoqing; Yin, Chengjiu – Educational Technology Research and Development, 2021
Social learning theory posits that learning is most effective when providing learners with opportunities to observe and interact with peers. Unfortunately, current K-12 programming education overemphasizes individual learning and discourages learners from observing and interacting with others. The Scratch online community provides youth…
Descriptors: Correlation, Computer Science Education, Programming Languages, Elementary Secondary Education
Kahn, Ken; Winters, Niall – British Journal of Educational Technology, 2021
Constructionism, long before it had a name, was intimately tied to the field of Artificial Intelligence. Soon after the birth of Logo at BBN, Seymour Papert set up the Logo Group as part of the MIT AI Lab. Logo was based upon Lisp, the first prominent AI programming language. Many early Logo activities involved natural language processing,…
Descriptors: Artificial Intelligence, Man Machine Systems, Programming Languages, Programming
Hsu, Wen-Chin; Gainsburg, Julie – Journal of Educational Computing Research, 2021
Block-based programming languages (BBLs) have been proposed as a way to prepare students for learning to program in more sophisticated, text-based languages, such as Java. Hybrid BBLs add the ability to view and edit the block commands in auto-generated, text-based code. We compared the use of a non-hybrid BBL (Scratch), a hybrid BBL (Pencil…
Descriptors: Computer Science Education, Introductory Courses, Teaching Methods, Student Attitudes
Hoffman, Heather J.; Elmi, Angelo F. – Journal of Statistics and Data Science Education, 2021
Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students' experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures…
Descriptors: Statistics Education, Programming Languages, Troubleshooting, Coding
Kwon, Yeil; Sahin, Nesrin – International Society for Technology, Education, and Science, 2021
Probability is generally considered one of the most challenging areas to teach in mathematics education due to its intricate nature. However, the simulation-based teaching method can increase students' accessibility significantly to the probability problems because it enables students to resolve the problems with minimal mathematical skills. By…
Descriptors: Probability, Mathematics Instruction, Difficulty Level, Teaching Methods