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Direct linkJi-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2023
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
McChesney, Katrina; Aldridge, Jill – International Journal of Research & Method in Education, 2019
A recurring debate in mixed methods research involves the relationship between research methods and research paradigms. Whereas some scholars appear to assume that qualitative and quantitative research methods each necessarily belong with particular research paradigms, others have called for greater flexibility and have taken a variety of stances…
Descriptors: Mixed Methods Research, Models, Research Design, Data Collection
Finch, W. Holmes; Finch, Maria Hernández – Journal of Experimental Education, 2018
Single subject (SS) designs are popular in educational and psychological research. There exist several statistical techniques designed to analyze such data and to address the question of whether an intervention has the desired impact. Recently, researchers have suggested that generalized additive models (GAMs) might be useful for modeling…
Descriptors: Educational Research, Longitudinal Studies, Simulation, Models
Yu, Chong Ho; Lee, Hyun Seo; Lara, Emily; Gan, Siyan – Practical Assessment, Research & Evaluation, 2018
Big data analytics are prevalent in fields like business, engineering, public health, and the physical sciences, but social scientists are slower than their peers in other fields in adopting this new methodology. One major reason for this is that traditional statistical procedures are typically not suitable for the analysis of large and complex…
Descriptors: Data Analysis, Social Sciences, Social Science Research, 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
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
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
Opper, Isaac M. – RAND Corporation, 2020
Researchers often include covariates when they analyze the results of randomized controlled trials (RCTs), valuing the increased precision of the estimates over the potential of inducing small-sample bias when doing so. In this paper, we develop a sufficient condition which ensures that the inclusion of covariates does not induce small-sample bias…
Descriptors: Artificial Intelligence, Man Machine Systems, Educational Technology, Technology Uses in Education
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
Anika Alam; A. Brooks Bowden – Society for Research on Educational Effectiveness, 2024
Background: The importance of high school completion for jobs and postsecondary opportunities is well- documented. Combined with federal laws where high school graduation rate is a core performance indicator, school systems and states face pressure to actively monitor and assess high school completion. This proposal employs machine learning…
Descriptors: Dropout Characteristics, Prediction, Artificial Intelligence, At Risk Students
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2022
This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Kang, Yoonjeong; Hancock, Gregory R. – Journal of Experimental Education, 2017
Structured means analysis is a very useful approach for testing hypotheses about population means on latent constructs. In such models, a z test is most commonly used for testing the statistical significance of the relevant parameter estimates or of the differences between parameter estimates, where a z value is computed based on the asymptotic…
Descriptors: Models, Statistical Analysis, Hypothesis Testing, Statistical Significance
Tarray, Tanveer A.; Singh, Housila P.; Yan, Zaizai – Sociological Methods & Research, 2017
This article addresses the problem of estimating the proportion Pi[subscript S] of the population belonging to a sensitive group using optional randomized response technique in stratified sampling based on Mangat model that has proportional and Neyman allocation and larger gain in efficiency. Numerically, it is found that the suggested model is…
Descriptors: Models, Efficiency, Sampling, Research Problems
Satinem; Juwati – Advances in Language and Literary Studies, 2018
The research aims to develop the product of Teaching Materials of Poetry Writing Using Pictures. This developed teaching material result is expected to be used by the students of grade V of SD Xaverius Lubuklinggau, SD Negeri 44 Lubuklinggau, and SD Negeri 20 Lubuklinggau in learning to write poetry. The method used in research is research and…
Descriptors: Instructional Materials, Material Development, Poetry, Pictorial Stimuli
Schlauch, Robert S.; Carney, Edward – Journal of Speech, Language, and Hearing Research, 2018
Purpose: Computer simulation was used to estimate the statistical properties of searches for maximum word recognition ability (PB max). These involve presenting multiple lists and discarding all scores but that of the 1 list that produced the highest score. The simulations, which model limitations inherent in the precision of word recognition…
Descriptors: Word Recognition, Computer Simulation, Scores, Phonemes
