| Autor: |
Heffernan, Neil, Heineman, George, Korinn Ostrow, Botelho, Anthony, Baker, Ryan, Stein, Rebecca, Decherney, Peter |
| Rok vydání: |
2020 |
| DOI: |
10.6084/m9.figshare.11425899.v1 |
| Popis: |
Research on Adaptive Intelligent Learning for K-12 and MOOCs (RAILKaM) cyber infrastructure will enable 20 researchers to run large-scale field experiments on basic principles in the educational contexts of K-12 mathematics learning and university Massive Online Open Courses (MOOCs). RAILKaM will integrate ASSISTments, an online learning platform used by more than 100,000 K-12 students, with MOOCs offered by the University of Pennsylvania and used by hundreds of thousands of learners each year, in order to enable broader populations, more robust student interactions, and more bountiful data collection than currently feasible in either environment alone. RAILKaM will also support 75 data scientists by supplying carefully redacted datasets that protect student privacy. In facilitating 1) high-power, replicable experiments with diverse student populations and 2) extensive measurement, RAILKaM will increase the efficiency and ease of conducting quality educational research in online learning environments, bringing research methods and long-term learning outcomes to 21st-century classrooms. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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