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Tae Yeon Kwon; A. Corinne Huggins-Manley; Jonathan Templin; Mingying Zheng – Journal of Educational Measurement, 2024
In classroom assessments, examinees can often answer test items multiple times, resulting in sequential multiple-attempt data. Sequential diagnostic classification models (DCMs) have been developed for such data. As student learning processes may be aligned with a hierarchy of measured traits, this study aimed to develop a sequential hierarchical…
Descriptors: Classification, Accuracy, Student Evaluation, Sequential Approach
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Liqing Qiu; Lulu Wang – IEEE Transactions on Education, 2025
In recent years, knowledge tracing (KT) within intelligent tutoring systems (ITSs) has seen rapid development. KT aims to assess a student's knowledge state based on past performance and predict the correctness of the next question. Traditional KT often treats questions with different difficulty levels of the same concept as identical…
Descriptors: Intelligent Tutoring Systems, Technology Uses in Education, Questioning Techniques, Student Evaluation
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Tae Yeon Kwon; A. Corinne Huggins-Manley; Jonathan Templin; Mingying Zheng – Grantee Submission, 2023
In classroom assessments, examinees can often answer test items multiple times, resulting in sequential multiple-attempt data. Sequential diagnostic classification models (DCMs) have been developed for such data. As student learning processes may be aligned with a hierarchy of measured traits, this study aimed to develop a sequential hierarchical…
Descriptors: Classification, Accuracy, Student Evaluation, Sequential Approach
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George Kinnear; Paola Iannone; Ben Davies – Educational Studies in Mathematics, 2025
Example-generation tasks have been suggested as an effective way to both promote students' learning of mathematics and assess students' understanding of concepts. E-assessment offers the potential to use example-generation tasks with large groups of students, but there has been little research on this approach so far. Across two studies, we…
Descriptors: Mathematics Skills, Learning Strategies, Skill Development, Student Evaluation
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Samah AlKhuzaey; Floriana Grasso; Terry R. Payne; Valentina Tamma – International Journal of Artificial Intelligence in Education, 2024
Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…
Descriptors: Test Items, Test Construction, Difficulty Level, Prediction
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Lin, Jing-Wen; Chao, Hsiu-Yi – Science Education, 2024
Science education reforms advocate modeling as a core practice in which "analogy" is a significant form and "analogical modeling" is a creative process for scientific explanation and discovery. This study adopts the self-generated analogical modeling approach involving electricity, which considers all the modeling subprocesses…
Descriptors: Science Education, Logical Thinking, Energy, Models
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Yang Zhen; Xiaoyan Zhu – Educational and Psychological Measurement, 2024
The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…
Descriptors: Artificial Intelligence, Models, Cheating, Identification
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Kaufmann, Esther – Journal of Education for Teaching: International Research and Pedagogy, 2023
Teachers need to judge students accurately to ensure social justice within classrooms. Currently, many reviews have estimated how accurately teachers overall judge students, but only a few provided clues about how teachers' accuracy could be improved. To provide insight regarding the sources of teachers' (in)accuracy, we review and synthesise lens…
Descriptors: Teacher Education, Models, Social Justice, Accuracy
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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
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Nicholas Charlton; Richard Newsham-West – Higher Education Research and Development, 2024
Program-level assessment is a holistic approach for arranging assessments throughout a degree program that supports sequential development of discipline knowledge, transferable skills and career readiness. Currently, the modular arrangement of courses means that student learning is partial, limited to passing the assessment and compartmentalized…
Descriptors: Models, Program Evaluation, Holistic Approach, Higher Education
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Forthmann, Boris; Förster, Natalie; Souvignier, Elmar – Journal of Intelligence, 2022
Monitoring the progress of student learning is an important part of teachers' data-based decision making. One such tool that can equip teachers with information about students' learning progress throughout the school year and thus facilitate monitoring and instructional decision making is learning progress assessments. In practical contexts and…
Descriptors: Learning Processes, Progress Monitoring, Robustness (Statistics), Bayesian Statistics
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Deepa Ramadurai; Judy A. Shea – Advances in Health Sciences Education, 2024
Teaching equitable clinical practice is of critical importance, yet how best to do so remains unknown. Educators utilize implementation science frameworks to disseminate clinical evidence-based practices (EBP). The Health Equity Implementation Framework (HEIF) is one of these frameworks, and it delineates how health equity may be concomitantly…
Descriptors: Social Differences, Medical Education, Health Services, Guidelines
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Constance Tucker; Sarah Jacobs; Kirstin Moreno – Intersection: A Journal at the Intersection of Assessment and Learning, 2024
Learning outcomes and assessment frameworks guide educators in curricular decisionmaking, impact assessment, gap identification, and equity evaluation, aligning with anticipated learning objectives. Common frameworks include Bloom's taxonomy, Kirkpatrick's model, Fink's taxonomy, and Moore's Outcomes model. The authors identified a lack of focus…
Descriptors: Student Evaluation, Outcomes of Education, Taxonomy, Decision Making
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Groth, Randall E.; Choi, Yoojin – Educational Studies in Mathematics, 2023
Learning to interpret data in context is an important educational outcome. To assess students' attainment of this outcome, it is necessary to examine the interplay between their contextual and statistical reasoning. We describe a research method designed to do so. The method draws upon Toulmin's (1958, 2003) model of argumentation for the first…
Descriptors: Student Evaluation, Data Interpretation, Evaluative Thinking, Evaluation Methods
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Tabares, Marta S.; Vallejo, Paola; Montoya, Alex; Correa, Daniel – Journal of Computing in Higher Education, 2022
Understanding learners' behavior is the key to the success of any learning process. The more we know about them, the more likely we can personalize learning experiences and provide successful feedback. This paper presents a feedback model implemented in a ubiquitous microlearning environment based on contextual and behavioral information and…
Descriptors: Feedback (Response), Models, Student Behavior, Educational Environment
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