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Tegan Little; Phillip Dawson; David Boud; Joanna Tai – Assessment & Evaluation in Higher Education, 2025
Whilst contemporary ideas of feedback provide multiple insights into how feedback should be processed and enacted by students in a recipient role, little attention has been paid to understand what it takes for students to provide effective feedback to others. This conceptual paper draws on literature from peer feedback and feedback literacy to…
Descriptors: Peer Evaluation, Feedback (Response), Social Environment, Emotional Response
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Shulan Xia; Peida Zhan; Kennedy Kam Ho Chan; Lijun Wang – Journal of Research in Science Teaching, 2024
Concept mapping is widely used as a tool for assessing students' understanding of science. To fully realize the diagnostic potential of concept mapping, a scoring method that not only provides an objective and accurate assessment of students' drawn concept maps but also provides a detailed understanding of students' proficiency and deficiencies in…
Descriptors: Concept Mapping, Student Evaluation, Scoring, Science Education
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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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Khaleel Asyraaf Mat Sanusi; Deniz Iren; Nardie Fanchamps; Mai Geisen; Roland Klemke – Educational Technology Research and Development, 2025
Psychomotor skill training has traditionally relied on the physical presence of both teacher and learner for effective demonstrations and feedback, posing challenges for remote and self-directed learning. Technological advancements have given rise to immersive learning environments (ILEs), offering novel solutions for interactive and multimodal…
Descriptors: Psychomotor Skills, Skill Development, Computer Simulation, Electronic Learning
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Koen Suzelis; Gabriel Mott; John Curiel – Journal of Academic Ethics, 2025
Student evaluations of teaching (SET) act as the primary means to gauge instructor effectiveness. Likewise, SETs provide the primary qualitative feedback to instructors via student comments. However, mostly students with strong feelings tend to write comments. Among the most recallable are toxic comments: comments that are unhelpful/hurtful in…
Descriptors: Student Evaluation of Teacher Performance, Automation, Identification, Student Attitudes
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Stephanie Fuchs; Alexandra Werth; Cristóbal Méndez; Jonathan Butcher – Journal of Engineering Education, 2025
Background: High-quality feedback is crucial for academic success, driving student motivation and engagement while research explores effective delivery and student interactions. Advances in artificial intelligence (AI), particularly natural language processing (NLP), offer innovative methods for analyzing complex qualitative data such as feedback…
Descriptors: Artificial Intelligence, Training, Data Analysis, Natural Language Processing
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Elena Cano García; Andrea Jardí Ferré; Laia Lluch Molins; Ludmila Martins Gironelli – Assessment & Evaluation in Higher Education, 2024
Evaluative judgement is the ability to understand what constitutes the quality of a performance or product and to apply this understanding in the evaluation of one's own or another's task. It is, therefore, a key element in the development of learning to learn competences linked to professionalism. Experiences that explicitly encourage it in…
Descriptors: Feedback (Response), Peer Evaluation, Evaluative Thinking, College Students
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Orkun Kocak; Sahin Idil – Journal of Education in Science, Environment and Health, 2025
This study is developing a Deep Learning model automating the coding of drawings students provide about climate change phenomena in our world, as a learning contribution through formative assessment. We started first with ResNet50 architecture, but ultimately, we settled on MobileNetV2 reduced architecture for the sake of being able to integrate…
Descriptors: Climate, Artificial Intelligence, Accuracy, Environmental Education
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Khaldi, Amina; Bouzidi, Rokia; Nader, Fahima – Smart Learning Environments, 2023
In recent years, university teaching methods have evolved and almost all higher education institutions use e-learning platforms to deliver courses and learning activities. However, these digital learning environments present significant dropout and low completion rates. This is primarily due to the lack of student motivation and engagement.…
Descriptors: Gamification, Electronic Learning, Higher Education, Recognition (Achievement)
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Zheng, Rong; Busemeyer, Jerome R.; Nosofsky, Robert M. – Cognitive Science, 2023
Though individual categorization or decision processes have been studied separately in many previous investigations, few studies have investigated how they interact by using a two-stage task of first categorizing and then deciding. To address this issue, we investigated a categorization-decision task in two experiments. In both, participants were…
Descriptors: Classification, Decision Making, Task Analysis, Feedback (Response)
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Liu, Chengyuan; Doshi, Divyang; Shang, Ruixuan; Cui, Jialin; Jia, Qinjin; Gehringer, Edward – Journal of Educational Data Mining, 2023
A peer-assessment system provides a structured learning process for students and allows them to write textual feedback on each other's assignments and projects. This helps instructors or teaching assistants perform a more comprehensive evaluation of students' work. However, the contribution of peer assessment to students' learning relies heavily…
Descriptors: Peer Evaluation, Student Evaluation, Feedback (Response), Educational Quality
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Soomaiya Hamid; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
E-learning is the process of sharing knowledge out of the traditional classrooms through different online tools using internet. The availability and use of these tools are not easy for every student. Many institutions gather e-learning feedback to know the problems of students to improve their systems. In e-learning systems, typically a high…
Descriptors: Feedback (Response), Electronic Learning, Automation, Classification
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Daniel Corral; Shana K. Carpenter – Cognitive Research: Principles and Implications, 2024
We report six experiments that examine how two essential components of a category-learning paradigm, training and feedback, can be manipulated to maximize learning and transfer of real-world, complex concepts. Some subjects learned through classification and were asked to classify hypothetical experiment scenarios as either true or non-true…
Descriptors: Concept Formation, Teaching Methods, Observational Learning, Classification
Zachary Conrad – ProQuest LLC, 2021
In the past twenty-five years, assessment developers and educators have been seeking ways to make assessments more informative and to advance understandings of students' cognitive processes (Ercikan, 2006; Leighton & Gierl, 2007). Demands for personalized formative assessment feedback have stimulated interest in the application of diagnostic…
Descriptors: Evaluation, Test Validity, Feedback (Response), Individualized Instruction
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Kenan Dikilitas; Tim Marshall; Masoumeh Shahverdi – Palgrave Macmillan, 2025
This open access book maps the role of challenge-based learning (CBL) in the transformation of higher education pedagogy, towards being sector-informed as well as student-driven. CBL democratises the process of learning by repositioning students as drivers, who are empowered to make decisions on course content, assess needs in the real world and…
Descriptors: Teaching Methods, Student Centered Learning, Problem Based Learning, Program Implementation
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