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Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – AERA Open, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Identification, Two Year College Students, Community Colleges
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Ramesh, Arti; Goldwasser, Dan; Huang, Bert; Daume, Hal; Getoor, Lise – IEEE Transactions on Learning Technologies, 2020
Maintaining and cultivating student engagement is critical for learning. Understanding factors affecting student engagement can help in designing better courses and improving student retention. The large number of participants in massive open online courses (MOOCs) and data collected from their interactions on the MOOC open up avenues for studying…
Descriptors: Online Courses, Learner Engagement, Student Behavior, Success
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Jaylin Lowe; Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…
Descriptors: Randomized Controlled Trials, Middle School Mathematics, Middle School Students, Middle Schools
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Aiken, John M.; Henderson, Rachel; Caballero, Marcos D. – Physical Review Physics Education Research, 2019
Physics education research (PER) has used quantitative modeling techniques to explore learning, affect, and other aspects of physics education. However, these studies have rarely examined the predictive output of the models, instead focusing on the inferences or causal relationships observed in various data sets. This research introduces a modern…
Descriptors: Physics, Bachelors Degrees, College Science, Student Records
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Gomes, Cristiano Mauro Assis; Almeida, Leandro S. – Practical Assessment, Research & Evaluation, 2017
Predictive studies have been widely undertaken in the field of education to provide strategic information about the extensive set of processes related to teaching and learning, as well as about what variables predict certain educational outcomes, such as academic achievement or dropout. As in any other area, there is a set of standard techniques…
Descriptors: Predictive Measurement, Statistical Analysis, Decision Making, Foreign Countries
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Howe, Christopher C. F.; Moir, Hannah J.; Easton, Chris – Measurement in Physical Education and Exercise Science, 2017
This study establishes tri-axial activity count (AC) cut-points for the GT3X+ accelerometer to classify physical activity intensity in overweight and obese adults. Further, we examined the accuracy of established and novel energy expenditure (EE) prediction equations based on AC and other metrics. "Part 1": Twenty overweight or obese…
Descriptors: Obesity, Adults, Exercise Physiology, Exercise
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Hackett, Daniel A.; Davies, Timothy B.; Ibel, Denis; Cobley, Stephen; Sanders, Ross – Measurement in Physical Education and Exercise Science, 2018
This study examined the predictive ability of the medicine ball chest throw and vertical jump for muscular strength and power in adolescents. One hundred and ninety adolescents participated in this study. Participants performed trials of the medicine ball chest throw and vertical jump, with vertical jump peak power calculated via an estimation…
Descriptors: Predictive Measurement, Muscular Strength, Adolescents, Age Differences
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Fako, Thabo T.; Nkhukhu-Orlando, Esther; Wilson, Debra R.; Forcheh, Ntonghanwah; Linn, James G. – International Journal of Educational Administration and Policy Studies, 2018
Organizational commitment is a major determinant of organizational effectiveness and desirable employee attitudes and behaviours. Highly committed academic staff are the backbone of universities since they play an important role in the success of their institutions. This study investigated factors associated with organizational commitment among…
Descriptors: Foreign Countries, Organizational Climate, Performance Factors, Employee Attitudes
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Almeda, Ma. Victoria; Zuech, Joshua; Utz, Chris; Higgins, Greg; Reynolds, Rob; Baker, Ryan S. – Online Learning, 2018
Online education continues to become an increasingly prominent part of higher education, but many students struggle in distance courses. For this reason, there has been considerable interest in predicting which students will succeed in online courses and which will receive poor grades or drop out prior to completion. Effective intervention depends…
Descriptors: Performance Factors, Online Courses, Electronic Learning, Models
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Hubbard, Joanna K.; Potts, Macy A.; Couch, Brian A. – CBE - Life Sciences Education, 2017
Assessments represent an important component of undergraduate courses because they affect how students interact with course content and gauge student achievement of course objectives. To make decisions on assessment design, instructors must understand the affordances and limitations of available question formats. Here, we use a crossover…
Descriptors: Test Format, Questioning Techniques, Undergraduate Students, Objective Tests
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Austin, Bruce; French, Brian; Adesope, Olusola; Gotch, Chad – Journal of Experimental Education, 2017
Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for…
Descriptors: Predictor Variables, Models, Predictive Measurement, Statistical Analysis
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Szadokierski, Isadora; Burns, Matthew K.; McComas, Jennifer J. – School Psychology Review, 2017
The current study used the learning hierarchy/instructional hierarchy phases of acquisition and fluency to predict intervention effectiveness based on preintervention reading skills. Preintervention reading accuracy (percentage of words read correctly) and rate (number of words read correctly per minute) were assessed for 49 second- and…
Descriptors: Intervention, Program Effectiveness, Predictive Measurement, Reading Rate
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Hanauer, David I.; Graham, Mark J.; Hatfull, Graham F. – CBE - Life Sciences Education, 2016
Curricular changes that promote undergraduate persistence in science, technology, engineering, and mathematics (STEM) disciplines are likely associated with particular student psychological outcomes, and tools are needed that effectively assess these developments. Here, we describe the theoretical basis, psychometric properties, and predictive…
Descriptors: College Students, Academic Persistence, Psychometrics, Predictive Validity
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Edyburn, Kelly L.; Quirk, Matthew; Felix, Erika; Swami, Sruthi; Goldstein, Ariel; Terzieva, Antoniya; Scheller, Jennifer – Literacy Research and Instruction, 2017
This study examined the relative contributions of Latino/a children's (N = 102) school readiness and early literacy skills during kindergarten in predicting first grade reading achievement. By using discriminant function analyses, the current study identified a set of areas to assess that could be used to effectively screen children during…
Descriptors: Kindergarten, Hispanic American Students, Reading Achievement, Literacy
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Williamson, Ben – Journal of Education Policy, 2016
Educational institutions and governing practices are increasingly augmented with digital database technologies that function as new kinds of policy instruments. This article surveys and maps the landscape of digital policy instrumentation in education and provides two detailed case studies of new digital data systems. The Learning Curve is a…
Descriptors: Visualization, Synchronous Communication, Governance, Data Collection
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