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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
Pu Wang; Yifeng Lin; Tiesong Zhao – Education and Information Technologies, 2025
With the emergence of Artificial Intelligence (AI), smart education has become an attractive topic. In a smart education system, automated classrooms and examination rooms could help reduce the economic cost of teaching, and thus improve teaching efficiency. However, existing AI algorithms suffer from low surveillance accuracies and high…
Descriptors: Supervision, Artificial Intelligence, Technology Uses in Education, Automation
Mohammad Arif Ul Alam; Geeta Verma; Eumie Jhong; Justin Barber; Ashis Kumer Biswas – International Educational Data Mining Society, 2025
The growing demand for microcredentials in education and workforce development necessitates scalable, accurate, and fair assessment systems for both soft and hard skills based on students' lived experience narratives. Existing approaches struggle with the complexities of hierarchical credentialing and the mitigation of algorithmic bias related to…
Descriptors: Microcredentials, Sex, Ethnicity, Artificial Intelligence
Jinfang Yao; Shaidatul Akma Adi Kasuma; Hisham Noori Hussain Al-Hashimy – Journal of Interdisciplinary Studies in Education, 2025
Through this paper, we aim to explore the ethical considerations related to machine translation, with a focus on eliminating bias and enhancing cultural sensitivity. By considering the experiences of individual participants, we aim to strengthen the ability of algorithms to adapt to diverse cultural environments, thereby contributing to the…
Descriptors: Translation, Automation, Ethics, Cultural Relevance
Kebede, Mihiretu M.; Le Cornet, Charlotte; Fortner, Renée Turzanski – Research Synthesis Methods, 2023
We aimed to evaluate the performance of supervised machine learning algorithms in predicting articles relevant for full-text review in a systematic review. Overall, 16,430 manually screened titles/abstracts, including 861 references identified relevant for full-text review were used for the analysis. Of these, 40% (n = 6573) were sub-divided for…
Descriptors: Automation, Literature Reviews, Artificial Intelligence, Algorithms
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)
Guher Gorgun; Okan Bulut – Education and Information Technologies, 2024
In light of the widespread adoption of technology-enhanced learning and assessment platforms, there is a growing demand for innovative, high-quality, and diverse assessment questions. Automatic Question Generation (AQG) has emerged as a valuable solution, enabling educators and assessment developers to efficiently produce a large volume of test…
Descriptors: Computer Assisted Testing, Test Construction, Test Items, Automation
Daniel J. Carragher; Daniel Sturman; Peter J. B. Hancock – Cognitive Research: Principles and Implications, 2024
The human face is commonly used for identity verification. While this task was once exclusively performed by humans, technological advancements have seen automated facial recognition systems (AFRS) integrated into many identification scenarios. Although many state-of-the-art AFRS are exceptionally accurate, they often require human oversight or…
Descriptors: Automation, Human Body, Man Machine Systems, Accuracy
Hanxiang Du; Wanli Xing; Bo Pei – Interactive Learning Environments, 2023
Participating in online communities has significant benefits to students learning in terms of students' motivation, persistence, and learning outcomes. However, maintaining and supporting online learning communities is very challenging and requires tremendous work. Automatic support is desirable in this situation. The purpose of this work is to…
Descriptors: Electronic Learning, Communities of Practice, Automation, Artificial Intelligence
Bin Tan; Hao-Yue Jin; Maria Cutumisu – Computer Science Education, 2024
Background and Context: Computational thinking (CT) has been increasingly added to K-12 curricula, prompting teachers to grade more and more CT artifacts. This has led to a rise in automated CT assessment tools. Objective: This study examines the scope and characteristics of publications that use machine learning (ML) approaches to assess…
Descriptors: Computation, Thinking Skills, Artificial Intelligence, Student Evaluation
Walter Gander – Informatics in Education, 2024
When the new programming language Pascal was developed in the 1970's, Walter Gander did not like it because because many features which he appreciated in prior programming languages were missing in Pascal. For example the block structure was gone, there were no dynamical arrays, no functions or procedures were allowed as parameters of a procedure,…
Descriptors: Computer Software, Programming Languages, Algorithms, Automation
Ulrike Padó; Yunus Eryilmaz; Larissa Kirschner – International Journal of Artificial Intelligence in Education, 2024
Short-Answer Grading (SAG) is a time-consuming task for teachers that automated SAG models have long promised to make easier. However, there are three challenges for their broad-scale adoption: A technical challenge regarding the need for high-quality models, which is exacerbated for languages with fewer resources than English; a usability…
Descriptors: Grading, Automation, Test Format, Computer Assisted Testing
Aaron Wolf – Educational Theory, 2025
Much has been written about how to improve the fairness of AI tools for decision-making but less has been said about how to approach this new field from the perspective of philosophy of education. My goal in this paper is to bring together criteria from the general algorithmic fairness literature with prominent values of justice defended by…
Descriptors: Algorithms, Artificial Intelligence, Technology Uses in Education, Educational Philosophy
Ana-Inés Renta-Davids; Marta Camarero-Figuerola; Mar Camacho – Review of Education, 2025
The increasing integration of Artificial Intelligence (AI) in educational settings is transforming the role of school leaders, reshaping how decisions are made, and introducing both opportunities and challenges. This paper presents the findings of a scoping review that synthesises the current literature on AI's impact on educational leadership.…
Descriptors: Artificial Intelligence, Instructional Leadership, Technology Integration, Decision Making
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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