Disrupting Learning of Statistics: Using an Appreciative Inquiry Approach to Create Smart Learning Designs

Disrupting Learning of Statistics: Using an Appreciative Inquiry Approach to Create Smart Learning Designs

Lucia-Marie Ganendran (Prince Mohammad Bin Fahd University, Saudi Arabia)
Copyright: © 2019 |Pages: 18
DOI: 10.4018/978-1-5225-6136-1.ch004

Abstract

Saudi Arabia, with its deeply conservative yet rapidly changing society, has adopted an ambitious blueprint for the future in Vision 2030. One of its goals is to increase women's participation in the workforce from 22% to 30%. This case study focused on Saudi female undergraduates undertaking an introductory statistics course. With an emphasis on disruption and smart learning, the author created interventions and tracked changes in attitudes and perceptions of students towards statistics from the beginning to the end of the course. Reusable online resources in the form of a series of content and problem-solving videos were introduced as the semester progressed. At the same time, an appreciative inquiry approach was used to foster a positive change environment. An online forum was created to encourage student discussion and feedback throughout the semester, and anonymous course evaluations were conducted at the end of course. Qualitative and quantitative results are presented here.
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Theoretical Framework

Statistics is a discipline which provides a set of tools for dealing with data. The study of statistics and the value of being able to apply critical thinking skills in statistics is recognized to be an integral part of a university student’s repertoire, so much so that introductory courses in statistics are now mandatory in many undergraduate degree programs worldwide.

The traditional concept of mathematics is that of being able to operate on and manipulate numbers. The study of statistics requires a different kind of critical thinking because it is not concerned only with the skillful manipulation of numbers, but it extracts a story from groups of numbers, referred to as data. It is unique because “data are not just numbers, they are numbers with a context” (Cobb & Moore, 1997, p. 801), and it is this context which provides meaning in data analysis (Cobb & Moore, 1997). In statistics, context dictates procedure and interpretation of results (Gal & Garfield, 1997). Statistics is a highly conceptual field, not simply a collection of methods to solve problems, and it is this that distinguishes it from the study of mathematics (Brown & Kass, 2009).

Key Terms in this Chapter

Undergraduate: A university or college student who has not completed a first degree.

Smart Learning: Learning anytime, anywhere, based on individual cognitive ability, by using an advanced electronic device also called advanced distributed learning, e-learning, online leaning, hybrid learning, and blended learning.

Vision 2030: A proposal to reduce Saudi Arabia's dependence on oil, diversify its economy, and develop public service sectors such as education, infrastructure, health, tourism, and recreation. It includes a goal to increase women’s participation in the workforce from 22% to 30% via the National Transformation Program for Education Reform, which aims to provide the young Saudi workforce with a strong basis for employment.

Attitude: A way of behaving that reflects feelings or opinions about someone or something.

Appreciative Inquiry: A management tool that seeks to design change for the future by discovering and sharing past positive experiences in four distinct stages: discover, dream, design, and destiny.

Disruption: A problem or disturbance which interrupts a process, event, or activity.

Statistics: The science or practice of gathering and analyzing numerical data in large quantities, especially to infer proportions in general from those in a representative sample.

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