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Maki, Kathrin E.; McGill, Ryan J.; Conoyer, Sarah J.; Fefer, Sarah A.; Ward, Thomas – Journal of Psychoeducational Assessment, 2021
Patterns of strengths and weaknesses represent relatively novel methods for identifying specific learning disabilities (SLD) with proponents asserting that the incorporation of multiple sources of assessment data and professional judgment play a key role in their utility. In this study, we examined if the sequential presentation of assessment data…
Descriptors: Sequential Approach, Data, Learning Disabilities, Disability Identification
Ziying Li; A. Corinne Huggins-Manley; Walter L. Leite; M. David Miller; Eric A. Wright – Educational and Psychological Measurement, 2022
The unstructured multiple-attempt (MA) item response data in virtual learning environments (VLEs) are often from student-selected assessment data sets, which include missing data, single-attempt responses, multiple-attempt responses, and unknown growth ability across attempts, leading to a complex and complicated scenario for using this kind of…
Descriptors: Sequential Approach, Item Response Theory, Data, Simulation
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Frey, Regina F.; Fisher, Beth A.; Solomon, Erin D.; Leonard, Denise A.; Mutambuki, Jacinta M.; Cohen, Cheryl A.; Luo, Jia; Pondugula, Santhi – Journal of College Science Teaching, 2016
This article describes a visual approach to integrating observational data into self-evaluation and peer review of teaching, practices that can lead to adoption of evidence-based active-learning strategies in STEM. This approach was designed to be implemented for undergraduate courses across disciplines. The presentation of observational data in a…
Descriptors: Active Learning, Self Evaluation (Individuals), Peer Evaluation, Educational Practices