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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
Guido Lang; Tamilla Triantoro; Jason H. Sharp – Journal of Information Systems Education, 2024
This study explores the potential of large language models (LLMs), specifically GPT-4 and Gemini, in generating teaching cases for information systems courses. A unique prompt for writing three different types of teaching cases such as a descriptive case, a normative case, and a project-based case on the same IS topic (i.e., the introduction of…
Descriptors: Computational Linguistics, Computer Software, Artificial Intelligence, Readability Formulas
UK Department for Education, 2024
This report sets out the findings of the technical development work completed as part of the Use Cases for Generative AI in Education project, commissioned by the Department for Education (DfE) in September 2023. It has been published alongside the User Research Report, which sets out the findings from the ongoing user engagement activity…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Software, Computational Linguistics
Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – Grantee Submission, 2024
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change
Granados, Adrián; Lorenzo-Espejo, Antonio; Lorenzo, Francisco – International Journal of Bilingual Education and Bilingualism, 2022
However influential the interdependence hypothesis has become in bilingual research, it still lacks full empirical support. This longitudinal study explores the parallels in the biliteracy development (L1 Spanish and L2 English) of 20 students in a European immersion programme (i.e. CLIL) over a two-year period. A bilingual learner corpus of…
Descriptors: Bilingualism, Literacy, Second Language Learning, Second Language Instruction
Crossley, Scott A.; Skalicky, Stephen; Dascalu, Mihai; McNamara, Danielle S.; Kyle, Kristopher – Discourse Processes: A multidisciplinary journal, 2017
Research has identified a number of linguistic features that influence the reading comprehension of young readers; yet, less is known about whether and how these findings extend to adult readers. This study examines text comprehension, processing, and familiarity judgment provided by adult readers using a number of different approaches (i.e.,…
Descriptors: Reading Processes, Reading Comprehension, Readability, Adults
Aziz, Anealka; Fook, Chan Yuen; Alsree, Zubaida – Advances in Language and Literary Studies, 2010
Reading materials are considered having high readability if readers are interested to read the materials, understand the content of the materials and able to read the materials fluently. In contrast, reading materials with low readability discourage readers from reading the materials, create difficulties for readers to understand the content of…
Descriptors: Readability, Computational Linguistics, Reading Materials, Second Language Learning