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Liang, Zibo; Mu, Lan; Chen, Jie; Xie, Qing – Education and Information Technologies, 2023
In recent years, online learning methods have gradually been accepted by more and more people. A large number of online teaching courses and other resources (MOOCs) have also followed. To attract students' interest in learning, many scholars have built recommendation systems for MOOCs. However, students need a variety of different learning…
Descriptors: MOOCs, Artificial Intelligence, Graphs, Educational Resources
Belzak, William C. M. – Educational Measurement: Issues and Practice, 2023
Test developers and psychometricians have historically examined measurement bias and differential item functioning (DIF) across a single categorical variable (e.g., gender), independently of other variables (e.g., race, age, etc.). This is problematic when more complex forms of measurement bias may adversely affect test responses and, ultimately,…
Descriptors: Test Bias, High Stakes Tests, Artificial Intelligence, Test Items
Kumar, Rahul – International Journal for Educational Integrity, 2023
This paper presents the case of an adjunct university professor to illustrate the dilemma of using artificial intelligence (AI) technology to grade student papers. The hypothetical case discusses the benefits of using a commercial AI service to grade student papers--including discretion, convenience, pedagogical merits of consistent feedback for…
Descriptors: College Faculty, Artificial Intelligence, Grading, Research Papers (Students)
Ingrisone, Soo Jeong; Ingrisone, James N. – Educational Measurement: Issues and Practice, 2023
There has been a growing interest in approaches based on machine learning (ML) for detecting test collusion as an alternative to the traditional methods. Clustering analysis under an unsupervised learning technique appears especially promising to detect group collusion. In this study, the effectiveness of hierarchical agglomerative clustering…
Descriptors: Identification, Cooperation, Computer Assisted Testing, Artificial Intelligence
Matthews, Benjamin; Shannon, Barrie; Roxburgh, Mark – International Journal of Art & Design Education, 2023
Digital automation is on the rise in a diverse range of industries. The technologies employed here often make use of artificial intelligence (AI) and its common form, machine learning (ML) to augment or replace the work completed by human agents. The recent emergence of a variety of design automation platforms inspired the authors to undertake a…
Descriptors: Artificial Intelligence, Automation, Design, Electronic Learning
Kubsch, Marcus; Krist, Christina; Rosenberg, Joshua M. – Journal of Research in Science Teaching, 2023
Machine learning (ML) has become commonplace in educational research and science education research, especially to support assessment efforts. Such applications of machine learning have shown their promise in replicating and scaling human-driven codes of students' work. Despite this promise, we and other scholars argue that machine learning has…
Descriptors: Science Education, Educational Research, Artificial Intelligence, Models
Albornoz-De Luise, Romina Soledad; Arevalillo-Herraez, Miguel; Arnau, David – IEEE Transactions on Learning Technologies, 2023
In this article, we analyze the potential of conversational frameworks to support the adaptation of existing tutoring systems to a natural language form of interaction. We have based our research on a pilot study, in which the open-source machine learning framework Rasa has been used to build a conversational agent that interacts with an existing…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Artificial Intelligence, Models
Chen, Yawen; Zhai, Linbo – Education and Information Technologies, 2023
Accompanied with the development of storage and processing capacity of modern technology, educational data increases sharply. It is difficult for educational researchers to derive useful information from much educational data. Therefore, educational data mining techniques are important for the development of modern education field. Recently,…
Descriptors: Academic Achievement, Artificial Intelligence, Data Use, Information Retrieval
Bellaiche, Lucas; Shahi, Rohin; Turpin, Martin Harry; Ragnhildstveit, Anya; Sprockett, Shawn; Barr, Nathaniel; Christensen, Alexander; Seli, Paul – Cognitive Research: Principles and Implications, 2023
With the recent proliferation of advanced artificial intelligence (AI) models capable of mimicking human artworks, AI creations might soon replace products of human creativity, although skeptics argue that this outcome is unlikely. One possible reason this may be unlikely is that, independent of the physical properties of art, we place great value…
Descriptors: Artificial Intelligence, Art Products, Creativity, Preferences
Rahayu, Nur W.; Ferdiana, Ridi; Kusumawardani, Sri S. – Education and Information Technologies, 2023
Learning path recommender systems are emerging. Given the popularity of ontology/knowledge-based systems in adaptive learning, this work reviews learning path in ontology-based recommender systems. The review covers recommendation trends, ontology use, recommendation process, recommendation technique, contributing factors, and recommender…
Descriptors: Artificial Intelligence, Learning Processes, Educational Technology, Individualized Instruction
Yibei Yin – International Journal of Web-Based Learning and Teaching Technologies, 2023
In order to study the big data of college students' employment, this paper takes the big data of college students' employment as the premise, analyzes the current employment data by establishing a DBN model, and puts forward relevant management measures, aiming to provide scientific basis for the management of graduates' employment data. The…
Descriptors: College Students, Student Employment, Data Analysis, Artificial Intelligence
Bailey, John – Education Next, 2023
This article reports on the release of AI tools that can generate text, images, music, and video with no need for complicated coding but simply in response to instructions given in natural language. AI is also raising pressing ethical questions around bias, appropriate use, and plagiarism. In the realm of education, this technology will influence…
Descriptors: Artificial Intelligence, Technology Uses in Education, Barriers, Affordances
Rico-Juan, Juan Ramon; Sanchez-Cartagena, Victor M.; Valero-Mas, Jose J.; Gallego, Antonio Javier – IEEE Transactions on Learning Technologies, 2023
Online Judge (OJ) systems are typically considered within programming-related courses as they yield fast and objective assessments of the code developed by the students. Such an evaluation generally provides a single decision based on a rubric, most commonly whether the submission successfully accomplished the assignment. Nevertheless, since in an…
Descriptors: Artificial Intelligence, Models, Student Behavior, Feedback (Response)
Ted M. Clark – Journal of Chemical Education, 2023
The artificial intelligence chatbot ChatGPT was used to answer questions from final exams administered in two general chemistry courses, including questions with closed-response format and with open-response format. For closed-response questions, ChatGPT was very capable at identifying the concept even when the question included a great deal of…
Descriptors: Artificial Intelligence, Science Tests, Chemistry, Science Instruction
Qiwei He; Qingzhou Shi; Elizabeth L. Tighe – Grantee Submission, 2023
Increased use of computer-based assessments has facilitated data collection processes that capture both response product data (i.e., correct and incorrect) and response process data (e.g., time-stamped action sequences). Evidence suggests a strong relationship between respondents' correct/incorrect responses and their problem-solving proficiency…
Descriptors: Artificial Intelligence, Problem Solving, Classification, Data Use