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Training graduate students to teach statistics and data science from a distance

Rummerfield, Wendy; Ricci, Federica Zoe; Dogucu, Mine; (2021) Training graduate students to teach statistics and data science from a distance. In: Helenius, R and Falck, E, (eds.) Proceedings of the IASE 2021 Satellite Conference. International Association for Statistical Education Green open access

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Abstract

Enrollment in undergraduate statistics and data science courses has rapidly increased in just the last decade, resulting in an increased reliance on graduate teaching assistants (GTAs) and graduate instructors of record (GRIs). In the age of the COVID-19 pandemic, teaching from a distance has become a necessity. Many instructors, including GTAs and GRIs, need to adapt to new technologies and reconsider pedagogical decisions. This paper presents our experiences from a graduate teaching fellowship program created because of the pandemic. The program had two major components: 1) pedagogical workshops attended by teaching fellows from multiple disciplines across the university and 2) one-on-one mentoring by a faculty member from the fellow’s primary discipline. Here, we provide a unique look at graduate training from both the perspective of the mentor and the mentee. We share a sample training curriculum and propose recommendations for those interested in implementing teaching training opportunities for graduate students.

Type: Proceedings paper
Title: Training graduate students to teach statistics and data science from a distance
Event: Satellite conference of the International Association for Statistical Education (IASE)
Location: Online conference
Dates: August - September 2021
Open access status: An open access version is available from UCL Discovery
DOI: 10.52041/iase.iwvgy
Publisher version: https://iase-web.org/documents/papers/sat2021/IASE...
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher's terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10163831
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