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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
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
Chou, Shih Yung; Luo, Jiaxi; Ramser, Charles – Journal of International Education in Business, 2021
Purpose: The purpose of this study is to examine student sentiments regarding high-quality vs low-quality teaching. Design/methodology/approach: This study uses a text mining technique to identify the positive and negative patterns of student sentiments from student evaluations of teaching (SET) provided on Ratemyprofessors.com. After identifying…
Descriptors: Educational Quality, Student Attitudes, Positive Attitudes, Negative Attitudes
Taylor, Z. W. – Journal of Student Affairs Research and Practice, 2019
Research suggests that L2 students (English-language learners) do not access postsecondary education as the same level as L1 (native English-speaking) peers. Using a computational linguistics approach, this study analyzes financial aid application instructions from 341 randomly selected four-year, Title IV-participating U.S. institutions. Results…
Descriptors: Student Financial Aid, Second Language Learning, Achievement Gap, Academic Achievement
Goh, Tiong-Thye; Sun, Hui; Yang, Bing – Computer Assisted Language Learning, 2020
This study investigates the extent to which microfeatures -- such as basic text features, readability, cohesion, and lexical diversity based on specific word lists -- affect Chinese EFL writing quality. Data analysis was conducted using natural language processing, correlation analysis and stepwise multiple regression analysis on a corpus of 268…
Descriptors: Essays, Writing Tests, English (Second Language), Second Language Learning