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Teaching Statistics: A Technology-Enhanced Supportive Instruction (TSI) Model During the Covid-19 Pandemic and Beyond

Authors :
Serina Al-Haddad
Nancy Chick
Farshid Safi
Source :
Journal of Statistics and Data Science Education, Vol 32, Iss 2, Pp 129-142 (2024)
Publication Year :
2024
Publisher :
Taylor & Francis Group, 2024.

Abstract

AbstractMany approaches exist in teaching statistics, however, learning statistics is frequently perceived by students as challenging. While evidence-based teaching approaches like case discussions and flipped-classroom models have been successfully incorporated into multiple disciplines, these methods can have inadequate success when students are affectively detached or sometimes paralyzed by the subject. The sudden need to switch to virtual teaching in Spring 2020 created unprecedented challenges that were overwhelming for instructors and students. This article explores the challenges of teaching a statistics course, and the importance of purposeful use of technology and supportive feedback to effectively engage students and promote learning. Furthermore, this article discusses the results of implementing a Technology-enhanced Supportive Instruction (TSI) model (used since Fall 2019) in teaching a business statistics course. The TSI model uses Microsoft Excel in conjunction with intentional interactions between the student and teacher to help students stay engaged in face-to-face and remote learning. The analysis of Fall 2020 course evaluations, when the course was taught in a dual mode, shows positive students’ perception of instruction and engagement, and indicates that Fall 2020 ratings during dual-mode instruction were not different from Fall 2019 ratings during face-to-face instruction, which supports the potential utility of the model. Supplementary materials for this article are available online.

Details

Language :
English
ISSN :
26939169
Volume :
32
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Journal of Statistics and Data Science Education
Publication Type :
Academic Journal
Accession number :
edsdoj.fa996141a1a49709ea341818f365085
Document Type :
article
Full Text :
https://doi.org/10.1080/26939169.2024.2315939