April 29, 2022, 1:11 a.m. | Alexander Scarlatos, Christopher Brinton, Andrew Lan

cs.LG updates on arXiv.org arxiv.org

Educational process data, i.e., logs of detailed student activities in
computerized or online learning platforms, has the potential to offer deep
insights into how students learn. One can use process data for many downstream
tasks such as learning outcome prediction and automatically delivering
personalized intervention. However, analyzing process data is challenging since
the specific format of process data varies a lot depending on different
learning/testing scenarios. In this paper, we propose a framework for learning
representations of educational process data …

arxiv bert data educational framework learning process representation representation learning

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Data Strategy & Management - Private Equity Sector - Manager - Consulting - Location OPEN

@ EY | New York City, US, 10001-8604

Data Engineer- People Analytics

@ Volvo Group | Gothenburg, SE, 40531