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

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.
 
 

Bite-sized and peer-assisted video-based learning in statistics education: benefits on attainment, attitudes and preferences of university students

“…Our current research examines the use of precision teaching (Kubina et al, 2000;Lindsley, 1992), whereby the learning of individual students is closely monitored, in online video-based learning designs for statistics (Tan et al, 2021). Table 1 Counter-balanced order of conditions across sessions and across participants.…”