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- Assessment (2)
- Examinee motivation (2)
- Higher education (2)
- Estimation methods (1)
- Ethical reasoning (1)
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- Faculty development (1)
- Higher education assessment (1)
- Item response theory (1)
- Learning improvement (1)
- Low-stakes testing (1)
- Metropolis-Hastings Robbins-Monro algorithm (1)
- Missing data (1)
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- Multilevel (1)
- Multiple imputation (1)
- Planned missingness (1)
- Simulation study (1)
- Value-added (1)
Articles 1 - 4 of 4
Full-Text Articles in Education
Improving Student Learning In Higher Education: A Mixed Methods Study, Megan R. Good
Improving Student Learning In Higher Education: A Mixed Methods Study, Megan R. Good
Dissertations, 2014-2019
To improve quality, higher education must be able to demonstrate learning improvement. To do so, academic degree program leaders must assess learning, intervene, and then re-assess to determine if the intervention was indeed an improvement (Fulcher, Good, Coleman, and Smith, 2014). This seemingly “simple model” is rarely enacted in higher education (Blaich & Wise, 2011). The purpose of this embedded mixed methods study was to investigate the effectiveness and experience of a faculty development program focused on a specific programmatic learning outcome. Specifically, the intervention was intended to increase students’ ethical reasoning skills aligned with a university-wide program. The results …
The Effects Of A Planned Missingness Design On Examinee Motivation And Psychometric Quality, Matthew S. Swain
The Effects Of A Planned Missingness Design On Examinee Motivation And Psychometric Quality, Matthew S. Swain
Dissertations, 2014-2019
Assessment practitioners in higher education face increasing demands to collect assessment and accountability data to make important inferences about student learning and institutional quality. The validity of these high-stakes decisions is jeopardized, particularly in low-stakes testing contexts, when examinees do not expend sufficient motivation to perform well on the test. This study introduced planned missingness as a potential solution. In planned missingness designs, data on all items are collected but each examinee only completes a subset of items, thus increasing data collection efficiency, reducing examinee burden, and potentially increasing data quality. The current scientific reasoning test served as the Long …
Examining The Performance Of The Metropolis-Hastings Robbins-Monro Algorithm In The Estimation Of Multilevel Multidimensional Irt Models, Bozhidar M. Bashkov
Examining The Performance Of The Metropolis-Hastings Robbins-Monro Algorithm In The Estimation Of Multilevel Multidimensional Irt Models, Bozhidar M. Bashkov
Dissertations, 2014-2019
The purpose of this study was to review the challenges that exist in the estimation of complex (multidimensional) models applied to complex (multilevel) data and to examine the performance of the recently developed Metropolis-Hastings Robbins-Monro (MH-RM) algorithm (Cai, 2010a, 2010b), designed to overcome these challenges and implemented in both commercial and open-source software programs. Unlike other methods, which either rely on high-dimensional numerical integration or approximation of the entire multidimensional response surface, MH-RM makes use of Fisher’s Identity to employ stochastic imputation (i.e., data augmentation) via the Metropolis-Hastings sampler and then apply the stochastic approximation method of Robbins and Monro …
The Effect Of Examinee Motivation On Value-Added Estimates, Laura M. Williams
The Effect Of Examinee Motivation On Value-Added Estimates, Laura M. Williams
Dissertations, 2014-2019
Questions regarding the quality of education, both in K-12 systems and higher education, are common. Methods for measuring quality in education have been developed in the past decades, with value-added estimates emerging as one of the most well-known methods. Value-added methods purport to indicate how much students learn over time as a result of their attendance at a particular school. Controversy has surrounded the algorithms used to generate value-added estimates as well as the uses of the estimates to make decisions about school and teacher quality. In higher education, most institutions used cross-sectional rather than longitudinal data to estimate value-added. …