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Saida Ulfa; Ence Surahman; Izzul Fatawi; Hirashima Tsukasa – Electronic Journal of e-Learning, 2024
The purpose of this study was to evaluate the factors that influence behavioural intention (BI) to use the Online Summary-with Automated Feedback (OSAF) in a MOOCs platform. Task-Technology Fit (TTF) was the main framework used to analyse the match between task requirements and technology characteristics, predictng the utilisation of the…
Descriptors: MOOCs, Intention, Automation, Feedback (Response)
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Xavier Ochoa; Heru Zhao – Journal of Learning Analytics, 2024
Providing automated feedback that facilitates the practice and acquisition of oral presentation skills has been one of the notable applications of multimodal learning analytics (MmLA). However, the closedness and general unavailability of existing systems have reduced their potential impact and benefits. This work introduces OpenOPAF, an…
Descriptors: Open Source Technology, Multimedia Materials, Automation, Feedback (Response)
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Yan Xiong; Guo Xinya; Junjie Xu – Education and Information Technologies, 2024
Learning engagement is an essential indication to define students' learning pacification in the class, and its automated identification technique is the foundation for exploring how to effectively explain the motive of learning impact modifications and making intelligent teaching choices. Current research have demonstrated that there is a direct…
Descriptors: Learner Engagement, Learning Processes, Automation, Artificial Intelligence
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Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
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Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – International Journal of Artificial Intelligence in Education, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
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Sun, Xiaohua; Liu, Haochen; Liang, Peng – IEEE Transactions on Education, 2023
Contribution: This research designs an experimental education project of an automatic material magnetism properties measurement system. It explores how the do-it-yourself (DIY), hands-on establishment, and hardware-software integration experiment system could be leveraged to enhance the understanding of the electromagnetism theory and…
Descriptors: Magnets, Hands on Science, Technology Uses in Education, Automation
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Pallath, Akash; Zhang, Qiyang – Research Synthesis Methods, 2023
Systematic reviews are vital instruments for researchers to understand broad trends in a field and synthesize evidence on the effectiveness of interventions in addressing specific issues. The quality of a systematic review depends critically on having comprehensively surveyed all relevant literature on the review topic. In addition to database…
Descriptors: Literature Reviews, Online Searching, Automation, Citations (References)
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Buczak, Philip; Huang, He; Forthmann, Boris; Doebler, Philipp – Journal of Creative Behavior, 2023
Traditionally, researchers employ human raters for scoring responses to creative thinking tasks. Apart from the associated costs this approach entails two potential risks. First, human raters can be subjective in their scoring behavior (inter-rater-variance). Second, individual raters are prone to inconsistent scoring patterns…
Descriptors: Computer Assisted Testing, Scoring, Automation, Creative Thinking
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Han, Yong; Wu, Wenjun; Liang, Yu; Zhang, Lijun – IEEE Transactions on Learning Technologies, 2023
Peer grading has diverse applications in many fields, including the peer grading of open assignments in online courses. The major challenge in peer grading is improving the seriousness (reviewing carefully) of reviewers. Previous studies have proposed several incentive reward mechanisms intended to reward or punish reviewers. Although these…
Descriptors: Grading, Peer Evaluation, Online Courses, Small Classes
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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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Lee, Hyeonju; Ha, Minsu; Lee, Jurim; Aini, Rahmi Qurota; Rusmana, Ai Nurlaelasari; Sya'bandari, Yustika; Lee, Jun-Ki; Shin, Sein; Lee, Gyeong-Geon; Choo, Jaegul; Choi, Sungchul; Kim, Namhyoung; Park, Jisun – Technology, Knowledge and Learning, 2023
This study aimed to develop an automated computer scoring system (ACSS) incorporating a Korean spell checker to assess students' constructed responses and to check the efficacy of this system. To accomplish this, we examined the performance of automatic spelling correction in reporting and correcting spelling errors, the interaction of gender and…
Descriptors: Spelling, Error Correction, Foreign Countries, Automation
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García-Orosa, Berta; Canavilhas, João; Vázquez-Herrero, Jorge – Comunicar: Media Education Research Journal, 2023
The influence of algorithms on society is increasing due to their growing presence in all areas of daily life. Although we are not always aware of it, they sometimes usurp the identity of other social actors. The main purpose of this article is to address the meta-research on the field of artificial intelligence and communication from a holistic…
Descriptors: Algorithms, Artificial Intelligence, Communications, Holistic Approach
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Nespor, Jan; Fitz, Julie – Discourse: Studies in the Cultural Politics of Education, 2023
Schools produce multiple products and digitization articulates with them in different ways. In this paper we expand the frame for analyzing instructional automation by examining its implications for three scholastic products -- embodied learning, grades and test scores, and the narratives that connect the two. We draw on data from interviews with…
Descriptors: Educational Technology, Automation, Virtual Schools, Elementary Schools
Selcuk Acar; Kelly Berthiaume; Katalin Grajzel; Denis Dumas; Charles Flemister; Peter Organisciak – Gifted Child Quarterly, 2023
In this study, we applied different text-mining methods to the originality scoring of the Unusual Uses Test (UUT) and Just Suppose Test (JST) from the Torrance Tests of Creative Thinking (TTCT)--Verbal. Responses from 102 and 123 participants who completed Form A and Form B, respectively, were scored using three different text-mining methods. The…
Descriptors: Creative Thinking, Creativity Tests, Scoring, Automation
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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
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