Abstract:

Math phobia is ever present in our society. Socially it is acceptable (even expected!) to be bad at math, and a significant portion of students find math stressful (as indicated, for example, by the 2012 PISA report). Yet math education is critical for success in many fields of study, from programming through STEM to various quantitative business fields and even philosophy. Math phobia is even present among engineering and programming students, who otherwise have aptitude for quantitative disciplines.

Constructionism is an approach proposed by Seymour Papert to re-invigorate the interest of students in Mathematics and STEM fields. In his influential initial work, Mindstorms (1980), he envisions a future where children grow up using the computer, getting inspired by it, thus finding Mathematics and STEM more exciting and less daunting. In the four decades since, constructionism has been used primarily in the pre-university education to enhance student learning (a great integrated example is the British ScratchMath program aiming at 5th and 6th grade students). Over the past decade, constructionist approaches started to appear at university-level education too.

This paper describes a constructionist workshop designed to provide support for freshman business, economics or data science students studying statistics. At the Business School of Saint Mary's College of California, every student is expected to pass an introductory statistics class, irrespective of their chosen major or concentration. This means that the course is taken by students from vastly different backgrounds. The proposed workshop would target students with some introductory computer science background (specifically, Python). This pre-existing programming knowledge would be used in the workshops to guide the students through the process of implementing various statistical calculations. Instead of learning how to use existing statistical packages (which the students do in the main course anyway), they would re-implement the calculations themselves. Through this re-construction, they need to get a thorough understanding of how the various equations and algorithms operate, think through how to handle edge cases, and how they could utilize their earlier implementations to expand them to more complex calculations. They will not just memorize formulas or utilize them, but carefully examine and understand them to be able to implement them. By the end of the workshop, the students are expected to have gained a more thorough, deep and meaningful understanding of the various statistical tools and techniques, leading to better knowledge retention and improved ability to utilize these skills.

The paper starts by showcasing studies introducing the problem, and then will sketch out the structure of the proposed workshops, the programming environments to be considered, the expected learning outcomes and the planned forms of assessments of said learning outcomes.

Keywords:

Statistics education, Math phobia, Constructionism, Constructivism.