Accelerated Apprenticeship - Teaching Data Science Problem Solving Skills at Scale - Robotics Institute Carnegie Mellon University

Accelerated Apprenticeship – Teaching Data Science Problem Solving Skills at Scale

Lujie Chen and Artur Dubrawski
Conference Paper, Proceedings of 5th Annual ACM Conference on Learning at Scale (L@S '18), June, 2018

Abstract

It often takes years of hands-on practice to build operational problem solving skills for a data scientist to be sufficiently competent to tackle real world problems. In this research, we explore a new scalable technology-enhanced learning (TEL) platform that enables accelerated apprenticeship process via a repository of caselets - small but focused case studies with scaffolding questions and feedback. In this paper, we report rationales of the design, caselet authoring process, and the planned experiment with cohorts of students who will use caselets while taking graduate level data science courses.

BibTeX

@conference{Chen-2018-121805,
author = {Lujie Chen and Artur Dubrawski},
title = {Accelerated Apprenticeship - Teaching Data Science Problem Solving Skills at Scale},
booktitle = {Proceedings of 5th Annual ACM Conference on Learning at Scale (L@S '18)},
year = {2018},
month = {June},
}
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.