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Herfort, Jonas Dreyøe; Tamborg, Andreas Lindenskov; Meier, Florian; Allsopp, Benjamin Brink; Misfeldt, Morten – Educational Studies in Mathematics, 2023
Mathematics education is like many scientific disciplines witnessing an increase in scientific output. Examining and reviewing every paper in an area in detail are time-consuming, making comprehensive reviews a challenging task. Unsupervised machine learning algorithms like topic models have become increasingly popular in recent years. Their…
Descriptors: Mathematics Education, Technology Uses in Education, Artificial Intelligence, Algorithms
Durall Gazulla, Eva; Martins, Ludmila; Fernández-Ferrer, Maite – Education and Information Technologies, 2023
Collaborative design approaches have been increasingly adopted in the design of learning technologies since they contribute to develop pedagogically inclusive and appropriate learning designs. Despite the positive reception of collaborative design strategies in technology-enhanced learning, little attention has been dedicated to analyzing the…
Descriptors: Instructional Design, Cooperation, Educational Technology, Artificial Intelligence
Mizumoto, Atsushi – Language Learning, 2023
Researchers often make claims regarding the importance of predictor variables in multiple regression analysis by comparing standardized regression coefficients (standardized beta coefficients). This practice has been criticized as a misuse of multiple regression analysis. As a remedy, I highlight the use of dominance analysis and random forests, a…
Descriptors: Predictor Variables, Artificial Intelligence, Evaluation Methods, Multiple Regression Analysis
Huo, Huade; Cui, Jiashan; Hein, Sarah; Padgett, Zoe; Ossolinski, Mark; Raim, Ruth; Zhang, Jijun – Journal of College Student Retention: Research, Theory & Practice, 2023
Student attrition represents one of the greatest challenges facing U.S. postsecondary institutions. Approximately 40 percent of students seeking a bachelor's degree do not graduate within 6 years; among nontraditional students, who make up half of the undergraduate population, dropout rates are even higher. In this study, we developed a machine…
Descriptors: Student Attrition, Postsecondary Education, Nontraditional Students, Dropout Rate
Lu, Chunyan; Minneyfield, Aarren; Jia, Min; Lu, Jun; Zheng, Yan; Huo, Jingying; Wang, Ningyi; Wu, Yihua; Brantley, Jennifer – Journal of Workplace Learning, 2023
Purpose: The purpose of this paper is to explore more agile and effective learning processes that help identify potentially high-performing staff during workplace training. Design/methodology/approach: To test the efficacy of the learning-oriented assessment (LOA) process in workplace training, a pharmaceutical sales organization implemented an…
Descriptors: Workplace Learning, Job Training, Learning Processes, Artificial Intelligence
Badal, Yudish Teshal; Sungkur, Roopesh Kevin – Education and Information Technologies, 2023
The outbreak of COVID-19 has caused significant disruption in all sectors and industries around the world. To tackle the spread of the novel coronavirus, the learning process and the modes of delivery had to be altered. Most courses are delivered traditionally with face-to-face or a blended approach through online learning platforms. In addition,…
Descriptors: Prediction, Models, Learning Analytics, Grades (Scholastic)
da Silva, Felipe Leite; Slodkowski, Bruna Kin; da Silva, Ketia Kellen Araújo; Cazella, Sílvio César – Education and Information Technologies, 2023
Recommender systems have become one of the main tools for personalized content filtering in the educational domain. Those who support teaching and learning activities, particularly, have gained increasing attention in the past years. This growing interest has motivated the emergence of new approaches and models in the field, in spite of it, there…
Descriptors: Literature Reviews, Artificial Intelligence, Educational Research, Trend Analysis
Buczak, Philip; Huang, He; Forthmann, Boris; Doebler, Philipp – Journal of Creative Behavior, 2023
Traditionally, researchers employ human raters for scoring responses to creative thinking tasks. Apart from the associated costs this approach entails two potential risks. First, human raters can be subjective in their scoring behavior (inter-rater-variance). Second, individual raters are prone to inconsistent scoring patterns…
Descriptors: Computer Assisted Testing, Scoring, Automation, Creative Thinking
Urtasun, Ainhoa – Industry and Higher Education, 2023
This report describes a teaching experience with undergraduates to approach, in a simple and practical way, artificial intelligence (AI) and machine learning (ML) -- general-purpose technologies that are highly demanded in any industry today. The article shows how business undergraduates with no prior experience in coding can use AI and ML to…
Descriptors: Undergraduate Students, Student Empowerment, Artificial Intelligence, Business Education
Sajja, Ramteja; Sermet, Yusuf; Cwiertny, David; Demir, Ibrahim – International Journal of Educational Technology in Higher Education, 2023
Miscommunication between instructors and students is a significant obstacle to post-secondary learning. Students may skip office hours due to insecurities or scheduling conflicts, which can lead to missed opportunities for questions. To support self-paced learning and encourage creative thinking skills, academic institutions must redefine their…
Descriptors: College Students, Artificial Intelligence, Teaching Assistants, Intelligent Tutoring Systems
Ramaswami, Gomathy; Susnjak, Teo; Mathrani, Anuradha; Umer, Rahila – Technology, Knowledge and Learning, 2023
Learning analytics dashboards (LADs) provide educators and students with a comprehensive snapshot of the learning domain. Visualizations showcasing student learning behavioral patterns can help students gain greater self-awareness of their learning progression, and at the same time assist educators in identifying those students who may be facing…
Descriptors: Prediction, Learning Analytics, Learning Management Systems, Identification
Daniel, Shannon; Pacheco, Mark; Smith, Blaine; Burriss, Sarah; Hundley, Melanie – Journal of Adolescent & Adult Literacy, 2023
With increased availability, accessibility, and capability of artificial intelligence (AI) tools, we argue that human processes of virtuous and multimodal composition can support meaningful communication. After defining our perspectives on writerly virtue and multimodality, we suggest how writers and their instructors might approach the use of AI…
Descriptors: Writing (Composition), Artificial Intelligence, Technology Uses in Education, Writing Processes
Scull, W. Reed; Perkins, Mark Andrew; Carrier, Jonathan W.; Barber, Michael – Community College Journal of Research and Practice, 2023
Given pressing enrollment, retention and completion issues at community colleges, the use of data analytic tools has gained more relevance for practitioners and scholars. Among these tools is machine learning, but its use is relatively new to community colleges and institutional research practice. This exploratory qualitative study examined a…
Descriptors: Community Colleges, Researchers, Knowledge Level, Artificial Intelligence
Ning, Xiaoke – International Journal of Web-Based Learning and Teaching Technologies, 2023
With the vigorous development of intelligent campus construction, great changes have taken place in the development of information technology in colleges and universities from the previous digital to intelligent development. In the teaching process, the analysis of students' classroom learning has also changed from the previous manual observation…
Descriptors: College Students, Algorithms, Student Behavior, Artificial Intelligence
Farrow, Robert – Learning, Media and Technology, 2023
Explicable AI in education (XAIED) has been proposed as a way to improve trust and ethical practice in algorithmic education. Based on a critical review of the literature, this paper argues that XAI should be understood as part of a wider socio-technical turn in AI. The socio-technical perspective indicates that explicability is a relative term.…
Descriptors: Artificial Intelligence, Algorithms, Computer Uses in Education, Language Usage

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