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Direct linkHayes, Brett K.; Liew, Shi Xian; Desai, Saoirse Connor; Navarro, Danielle J.; Wen, Yuhang – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
The samples of evidence we use to make inferences in everyday and formal settings are often subject to selection biases. Two property induction experiments examined group and individual sensitivity to one type of selection bias: sampling frames - causal constraints that only allow certain types of instances to be sampled. Group data from both…
Descriptors: Logical Thinking, Inferences, Bias, Individual Differences
Download full textRodriguez, AE; Rosen, John – Research in Higher Education Journal, 2023
The various empirical models built for enrollment management, operations, and program evaluation purposes may have lost their predictive power as a result of the recent collective impact of COVID restrictions, widespread social upheaval, and the shift in educational preferences. This statistical artifact is known as model drifting, data-shift,…
Descriptors: Models, Enrollment Management, School Holding Power, Data
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
Misato Hiraga – ProQuest LLC, 2024
This dissertation developed a new learner corpus of Japanese and introduced an error and linguistic annotation scheme specifically designed for Japanese particles. The corpus contains texts written by learners who are in the first year to fourth year university level Japanese courses. The texts in the corpus were tagged with part-of-speech and…
Descriptors: Japanese, Computational Linguistics, Form Classes (Languages), Error Analysis (Language)
Harrison, Colin D.; Nguyen, Tiffy A.; Seidel, Shannon B.; Escobedo, Alycia M.; Hartman, Courtney; Lam, Katie; Liang, Kristen S.; Martens, Miranda; Acker, Gigi N.; Akana, Susan F.; Balukjian, Brad; Benton, Hilary P.; Blair, J. R.; Boaz, Segal M.; Boyer, Katharyn E.; Bram, Jason B.; Burrus, Laura W.; Byrd, Dana T.; Caporale, Natalia; Carpenter, Edward J.; Chan, Yee-Hung M.; Chen, Lily; Chovnick, Amy; Chu, Diana S.; Clarkson, Bryan K.; Cooper, Sara E.; Creech, Catherine J.; de la Torre, José R.; Denetclaw, Wilfred F.; Duncan, Kathleen; Edwards, Amelia S.; Erickson, Karen; Fuse, Megumi; Gorga, Joseph J.; Govindan, Brinda; Green, L. Jeanette; Hankamp, Paul Z.; Harris, Holly E.; He, Zheng-Hui; Ingalls, Stephen B.; Ingmire, Peter D.; Jacobs, J. Rebecca; Kamakea, Mark; Kimpo, Rhea R.; Knight, Jonathan D.; Krause, Sara K.; Krueger, Lori E.; Light, Terrye L.; Lund, Lance; Márquez-Magaña, Leticia M.; McCarthy, Briana K.; McPheron, Linda; Miller-Sims, Vanessa C.; Moffatt, Cristopher A.; Muick, Pamela C.; Nagami, Paul H.; Nusse, Gloria; Okimura, K. M.; Pasion, Sally G.; Patterson, Robert; Pennings, Pleuni S.; Riggs, Blake; Romeo, Joseph M.; Roy, Scott W.; Russo-Tait, Tatiane; Schultheis, Lisa M.; Sengupta, Lakshmikanta; Spicer, Greg S.; Swei, Andrea; Wade, Jennifer M.; Willsie, Julia K.; Kelley, Loretta A.; Owens, Melinda T.; Trujillo, Gloriana; Domingo, Carmen; Schinske, Jeffrey N.; Tanner, Kimberly D. – CBE - Life Sciences Education, 2019
Instructor Talk--noncontent language used by instructors in classrooms--is a recently defined and promising variable for better understanding classroom dynamics. Having previously characterized the Instructor Talk framework within the context of a single course, we present here our results surrounding the applicability of the Instructor Talk…
Descriptors: Classroom Communication, Language Usage, Novelty (Stimulus Dimension), Models
Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – Annenberg Institute for School Reform at Brown University, 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, Higher Education, Predictive Measurement, Models
Moeller, Julia; Viljaranta, Jaana; Kracke, Bärbel; Dietrich, Julia – Frontline Learning Research, 2020
This article proposes a study design developed to disentangle the objective characteristics of a learning situation from individuals' subjective perceptions of that situation. The term objective characteristics refers to the agreement across students, whereas subjective perceptions refers to inter-individual heterogeneity. We describe a novel…
Descriptors: Student Attitudes, College Students, Lecture Method, Student Interests
Damrongpanit, Suntonrapot – Universal Journal of Educational Research, 2019
The purposes of this study were to test the structural validity and to test the parameters invariance of the self-discipline measurement model for good student citizenship among the models, using the data from the 1,047 complete questionnaires and the reducing length questionnaires with multiple matrix sampling technique. The sample size of this…
Descriptors: Factor Structure, Questionnaires, Test Length, Citizenship
Belfield, Clive; Bailey, Thomas – Center for Analysis of Postsecondary Education and Employment, 2017
Recently, studies have adopted fixed effects modeling to identify the returns to college. This method has the advantage over ordinary least squares estimates in that unobservable, individual-level characteristics that may bias the estimated returns are differenced out. But the method requires extensive longitudinal data and involves complex…
Descriptors: Associate Degrees, Outcomes of Education, Education Work Relationship, Robustness (Statistics)
Shchipanova, Dina Ye.; Lebedeva, Ekaterina V.; Sukhinin, Valentin P.; Valieva, Elizaveta N. – International Journal of Environmental and Science Education, 2016
The importance of the studied issue is conditioned by the fact that high dynamic of processes in the labour market requires constant work of an individual on self-determination and search for significance of his/her professional activity. The purpose of research is theoretical development and empirical verification of the types of strategies of…
Descriptors: Classification, Self Determination, Personality Traits, Semantics
Lee, Hollylynne S.; Doerr, Helen M.; Tran, Dung; Lovett, Jennifer N. – Statistics Education Research Journal, 2016
Repeated sampling approaches to inference that rely on simulations have recently gained prominence in statistics education, and probabilistic concepts are at the core of this approach. In this approach, learners need to develop a mapping among the problem situation, a physical enactment, computer representations, and the underlying randomization…
Descriptors: Probability, Inferences, Statistics, Teaching Methods
Augustyniak, Lisa J. – ProQuest LLC, 2015
Community college leaders face unprecedented change, and some have begun reexamining their institutional strategic planning processes. Yet, studies in higher education strategic planning spend little time examining how community colleges formulate their strategic plans. This mixed-method qualitative study used an expert sampling method to identify…
Descriptors: Strategic Planning, Qualitative Research, Models, Accreditation (Institutions)
Kezar, Adrianna; Gehrke, Sean – Journal of STEM Education: Innovations and Research, 2017
A community of practice (CoP) is a group of people who share a concern or a passion for something they do and learn how to do it as they interact regularly. Higher education leaders are attracted to CoPs because they are a peer-based model of learning with colleagues, which works well for professionals such as faculty. These authors identified…
Descriptors: STEM Education, Communities of Practice, Higher Education, Models
Zimmermann, Judith; Brodersen, Kay H.; Heinimann, Hans R.; Buhmann, Joachim M. – Journal of Educational Data Mining, 2015
The graduate admissions process is crucial for controlling the quality of higher education, yet, rules-of-thumb and domain-specific experiences often dominate evidence-based approaches. The goal of the present study is to dissect the predictive power of undergraduate performance indicators and their aggregates. We analyze 81 variables in 171…
Descriptors: Undergraduate Students, Graduate Students, Academic Achievement, Prediction
Matorera, D.; Fraser, W. J. – South African Journal of Education, 2016
Business schools are globally often seen as structured, purpose-driven, multi-sector and multi-perspective organisations. This article is based on the response of a graduate school to an innovative industrial Quality Function Deployment-based model (QFD), which was to be adopted initially in a Master's degree programme for quality assurance…
Descriptors: Case Studies, Qualitative Research, Interviews, College Faculty
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