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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
Heiner, Cecily; Zachary, Joseph L. – International Working Group on Educational Data Mining, 2009
Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This paper analyzes 411 questions from an introductory Java programming course by reducing the natural…
Descriptors: Classification, Questioning Techniques, Introductory Courses, Computer Science Education
Aarons, Louis – 1998
This paper describes the rationale for development of a self-instructional program using the bilingual-dichotic method, which accelerates the learning of foreign words. First, ways of learning vocabulary and the use of bilingual word lists for direct instruction with beginners are noted, and criteria are given for selection of words. Differences…
Descriptors: Associative Learning, Brain Hemisphere Functions, Classroom Techniques, Contrastive Linguistics