March 20, 2024, 4:42 a.m. | R. Cerezo, A. Bogarin, M. Esteban, C. Romero

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.12068v1 Announce Type: cross
Abstract: Content assessment has broadly improved in e-learning scenarios in recent decades. However, the eLearning process can give rise to a spatial and temporal gap that poses interesting challenges for assessment of not only content, but also students' acquisition of core skills such as self-regulated learning. Our objective was to discover students' self-regulated learning processes during an eLearning course by using Process Mining Techniques. We applied a new algorithm in the educational domain called Inductive Miner …

abstract acquisition arxiv assessment challenges core cs.cy cs.lg e-learning elearning gap however mining process process mining skills spatial students temporal type

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

Business Data Scientist, gTech Ads

@ Google | Mexico City, CDMX, Mexico

Lead, Data Analytics Operations

@ Zocdoc | Pune, Maharashtra, India