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Kristy J. Wilson; Allison K. Chatterjee – Biochemistry and Molecular Biology Education, 2024
Students often see college courses as the presentation of disconnected facts, especially in the life sciences. Student-created Structure Mechanism/Relationship Function (SMRF) models were analyzed to understand students' abilities to make connections between genotype, phenotype, and evolution. Students were divided into two sections; one section…
Descriptors: College Students, Genetics, Models, Classification
Kajal Mahawar; Punam Rattan – Education and Information Technologies, 2025
Higher education institutions have consistently strived to provide students with top-notch education. To achieve better outcomes, machine learning (ML) algorithms greatly simplify the prediction process. ML can be utilized by academicians to obtain insight into student data and mine data for forecasting the performance. In this paper, the authors…
Descriptors: Electronic Learning, Artificial Intelligence, Academic Achievement, Prediction
Lauren A. Mason; Abigail Miller; Gregory Hughes; Holly A. Taylor – Cognitive Research: Principles and Implications, 2025
False alarming, or detecting an error when there is not one, is a pervasive problem across numerous industries. The present study investigated the role of elaboration, or additional information about non-error differences in complex visual displays, for mitigating false error responding. In Experiment 1, learners studied errors and non-error…
Descriptors: Error Correction, Error Patterns, Evaluation Methods, Visual Aids
Alexia Micallef; Philip M. Newton – Teaching of Psychology, 2024
Background: Prior research suggests that the teaching of abstract concepts can be enhanced by the use of concrete examples, but there are few controlled studies. Objective: To replicate key findings from experiment one from Rawson et al. (2015). Method: Experiment participants studied definitions of abstract concepts from psychology, either with…
Descriptors: Teaching Methods, Instructional Effectiveness, Psychology, Concept Formation
Sijia Huang; Seungwon Chung; Carl F. Falk – Journal of Educational Measurement, 2024
In this study, we introduced a cross-classified multidimensional nominal response model (CC-MNRM) to account for various response styles (RS) in the presence of cross-classified data. The proposed model allows slopes to vary across items and can explore impacts of observed covariates on latent constructs. We applied a recently developed variant of…
Descriptors: Response Style (Tests), Classification, Data, Models
Kyle Grayson; J. Paul Grayson – Quality in Higher Education, 2024
Quality of universities is best viewed through the eyes of stakeholders. Yet, in the United Kingdom and elsewhere, rankings conducted by various agencies purport to provide one overall measure of university quality. This article re-examines some of the data used by university rankers. In so doing, it shows that their information can be repackaged…
Descriptors: Universities, Educational Quality, Reputation, Institutional Evaluation
Kwaku Adu-Gyamfi; Kayla Chandler; Anthony Thompson – School Science and Mathematics, 2025
The challenge posed by algebra story problems creates a significant hurdle for many students, transcending both the mathematical content of the problem and the specific instructional background received. This study offers a distinctive contribution to the existing literature by focusing on the cognitive conditions essential for comprehension in…
Descriptors: Algebra, Mathematics Instruction, Barriers, Cognitive Processes
Huggins, Kristin A. – ProQuest LLC, 2023
Voice misclassification threatens the vocal longevity and long-term career success of voice students enrolled in higher education (HE) vocal programs. Not every singer possesses the musculature required to support the unique vocal fold density and subglottal pressure necessary to sing repertoire and roles associated with certain voice types…
Descriptors: Singing, Higher Education, Classification, Methods
Kye, Anna – ProQuest LLC, 2023
Every year, the national high school graduation rate is declining and impacting the number of students applying to colleges. Moreover, the majority of students are applying to more than one college. This makes a lot of colleges to be highly competitive in student recruitment for enrollment and thus, the necessity for institutions to anticipate…
Descriptors: Comparative Analysis, Classification, College Enrollment, Prediction
Lee, Chansoon – Educational Measurement: Issues and Practice, 2022
Appropriate placement into courses at postsecondary institutions is critical for the success of students in terms of retention and graduation rates. To reduce the number of students who are misplaced, using multiple measures in placing students is encouraged. However, in practice most postsecondary schools utilize only a few measures to determine…
Descriptors: Classification, Models, Student Placement, College Students
Lepori, Benedetto – Studies in Higher Education, 2022
Classifications are a basic tool for research, which allow summarizing the diversity of objects in a number of categories that fits the cognitive abilities of the human mind. Their relevance for higher education is emphasized by the differentiation of institutional profiles. Yet, unlike in the US, there is currently no classification of European…
Descriptors: Foreign Countries, Higher Education, Classification, Specialization
Melina Verger; Chunyang Fan; Sébastien Lallé; François Bouchet; Vanda Luengo – Journal of Educational Data Mining, 2024
Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes, leading to potential discrimination against certain individuals and harmful long-term…
Descriptors: Algorithms, Prediction, Bias, Classification
Caitlin R. Bowman; Dagmar Zeithamova – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
A major question for the study of learning and memory is how to tailor learning experiences to promote knowledge that generalizes to new situations. In two experiments, we used category learning as a representative domain to test two factors thought to influence the acquisition of conceptual knowledge: the number of training examples (set size)…
Descriptors: Classification, Learning Processes, Generalization, Recognition (Psychology)
Sghir, Nabila; Adadi, Amina; Lahmer, Mohammed – Education and Information Technologies, 2023
The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…
Descriptors: Prediction, Learning Analytics, Artificial Intelligence, Data Collection
Carter-Sowell, Adrienne R.; Miller, Gabe H.; Ganesan, Asha; Kelly, Kimberle A.; Wang, Ran; Crist, Jaren D. – Journal of STEM Education: Innovations and Research, 2023
For 25 years, the National Science Foundation's Alliances for Graduate Education and the Professoriate (AGEP) program has been supporting efforts to broaden participation and meaningfully diversify the Science, Technology, Engineering, and Mathematics (STEM) postdoctoral and faculty ranks. To examine the structures and strategies carried out by…
Descriptors: Graduate Study, College Faculty, Diversity (Faculty), STEM Education