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Krefeld-Schwalb, Antonia; Donkin, Chris; Newell, Ben R.; Scheibehenne, Benjamin – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2019
Past research indicates that individuals respond adaptively to contextual factors in multiattribute choice tasks. Yet it remains unclear how this adaptation is cognitively governed. In this article, empirically testable implementations of two prominent competing theoretical frameworks are developed and compared across two multiattribute choice…
Descriptors: Models, Cues, Probability, Experiments
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Nahar, Khaledun; Shova, Boishakhe Islam; Ria, Tahmina; Rashid, Humayara Binte; Islam, A. H. M. Saiful – Education and Information Technologies, 2021
Information is everywhere in a hidden and scattered way. It becomes useful when we apply Data mining to extracts the hidden, meaningful, and potentially useful patterns from these vast data resources. Educational data mining ensures a quality education by analyzing educational data based on various aspects. In this paper, we have analyzed the…
Descriptors: Learning Analytics, College Students, Engineering Education, Data Collection
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Wu, Wei; Jia, Fan; Kinai, Richard; Little, Todd D. – International Journal of Behavioral Development, 2017
Spline growth modelling is a popular tool to model change processes with distinct phases and change points in longitudinal studies. Focusing on linear spline growth models with two phases and a fixed change point (the transition point from one phase to the other), we detail how to find optimal data collection designs that maximize the efficiency…
Descriptors: Longitudinal Studies, Data Collection, Models, Change
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Fisher, Molly H.; Thomas, Jonathan; Schack, Edna O.; Jong, Cindy; Tassell, Janet – Mathematics Education Research Journal, 2018
This study examined the impact of an intervention, focused on professional noticing of children's conceptual development in whole number and arithmetic reasoning, on preservice elementary teachers' (PSETs') professional noticing skills, attitudes toward mathematics, and mathematical knowledge for teaching mathematics. A video-based professional…
Descriptors: Numeracy, Preservice Teachers, Intervention, Children
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Su, Shu-Ching; Sedory, Stephen A.; Singh, Sarjinder – Sociological Methods & Research, 2015
In this article, we adjust the Kuk randomized response model for collecting information on a sensitive characteristic for increased protection and efficiency by making use of forced "yes" and forced "no" responses. We first describe Kuk's model and then the proposed adjustment to Kuk's model. Next, by means of a simulation…
Descriptors: Data Collection, Models, Responses, Efficiency
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Peresso, Randolph – Compare: A Journal of Comparative and International Education, 2017
This paper focuses on the methodology adopted for Malta+5, which builds on Robin Alexander's work by comparing the five pedagogical cultures he studied to the one in Malta. It reflects critically on the research process adopted in this study, and shows how, despite the very limited experience and resources, applying the methodology, frameworks and…
Descriptors: Organizational Culture, Teaching Methods, Comparative Analysis, Models
Beheshti, Behzad; Desmarais, Michel C. – International Educational Data Mining Society, 2015
This study investigates the issue of the goodness of fit of different skills assessment models using both synthetic and real data. Synthetic data is generated from the different skills assessment models. The results show wide differences of performances between the skills assessment models over synthetic data sets. The set of relative performances…
Descriptors: Goodness of Fit, Student Evaluation, Skills, Models
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Lopes, J. B.; Silva, A. A.; Cravino, J. P.; Santos, C. A.; Cunha, A.; Pinto, A.; Silva, A.; Viegas, C.; Saraiva, E.; Branco, M. J. – Research in Science Education, 2014
This study deals with the problem of how to collect genuine and useful data about science classroom practices, and preserving the complex and holistic nature of teaching and learning. Additionally, we were looking for an instrument that would allow comparability and verifiability for teaching and research purposes. Given the multimodality of…
Descriptors: Science Education, Data Collection, Educational Practices, Holistic Approach
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Knowles, Jared E. – Journal of Educational Data Mining, 2015
The state of Wisconsin has one of the highest four year graduation rates in the nation, but deep disparities among student subgroups remain. To address this the state has created the Wisconsin Dropout Early Warning System (DEWS), a predictive model of student dropout risk for students in grades six through nine. The Wisconsin DEWS is in use…
Descriptors: Dropouts, Models, Prediction, Risk
Strecht, Pedro; Cruz, Luís; Soares, Carlos; Mendes-Moreira, João; Abreu, Rui – International Educational Data Mining Society, 2015
Predicting the success or failure of a student in a course or program is a problem that has recently been addressed using data mining techniques. In this paper we evaluate some of the most popular classification and regression algorithms on this problem. We address two problems: prediction of approval/failure and prediction of grade. The former is…
Descriptors: Comparative Analysis, Classification, Regression (Statistics), Mathematics
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Pinho-Lopes, Margarida; Macedo, Joaquim – European Journal of Engineering Education, 2016
Since 2007/2008 project-based learning models have been used to deliver two fundamental courses on Geotechnics in University of Aveiro, Portugal. These models have evolved and have encompassed either cooperative or collaborative teamwork. Using data collected in five editions of each course (Soil Mechanics I and Soil Mechanics II), the different…
Descriptors: Foreign Countries, Active Learning, Student Projects, Engineering Education
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Gray, Geraldine; McGuinness, Colm; Owende, Philip; Hofmann, Markus – Journal of Learning Analytics, 2016
This paper reports on a study to predict students at risk of failing based on data available prior to commencement of first year. The study was conducted over three years, 2010 to 2012, on a student population from a range of academic disciplines, n=1,207. Data was gathered from both student enrollment data and an online, self-reporting,…
Descriptors: Prediction, At Risk Students, Academic Failure, College Freshmen
Cheema, Jehanzeb R. – Review of Educational Research, 2014
Missing data are a common occurrence in survey-based research studies in education, and the way missing values are handled can significantly affect the results of analyses based on such data. Despite known problems with performance of some missing data handling methods, such as mean imputation, many researchers in education continue to use those…
Descriptors: Educational Research, Data, Data Collection, Data Processing
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Miller, Nathan Brad; Bell, Bryan – Journal of Continuing Higher Education, 2016
Increased federal attention to student completion metrics and uncertain financial forecasts have heightened the tenor of student retention conversations. Improved institutional retention rates will lead to higher completion rates and relieve some funding concerns. To accomplish these improvements, institutions have invested in analytics to better…
Descriptors: Academic Persistence, School Holding Power, Acceleration (Education), Communication Strategies
Lloyd, Sonya LaShawn – ProQuest LLC, 2014
Providing academic assistance to English Language Learners (ELLs) is varied and often ineffective. The purpose of this causal-comparative study was to determine if there was a relationship between 9th grade students' performance on the High School Graduation Exam (HSGE) in reading and language and the Push-in and Pull-out models of instruction.…
Descriptors: English Language Learners, Secondary School Students, Grade 9, Program Evaluation
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