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Haesebrouck, Tim – Sociological Methods & Research, 2023
The field of qualitative comparative analysis (QCA) is witnessing a heated debate on which one of the QCA's main solution types should be at the center of substantive interpretation. This article argues that the different QCA solutions have complementary strengths. Therefore, researchers should interpret the three solution types in an integrated…
Descriptors: Qualitative Research, Comparative Analysis, Data Analysis, Data Collection
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
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
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
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
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
Nelson, Peter M.; Van Norman, Ethan R.; Klingbeil, Dave A.; Parker, David C. – Psychology in the Schools, 2017
Although extensive research exists on the use of curriculum-based measures for progress monitoring, little is known about using computer adaptive tests (CATs) for progress-monitoring purposes. The purpose of this study was to evaluate the impact of the frequency of data collection on individual and group growth estimates using a CAT. Data were…
Descriptors: Progress Monitoring, Computer Assisted Testing, Data Collection, Scheduling
Yanagida, Takuya; Gradinger, Petra; Strohmeier, Dagmar; Solomontos-Kountouri, Olga; Trip, Simona; Bora, Carmen – International Journal of Developmental Science, 2016
Many large-scale cross-national studies rely on a single-item measurement when comparing prevalence rates of traditional bullying, traditional victimization, cyberbullying, and cyber-victimization between countries. However, the reliability and validity of single-item measurement approaches are highly problematic and might be biased. Data from…
Descriptors: Bullying, Victims of Crime, Computer Mediated Communication, Comparative Analysis
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
Monitoring and Depth of Strategy Use in Computer-Based Learning Environments for Science and History
Deekens, Victor M.; Greene, Jeffrey A.; Lobczowski, Nikki G. – British Journal of Educational Psychology, 2018
Background: Self-regulated learning (SRL) models position metacognitive monitoring as central to SRL processing and predictive of student learning outcomes (Winne & Hadwin, 2008; Zimmerman, 2000). A body of research evidence also indicates that depth of strategy use, ranging from surface to deep processing, is predictive of learning…
Descriptors: Independent Study, Learning Strategies, Electronic Learning, Computer Assisted Instruction
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
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
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
Lei, Wu; Qing, Fang; Zhou, Jin – International Journal of Distance Education Technologies, 2016
There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…
Descriptors: Causal Models, Attribution Theory, Correlation, Evaluation Methods