Publication Date
| In 2026 | 0 |
| Since 2025 | 6 |
| Since 2022 (last 5 years) | 9 |
| Since 2017 (last 10 years) | 13 |
| Since 2007 (last 20 years) | 21 |
Descriptor
Source
Author
| Allen, Laura | 1 |
| Almeroth, Kevin | 1 |
| Ana Laura Blanco Troncoso | 1 |
| Balyan, Renu | 1 |
| Banawan, Michelle | 1 |
| Baofeng Ren | 1 |
| Benjamin Brummernhenrich | 1 |
| Binelli, Vincent | 1 |
| Boxuan Ma | 1 |
| Carmichael, P. | 1 |
| Chaohua Ou | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 15 |
| Reports - Research | 14 |
| Speeches/Meeting Papers | 5 |
| Reports - Descriptive | 4 |
| Reports - Evaluative | 3 |
| Tests/Questionnaires | 1 |
Education Level
| Higher Education | 21 |
| Postsecondary Education | 21 |
| High Schools | 2 |
| Secondary Education | 2 |
| Adult Education | 1 |
| Elementary Secondary Education | 1 |
Audience
Location
| United Kingdom | 3 |
| California | 1 |
| Germany | 1 |
| Philippines | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Darius Hennekeuser; Daryoush Daniel Vaziri; David Golchinfar; Dirk Schreiber; Gunnar Stevens – International Journal of Artificial Intelligence in Education, 2025
Large Language Models (LLMs) are rapidly gaining attention across the open-source and commercial fields, bolstered by their constantly growing capabilities. While such models have a vast array of applications, their integration into higher education--as supportive tools for lecturers--has been largely unexplored. Exploring this area entails…
Descriptors: Lecture Method, College Instruction, Higher Education, College Faculty
Ishrat Ahmed; Wenxing Liu; Rod D. Roscoe; Elizabeth Reilley; Danielle S. McNamara – Grantee Submission, 2025
Large language models (LLMs) are increasingly being utilized to develop tools and services in various domains, including education. However, due to the nature of the training data, these models are susceptible to inherent social or cognitive biases, which can influence their outputs. Furthermore, their handling of critical topics, such as privacy…
Descriptors: Artificial Intelligence, Natural Language Processing, Computer Mediated Communication, College Students
Tianyuan Yang; Baofeng Ren; Chenghao Gu; Boxuan Ma; Shin 'ichi Konomi – International Association for Development of the Information Society, 2024
As education increasingly shifts towards a technology-driven model, artificial intelligence systems like ChatGPT are gaining recognition for their potential to enhance educational support. In university education and MOOC environments, students often select courses that align with their specific needs. During this process, access to information…
Descriptors: Concept Formation, Artificial Intelligence, Computer Uses in Education, MOOCs
Wenhao Wang; Etsuko Kumamoto; Chengjiu Yin – International Educational Data Mining Society, 2024
The e-book system, widely used in learning and teaching, has generated a large amount of log data over time. Researchers analyzing these data have discovered the existence of student's jump back behavior, which is positively correlated with academic achievement. However, they also found that this behavior has the disadvantage of low efficiency. To…
Descriptors: Electronic Books, Natural Language Processing, Artificial Intelligence, Reading
Michelle Ehrenpreis; John DeLooper – portal: Libraries and the Academy, 2025
In November 2019, the Leonard Lief Library implemented Ivy.ai, a proprietary chatbot on its website. This implementation was the first academic library installation of a vendor-supplied chatbot to be discussed in the professional literature. This chatbot functioned as a new tool that assisted users seeking information from the library website.…
Descriptors: Academic Libraries, Artificial Intelligence, Natural Language Processing, Intelligent Tutoring Systems
Wesley Morris; Scott Crossley; Langdon Holmes; Chaohua Ou; Mihai Dascalu; Danielle McNamara – International Journal of Artificial Intelligence in Education, 2025
As intelligent textbooks become more ubiquitous in classrooms and educational settings, the need to make them more interactive arises. An alternative is to ask students to generate knowledge in response to textbook content and provide feedback about the produced knowledge. This study develops Natural Language Processing models to automatically…
Descriptors: Formative Evaluation, Feedback (Response), Textbooks, Artificial Intelligence
Benjamin Brummernhenrich; Christian L. Paulus; Regina Jucks – British Journal of Educational Technology, 2025
Generative AI systems like chatbots are increasingly being introduced into learning, teaching and assessment scenarios at universities. While previous research suggests that users treat chatbots like humans, computer systems are still often perceived as less trustworthy, potentially impairing their usefulness in learning contexts. How are…
Descriptors: Higher Education, Artificial Intelligence, College Students, Feedback (Response)
Wan, Qian; Crossley, Scott; Banawan, Michelle; Balyan, Renu; Tian, Yu; McNamara, Danielle; Allen, Laura – International Educational Data Mining Society, 2021
The current study explores the ability to predict argumentative claims in structurally-annotated student essays to gain insights into the role of argumentation structure in the quality of persuasive writing. Our annotation scheme specified six types of argumentative components based on the well-established Toulmin's model of argumentation. We…
Descriptors: Essays, Persuasive Discourse, Automation, Identification
Mario de la Puente; Jose Torres; Ana Laura Blanco Troncoso; Yuraima Yuliza Hernández Meza; Jenny Xiomara Marquez Carrascal – Smart Learning Environments, 2024
This study investigated the effectiveness of using ChatGPT, a large language model (LLM), to enhance critical thinking and argumentation skills among undergraduate students studying international relations in a developing nation context. A total of 95 participants were randomly assigned to an experimental group (n = 48) and a control group (n =…
Descriptors: Artificial Intelligence, Computer Uses in Education, Critical Thinking, Persuasive Discourse
Jia, Qinjin; Cui, Jialin; Xiao, Yunkai; Liu, Chengyuan; Rashid, Parvez; Gehringer, Edward – International Educational Data Mining Society, 2021
Peer assessment has been widely applied across diverse academic fields over the last few decades, and has demonstrated its effectiveness. However, the advantages of peer assessment can only be achieved with high-quality peer reviews. Previous studies have found that high-quality review comments usually comprise several features (e.g., contain…
Descriptors: Peer Evaluation, Models, Artificial Intelligence, Evaluation Methods
Maricar C. Tegero; Jay P. Mabini – Journal of Teaching and Learning, 2025
This study examines the role of AI chatbots in simulating real-world teaching scenarios and developing core teaching competencies among pre-service teachers. Guided by the SAMR model, the research employed a single-case qualitative design involving eight Bachelor of Physical Education interns from a teacher education institution in the Eastern…
Descriptors: Foreign Countries, Artificial Intelligence, Preservice Teachers, Preservice Teacher Education
Lu, Owen H. T.; Huang, Anna Y. Q.; Tsai, Danny C. L.; Yang, Stephen J. H. – Educational Technology & Society, 2021
Human-guided machine learning can improve computing intelligence, and it can accurately assist humans in various tasks. In education research, artificial intelligence (AI) is applicable in many situations, such as predicting students' learning paths and strategies. In this study, we explore the benefits of repetitive practice of short-answer…
Descriptors: Test Items, Artificial Intelligence, Test Construction, Student Evaluation
Nguyen, Huy; Xiong, Wenting; Litman, Diane – International Journal of Artificial Intelligence in Education, 2017
A peer-review system that automatically evaluates and provides formative feedback on free-text feedback comments of students was iteratively designed and evaluated in college and high-school classrooms. Classroom assignments required students to write paper drafts and submit them to a peer-review system. When student peers later submitted feedback…
Descriptors: Computer Uses in Education, Computer Mediated Communication, Feedback (Response), Peer Evaluation
Feng, Hui-Hsien; Saricaoglu, Aysel; Chukharev-Hudilainen, Evgeny – CALICO Journal, 2016
Thanks to natural language processing technologies, computer programs are actively being used not only for holistic scoring, but also for formative evaluation of writing. CyWrite is one such program that is under development. The program is built upon Second Language Acquisition theories and aims to assist ESL learners in higher education by…
Descriptors: Error Patterns, Grammar, Language Proficiency, English (Second Language)
Liu, Hong P.; Klein, Jerry E. – International Association for Development of the Information Society, 2013
With the increasing complexity of technology and large quantities of data in our digital age, learning and training has become a major cost of employers. Employee competence depends more and more on how quickly one can acquire new knowledge and solve problems to meet pressing deadlines. This paper presents a practical method to use REU (Research…
Descriptors: Undergraduate Students, Student Research, Research Projects, Student Projects
Previous Page | Next Page »
Pages: 1 | 2
Peer reviewed
Direct link
