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Andrew Kwok-Fai Lui; Sin-Chun Ng; Stella Wing-Nga Cheung – Interactive Learning Environments, 2024
The technology of automated short answer grading (ASAG) can efficiently process answers according to human-prepared grading examples. Computer-assisted acquisition of grading examples uses a computer algorithm to sample real student responses for potentially good examples. The process is critical for optimizing the grading accuracy of machine…
Descriptors: Grading, Computer Uses in Education, Educational Technology, Artificial Intelligence
Atanu Bhattacharya; Kalyan Dasgupta; Binoy Paine – Journal of Chemical Education, 2024
In this paper, we present a computational chemistry project that demonstrates the quantum dynamics of a free particle, using both classical and quantum computing algorithms. This project can be used in a computational quantum chemistry course in which the instructor introduces quantum computing. Students write their own programs to simulate the…
Descriptors: Chemistry, Science Education, Quantum Mechanics, Computer Science
Bambang Sulistio; Arief Ramadhan; Edi Abdurachman; Muhammad Zarlis; Agung Trisetyarso – Education and Information Technologies, 2024
Computer science development, especially machine learning, is a thriving innovation essential for education. It makes the process of teaching and learning more accessible and manageable and also promotes equality. The positive influence of machine learning can also be felt in Islamic studies, particularly in Hadith studies. This literature review…
Descriptors: Electronic Learning, Artificial Intelligence, Computer Uses in Education, Islam
Farrow, Robert – Learning, Media and Technology, 2023
Explicable AI in education (XAIED) has been proposed as a way to improve trust and ethical practice in algorithmic education. Based on a critical review of the literature, this paper argues that XAI should be understood as part of a wider socio-technical turn in AI. The socio-technical perspective indicates that explicability is a relative term.…
Descriptors: Artificial Intelligence, Algorithms, Computer Uses in Education, Language Usage
Basil Hanafi; Mohammad Ali; Devyaani Singh – Discover Education, 2025
Quantum computing is the beginning of a new age for diverse industries, and educational technologies will significantly benefit from such quantum developments. This is a novel approach, applying quantum algorithms to enhance educational technologies, with no previous studies addressing the integration of quantum computing for personalized…
Descriptors: Educational Technology, Computer Security, Ethics, Algorithms
Donald Secreast – CEA Forum, 2023
"Using Sentiment Analysis to Ease Students toward or around Macroanalysis" introduces teachers to the mathematical analytical method currently being promoted by Matthew Jockers which he calls macroanalysis. This method uses an algorithm called "R," originally designed by researchers in sociology. In many ways, macroanalysis…
Descriptors: Literary Criticism, Statistical Analysis, Algorithms, Computer Uses in Education
Basil Wahn; Laura Schmitz – Cognitive Research: Principles and Implications, 2024
With the increased sophistication of technology, humans have the possibility to offload a variety of tasks to algorithms. Here, we investigated whether the extent to which people are willing to offload an attentionally demanding task to an algorithm is modulated by the availability of a bonus task and by the knowledge about the algorithm's…
Descriptors: College Students, Algorithms, Cognitive Processes, Technology Uses in Education
Mensure Alkis Küçükaydin; Hakan Çite; Hakan Ulum – Education and Information Technologies, 2024
Students enter the science, technology, engineering, and mathematics (STEM) pipeline in primary school, but leak out of it over time for various reasons. To prevent leaks, it is important to understand the variables that affect attitudes towards STEM learning from an early age. This study sought to examine the predictors of young students' STEM…
Descriptors: Foreign Countries, Elementary School Students, STEM Education, Student Attitudes
Siu-Cheung Kong; Wei Shen – Interactive Learning Environments, 2024
Logistic regression models have traditionally been used to identify the factors contributing to students' conceptual understanding. With the advancement of the machine learning-based research approach, there are reports that some machine learning algorithms outperform logistic regression models in terms of prediction. In this study, we collected…
Descriptors: Student Characteristics, Predictor Variables, Comprehension, Computation
Lonneke Boels; Enrique Garcia Moreno-Esteva; Arthur Bakker; Paul Drijvers – International Journal of Artificial Intelligence in Education, 2024
As a first step toward automatic feedback based on students' strategies for solving histogram tasks we investigated how strategy recognition can be automated based on students' gazes. A previous study showed how students' task-specific strategies can be inferred from their gazes. The research question addressed in the present article is how data…
Descriptors: Eye Movements, Learning Strategies, Problem Solving, Automation
Noawanit Songkram; Supattraporn Upapong; Heng-Yu Ku; Narongpon Aulpaijidkul; Sarun Chattunyakit; Nutthakorn Songkram – Interactive Learning Environments, 2024
This research proposes the integration of robotic education and scenario-based learning (SBL) paradigm for teaching computational thinking (CT) to enhance the computational abilities of primary school students, based on digital innovation and a teaching assistant robot acceptance model. The sample group consisted of 532 primary school teachers and…
Descriptors: Foreign Countries, Elementary School Students, Elementary School Teachers, Grade 1
Saira Anwar; Ahmed Ashraf Butt; Muhsin Menekse – Grantee Submission, 2023
This study explored the effectiveness of scaffolding in students' reflection writing process. We compared two sections of an introductory computer programming course (N=188). In Section 1, students did not receive any scaffolding while generating reflections, whereas in Section 2, students were scaffolded during the reflection writing process.…
Descriptors: Scaffolding (Teaching Technique), Writing Instruction, Writing Processes, Writing (Composition)
Mena-Guacas, Andres F.; Urueña Rodríguez, Jairo Alonso; Santana Trujillo, David Mauricio; Gómez-Galán, José; López-Meneses, Eloy – Contemporary Educational Technology, 2023
The diversity of topics in education makes it difficult for artificial intelligence (AI) to address them all in depth. Therefore, guiding to focus efforts on specific issues is essential. The analysis of competency development by fostering collaboration should be one of them because competencies are the way to validate that the educational…
Descriptors: Cooperative Learning, Skill Development, Artificial Intelligence, Educational Development
Nathan H. Bean – ProQuest LLC, 2022
Learning to program has long been known to be a difficult task, requiring a student to develop both fluency in the syntax and grammar of a formal programming language and learn the problem-solving approaches and techniques of computational thinking. The successful teaching strategies of the past have involved maintaining small teacher-student…
Descriptors: Algorithms, Coding, Supplementary Education, Programming

Martin, Rosario; Tortosa, Leandro – International Journal of Computer Algebra in Mathematics Education, 1999
Presents an algorithm to compute the critical path in a graph representing a project evaluation research task. Once the algorithm is executed, the last matrix obtained permits the visualization of some important information which leads to the determination of the weight of the critical path. (Author/MM)
Descriptors: Algorithms, Calculators, Computer Uses in Education, Higher Education