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Avery H. Closser; Adam Sales; Anthony F. Botelho – Grantee Submission, 2024
Emergent technologies present platforms for educational researchers to conduct randomized controlled trials (RCTs) and collect rich data on study students' performance, behavior, learning processes, and outcomes in authentic learning environments. As educational research increasingly uses methods and data collection from such platforms, it is…
Descriptors: Data Analysis, Educational Research, Randomized Controlled Trials, Sampling
Jordan 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
Ethan Prihar; Manaal Syed; Korinn Ostrow; Stacy Shaw; Adam Sales; Neil Heffernan – Grantee Submission, 2022
As online learning platforms become more ubiquitous throughout various curricula, there is a growing need to evaluate the effectiveness of these platforms and the different methods used to structure online education and tutoring. Towards this endeavor, some platforms have performed randomized controlled experiments to compare different user…
Descriptors: Educational Trends, Electronic Learning, Educational Experience, Educational Experiments
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
Ostrow, Korinn; Heffernan, Neil; Williams, Joseph Jay – Grantee Submission, 2017
Background/Context: Large-scale randomized controlled experiments conducted in authentic learning environments are commonly high stakes, carrying extensive costs and requiring lengthy commitments for all-or-nothing results amidst many potential obstacles. Educational technologies harbor an untapped potential to provide researchers with access to…
Descriptors: Educational Technology, Authentic Learning, Technology Uses in Education, Cooperation
Ostrow, Korinn S.; Selent, Doug; Wang, Yan; Van Inwegen, Eric G.; Heffernan, Neil T.; Williams, Joseph Jay – Grantee Submission, 2016
Researchers invested in K-12 education struggle not just to enhance pedagogy, curriculum, and student engagement, but also to harness the power of technology in ways that will optimize learning. Online learning platforms offer a powerful environment for educational research at scale. The present work details the creation of an automated system…
Descriptors: Learning Analytics, Technology Uses in Education, Randomized Controlled Trials, Automation
Heffernan, Neil T.; Ostrow, Korinn S.; Kelly, Kim; Selent, Douglas; Van Inwegen, Eric G.; Xiong, Xiaolu; Williams, Joseph Jay – Grantee Submission, 2016
Due to substantial scientific and practical progress, learning technologies can effectively adapt to the characteristics and needs of students. This article considers how learning technologies can adapt over time by crowdsourcing contributions from teachers and students -- explanations, feedback, and other pedagogical interactions. Considering the…
Descriptors: Artificial Intelligence, Educational Technology, Student Needs, Electronic Publishing