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Mark Johnson; Rafiq Saleh – Interactive Learning Environments, 2024
Educational assessment is inherently uncertain, where physiological, psychological and social factors play an important role in establishing judgements which are assumed to be "absolute". AI and other algorithmic approaches to grading of student work strip-out uncertainty, leading to a lack of inspectability in machine judgement and…
Descriptors: Artificial Intelligence, Evaluation Methods, Technology Uses in Education, Man Machine Systems
Tingting Li; Kevin Haudek; Joseph Krajcik – Journal of Science Education and Technology, 2025
Scientific modeling is a vital educational practice that helps students apply scientific knowledge to real-world phenomena. Despite advances in AI, challenges in accurately assessing such models persist, primarily due to the complexity of cognitive constructs and data imbalances in educational settings. This study addresses these challenges by…
Descriptors: Artificial Intelligence, Scientific Concepts, Models, Automation
Mohammad Hmoud; Hadeel Swaity; Eman Anjass; Eva María Aguaded-Ramírez – Electronic Journal of e-Learning, 2024
This research aimed to develop and validate a rubric to assess Artificial Intelligence (AI) chatbots' effectiveness in accomplishing tasks, particularly within educational contexts. Given the rapidly growing integration of AI in various sectors, including education, a systematic and robust tool for evaluating AI chatbot performance is essential.…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Test Construction
Adam Finkel-Gates – Journal of Learning Development in Higher Education, 2025
This study examines the impact of AI, particularly ChatGPT, on academic integrity and assessment practices in higher education. As AI integration grows, concerns about its potential to undermine academic rigour and increase inequalities have surfaced. Through interviews with students and a lecturer, the research explores the benefits and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Evaluation Methods
Igor Kotlyar; Joe Krasman – International Journal of Educational Technology in Higher Education, 2025
As AI technologies become increasingly integrated into education, this research investigates how students react to AI-generated versus human feedback in teamwork skills assessment. In Study 1, 108 students completed a virtual teamwork simulation and received assessment feedback framed as either AI- or human-generated. Students showed a clear…
Descriptors: Student Attitudes, Student Reaction, Artificial Intelligence, Man Machine Systems
Debby R. E. Cotton; Peter A. Cotton; J. Reuben Shipway – Innovations in Education and Teaching International, 2024
The use of artificial intelligence in academia is a hot topic in the education field. ChatGPT is an AI tool that offers a range of benefits, including increased student engagement, collaboration, and accessibility. However, is also raises concerns regarding academic honesty and plagiarism. This paper examines the opportunities and challenges of…
Descriptors: Integrity, Cheating, Artificial Intelligence, Man Machine Systems
Jacob Holster – Music Educators Journal, 2024
ChatGPT is emerging as a formidable asset for music educators, poised to enhance student engagement, refine assessment methods, and automate repetitive tasks related to music teaching. The core of this perspective revolves around the use of custom prompt templates that support individualized and reflexive teaching practices. The broader…
Descriptors: Music Education, Artificial Intelligence, Natural Language Processing, Man Machine Systems
Edmund De Leon Evangelista – Contemporary Educational Technology, 2025
The rapid advancement of artificial intelligence (AI) technologies, particularly OpenAI's ChatGPT, has significantly impacted higher education institutions (HEIs), offering opportunities and challenges. While these tools enhance personalized learning and content generation, they threaten academic integrity, especially in assessment environments.…
Descriptors: Artificial Intelligence, Integrity, Educational Strategies, Natural Language Processing
Shuling Yang; Carin Appleget – Journal of Digital Learning in Teacher Education, 2025
In this study, two literacy teacher educators developed a lesson plan activity to be completed during a focus group interview. Protocols for the focus group were developed using the AI literacy framework. The purpose of the study was to explore preservice teachers' (PSTs) interactions with GenAI and how GenAI functioned as evaluators of their…
Descriptors: Artificial Intelligence, Technology Uses in Education, Lesson Plans, Preservice Teachers
Thinley Wangdi; Karma Sonam Rigdel; Tashi Dawa; Kinga Tshering – Issues in Educational Research, 2025
In the last two years, there has been a significant increase in research studies on ChatGPT and its role in educational assessment. However, there is no comprehensive systematic literature review (SLR) on the potential use of ChatGPT for educational assessment, particularly with a focus on its practices and limitations. To address this gap, our…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Evaluation Methods
Yifan Zhang – ProQuest LLC, 2024
Computational thinking (CT) has been an increasing focus of research and practice since the seminal paper by Wing in 2006, especially in pre-college (K-12) education. Barr and Stephenson defined CT as a problem-solving methodology that can be automated, transferred, and applied across disciplines. With the challenges of fitting CT into already…
Descriptors: Mental Computation, Elementary Education, Problem Solving, Intellectual Disciplines
Jae Q. J. Liu; Kelvin T. K. Hui; Fadi Al Zoubi; Zing Z. X. Zhou; Dino Samartzis; Curtis C. H. Yu; Jeremy R. Chang; Arnold Y. L. Wong – International Journal for Educational Integrity, 2024
The application of artificial intelligence (AI) in academic writing has raised concerns regarding accuracy, ethics, and scientific rigour. Some AI content detectors may not accurately identify AI-generated texts, especially those that have undergone paraphrasing. Therefore, there is a pressing need for efficacious approaches or guidelines to…
Descriptors: Artificial Intelligence, Investigations, Identification, Human Factors Engineering
Leon Furze; Mike Perkins; Jasper Roe; Jason MacVaugh – Australasian Journal of Educational Technology, 2024
The rapid adoption of generative artificial intelligence (GenAI) technologies in higher education has raised concerns about academic integrity, assessment practices and student learning. Banning or blocking GenAI tools has proven ineffective, and punitive approaches ignore the potential benefits of these technologies. As a result, assessment…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Evaluation Methods
Rosenberg, Joshua M.; Krist, Christina – Journal of Science Education and Technology, 2021
Assessing students' participation in science practices presents several challenges, especially when aiming to differentiate meaningful (vs. rote) forms of participation. In this study, we sought to use machine learning (ML) for a novel purpose in science assessment: developing a construct map for students' "consideration of generality,"…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Models
Edwards, Chad; Edwards, Autumn; Albrehi, Fatima; Spence, Patric – Communication Education, 2021
Extending previous research on the Computers Are Social Actors paradigm and the human-to-human interaction script, this study examines the interpersonal impressions of a social robot evaluator versus a human evaluator in a performance evaluation context. A between-subjects experiment was conducted to measure participants' impressions of the…
Descriptors: Robotics, Man Machine Systems, Performance Based Assessment, Task Analysis

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