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Direct linkJordan Rickles; Margaret Clements; Iliana Brodziak de los Reyes; Mark Lachowicz; Shuqiong Lin; Jessica Heppen – Journal of Research on Educational Effectiveness, 2024
Online credit recovery will likely expand in the coming years as school districts try to address increased course failure rates brought on by the coronavirus pandemic. Some researchers and policymakers, however, raise concerns over how much students learn in online courses, and there is limited evidence about the effectiveness of online credit…
Descriptors: Online Courses, Electronic Learning, Repetition, Required Courses
Download full textJordan Rickles; Margaret Clements; Iliana Brodziak de los Reyes; Mark Lachowicz; Shuqiong Lin; Jessica Heppen – Grantee Submission, 2023
Online credit recovery will likely expand in the coming years as school districts try to address increased course failure rates brought on by the coronavirus pandemic. Some researchers and policymakers, however, raise concerns over how much students learn in online courses, and there is limited evidence about the effectiveness of online credit…
Descriptors: Online Courses, Electronic Learning, Repetition, Required Courses
Patikorn, Thanaporn; Selent, Douglas; Heffernan, Neil T.; Beck, Joseph E.; Zou, Jian – International Educational Data Mining Society, 2017
In this work, we describe a new statistical method to improve the detection of treatment effects in interventions. We call our method TAME (Trained Across Multiple Experiments). TAME takes advantage of multiple experiments with similar designs to create a single model. We use this model to predict the outcome of the dependent variable in unseen…
Descriptors: Statistical Analysis, Outcomes of Treatment, Intervention, Randomized Controlled Trials
Selent, Douglas; Patikorn, Thanaporn; Heffernan, Neil – Grantee Submission, 2016
In this paper, we present a dataset consisting of data generated from 22 previously and currently running randomized controlled experiments inside the ASSISTments online learning platform. This dataset provides data mining opportunities for researchers to analyze ASSISTments data in a convenient format across multiple experiments at the same time.…
Descriptors: Intelligent Tutoring Systems, Data, Randomized Controlled Trials, Electronic Learning
Kiewik, M.; VanDerNagel, J. E.?L.; Kemna, L. E.?M.; Engels, R. C.?M.?E.; DeJong, C. A.?J. – Journal of Intellectual Disability Research, 2016
Background: Students without intellectual disability (ID) start experimenting with tobacco and alcohol between 12 and 15?years of age. However, data for 12- to 15-year old students with ID are unavailable. Prevention programs, like "prepared on time" (based on the attitude-social influence-efficacy model), are successful, but their…
Descriptors: Smoking, Drinking, Early Adolescents, Adolescents
Schellinger, Adam M.; Toby, Megan; Jaciw, Andrew P.; Zacamy, Jenna – Empirical Education Inc., 2015
Empirical Education Inc. is the independent evaluator of WestEd's 2012 i3 Development grant for Internet-based Reading Apprenticeship Improving Science Education (iRAISE). This interim report provides an update on the progress of the randomized control trial (RCT) during the 2014-2015 school year. The RCT measures the impact of iRAISE on student…
Descriptors: Comparative Analysis, Program Effectiveness, Randomized Controlled Trials, Experimental Programs
Heppen, Jessica; Sorensen, Nicholas; Allensworth, Elaine; Walters, Kirk; Stachel, Suzanne; Michelman, Valerie – Society for Research on Educational Effectiveness, 2012
The consequences of failing core academic courses during the first year of high school are dire. In the Chicago Public Schools (CPS), only about one-fifth of off-track freshmen--students who fail more than one semester of a core academic course and/or fail to earn enough credits to be promoted to 10th grade--graduate high school, compared with…
Descriptors: High School Students, Grade 9, High School Freshmen, Public Schools
