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Showing 1 to 15 of 17 results Save | Export
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Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2023
This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…
Descriptors: Computational Linguistics, Programming, Computer Science Education, Programming Languages
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Sunil Hazari – Journal of Educational Research and Practice, 2024
In this article, I present a justification for implementing AI literacy courses in higher education. I explore the ethical concerns and biases surrounding AI technologies, highlighting the importance of critical analysis and responsible use of AI. I then propose a conceptual framework, focusing on awareness, skill development, and the practical…
Descriptors: Artificial Intelligence, Higher Education, Critical Thinking, Innovation
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Arun-Balajiee Lekshmi-Narayanan; Priti Oli; Jeevan Chapagain; Mohammad Hassany; Rabin Banjade; Vasile Rus – Grantee Submission, 2024
Worked examples, which present an explained code for solving typical programming problems are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the example code. However, instructors rarely have time to provide…
Descriptors: Coding, Computer Science Education, Computational Linguistics, Artificial Intelligence
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Maertens, Rien; Van Petegem, Charlotte; Strijbol, Niko; Baeyens, Toon; Jacobs, Arne Carla; Dawyndt, Peter; Mesuere, Bart – Journal of Computer Assisted Learning, 2022
Background: Learning to code is increasingly embedded in secondary and higher education curricula, where solving programming exercises plays an important role in the learning process and in formative and summative assessment. Unfortunately, students admit that copying code from each other is a common practice and teachers indicate they rarely use…
Descriptors: Plagiarism, Benchmarking, Coding, Computer Science Education
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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
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Samuel Boguslawski; Rowan Deer; Mark G. Dawson – Information and Learning Sciences, 2025
Purpose: Programming education is being rapidly transformed by generative AI tools and educators must determine how best to support students in this context. This study aims to explore the experiences of programming educators and students to inform future education provision. Design/methodology/approach: Twelve students and six members of faculty…
Descriptors: Programming, Computer Science Education, Personal Autonomy, Learning Motivation
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Marco Zappatore – Technology, Knowledge and Learning, 2024
This research aims to address the current gaps in computer-assisted translation (CAT) courses offered in bachelor's and master's programmes in scientific and technical translation (STT). A multi-framework course design methodology is proposed to support CAT teachers from the computer engineering field, improve student engagement, and promote…
Descriptors: Translation, Computational Linguistics, Computer Software, Language Skills
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Farrow, Elaine; Moore, Johanna D.; Gaševic, Dragan – Journal of Learning Analytics, 2022
By participating in asynchronous course discussion forums, students can work together to refine their ideas and construct knowledge collaboratively. Typically, some messages simply repeat or paraphrase course content, while others bring in new material, demonstrate reasoning, integrate concepts, and develop solutions. Through the messages they…
Descriptors: Asynchronous Communication, Computer Mediated Communication, Group Discussion, Learning Analytics
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McGowan, Ian S. – International Association for Development of the Information Society, 2020
Upto now, the knowledge building influence of the fundamental communicative functions during an on-line collaborative learning (OLCL) session, i.e. argumentative, responsive, elicitative, informative and imperative have been mainly based on results from qualitative studies, results that could have been strengthened by quantitative approaches.…
Descriptors: Higher Education, Online Courses, Cooperative Learning, Computer Science Education
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Blake, John – RELC Journal: A Journal of Language Teaching and Research, 2020
A purpose-built online error detection tool was developed to provide genre-specific corpus-based feedback on errors occurring in draft research articles and graduation theses. The primary envisaged users were computer science majors studying at a public university in Japan. This article discusses the development and evaluation of this interactive,…
Descriptors: Feedback (Response), Usability, Error Analysis (Language), Computational Linguistics
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Blake, John – Research-publishing.net, 2020
This article describes the development of a tense and aspect identifier, an online tool designed to help learners of English by harnessing a natural language processing pipeline to automatically classify verb groups into one of 12 grammatical tenses. Currently, there is no website or application that can automatically identify tense in context,…
Descriptors: Verbs, Computer Software, Teaching Methods, Computer Assisted Instruction
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Purgina, Marina; Mozgovoy, Maxim; Blake, John – Journal of Educational Computing Research, 2020
Gamification of language learning is a clear trend of recent years. Widespread use of smartphones and the rise of mobile gaming as a popular leisure activity contribute to the popularity of gamification, as application developers can rely on an unprecedented reach of their products and expect acceptance of game-like elements by the users. In terms…
Descriptors: Computer Games, Computer Simulation, Grammar, Computer Software
Ramachandran, Lakshmi – ProQuest LLC, 2013
Relevance helps identify to what extent a review's content pertains to that of the submission. Relevance metric helps distinguish generic or vague reviews from the useful ones. Relevance of a review to a submission can be determined by identifying semantic and syntactic similarities between them. Our work introduces the use of a word-order graph…
Descriptors: Evaluation, Evaluators, Semantics, Word Order
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Tang, Michael; David, Hyerle; Byrne, Roxanne; Tran, John – International Journal on E-Learning, 2012
This paper is a mathematical (Boolean) analysis a set of cognitive maps called Thinking Maps[R], based on Albert Upton's semantic principles developed in his seminal works, Design for Thinking (1961) and Creative Analysis (1961). Albert Upton can be seen as a brilliant thinker who was before his time or after his time depending on the future of…
Descriptors: Cognitive Mapping, Computer Science, Semiotics, Mathematical Concepts
Watters, Shana Kay – ProQuest LLC, 2010
For over 30 years, reference resolution, the process of determining what a noun phrase including a pronoun refers to in written and spoken language, has been an important and on-going area of research. Most existing pronominal reference resolution algorithms and systems are designed to use syntactic information and surface features (e.g. number…
Descriptors: Semantics, Verbs, Nouns, Computer Science
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