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Ludlow, Larry H.; O'Keefe, Theresa; Braun, Henry; Anghel, Ella; Szendey, Olivia; Matz, Christina; Howell, Burton – Practical Assessment, Research & Evaluation, 2022
Development of purpose is an important goal of post-secondary education. This study advances the measurement of purpose by (a) enriching the construct through incorporating the facet of horizon; (b) providing a framework for Rasch/Guttman Scenario score interpretation; and (c) providing evidence of convergent, divergent, and known groups validity.
Descriptors: Higher Education, Role of Education, Measurement, Item Response Theory
Peel, Karen L. – Practical Assessment, Research & Evaluation, 2020
Interest in applied educational research methodology is growing as educators and researchers strive to seek empirical evidence about what is effective teaching within distinctive contexts. However, for beginner researchers who are interested in conducting case studies within educational settings and are looking for an appropriate starting point,…
Descriptors: Educational Research, Content Analysis, Research Methodology, Data Collection
Kubsch, Marcus; Stamer, Insa; Steiner, Mara; Neumann, Knut; Parchmann, Ilka – Practical Assessment, Research & Evaluation, 2021
In light of the replication crisis in psychology, null-hypothesis significance testing (NHST) and "p"-values have been heavily criticized and various alternatives have been proposed, ranging from slight modifications of the current paradigm to banning "p"-values from journals. Since the physics education research community…
Descriptors: Data Analysis, Bayesian Statistics, Educational Research, Science Education
He, Lingjun; Levine, Richard A.; Fan, Juanjuan; Beemer, Joshua; Stronach, Jeanne – Practical Assessment, Research & Evaluation, 2018
In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…
Descriptors: Institutional Research, Regression (Statistics), Statistical Analysis, Data Analysis
Pek, Jolynn; Wong, Octavia; Wong, C. M. – Practical Assessment, Research & Evaluation, 2017
Data transformations have been promoted as a popular and easy-to-implement remedy to address the assumption of normally distributed errors (in the population) in linear regression. However, the application of data transformations introduces non-ignorable complexities which should be fully appreciated before their implementation. This paper adds to…
Descriptors: Data Analysis, Regression (Statistics), Statistical Inference, Data Interpretation
Boedeker, Peter – Practical Assessment, Research & Evaluation, 2017
Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There are many decisions to be made when constructing and estimating a model in HLM including which estimation technique to use. Three of the estimation techniques available when analyzing data with HLM are maximum likelihood, restricted maximum…
Descriptors: Hierarchical Linear Modeling, Maximum Likelihood Statistics, Bayesian Statistics, Computation
Beaujean, A. Alexander; Morgan, Grant B. – Practical Assessment, Research & Evaluation, 2016
Education researchers often study count variables, such as times a student reached a goal, discipline referrals, and absences. Most researchers that study these variables use typical regression methods (i.e., ordinary least-squares) either with or without transforming the count variables. In either case, using typical regression for count data can…
Descriptors: Multiple Regression Analysis, Educational Research, Least Squares Statistics, Models