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Hayes, 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
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Rodriguez, 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
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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
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)
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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
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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
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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)
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Vadeboncoeur, Claudia; Townsend, Nick; Foster, Charlie; Sheehan, Mark – Research Ethics, 2016
Conducting large multi-site research within universities highlights inconsistencies between universities in approaches, requirements and responses of research ethics committees. Within the context of a social science research study, we attempted to obtain ethical approval from 101 universities across England to recruit students for a short online…
Descriptors: Foreign Countries, Social Science Research, Ethics, Recruitment
Fry, Elizabeth Brondos – ProQuest LLC, 2017
Recommended learning goals for students in introductory statistics courses include the ability to recognize and explain the key role of randomness in designing studies and in drawing conclusions from those studies involving generalizations to a population or causal claims (GAISE College Report ASA Revision Committee, 2016). The purpose of this…
Descriptors: Introductory Courses, Statistics, Concept Formation, Sampling
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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
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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)
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Hills, Thomas T.; Hertwig, Ralph – Psychological Review, 2012
Gonzalez and Dutt (2011) recently reported that trends during sampling, prior to a consequential risky decision, reveal a gradual movement from exploration to exploitation. That is, even when search imposes no immediate costs, people adopt the same pattern manifest in costly search: early exploration followed by later exploitation. From this…
Descriptors: Decision Making, Models, Inferences, Sampling
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