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Neil C. C. Brown; Pierre Weill-Tessier; Juho Leinonen; Paul Denny; Michael Kölling – ACM Transactions on Computing Education, 2025
Motivation: Students learning to program often reach states where they are stuck and can make no forward progress--but this may be outside the classroom where no instructor is available to help. In this situation, an automatically generated next-step hint can help them make forward progress and support their learning. It is important to know what…
Descriptors: Artificial Intelligence, Programming, Novices, Technology Uses in Education
Marwan, Samiha; Price, Thomas W. – IEEE Transactions on Learning Technologies, 2023
Novice programmers often struggle on assignments, and timely help, such as a hint on what to do next, can help students continue to progress and learn, rather than giving up. However, in large programming classrooms, it is hard for instructors to provide such real-time support for every student. Researchers have, therefore, put tremendous effort…
Descriptors: Data Use, Cues, Programming, Computer Science Education
Emerson, Andrew; Rodríguez, Fernando J.; Mott, Bradford; Smith, Andy; Min, Wookhee; Boyer, Kristy Elizabeth; Smith, Cody; Wiebe, Eric; Lester, James – International Educational Data Mining Society, 2019
Recent years have seen a growing interest in block-based programming environments for computer science education. While these environments hold significant potential for novice programmers, they lack the adaptive support necessary to accommodate students exhibiting a wide range of initial capabilities and dispositions toward computing. A promising…
Descriptors: Programming, Computer Science Education, Feedback (Response), Prediction
Paassen, Benjamin; Hammer, Barbara; Price, Thomas William; Barnes, Tiffany; Gross, Sebastian; Pinkwart, Niels – Journal of Educational Data Mining, 2018
Intelligent tutoring systems can support students in solving multi-step tasks by providing hints regarding what to do next. However, engineering such next-step hints manually or via an expert model becomes infeasible if the space of possible states is too large. Therefore, several approaches have emerged to infer next-step hints automatically,…
Descriptors: Intelligent Tutoring Systems, Cues, Educational Technology, Technology Uses in Education
Mather, Richard – Research in Learning Technology, 2015
A mixed-methods approach is evaluated for exploring collaborative behaviour, acceptance and progress surrounding an interactive technology for learning computer programming. A review of literature reveals a compelling case for using mixed-methods approaches when evaluating technology-enhanced-learning environments. Here, ethnographic approaches…
Descriptors: Mixed Methods Research, Programming, Cooperative Learning, Technology Uses in Education
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
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers

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