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Karl Lundengård; Peter Johnson; Phil Ramsden – International Journal for Technology in Mathematics Education, 2024
Formative feedback is important in learning. Automating the provision of specific, objective, constructive feedback to large cohorts requires complex algorithms that most teachers do not have time to develop, suggesting that a community effort is needed to create a library of specialised algorithms. We present an exemplar algorithm for a class of…
Descriptors: Automation, Feedback (Response), Algorithms, Science Education
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Xiaomeng Huang; Xavier Ochoa – Journal of Learning Analytics, 2025
Collaboration skills are fundamental to effective collaborative learning, career success, and responsible citizenship. Collaborative learning analytics (CLA) systems hold significant potential in helping students develop these skills by automatically collecting group interaction data, analyzing skill levels, and providing actionable feedback so…
Descriptors: Learning Analytics, Cooperative Learning, Cooperation, Skill Development
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Ishaya Gambo; Faith-Jane Abegunde; Omobola Gambo; Roseline Oluwaseun Ogundokun; Akinbowale Natheniel Babatunde; Cheng-Chi Lee – Education and Information Technologies, 2025
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…
Descriptors: Automation, Grading, Artificial Intelligence, Computer Assisted Testing
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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)
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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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Marcus Messer; Neil C. C. Brown; Michael Kölling; Miaojing Shi – ACM Transactions on Computing Education, 2024
We conducted a systematic literature review on automated grading and feedback tools for programming education. We analysed 121 research papers from 2017 to 2021 inclusive and categorised them based on skills assessed, approach, language paradigm, degree of automation, and evaluation techniques. Most papers assess the correctness of assignments in…
Descriptors: Automation, Grading, Feedback (Response), Programming
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Anderson Pinheiro Cavalcanti; Rafael Ferreira Mello; Dragan Gaševic; Fred Freitas – International Journal of Artificial Intelligence in Education, 2024
Educational feedback is a crucial factor in the student's learning journey, as through it, students are able to identify their areas of deficiencies and improve self-regulation. However, the literature shows that this is an area of great dissatisfaction, especially in higher education. Providing effective feedback becomes an increasingly…
Descriptors: Prediction, Feedback (Response), Artificial Intelligence, Automation
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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
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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
Sungbok Shin – ProQuest LLC, 2024
Data visualization is a powerful strategy for using graphics to represent data for effective communication and analysis. Unfortunately, creating effective data visualizations is a challenge for both novice and expert design users. The task often involves an iterative process of trial and error, which by its nature, is time-consuming. Designers…
Descriptors: Artificial Intelligence, Computer Simulation, Visualization, Feedback (Response)
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Ren, Ping; Yang, Liu; Luo, Fang – Education and Information Technologies, 2023
Student feedback is crucial for evaluating the performance of teachers and the quality of teaching. Free-form text comments obtained from open-ended questions are seldom analyzed comprehensively since it is difficult to interpret and score compared to standardized rating scales. To solve this problem, the present study employed aspect-level…
Descriptors: Student Attitudes, Student Evaluation of Teacher Performance, Feedback (Response), Prediction
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Muhammad Afzaal; Aayesha Zia; Jalal Nouri; Uno Fors – Technology, Knowledge and Learning, 2024
Self-regulated learning is an essential skill that can help students plan, monitor, and reflect on their learning in order to achieve their learning goals. However, in situations where there is a lack of effective feedback and recommendations, it becomes challenging for students to self-regulate their learning. In this paper, we propose an…
Descriptors: Feedback (Response), Artificial Intelligence, Independent Study, Automation
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Wang, Qi; Rose, Carolyn P.; Ma, Ning; Jiang, Shiyan; Bao, Haogang; Li, Yanyan – IEEE Transactions on Learning Technologies, 2022
Forums are essential components facilitating interactions in online courses. However, in large-scale courses, many posts generated, which results in learners' difficulties. First, the posts are poorly organized and some deviate from the topic, making it difficult for learners' knowledge acquisition. Second, learners cannot receive timely feedback…
Descriptors: Design, Automation, Feedback (Response), Scaffolding (Teaching Technique)
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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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