Section

Developing teaching practice

Abstract

Welcome to this special issue of the Journal of University Teaching and Learning Practice. Over the past 50 years, great strides have been taken in the use of technology and distance learning across the disciplines and there has been rising interest in research-informed teaching. Correspondingly, there has been a movement towards greater openness on the part of statistical educators to change their teaching practices in an effort to strive for excellence. In this special issue, a variety of approaches to teaching statistics to non-specialists are presented, all of which have a grounding in the pedagogical literature and involve innovative practices within the authors’ own institutions. With the support of a ‘ten tips’ article involving a book review, consideration is also given to maintaining quality standards. This includes recognising the place of statistics among the sciences and ensuring that making the subject accessible does not lead to compromises in student understanding of statistical inference and the conditions for use of basic statistical procedures. The papers are united in addressing challenges in the teaching of statistics to non-specialists and as such, should assist in supporting communities of practice in this teaching area. In adjusting to the varying social distancing measures presented by the Covid-19 pandemic, we have both observed and participated in new ways of building bridges with students which have unquestionably reshaped the landscape of learning and teaching. Many of us who have found these experiences rewarding will be reluctant to return to status quo as post-pandemic plans unfold, since responding to the need for creativity in distance learning provision has proved beneficial to our own personal professional development in serving the needs of our students. Others may have felt ill-prepared to reconstruct their course content due to a lack of time, training and resources. Either way, I hope that many of the ideas and recommendations provided in this special issue will prove supportive and serve as an impetus to press on in an effort to make the learning of statistics an attractive and rewarding option for non-specialists while maintaining quality standards, particularly where staff resources are limited.

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