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Leonie Fleck; Dorothee Amelung; Anna Fuchs; Benjamin Mayer; Malvin Escher; Lena Listunova; Jobst-Hendrik Schultz; Andreas Möltner; Clara Schütte; Tim Wittenberg; Isabella Schneider; Sabine C. Herpertz – Advances in Health Sciences Education, 2025
Doctors' interactional competencies play a crucial role in patient satisfaction, well-being, and compliance. Accordingly, it is in medical schools' interest to select candidates with strong interactional abilities. While Multiple Mini Interviews (MMIs) provide a useful context to assess such abilities, the evaluation of candidate performance…
Descriptors: Medical Students, Medical Schools, College Admission, Admission Criteria
Dignum, Frank – International Journal of Social Research Methodology, 2023
The general feeling is that no predictions can be made based on agent-based social simulations. The outcomes of social simulations are based on the behaviors of individuals and their interactions. Behavioral models are always incomplete and often, also incorrect with respect to real behavior and thus the outcomes of agent-based social simulations…
Descriptors: Prediction, Predictive Validity, Educational Policy, Policy Formation
Jewoong Moon; Fengfeng Ke; Zlatko Sokolikj – Technology, Knowledge and Learning, 2025
In this exploratory study, we designed and validated game-based performance tasks to assess the development of representational flexibility in autistic adolescents through virtual reality (VR)-based training. Representational flexibility, a critical cognitive ability, involves attention switching, generating representations, and recognizing…
Descriptors: Game Based Learning, Educational Games, Performance, Task Analysis
Javier Del Olmo-Muñoz; Pascual D. Diago; David Arnau; David Arnau-Blasco; José Antonio González-Calero – ZDM: Mathematics Education, 2024
This research, following a sequential mixed-methods design, delves into metacognitive control in problem solving among 5- to 6-year-olds, using two floor-robot environments. In an initial qualitative phase, 82 pupils participated in tasks in which they directed a floor robot to one of two targets, with the closer target requiring more cognitive…
Descriptors: Elementary School Students, Metacognition, Robotics, Computer Simulation
Christine M. White; Christopher Schatschneider – Contemporary School Psychology, 2024
Universal screening to predict students' risk for reading problems is a foundational component of the Multi-Tiered Systems of Support framework and is required by law in many US states. School or district administrators are tasked with selecting screening assessments that are both technically adequate and feasible given the resources of their…
Descriptors: Screening Tests, Reading Tests, Reading Difficulties, Classification
Christine M. White; Christopher Schatschneider – Grantee Submission, 2023
Universal screening to predict students' risk for reading problems is a foundational component of the Multi-Tiered Systems of Support framework and is required by law in many US states. School or district administrators are tasked with selecting screening assessments that are both technically adequate and feasible given the resources of their…
Descriptors: Screening Tests, Reading Tests, Reading Difficulties, Classification
Olive, David Monllao; Huynh, Du Q.; Reynolds, Mark; Dougiamas, Martin; Wiese, Damyon – IEEE Transactions on Learning Technologies, 2019
A significant amount of research effort has been put into finding variables that can identify students at risk based on activity records available in learning management systems (LMS). These variables often depend on the context, for example, the course structure, how the activities are assessed or whether the course is entirely online or a…
Descriptors: Prediction, Identification, At Risk Students, Online Courses
Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement

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