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Hadis Anahideh; Nazanin Nezami; Abolfazl Asudeh – Grantee Submission, 2025
It is of critical importance to be aware of the historical discrimination embedded in the data and to consider a fairness measure to reduce bias throughout the predictive modeling pipeline. Given various notions of fairness defined in the literature, investigating the correlation and interaction among metrics is vital for addressing unfairness.…
Descriptors: Correlation, Measurement Techniques, Guidelines, Semantics
Xiaohua Liu; Yangyu Xiao – Education and Information Technologies, 2025
The bulk of recent research on generative AI (GenAI) in education mainly focused on its potential pedagogical uses as well as how students actually exploit such tools during learning, while little has been done to systematically investigate how teachers integrate those tools in different parts of their teaching process. To bridge this gap, the…
Descriptors: College Faculty, Foreign Countries, Artificial Intelligence, Second Language Instruction
Assim S. Alrajhi – Education and Information Technologies, 2025
Motivated by the proliferation of artificial intelligence that has the potential to promote self-access learning, this study utilizes a sequential explanatory quasi-experimental mixed methods design to investigate the efficacy of Google Assistant (GA) in facilitating second language (L2) vocabulary learning compared to online dictionaries. A…
Descriptors: English (Second Language), Second Language Learning, Artificial Intelligence, Vocabulary Development
Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
William Neil Littell; Brittany L. Peterson – Communication Teacher, 2025
Artificial intelligence (AI) is fundamentally reshaping classroom experiences. In this activity, students in a graduate-level project management class engaged in real-time conversations with AI- powered chatbots as though they were actual people. Students were required to perform a stakeholder analysis on the key stakeholders involved in their…
Descriptors: Artificial Intelligence, Synchronous Communication, Computer Software, Executive Function
Emmanuel Dumbuya – Online Submission, 2025
The exponential growth of online learning has catalyzed significant pedagogical innovations and transformed the educational landscape. This paper explores the emerging trends in online learning, including the shift towards blended learning, the rise of personalized learning, and the integration of technology-enhanced pedagogical practices. The…
Descriptors: Educational Trends, Electronic Learning, Educational Innovation, Teaching Methods
Kheira Ouassif; Benameur Ziani – Education and Information Technologies, 2025
The integration of educational data mining and deep neural networks, along with the adoption of the Apriori algorithm for generating association rules, focuses to resolve the problem of misdirection of students in the university, leading to their failure and dropout. This is reached through the development of an intelligent model that predicts the…
Descriptors: Predictor Variables, College Students, Majors (Students), Decision Making
Leveraging Large Language Models to Generate Course-Specific Semantically Annotated Learning Objects
Dominic Lohr; Marc Berges; Abhishek Chugh; Michael Kohlhase; Dennis Müller – Journal of Computer Assisted Learning, 2025
Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…
Descriptors: Resource Units, Semantics, Automation, Questioning Techniques
Mark A. Flynn – Communication Teacher, 2025
This activity prompts students to go beyond the often reductionist responses to new technologies (e.g. technological determinism) by creating a media literacy-focused infographic about the role, uses, ethical concerns, and/or impact of generative AI (e.g. ChatGPT). Sample topics have included the role of AI in specific industries (e.g. film,…
Descriptors: Artificial Intelligence, Natural Language Processing, Media Literacy, Visual Aids
Pekka Isotalus; Marja Eklund; Karoliina Karppinen – Communication Teacher, 2025
Traditionally, feedback is regarded as crucial in the context of learning and teaching public speaking. In the current course, we analyzed the feedback provided to students by an artificial intelligence (AI) coach and students' learning experiences in developing public-speaking skills via this tool. The MySpeaker Rhetorich speech coach application…
Descriptors: Artificial Intelligence, Public Speaking, Feedback (Response), Teaching Methods

Conrad Borchers; Jeroen Ooge; Cindy Peng; Vincent Aleven – Grantee Submission, 2025
Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice materials. We explored how different levels of control (i.e., full AI control, shared control, and full learner control), combined…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Learner Controlled Instruction, Learning Analytics
Dayna O. H. Walker; Milan Larson – Journal of Management Education, 2025
The introduction of generative artificial intelligence (AI) technology is rapidly changing the field of human resource management (HRM). Management educators are called to prepare students for the opportunities and challenges this new technology will bring. Thus, our aim is to provide management educators with an assignment to introduce students…
Descriptors: Artificial Intelligence, Human Resources, Labor Force Development, Occupational Information
Pin-Hui Li; Hsin-Yu Lee; Chia-Ju Lin; Wei-Sheng Wang; Yueh-Min Huang – Journal of Educational Computing Research, 2025
The core purpose of integrating inquiry-based learning strategies into STEM activities is to create a challenging learning environment that stimulates students' active learning, thereby effectively enhancing their interest in learning, thinking skills, and practical application abilities. To achieve these goals, developing more technology-assisted…
Descriptors: Computer Software, Artificial Intelligence, Synchronous Communication, Active Learning
Lama Blaique; Hussein Ismail; Thomas P. Corbin Jr.; Hazem Aldabbas – Journal of Workplace Learning, 2025
Purpose: This study aims to explore the dynamic interplay between employee resilience (ER) and learning organisations, specifically examining the mediating influence of psychological empowerment (PE). Design/methodology/approach: Drawing on responses from 208 participants working in the United Arab Emirates, we used regression analysis with…
Descriptors: Foreign Countries, Employees, On the Job Training, Artificial Intelligence
Emmanuel Dumbuya – Online Submission, 2025
The integration of artificial intelligence (AI) into educational ecosystems represents a paradigm shift in pedagogical practices and educational governance. While AI offers unprecedented opportunities to personalize learning, optimize administrative processes, and provide intelligent tutoring, it poses significant challenges to maintaining human…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Technology Integration