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Oscar Karnalim; Hapnes Toba; Meliana Christianti Johan – Education and Information Technologies, 2024
Artificial Intelligence (AI) can foster education but can also be misused to breach academic integrity. Large language models like ChatGPT are able to generate solutions for individual assessments that are expected to be completed independently. There are a number of automated detectors for AI assisted work. However, most of them are not dedicated…
Descriptors: Artificial Intelligence, Academic Achievement, Integrity, Introductory Courses
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Irem Nur Çelik; Kati Bati – Informatics in Education, 2025
In this study, we aimed to investigate the impact of cooperative learning on the computational thinking skills and academic performances of middle school students in the computational problem-solving approach. We used the pretest-posttest control group design of the quasiexperimental method. In the research, computational problem-solving…
Descriptors: Cooperative Learning, Academic Achievement, Computation, Thinking Skills
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Oscar Karnalim – Informatics in Education, 2024
Programming students need to be informed about plagiarism and collusion. Hence, we developed an assessment submission system to remind students about the matter. Each submission will be compared to others and any similarities that do not seem a result of coincidence will be reported along with their possible reasons. The system also employs…
Descriptors: Programming, Integrity, Academic Achievement, Plagiarism
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Satratzemi, Maya; Stelios, Xinogalos; Tsompanoudi, Despina – Journal of Educational Computing Research, 2023
This paper presents a Systematic Literature Review (SLR) of fifty-seven studies on Distributed Pair Programming (DPP) in higher education, identifying which studies investigated factors on the effectiveness of DPP as a method for learning programming, factors related to mediating and stimulating interactions between students, the…
Descriptors: Programming, Teamwork, Higher Education, Instructional Effectiveness
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Deepak Dawar – Information Systems Education Journal, 2024
Learning computer programming is typically difficult for newcomers. Demotivation and learned helplessness have received much attention. Besides the subject's intricacy, low in-class participation has been associated with poor student achievement. This paper presents a follow-up, stage 2 study on the novel instructional technique, Student-Driven…
Descriptors: College Students, Computer Science Education, Required Courses, Elective Courses
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Fang, Jian-Wen; Shao, Dan; Hwang, Gwo-Jen; Chang, Shao-Chen – Journal of Educational Computing Research, 2022
Scholars believe that computational thinking is one of the essential competencies of the 21st century and computer programming courses have been recognized as a potential means of fostering students' computational thinking. In tradition instruction, PFCT (problem identification, flow definition, coding, and testing) is a commonly adopted procedure…
Descriptors: Computation, Thinking Skills, Programming, Computer Science Education
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Moreno-León, Jesús; Robles, Gregorio; Román-González, Marcos – Journal of Information Technology Education: Research, 2016
The introduction of computer programming in K-12 has become mainstream in the last years, as countries around the world are making coding part of their curriculum. Nevertheless, there is a lack of empirical studies that investigate how learning to program at an early age affects other school subjects. In this regard, this paper compares three…
Descriptors: Foreign Countries, Programming, Computer Science Education, Introductory Courses
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Blikstein, Paulo; Worsley, Marcelo; Piech, Chris; Sahami, Mehran; Cooper, Steven; Koller, Daphne – Journal of the Learning Sciences, 2014
New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…
Descriptors: Programming, Computer Science Education, Learning Processes, Introductory Courses
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Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
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Sampson, Demetrios G., Ed.; Ifenthaler, Dirk, Ed.; Isaías, Pedro, Ed. – International Association for Development of the Information Society, 2018
The aim of the 2018 International Association for Development of the Information Society (IADIS) Cognition and Exploratory Learning in the Digital Age (CELDA) conference was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There have been advances in both cognitive…
Descriptors: Learning Processes, Teaching Methods, Educational Technology, Technology Uses in Education
Nunes, Miguel Baptista, Ed.; McPherson, Maggie, Ed. – International Association for Development of the Information Society, 2015
These proceedings contain the papers of the International Conference e-Learning 2015, which was organised by the International Association for Development of the Information and Society and is part of the Multi Conference on Computer Science and Information Systems (Las Palmas de Gran Canaria, Spain, July 21-24, 2015). The e-Learning 2015…
Descriptors: Conference Papers, Failure, Electronic Learning, Success
Pechenizkiy, Mykola; Calders, Toon; Conati, Cristina; Ventura, Sebastian; Romero, Cristobal; Stamper, John – International Working Group on Educational Data Mining, 2011
The 4th International Conference on Educational Data Mining (EDM 2011) brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large datasets to answer educational research questions. The conference, held in Eindhoven, The Netherlands, July 6-9, 2011, follows the three previous editions…
Descriptors: Academic Achievement, Logical Thinking, Profiles, Tutoring
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection