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Sophia Soomin Lee; Robert L. Moore – Online Learning, 2024
In this systematic review, we synthesize ten empirical peer-reviewed articles published between 2019 and 2023 that used generative artificial intelligence (GenAI) for automated feedback in higher education. There are significant opportunities and challenges to integrate these tools effectively into learning environments as the demand for timely…
Descriptors: Artificial Intelligence, Higher Education, Feedback (Response), Grading
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Onur Karademir; Daniele Di Mitri; Jan Schneider; Ioana Jivet; Jörn Allmang; Sebastian Gombert; Marcus Kubsch; Knut Neumann; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: Teacher dashboards can help secondary school teachers manage online learning activities and inform instructional decisions by visualising information about class learning. However, when designing teacher dashboards, it is not trivial to choose which information to display, because not all of the vast amount of information retrieved…
Descriptors: Learning Analytics, Secondary School Teachers, Educational Technology, Design
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Xiaoyan Shi – International Journal of Web-Based Learning and Teaching Technologies, 2024
In order to avoid students' negative learning mood, contemporary teachers are required to abandon the application of spoon-feeding teaching method in English classroom teaching, adopt micro-class teaching method, highlight the teaching characteristics of being close to the people, and create an efficient, short, and special teaching space to meet…
Descriptors: Video Technology, Natural Language Processing, Captions, Technology Uses in Education
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Sebastião Quintas; Mathieu Balaguer; Julie Mauclair; Virginie Woisard; Julien Pinquier – International Journal of Language & Communication Disorders, 2024
Background: Perceptual measures such as speech intelligibility are known to be biased, variant and subjective, to which an automatic approach has been seen as a more reliable alternative. On the other hand, automatic approaches tend to lack explainability, an aspect that can prevent the widespread usage of these technologies clinically. Aims: In…
Descriptors: Speech Communication, Cancer, Human Body, Intelligibility
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Naima Debbar – International Journal of Contemporary Educational Research, 2024
Intelligent systems of essay grading constitute important tools for educational technologies. They can significantly replace the manual scoring efforts and provide instructional feedback as well. These systems typically include two main parts: a feature extractor and an automatic grading model. The latter is generally based on computational and…
Descriptors: Test Scoring Machines, Computer Uses in Education, Artificial Intelligence, Essay Tests
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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
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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Ankit Dhamija; Deepika Dhamija – Journal of Interdisciplinary Studies in Education, 2025
The rapid integration of AI in education has transformed instructional methodologies and administrative tasks. However, higher education teachers face challenges in creating quality assignments amidst increasing administrative burdens. This study investigates the potential of AI, specifically ChatGPT, in streamlining assignment creation. By…
Descriptors: College Faculty, Teacher Attitudes, Computer Attitudes, Artificial Intelligence
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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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Arinjoy Basak; Nicole P. Pitterson; Clifford A. Shaffer; Sneha Patel Davison; David A. Dillard; Jacob Grohs – Advances in Engineering Education, 2025
Motivated by the benefits of repeated deliberate practice, we created an interactive exercise system for use in an undergraduate engineering mechanics class that focuses on practicing learned fundamental concepts. These exercises take the form of traditional word problems commonly found in mechanics courses, involving things like selecting and…
Descriptors: Usability, Electronic Learning, Computer Mediated Communication, Engineering Education
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Jonathan Liu; Seth Poulsen; Erica Goodwin; Hongxuan Chen; Grace Williams; Yael Gertner; Diana Franklin – ACM Transactions on Computing Education, 2025
Algorithm design is a vital skill developed in most undergraduate Computer Science (CS) programs, but few research studies focus on pedagogy related to algorithms coursework. To understand the work that has been done in the area, we present a systematic survey and literature review of CS Education studies. We search for research that is both…
Descriptors: Teaching Methods, Algorithms, Design, Computer Science Education
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Wallace N. Pinto Jr.; Jinnie Shin – Journal of Educational Measurement, 2025
In recent years, the application of explainability techniques to automated essay scoring and automated short-answer grading (ASAG) models, particularly those based on transformer architectures, has gained significant attention. However, the reliability and consistency of these techniques remain underexplored. This study systematically investigates…
Descriptors: Automation, Grading, Computer Assisted Testing, Scoring
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