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Murphy, Dillon H.; Halamish, Vered; Rhodes, Matthew G.; Castel, Alan D. – Metacognition and Learning, 2023
Predicting what we will remember and forget is crucial for daily functioning. We were interested in whether evaluating something as likely to be remembered or forgotten leads to enhanced memory for "both" forms of information relative to information that was not judged for memorability. We presented participants with lists of words to…
Descriptors: Memory, Prediction, Recall (Psychology), Control Groups
Hosek, James; Knapp, David; Mattock, Michael G.; Asch, Beth J. – Educational Researcher, 2023
Retirement incentives are frequently used by school districts facing financial difficulties. They provide a means of either decreasing staff size or replacing retiring senior teachers with less expensive junior teachers. We analyze a one-time retirement incentive in a large school district paid to teachers willing to retire at the end of the…
Descriptors: Incentives, Teacher Retirement, Compensation (Remuneration), Prediction
Zhao, Li; Zheng, Yi; Zhao, Junbang; Li, Guoqiang; Compton, Brian J.; Zhang, Rui; Fang, Fang; Heyman, Gail D.; Lee, Kang – Child Development, 2023
Academic cheating is common, but little is known about its early emergence. It was examined among Chinese second to sixth graders (N = 2094; 53% boys, collected between 2018 and 2019) using a machine learning approach. Overall, 25.74% reported having cheated, which was predicted by the best machine learning algorithm (Random Forest) at a mean…
Descriptors: Cheating, Elementary School Students, Artificial Intelligence, Foreign Countries
Julee Gard – ProQuest LLC, 2023
University leaders do not have sufficient tools easily available to guide their decision-making related to institutional financial wellbeing. Currently, many financial indicators used by leaders of tuition-dependent higher education institutions are not focused on vital metrics such as liquidity and cash earnings. The twofold purpose of this…
Descriptors: Private Colleges, Tuition, Income, Prediction
Senthil Kumaran, V.; Malar, B. – Interactive Learning Environments, 2023
Churn in e-learning refers to learners who gradually perform less and become lethargic and may potentially drop out from the course. Churn prediction is a highly sensitive and critical task in an e-learning system because inaccurate predictions might cause undesired consequences. A lot of approaches proposed in the literature analyzed and modeled…
Descriptors: Electronic Learning, Dropouts, Accuracy, Classification
Yaosheng Lou; Kimberly F. Colvin – Discover Education, 2025
Predicting student performance has been a critical focus of educational research. With an effective predictive model, schools can identify potentially at-risk students and implement timely interventions to support student success. Recent developments in educational data mining (EDM) have introduced several machine learning techniques that can…
Descriptors: Educational Research, Data Collection, Performance, Prediction
Melissa Meindl; David Wilkins – Child Care in Practice, 2025
Child protection social workers in England are required to make many decisions in their day-to-day work, including whether to accept a referral, undertake a child protection investigation, pursue care proceedings, or close the case. Many of these decisions involve implicit or explicit predictions about the likelihood of future actions, events, and…
Descriptors: Foreign Countries, Caseworkers, Social Work, Prediction
Melanie Muniandy; Amanda L. Richdale; Samuel R. C. Arnold; Julian N. Trollor; Lauren P. Lawson – Journal of Autism and Developmental Disorders, 2025
The stress literature suggests that coping strategies are implicated in mental health outcomes. However, the longitudinal relationship between coping strategies and mental health in the autistic adult population has not yet been examined. This 2-year longitudinal study examined the predictive role of both baseline and change in coping strategy use…
Descriptors: Coping, Mental Health, Autism Spectrum Disorders, Adults
Roslyn Wong; Aaron Veldre; Sally Andrews – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
Evidence of processing costs for unexpected words presented in place of a more expected completion remains elusive in the eye-movement literature. The current study investigated whether such prediction error costs depend on the source of constraint violation provided by the prior context. Participants' eye movements were recorded as they read…
Descriptors: Reading Processes, Eye Movements, Prediction, Probability
Yves Nievergelt – International Journal of Mathematical Education in Science and Technology, 2024
On 24 June 1994 at Fairchild Air Force Base, during practice for an air show, a low-flying B-52H aircraft banked its wings vertically and crashed. Emphasizing the activity of modeling drag and gravity, these notes examine the possibility of recovery with several models. First, with algebra, historical data lead to a model where in a free fall near…
Descriptors: Air Transportation, Mathematical Models, Prevention, Calculus
Faming Wang; Ronnel B. King; Lingyi Fu; Ching-Sing Chai; Shing On Leung – International Journal of Science Education, 2024
Resilient students attain high levels of academic achievement despite the presence of chronic socioeconomic disadvantage. Identifying factors that promote resilience in the domain of science is crucial to making equitable and high-quality science education accessible for all students. Rooted in the opportunity-propensity framework, this study…
Descriptors: Resilience (Psychology), Foreign Countries, Grade 8, Science Education
Thanh Thuy Do; Golnoosh Babaei; Paolo Pagnottoni – Measurement: Interdisciplinary Research and Perspectives, 2024
Complex Machine Learning (ML) models used to support decision-making in peer-to-peer (P2P) lending often lack clear, accurate, and interpretable explanations. While the game-theoretic concept of Shapley values and its computationally efficient variant Kernel SHAP may be employed for this aim, similarly to other existing methods, the latter makes…
Descriptors: Artificial Intelligence, Risk Management, Credit (Finance), Prediction
Benjamin Goecke; Paul V. DiStefano; Wolfgang Aschauer; Kurt Haim; Roger Beaty; Boris Forthmann – Journal of Creative Behavior, 2024
Automated scoring is a current hot topic in creativity research. However, most research has focused on the English language and popular verbal creative thinking tasks, such as the alternate uses task. Therefore, in this study, we present a large language model approach for automated scoring of a scientific creative thinking task that assesses…
Descriptors: Creativity, Creative Thinking, Scoring, Automation
Gideon D. Eduah – ProQuest LLC, 2024
The Critical Thinking Assessment Test (CAT) is a tool for evaluating students' critical thinking skills in various educational institutions within and outside the United States. While institutions regard the CAT as a high-stakes assessment, students may perceive it as a low-stakes test due to its lack of personal or academic repercussions. This…
Descriptors: Critical Thinking, Student Evaluation, Student Motivation, Tests
Anagha Ani; Ean Teng Khor – Education and Information Technologies, 2024
Predictive modelling in the education domain can be utilised to significantly improve teaching and learning experiences. Massive Open Online Courses (MOOCs) generate a large volume of data that can be exploited to predict and evaluate student performance based on various factors. This paper has two broad aims. Firstly, to develop and tune several…
Descriptors: MOOCs, Classification, Artificial Intelligence, Prediction