A technology-enhanced learning intervention for statistics in higher education using bite-sized video-based learning and precision teaching

Angel Tan, Jean Davies, Roderick I. Nicolson, Themis Karaminis

Research output: Contribution to journalArticlepeer-review

Abstract

Adjustments to life and learning following the COVID-19 pandemic have transformed user acceptance of online learning methods. It is, therefore, imperative to analyse factors relating to user performance and preferences for such interactions. In this study, we combined video-based learning with precision teaching to reinforce previously learnt statistics skills in university students without a mathematical background. We developed a learning design consisting of eight ‘bite-sized’ online learning episodes. Each episode started with a brief learning video followed by a practice phase and an end-of-episode assessment. The practice phase differed in two groups of participants, matched on statistics attainment pre- intervention. A precision-teaching intervention group (N = 19) completed practice guided by a frequency-based approach aiming at building fluency in statistics. A control group (N = 19) completed self-directed practice for the same amount of time as the intervention group. All participants completed a statistics attainment test and a questionnaire on their attitudes towards statistics pre- and post- intervention, and a review of the learning materials post-intervention. The intervention group achieved, consistently, higher scores in all end-of-episode assessments compared to the control group. Both groups showed significant and comparable improvements in statistics attainment post-intervention. Both groups also reported more positive feelings towards statistics post-intervention, while the review of the learning materials suggested that the video-based learning design was well-received by students. Our results suggest that video-based learning has great potential to support, as a supplementary teaching aid, university students in learning statistics. We discuss future research directions and implications of the study.
Original languageEnglish
Number of pages27
JournalResearch and Practice in Technology Enhanced Learning
Volume18
Issue number1
Early online date30 Aug 2022
DOIs
Publication statusPublished - 28 Feb 2023

Bibliographical note

Copyright © The Author(s). 2023 Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes weremade. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/

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