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Yoonseo Kim – TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 2025
This study explores the potential of OpenAI's ChatGPT-4 (gpt-4-0613) as an automated essay scoring (AES) tool in a trial involving 300 essays from an American university's academic English program placement test. Three prompting strategies (minimal/detailed rubric, require/not require rationale, and with/without scoring examples) were tested for…
Descriptors: Automation, Scoring, Artificial Intelligence, Placement Tests
Luyang Fang; Gyeonggeon Lee; Xiaoming Zhai – Journal of Educational Measurement, 2025
Machine learning-based automatic scoring faces challenges with imbalanced student responses across scoring categories. To address this, we introduce a novel text data augmentation framework that leverages GPT-4, a generative large language model specifically tailored for imbalanced datasets in automatic scoring. Our experimental dataset consisted…
Descriptors: Computer Assisted Testing, Artificial Intelligence, Automation, Scoring
Zhelyazko Terziyski; Daniela Orozova; Nadezhda Angelova; Margarita Terziyska – International Association for Development of the Information Society, 2025
The use of the Internet of Things (IoT) in e-learning creates new opportunities for automating administrative tasks and enhancing interaction between teachers and students. This paper introduces an IoT-based system for automatic attendance tracking that fits into an intelligent learning environment. The system utilizes a local web server that…
Descriptors: Internet, Networks, Electronic Learning, Automation
Feng Hsu Wang – IEEE Transactions on Learning Technologies, 2024
Due to the development of deep learning technology, its application in education has received increasing attention from researchers. Intelligent agents based on deep learning technology can perform higher order intellectual tasks than ever. However, the high deployment cost of deep learning models has hindered their widespread application in…
Descriptors: Learning Processes, Models, Man Machine Systems, Cooperative Learning
Karima Bouziane; Abdelmounim Bouziane – Discover Education, 2024
The evaluation of student essay corrections has become a focal point in understanding the evolving role of Artificial Intelligence (AI) in education. This study aims to assess the accuracy, efficiency, and cost-effectiveness of ChatGPT's essay correction compared to human correction, with a primary focus on identifying and rectifying grammatical…
Descriptors: Artificial Intelligence, Essays, Writing Skills, Grammar
Valdemar Švábenský; Jan Vykopal; Pavel Celeda; Ján Dovjak – Education and Information Technologies, 2024
Computer-supported learning technologies are essential for conducting hands-on cybersecurity training. These technologies create environments that emulate a realistic IT infrastructure for the training. Within the environment, training participants use various software tools to perform offensive or defensive actions. Usage of these tools generates…
Descriptors: Computer Security, Information Security, Training, Feedback (Response)
Joseph E. Aoun – MIT Press, 2024
In 2017, "Robot-Proof," the first edition, foresaw the advent of the AI economy and called for a new model of higher education designed to help human beings flourish alongside smart machines. That economy has arrived. Creative tasks that, seven years ago, seemed resistant to automation can now be performed with a simple prompt. As a…
Descriptors: Artificial Intelligence, Higher Education, Educational Technology, Technology Uses in Education
Brian E. Clauser; Victoria Yaneva; Peter Baldwin; Le An Ha; Janet Mee – Applied Measurement in Education, 2024
Multiple-choice questions have become ubiquitous in educational measurement because the format allows for efficient and accurate scoring. Nonetheless, there remains continued interest in constructed-response formats. This interest has driven efforts to develop computer-based scoring procedures that can accurately and efficiently score these items.…
Descriptors: Computer Uses in Education, Artificial Intelligence, Scoring, Responses
Ramnarain-Seetohul, Vidasha; Bassoo, Vandana; Rosunally, Yasmine – Education and Information Technologies, 2022
In automated essay scoring (AES) systems, similarity techniques are used to compute the score for student answers. Several methods to compute similarity have emerged over the years. However, only a few of them have been widely used in the AES domain. This work shows the findings of a ten-year review on similarity techniques applied in AES systems…
Descriptors: Computer Assisted Testing, Essays, Scoring, Automation
Jones, Michael; Idrovo-Carlier, Sandra; Rodriguez, Alfredo J. – Higher Education, Skills and Work-based Learning, 2022
Purpose: The purpose of this paper is to identify workforce skills that protect an occupation from elimination due to automation technology. Design/methodology/approach: The authors apply a Gaussian process (GP) classifier, based on the level of non-automatable work activities in an occupation, to USA and Colombian occupational datasets. Findings:…
Descriptors: Foreign Countries, Automation, Job Skills, Occupations
Ferrara, Steve; Qunbar, Saed – Journal of Educational Measurement, 2022
In this article, we argue that automated scoring engines should be transparent and construct relevant--that is, as much as is currently feasible. Many current automated scoring engines cannot achieve high degrees of scoring accuracy without allowing in some features that may not be easily explained and understood and may not be obviously and…
Descriptors: Artificial Intelligence, Scoring, Essays, Automation
Zesch, Torsten; Horbach, Andrea; Zehner, Fabian – Educational Measurement: Issues and Practice, 2023
In this article, we systematize the factors influencing performance and feasibility of automatic content scoring methods for short text responses. We argue that performance (i.e., how well an automatic system agrees with human judgments) mainly depends on the linguistic variance seen in the responses and that this variance is indirectly influenced…
Descriptors: Influences, Academic Achievement, Feasibility Studies, Automation
Matthews, Benjamin; Shannon, Barrie; Roxburgh, Mark – International Journal of Art & Design Education, 2023
Digital automation is on the rise in a diverse range of industries. The technologies employed here often make use of artificial intelligence (AI) and its common form, machine learning (ML) to augment or replace the work completed by human agents. The recent emergence of a variety of design automation platforms inspired the authors to undertake a…
Descriptors: Artificial Intelligence, Automation, Design, Electronic Learning
Arantes, Janine Aldous; Vicars, Mark – Qualitative Research Journal, 2023
Purpose: The purpose of this paper is to examine how automation in the ever-changing technological landscape is increasing integrated into, and has become a significant presence in, our personal lives. Design/methodology/approach: Through post qualitative inquiry, the authors provide a contemplation of automation and its effect on creativity, as a…
Descriptors: Automation, Creativity, Computer Mediated Communication, Interaction
Abbas, Mohsin; van Rosmalen, Peter; Kalz, Marco – IEEE Transactions on Learning Technologies, 2023
For predicting and improving the quality of essays, text analytic metrics (surface, syntactic, morphological, and semantic features) can be used to provide formative feedback to the students in higher education. In this study, the goal was to identify a sufficient number of features that exhibit a fair proxy of the scores given by the human raters…
Descriptors: Feedback (Response), Automation, Essays, Scoring

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