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Benny G. Johnson; Jeffrey S. Dittel; Rachel Van Campenhout – International Educational Data Mining Society, 2024
Combining formative practice with the primary expository content in a learning by doing method is a proven approach to increase student learning. Artificial intelligence has led the way for automatic question generation (AQG) systems that can generate volumes of formative practice otherwise prohibitive with human effort. One such AQG system was…
Descriptors: Artificial Intelligence, Automation, Textbooks, Questioning Techniques
Firoozi, Tahereh; Mohammadi, Hamid; Gierl, Mark J. – Educational Measurement: Issues and Practice, 2023
Research on Automated Essay Scoring has become increasing important because it serves as a method for evaluating students' written responses at scale. Scalable methods for scoring written responses are needed as students migrate to online learning environments resulting in the need to evaluate large numbers of written-response assessments. The…
Descriptors: Active Learning, Automation, Scoring, Essays
Fernandez-Gauna, Borja; Rojo, Naiara; Graña, Manuel – International Journal of Educational Technology in Higher Education, 2023
We describe an automated assessment process for team-coding assignments based on DevOps best practices. This system and methodology includes the definition of Team Performance Metrics measuring properties of the software developed by each team, and their correct use of DevOps techniques. It tracks the progress on each of metric by each group. The…
Descriptors: Computer Software, Programming, Coding, Teamwork
Martin, Joshua L.; Wright, Kelly Elizabeth – Applied Linguistics, 2023
Research on bias in artificial intelligence has grown exponentially in recent years, especially around racial bias. Many modern technologies which impact people's lives have been shown to have significant racial biases, including automatic speech recognition (ASR) systems. Emerging studies have found that widely-used ASR systems function much more…
Descriptors: Automation, Speech Communication, Black Dialects, Racism
Buckingham Shum, Simon; Lim, Lisa-Angelique; Boud, David; Bearman, Margaret; Dawson, Phillip – International Journal of Educational Technology in Higher Education, 2023
Effective learning depends on effective feedback, which in turn requires a set of skills, dispositions and practices on the part of both students and teachers which have been termed "feedback literacy." A previously published teacher "feedback literacy competency framework" has identified what is needed by teachers to implement…
Descriptors: Automation, Feedback (Response), Learning Analytics, Artificial Intelligence
Alexandra C. Salem; Robert C. Gale; Mikala Fleegle; Gerasimos Fergadiotis; Steven Bedrick – Journal of Speech, Language, and Hearing Research, 2023
Purpose: To date, there are no automated tools for the identification and fine-grained classification of paraphasias within discourse, the production of which is the hallmark characteristic of most people with aphasia (PWA). In this work, we fine-tune a large language model (LLM) to automatically predict paraphasia targets in Cinderella story…
Descriptors: Aphasia, Prediction, Story Telling, Oral Language
Alonzo, Oliver – ProQuest LLC, 2023
Automatic Text Simplification (ATS) consists of computing techniques to rewrite text to make it simpler to read and understand, and prior research has explored its use to provide reading assistance to various user groups who may benefit from reading support. Prior literacy research has identified great diversity in literacy skills among DHH…
Descriptors: Automation, Assistive Technology, Deafness, Hearing Impairments
Chaudhuri, Nandita Bhanja; Dhar, Debayan; Yammiyavar, Pradeep G. – International Journal of Technology and Design Education, 2022
Evaluating novelty in design education is subjective and generally depends on expert's referential metrics. Presently, practitioners in this field perform subjective evaluation of answers of prospective students, but many a time, humans are prone to errors when associated with repetitive tasks on large-scale. Therefore, this paper attempts to…
Descriptors: Novelty (Stimulus Dimension), Automation, Evaluation, Aptitude
Fu, Yanyan; Choe, Edison M.; Lim, Hwanggyu; Choi, Jaehwa – Educational Measurement: Issues and Practice, 2022
This case study applied the "weak theory" of Automatic Item Generation (AIG) to generate isomorphic item instances (i.e., unique but psychometrically equivalent items) for a large-scale assessment. Three representative instances were selected from each item template (i.e., model) and pilot-tested. In addition, a new analytical framework,…
Descriptors: Test Items, Measurement, Psychometrics, Test Construction
Johnson, Matthew S.; Liu, Xiang; McCaffrey, Daniel F. – Journal of Educational Measurement, 2022
With the increasing use of automated scores in operational testing settings comes the need to understand the ways in which they can yield biased and unfair results. In this paper, we provide a brief survey of some of the ways in which the predictive methods used in automated scoring can lead to biased, and thus unfair automated scores. After…
Descriptors: Psychometrics, Measurement Techniques, Bias, Automation
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
Munish Saini; Eshan Sengupta; Naman Sharma – Education and Information Technologies, 2025
To be an effective teacher, one must possess strong learning abilities. Developing lesson planning, pursuing learning objectives, and assessing post-lesson accomplishments all these depend on reflection and ongoing learning. As education is context-specific, the iterative process of preparing, reflecting, and improving is what makes teaching…
Descriptors: Artificial Intelligence, Technology Uses in Education, Nonverbal Communication, Feedback (Response)
Neslihan Kurt – Journal of Education and Learning, 2025
The aim of this research is to evaluate the OpenZeka Mini Autonomous Race Car (MARC), Turkey's first autonomous vehicle competition, within the scope of the education program. The study employed the case study technique, adopting "Responsive" and "Analytical" Program Evaluation Models as the research framework. Initially,…
Descriptors: Foreign Countries, Competition, Artificial Intelligence, Training
Michel C. Desmarais; Arman Bakhtiari; Ovide Bertrand Kuichua Kandem; Samira Chiny Folefack Temfack; Chahé Nerguizian – International Educational Data Mining Society, 2025
We propose a novel method for automated short answer grading (ASAG) designed for practical use in real-world settings. The method combines LLM embedding similarity with a nonlinear regression function, enabling accurate prediction from a small number of expert-graded responses. In this use case, a grader manually assesses a few responses, while…
Descriptors: Grading, Automation, Artificial Intelligence, Natural Language Processing
Zifeng Liu; Wanli Xing; Chenglu Li; Fan Zhang; Hai Li; Victor Minces – Journal of Learning Analytics, 2025
Creativity is a vital skill in science, technology, engineering, and mathematics (STEM)-related education, fostering innovation and problem-solving. Traditionally, creativity assessments relied on human evaluations, such as the consensual assessment technique (CAT), which are resource-intensive, time-consuming, and often subjective. Recent…
Descriptors: Creativity, Elementary School Students, Artificial Intelligence, Man Machine Systems

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