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Showing 1 to 15 of 25 results Save | Export
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Domicián Máté; Judit T. Kiss; Mária Csernoch – Education and Information Technologies, 2025
The impact of cognitive biases, particularly biased self-assessment, on learning outcomes and decision-making in higher education is of great significance. This study delves into the confluence of cognitive biases and user experience in spreadsheet programming as a crucial IT skill across various academic disciplines. Through a quantitative…
Descriptors: Programming, Spreadsheets, Computer Science Education, STEM Education
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Yunsung Kim; Jadon Geathers; Chris Piech – International Educational Data Mining Society, 2024
"Stochastic programs," which are programs that produce probabilistic output, are a pivotal paradigm in various areas of CS education from introductory programming to machine learning and data science. Despite their importance, the problem of automatically grading such programs remains surprisingly unexplored. In this paper, we formalize…
Descriptors: Grading, Automation, Accuracy, Programming
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Melina Verger; Chunyang Fan; Sébastien Lallé; François Bouchet; Vanda Luengo – Journal of Educational Data Mining, 2024
Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes, leading to potential discrimination against certain individuals and harmful long-term…
Descriptors: Algorithms, Prediction, Bias, Classification
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Iria Estévez-Ayres; Patricia Callejo; Miguel Ángel Hombrados-Herrera; Carlos Alario-Hoyos; Carlos Delgado Kloos – International Journal of Artificial Intelligence in Education, 2025
The emergence of Large Language Models (LLMs) has marked a significant change in education. The appearance of these LLMs and their associated chatbots has yielded several advantages for both students and educators, including their use as teaching assistants for content creation or summarisation. This paper aims to evaluate the capacity of LLMs…
Descriptors: Artificial Intelligence, Natural Language Processing, Computer Mediated Communication, Technology Uses in Education
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Sa Li; Jingjing Dong – International Journal of Web-Based Learning and Teaching Technologies, 2024
In order to deeply analyze and evaluate the changes in the comprehensive quality of college students' sports dance, the overall idea of systematically evaluating the changes in the comprehensive quality of college students' sports dance was established. Firstly, this article uses the triangular fuzzy number method to measure the evaluation…
Descriptors: Dance Education, Teaching Methods, Evaluation Methods, Programming Languages
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Zi Xiang Poh; Ean Teng Khor – International Journal on E-Learning, 2024
Machine learning and data mining techniques have been widely used in educational settings to identify the important features that tend to influence students' learning performance and predict their future performance. However, there is little to no research done in the context of Singapore's education. Hence, this study aims to fill the gap by…
Descriptors: Learning Analytics, Goodness of Fit, Academic Achievement, Online Courses
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Shaheen, Muhammad – Interactive Learning Environments, 2023
Outcome-based education (OBE) is uniquely adapted by most of the educators across the world for objective processing, evaluation and assessment of computing programs and its students. However, the extraction of knowledge from OBE in common is a challenging task because of the scattered nature of the data obtained through Program Educational…
Descriptors: Undergraduate Students, Programming, Computer Science Education, Educational Objectives
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Van Petegem, Charlotte; Deconinck, Louise; Mourisse, Dieter; Maertens, Rien; Strijbol, Niko; Dhoedt, Bart; De Wever, Bram; Dawyndt, Peter; Mesuere, Bart – Journal of Educational Computing Research, 2023
We present a privacy-friendly early-detection framework to identify students at risk of failing in introductory programming courses at university. The framework was validated for two different courses with annual editions taken by higher education students (N = 2 080) and was found to be highly accurate and robust against variation in course…
Descriptors: Pass Fail Grading, At Risk Students, Introductory Courses, Programming
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Kuroki, Masanori – Journal of Economic Education, 2023
As vast amounts of data have become available in business in recent years, the demand for data scientists has been rising. The author of this article provides a tutorial on how one entry-level machine learning competition from Kaggle, an online community for data scientists, can be integrated into an undergraduate econometrics course as an…
Descriptors: Statistics Education, Teaching Methods, Competition, Prediction
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Yang, Fan; Akanbi, Temitope; Chong, Oscar Wong; Zhang, Jiansong; Debs, Luciana; Chen, Yunfeng; Hubbard, Bryan J. – Journal of Civil Engineering Education, 2024
Computing technology is reshaping the way in which professionals in the architecture, engineering, and construction industries conduct their business. The execution of construction tasks is changing from traditional 2D to 3D building information modeling (BIM)-based concepts. The use of BIM is expanded and enriched by the introduction of advanced…
Descriptors: Civil Engineering, Engineering Education, Programming Languages, Construction Management
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Thoma, Athina; Iannone, Paola – International Journal of Research in Undergraduate Mathematics Education, 2022
This exploratory study reports on characteristics of proof production and proof writing observed in the work of first-year university students who took part in workshops on the theorem prover LEAN (https://leanprover.github.io). These workshops were voluntary and offered alongside a transition to proof module in a UK university. Through…
Descriptors: Validity, Mathematical Logic, Mathematics Instruction, Undergraduate Students
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Musa Adekunle Ayanwale; Jamiu Oluwadamilare Amusa; Adekunle Ibrahim Oladejo; Funmilayo Ayedun – Interchange: A Quarterly Review of Education, 2024
The study focuses on assessing the proficiency levels of higher education students, specifically the physics achievement test (PHY 101) at the National Open University of Nigeria (NOUN). This test, like others, evaluates various aspects of knowledge and skills simultaneously. However, relying on traditional models for such tests can result in…
Descriptors: Item Response Theory, Difficulty Level, Item Analysis, Test Items
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Hongxin Yan; Fuhua Lin; Kinshuk – Canadian Journal of Learning and Technology, 2024
Online higher education provides exceptional flexibility in learning but demands high self-regulated learning skills. The deficiency of self-regulated learning skills in many students highlights the need for support. This study introduces a confidence-based adaptive practicing system as an intelligent assessment and tutoring solution to enhance…
Descriptors: Self Management, Online Courses, Intelligent Tutoring Systems, Technology Uses in Education
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Chrysafiadi, Konstantina; Virvou, Maria; Tsihrintzis, George A.; Hatzilygeroudis, Ioannis – Education and Information Technologies, 2023
Nowadays, the improvement of digital learning with Artificial Intelligence has attracted a lot of research, as it provides solutions for individualized education styles which are independent of place and time. This is particularly the case for computer science, as a tutoring domain, which is rapidly growing and changing and as such, learners need…
Descriptors: Foreign Countries, Undergraduate Students, Computer Science Education, Programming
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Daleiden, Patrick; Stefik, Andreas; Uesbeck, P. Merlin; Pedersen, Jan – ACM Transactions on Computing Education, 2020
There are many paradigms available to address the unique and complex problems introduced with parallel programming. These complexities have implications for computer science education as ubiquitous multi-core computers drive the need for programmers to understand parallelism. One major obstacle to student learning of parallel programming is that…
Descriptors: Randomized Controlled Trials, Performance Factors, Programming, Computer Science Education
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