Publication Date
In 2025 | 2 |
Since 2024 | 6 |
Since 2021 (last 5 years) | 28 |
Since 2016 (last 10 years) | 41 |
Since 2006 (last 20 years) | 50 |
Descriptor
Source
Author
Cai, Zhiqiang | 3 |
Graesser, Arthur C. | 3 |
Olney, Andrew M. | 3 |
Bédi, Branislav | 2 |
Cardoso, Walcir | 2 |
Eagan, Brendan | 2 |
Erjavec, Tomaz | 2 |
Hu, Xiangen | 2 |
Ide, Nancy | 2 |
Jakopin, Primoz | 2 |
Jeevan Chapagain | 2 |
More ▼ |
Publication Type
Speeches/Meeting Papers | 74 |
Reports - Research | 34 |
Reports - Descriptive | 30 |
Reports - Evaluative | 10 |
Journal Articles | 2 |
Opinion Papers | 1 |
Tests/Questionnaires | 1 |
Education Level
Higher Education | 18 |
Postsecondary Education | 16 |
Secondary Education | 5 |
Middle Schools | 4 |
Elementary Education | 3 |
Junior High Schools | 3 |
Adult Education | 2 |
High Schools | 2 |
Grade 6 | 1 |
Grade 7 | 1 |
Grade 8 | 1 |
More ▼ |
Audience
Location
Europe | 5 |
China | 3 |
European Union | 3 |
Japan | 3 |
Netherlands | 2 |
Saudi Arabia | 2 |
Bulgaria | 1 |
Canada | 1 |
Czech Republic | 1 |
France | 1 |
Germany | 1 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
Flesch Reading Ease Formula | 1 |
International English… | 1 |
What Works Clearinghouse Rating
Gustavo Simas da Silva; Vânia Ribas Ulbricht – International Association for Development of the Information Society, 2023
ChatGPT and Bard, two chatbots powered by Large Language Models (LLMs), are propelling the educational sector towards a new era of instructional innovation. Within this educational paradigm, the present investigation conducts a comparative analysis of these groundbreaking chatbots, scrutinizing their distinct operational characteristics and…
Descriptors: Comparative Analysis, Teaching Methods, Computer Software, Artificial Intelligence
Maria Goldshtein; Jaclyn Ocumpaugh; Andrew Potter; Rod D. Roscoe – Grantee Submission, 2024
As language technologies have become more sophisticated and prevalent, there have been increasing concerns about bias in natural language processing (NLP). Such work often focuses on the effects of bias instead of sources. In contrast, this paper discusses how normative language assumptions and ideologies influence a range of automated language…
Descriptors: Language Attitudes, Computational Linguistics, Computer Software, Natural Language Processing
Alberto Giretti; Dilan Durmus; Massimo Vaccarini; Matteo Zambelli; Andrea Guidi; Franco Ripa di Meana – International Association for Development of the Information Society, 2023
This paper provides a possible strategy for integrating large language artificial intelligence models (LLMs) in supporting students' education in artistic or design activities. We outline the methodological foundations concerning the integration of CHATGPT LLM in the educational approach aimed at enhancing artistic conception and design ideation.…
Descriptors: Art Education, Design, Artificial Intelligence, Computer Software
Zhang, Haoran; Litman, Diane – Grantee Submission, 2021
Human essay grading is a laborious task that can consume much time and effort. Automated Essay Scoring (AES) has thus been proposed as a fast and effective solution to the problem of grading student writing at scale. However, because AES typically uses supervised machine learning, a human-graded essay corpus is still required to train the AES…
Descriptors: Essays, Grading, Writing Evaluation, Computational Linguistics

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

Devika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics

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
Zhang, Mengxue; Heffernan, Neil; Lan, Andrew – International Educational Data Mining Society, 2023
Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score…
Descriptors: Scoring, Computer Assisted Testing, Mathematics Instruction, Mathematics Tests
Ethan Prihar; Morgan Lee; Mia Hopman; Adam Tauman Kalai; Sofia Vempala; Allison Wang; Gabriel Wickline; Aly Murray; Neil Heffernan – Grantee Submission, 2023
Large language models have recently been able to perform well in a wide variety of circumstances. In this work, we explore the possibility of large language models, specifically GPT-3, to write explanations for middle-school mathematics problems, with the goal of eventually using this process to rapidly generate explanations for the mathematics…
Descriptors: Mathematics Instruction, Teaching Methods, Artificial Intelligence, Middle School Students
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
Chiera, Belinda; Bédi, Branislav; Zviel-Girshin, Rina – Research-publishing.net, 2022
Modern language learning applications have become 'smarter' and 'intelligent' by including Artificial Intelligence (AI) and Machine Learning (ML) technologies to collect different kinds of data. This data can be used for analysis on a microscopic and/or macroscopic level to provide granulation of knowledge. We analyzed 1,213 French language…
Descriptors: Computer Software, Computer Assisted Instruction, French, Second Language Learning
Yarbro, Jeffrey T.; Olney, Andrew M. – Grantee Submission, 2021
This paper presents WikiMorph, a tool that automatically breaks down words into morphemes, etymological compounds (morphemes from root languages), and generates contextual definitions for each component. It comes in two flavors: a dataset and a deep-learning-based model. The dataset was extracted from Wiktionary and contains over 450k entries. We…
Descriptors: Morphology (Languages), Computational Linguistics, Computer Software, Morphemes

Zirong Chen; Elizabeth Chason; Noah Mladenovski; Erin Wilson; Kristin Mullen; Stephen Martini; Meiyi Ma – Grantee Submission, 2025
Emergency response services are vital for enhancing public safety by safeguarding the environment, property, and human lives. As frontline members of these services, 9-1-1 dispatchers have a direct impact on response times and the overall effectiveness of emergency operations. However, traditional dispatcher training methods, which rely on…
Descriptors: Computational Linguistics, Cues, Emergency Programs, Safety
Chopra, Harshita; Lin, Yiwen; Samadi, Mohammad Amin; Cavazos, Jacqueline G.; Yu, Renzhe; Jaquay, Spencer; Nixon, Nia – International Educational Data Mining Society, 2023
Exploring students' discourse in academic settings over time can provide valuable insight into the evolution of learner engagement and participation in online learning. In this study, we propose an analytical framework to capture topics and the temporal progression of learner discourse. We employed a Contextualized Topic Modeling technique on…
Descriptors: Semantics, Computer Mediated Communication, Pandemics, COVID-19
Zviel-Girshin, Rina; Kuhn, Tanara Zingano; Luís, Ana R.; Koppel, Kristina; Todorovic, Branislava Šandrih; Holdt, Špela Arhar; Tiberius, Carole; Kosem, Iztok – Research-publishing.net, 2021
Despite the unquestionable academic interest on corpus-based approaches to language education, the use of corpora by teachers in their everyday practice is still not very widespread. One way to promote usage of corpora in language teaching is by making pedagogically appropriate corpora, labelled with different types of problems (for instance,…
Descriptors: Teaching Methods, Computational Linguistics, Computer Assisted Instruction, Second Language Learning