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Stella Y. Kim; Sungyeun Kim – Educational Measurement: Issues and Practice, 2025
This study presents several multivariate Generalizability theory designs for analyzing automatic item-generated (AIG) based test forms. The study used real data to illustrate the analysis procedure and discuss practical considerations. We collected the data from two groups of students, each group receiving a different form generated by AIG. A…
Descriptors: Generalizability Theory, Automation, Test Items, Students
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Kamila Misiejuk; Sonsoles López-Pernas; Rogers Kaliisa; Mohammed Saqr – Journal of Learning Analytics, 2025
Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…
Descriptors: Literature Reviews, Artificial Intelligence, Learning Analytics, Data Collection
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Yan Jiang; Lillie Ko-Wong; Ivan Valdovinos Gutierrez – Educational Researcher, 2025
In this essay, we explored the feasibility of utilizing artificial intelligence (AI) for qualitative data analysis in equity-focused research. Specifically, we compare thematic analyses of interview transcripts conducted by human coders with those performed by GPT-3 using a zero-shot chain-of-thought prompting strategy. Our results suggest that…
Descriptors: Artificial Intelligence, Feasibility Studies, Data Analysis, Interviews
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Zirou Lin; Hanbing Yan; Li Zhao – Journal of Computer Assisted Learning, 2024
Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…
Descriptors: Peer Evaluation, Automation, Grading, Models
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Tianqin Shi; Seung Jun Lee; Qingying Li – Decision Sciences Journal of Innovative Education, 2024
Smart supply chain management (SSCM) has recently attracted significant attention from both industry and academia, particularly in light of the COVID pandemic. This article reviews current literature on information and integration, process automation, advanced analytics, and related business curriculum in SSCM. Our survey results demonstrate a…
Descriptors: Supply and Demand, Information Management, Automation, Business Administration Education
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Jiang, Shiyan; Tang, Hengtao; Tatar, Cansu; Rosé, Carolyn P.; Chao, Jie – Learning, Media and Technology, 2023
It's critical to foster artificial intelligence (AI) literacy for high school students, the first generation to grow up surrounded by AI, to understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made to engage youth in understanding AI through…
Descriptors: Artificial Intelligence, High School Students, Models, Classification
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Karimah, Shofiyati Nur; Hasegawa, Shinobu – Smart Learning Environments, 2022
Recognizing learners' engagement during learning processes is important for providing personalized pedagogical support and preventing dropouts. As learning processes shift from traditional offline classrooms to distance learning, methods for automatically identifying engagement levels should be developed. This article aims to present a literature…
Descriptors: Learner Engagement, Automation, Electronic Learning, Literature Reviews
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Matsuda, Noboru; Wood, Jesse; Shrivastava, Raj; Shimmei, Machi; Bier, Norman – Journal of Educational Data Mining, 2022
A model that maps the requisite skills, or knowledge components, to the contents of an online course is necessary to implement many adaptive learning technologies. However, developing a skill model and tagging courseware contents with individual skills can be expensive and error prone. We propose a technology to automatically identify latent…
Descriptors: Skills, Models, Identification, Courseware
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Xiner Liu; Andres Felipe Zambrano; Ryan S. Baker; Amanda Barany; Jaclyn Ocumpaugh; Jiayi Zhang; Maciej Pankiewicz; Nidhi Nasiar; Zhanlan Wei – Journal of Learning Analytics, 2025
This study explores the potential of the large language model GPT-4 as an automated tool for qualitative data analysis by educational researchers, exploring which techniques are most successful for different types of constructs. Specifically, we assess three different prompt engineering strategies -- Zero-shot, Few-shot, and Fewshot with…
Descriptors: Coding, Artificial Intelligence, Automation, Data Analysis
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Richards, Bryant; Kolodziejczak, Nicholas; Mentzer, Kevin; Calnan, Kerry – Information Systems Education Journal, 2023
Organizations are keenly interested in employees trained in business analysis and robotic process automation. This is because those methods are growing in demand for improving efficiency in business processes. Business students exiting college must understand how to map out business processes and implement automation fundamentals to be competitive…
Descriptors: Robotics, Business Administration Education, Automation, Employment Potential
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Maio, Shannon; Dumas, Denis; Organisciak, Peter; Runco, Mark – Creativity Research Journal, 2020
In recognition of the capability of text-mining models to quantify aspects of language use, some creativity researchers have adopted text-mining models as a mechanism to objectively and efficiently score the Originality of open-ended responses to verbal divergent thinking tasks. With the increasing use of text-mining models in divergent thinking…
Descriptors: Creative Thinking, Scores, Reliability, Data Analysis
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Anand Jeyaraj – Journal of Information Systems Education, 2024
A significant activity in the business analytics process is enrichment, which deals with acquiring and combining data from external sources. While different strategies for enrichment are possible, it can be accomplished more efficiently through automation using Python scripts. Since business students may not be immersed in technology skills and…
Descriptors: Scaffolding (Teaching Technique), Business Administration Education, Data Analysis, Programming Languages
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Gardner, John; O'Leary, Michael; Yuan, Li – Journal of Computer Assisted Learning, 2021
Artificial Intelligence is at the heart of modern society with computers now capable of making process decisions in many spheres of human activity. In education, there has been intensive growth in systems that make formal and informal learning an anytime, anywhere activity for billions of people through online open educational resources and…
Descriptors: Artificial Intelligence, Educational Assessment, Formative Evaluation, Summative Evaluation
Yang, Yuanyuan; Majumdar, Rwitajit; Li, Huiyong; Akçapinar, Gökhan; Flanagan, Brendan; Ogata, Hiroaki – Research and Practice in Technology Enhanced Learning, 2021
Self-direction skill is considered a vital skill for twenty-first-century learners in both the learning context and physical activity context. Analysis skill for self-directed activities requires the students to analyze their own activity data for understanding their status in that activity. It is an important phase that determines whether an…
Descriptors: Data Analysis, Skill Development, Self Management, Independent Study
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Calvera-Isabal, Miriam; Santos, Patricia; Hoppe, H. -Ulrich; Schulten, Cleo – Comunicar: Media Education Research Journal, 2023
There is an increasing interest and growing practice in Citizen Science (CS) that goes along with the usage of websites for communication as well as for capturing and processing data and materials. From an educational perspective, it is expected that by integrating information about CS in a formal educational setting, it will inspire teachers to…
Descriptors: Citizen Participation, Science and Society, Scientific and Technical Information, Web Sites
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