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Wang, Yan; Kim, Eunsook; Yi, Zhiyao – Educational and Psychological Measurement, 2022
Latent profile analysis (LPA) identifies heterogeneous subgroups based on continuous indicators that represent different dimensions. It is a common practice to measure each dimension using items, create composite or factor scores for each dimension, and use these scores as indicators of profiles in LPA. In this case, measurement models for…
Descriptors: Robustness (Statistics), Profiles, Statistical Analysis, Classification
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Huiming Ding; Matt Homer – Advances in Health Sciences Education, 2025
Summative assessments are often underused for feedback, despite them being rich with data of students' applied knowledge and clinical and professional skills. To better inform teaching and student support, this study aims to gain insights from summative assessments through profiling students' performance patterns and identify those students…
Descriptors: Summative Evaluation, Profiles, Statistical Analysis, Outcomes of Education
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Onur Demirkaya; Sharon Frey; Sid Sharairi; JongPil Kim – International Electronic Journal of Elementary Education, 2025
This study compares latent profiles derived from student subgroups of varying levels of mathematical skills defined by achievement and ability assessment scores. Achievement and ability cut scores for identifying students at both ends of the mathematics spectrum were applied and the resulting latent profiles within each condition were compared.…
Descriptors: Profiles, Statistical Analysis, Academic Achievement, Mathematics Achievement
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Leili Tapak; Yadollah Hamidi; Zahra Toosi – Learning Organization, 2024
Purpose: Learning organization (LO) concept has received much attention in the last decades. The purpose of an LO is to proactively shape its future by fostering a culture of continuous learning among its members. This approach empowers the organization to adapt, evolve and innovate, aligning with the needs and aspirations of both internal and…
Descriptors: Organizational Learning, Questionnaires, Organizational Culture, Organizational Change
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Jelena Jovanovic; Dragan Gaševic; Lixiang Yan; Graham Baker; Andrew Murray; Danijela Gasevic – Journal of Computer Assisted Learning, 2024
Background: Learner profiles detected from digital trace data are typically triangulated with survey data to explain those profiles based on learners' internal conditions (e.g., motivation). However, survey data are often analysed with limited consideration of the interconnected nature of learners' internal conditions. Objectives: Aiming to enable…
Descriptors: Psychological Patterns, Networks, Profiles, Learning Processes