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Yongtian Cheng; K. V. Petrides – Educational and Psychological Measurement, 2025
Psychologists are emphasizing the importance of predictive conclusions. Machine learning methods, such as supervised neural networks, have been used in psychological studies as they naturally fit prediction tasks. However, we are concerned about whether neural networks fitted with random datasets (i.e., datasets where there is no relationship…
Descriptors: Psychological Studies, Artificial Intelligence, Cognitive Processes, Predictive Validity
Umar Shehzad; Mimi Recker; Jody Clarke-Midura – Assessment in Education: Principles, Policy & Practice, 2025
This study investigates the use of exit tickets as formative assessments in maths-integrated computer science (CS) lessons for grade 5 students. Exit tickets are brief surveys administered immediately after instructional activities. Using structural equation modelling (SEM), we analysed data from 1,067 students to examine the reliability and…
Descriptors: Formative Evaluation, Psychological Patterns, Computer Science Education, Grade 5
Katherine E. Castellano; Daniel F. McCaffrey; Joseph A. Martineau – Educational Measurement: Issues and Practice, 2025
Growth-to-standard models evaluate student growth against the growth needed to reach a future standard or target of interest, such as proficiency. A common growth-to-standard model involves comparing the popular Student Growth Percentile (SGP) to Adequate Growth Percentiles (AGPs). AGPs follow from an involved process based on fitting a series of…
Descriptors: Student Evaluation, Growth Models, Student Educational Objectives, Educational Indicators

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