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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
He, Dan – ProQuest LLC, 2023
This dissertation examines the effectiveness of machine learning algorithms and feature engineering techniques for analyzing process data and predicting test performance. The study compares three classification approaches and identifies item-specific process features that are highly predictive of student performance. The findings suggest that…
Descriptors: Artificial Intelligence, Data Analysis, Algorithms, Classification
Gani, Mohammed Osman; Ayyasamy, Ramesh Kumar; Sangodiah, Anbuselvan; Fui, Yong Tien – Education and Information Technologies, 2023
The automated classification of examination questions based on Bloom's Taxonomy (BT) aims to assist the question setters so that high-quality question papers are produced. Most studies to automate this process adopted the machine learning approach, and only a few utilised the deep learning approach. The pre-trained contextual and non-contextual…
Descriptors: Models, Artificial Intelligence, Natural Language Processing, Writing (Composition)
Monica Casella; Pasquale Dolce; Michela Ponticorvo; Nicola Milano; Davide Marocco – Educational and Psychological Measurement, 2024
Short-form development is an important topic in psychometric research, which requires researchers to face methodological choices at different steps. The statistical techniques traditionally used for shortening tests, which belong to the so-called exploratory model, make assumptions not always verified in psychological data. This article proposes a…
Descriptors: Artificial Intelligence, Test Construction, Test Format, Psychometrics
Andrea Zanellati; Daniele Di Mitri; Maurizio Gabbrielli; Olivia Levrini – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing is a well-known problem in AI for education, consisting of monitoring how the knowledge state of students changes during the learning process and accurately predicting their performance in future exercises. In recent years, many advances have been made thanks to various machine learning and deep learning techniques. Despite their…
Descriptors: Artificial Intelligence, Prior Learning, Knowledge Management, Models
Jun Liu; Cong Wang; Zile Liu; Minghui Gao; Yanhua Xu; Jiayu Chen; Yichun Cheng – Asia Pacific Journal of Education, 2024
The rapid advancement of generative AI technology offers new opportunities for the innovation and transformation of education. However, this also brings forth risks and challenges, including the potential to exacerbate educational inequality and integrity. This study aims to address the extensive controversies surrounding the application of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Bibliometrics, Content Analysis
Gwo-Jen Hwang; Kai-Yu Tang; Yun-Fang Tu – Interactive Learning Environments, 2024
This study provides research-based evidence to profile: (1) the roles of artificial intelligence in nursing; (2) its research applications; and (3) the research trends for future study. On the basis of the PRISMA statement, a series of AI and nursing education related keywords from the literature were used to retrieve high-quality journal articles…
Descriptors: Foreign Countries, Nursing Education, Nursing, Nursing Research
Chih-Pu Dai; Fengfeng Ke; Yanjun Pan; Jewoong Moon; Zhichun Liu – Educational Psychology Review, 2024
Computer-based simulations for learning offer affordances for advanced capabilities and expansive possibilities for knowledge construction and skills application. Virtual agents, when powered by artificial intelligence (AI), can be used to scaffold personalized and adaptive learning processes. However, a synthesis or a systematic evaluation of the…
Descriptors: Computer Simulation, Artificial Intelligence, Educational Technology, Program Effectiveness