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Jopke, Nikolaus; Gerrits, Lasse – International Journal of Social Research Methodology, 2019
There is a need to improve the ways in which Qualitative Comparative Analysis (QCA) handles qualitative data. To this end, we propose to include ideas and routines from Grounded Theory (GT) in QCA. We will first argue that there is a natural fit between the two on the ontological level. On the methodological level, we will demonstrate in what ways…
Descriptors: Qualitative Research, Comparative Analysis, Grounded Theory, Sampling
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Ames, Allison; Myers, Aaron – Educational Measurement: Issues and Practice, 2019
Drawing valid inferences from modern measurement models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. As Bayesian estimation is becoming more common, understanding the Bayesian approaches for evaluating model-data fit models…
Descriptors: Bayesian Statistics, Psychometrics, Models, Predictive Measurement
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Kell, Clare; Sweet, John – Innovations in Education and Teaching International, 2017
This paper shows how peer observation of learning and teaching (POLT) discussions can be augmented through the use of a dynamic visual notation that makes visible for interpretation, elements of teacher-learner and learner-earner nonverbal interactions. Making visible the nonverbal, physical, spatial and kinesics (eye-based) elements of…
Descriptors: Observation, Peer Evaluation, Visual Aids, Protocol Analysis
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Quinnell, Lorna – Australian Mathematics Teacher, 2014
The importance of mathematical visual images is indicated by the introductory paragraph in the Statistics and Probability content strand of the Australian Curriculum, which draws attention to the importance of learners developing skills to analyse and draw inferences from data and "represent, summarise and interpret data and undertake…
Descriptors: Foreign Countries, Mathematics Curriculum, National Curriculum, Mathematics Instruction
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Wurtz, Keith – Journal of Applied Research in the Community College, 2008
The purpose of this article is to provide the necessary tools for institutional researchers to conduct a logistic regression analysis and interpret the results. Aspects of the logistic regression procedure that are necessary to evaluate models are presented and discussed with an emphasis on cutoff values and choosing the appropriate number of…
Descriptors: Regression (Statistics), Predictor Variables, Educational Background, Grades (Scholastic)