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Kangkang Li; Chengyang Qian; Xianmin Yang – Education and Information Technologies, 2025
In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…
Descriptors: Student Developed Materials, Educational Quality, Automation, Artificial Intelligence
Fan Zhang; Xiangyu Wang; Xinhong Zhang – Education and Information Technologies, 2025
Intersection of education and deep learning method of artificial intelligence (AI) is gradually becoming a hot research field. Education will be profoundly transformed by AI. The purpose of this review is to help education practitioners understand the research frontiers and directions of AI applications in education. This paper reviews the…
Descriptors: Learning Processes, Artificial Intelligence, Technology Uses in Education, Educational Research
Ngoc My Bui; Jessie S. Barrot – Education and Information Technologies, 2025
With the generative artificial intelligence (AI) tool's remarkable capabilities in understanding and generating meaningful content, intriguing questions have been raised about its potential as an automated essay scoring (AES) system. One such tool is ChatGPT, which is capable of scoring any written work based on predefined criteria. However,…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
Rebecca L. Pharmer; Christopher D. Wickens; Benjamin A. Clegg – Cognitive Research: Principles and Implications, 2025
In two experiments, we examine how features of an imperfect automated decision aid influence compliance with the aid in a simplified, simulated nautical collision avoidance task. Experiment 1 examined the impact of providing transparency in the pre-task instructions regarding which attributes of the task that the aid uses to provide its…
Descriptors: Accountability, Automation, Compliance (Psychology), Task Analysis
Umar Alkafaween; Ibrahim Albluwi; Paul Denny – Journal of Computer Assisted Learning, 2025
Background: Automatically graded programming assignments provide instant feedback to students and significantly reduce manual grading time for instructors. However, creating comprehensive suites of test cases for programming problems within automatic graders can be time-consuming and complex. The effort needed to define test suites may deter some…
Descriptors: Automation, Grading, Introductory Courses, Programming
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
Ankit Dhamija; Deepika Dhamija – Journal of Interdisciplinary Studies in Education, 2025
The rapid integration of AI in education has transformed instructional methodologies and administrative tasks. However, higher education teachers face challenges in creating quality assignments amidst increasing administrative burdens. This study investigates the potential of AI, specifically ChatGPT, in streamlining assignment creation. By…
Descriptors: College Faculty, Teacher Attitudes, Computer Attitudes, Artificial Intelligence
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
Kudzayi Savious Tarisayi; Ronald Manhibi – Journal of Learning and Teaching in Digital Age, 2025
This paper critically examines the transformative potential of Artificial Intelligence (AI) in Zimbabwe's higher education system, focusing on how AI can enhance learning outcomes and optimize administrative processes. The study employs a qualitative research approach, gathering insights from key stakeholders in the educational sector to identify…
Descriptors: Foreign Countries, Artificial Intelligence, Technology Uses in Education, Higher Education
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
Guher Gorgun; Okan Bulut – Educational Measurement: Issues and Practice, 2025
Automatic item generation may supply many items instantly and efficiently to assessment and learning environments. Yet, the evaluation of item quality persists to be a bottleneck for deploying generated items in learning and assessment settings. In this study, we investigated the utility of using large-language models, specifically Llama 3-8B, for…
Descriptors: Artificial Intelligence, Quality Control, Technology Uses in Education, Automation
Sghaier Guizani; Tehseen Mazhar; Tariq Shahzad; Wasim Ahmad; Afsha Bibi; Habib Hamam – Discover Education, 2025
Artificial intelligence-driven Chatbots, especially large language models (LLMs) like GPT-4, represent significant progress in digital education. These models excel in mimicking human-like text and transforming learning and teaching methods. This study examines the development, application, and impact of LLMs in education. It highlights their role…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
Mustafa Yildiz; Hasan Kagan Keskin; Saadin Oyucu; Douglas K. Hartman; Murat Temur; Mücahit Aydogmus – Reading & Writing Quarterly, 2025
This study examined whether an artificial intelligence-based automatic speech recognition system can accurately assess students' reading fluency and reading level. Participants were 120 fourth-grade students attending public schools in Türkiye. Students read a grade-level text out loud while their voice was recorded. Two experts and the artificial…
Descriptors: Artificial Intelligence, Reading Fluency, Human Factors Engineering, Grade 4
Murat Polat; Ibrahim Hakan Karatas; Nurgün Varol – Leadership and Policy in Schools, 2025
The incorporation of artificial intelligence (AI) into educational management offers personalized learning, adaptive tutoring, and efficient resource management. However, ethical considerations such as fairness, transparency, accountability, and privacy are crucial. This paper reviews literature and conducts a bibliometric analysis on ethical AI…
Descriptors: Ethics, Artificial Intelligence, Technology Uses in Education, Leadership