Page 54 - Special Topic Session (STS) - Volume 3

STS515 Alison L. G. et al.
Table 1. Strategies for cultivating an Adaptive Statistical Mindset
Strategies \ Inquisitiveness Statistical Extroversion
Component Thinking
Open-ended X X X
investigations
Complex, real-world X X
data
Collaborative work X
Facilitated problem X X
solving
Authentic assessment X X
• Open-ended statistical investigations: Students in our courses carried out
team projects. Key features of these projects include purposely vague,
ambiguous questions and socially significant contexts. As a recent
example, students were provided with counts of incidents of harsh
braking, accidents, and near misses in motor vehicles, and the
corresponding traffic flow and location. Students were tasked with
comparing hazardous driving among locations. To do this they first
needed to consider how they might define “hazardous driving.” The
marking scheme rewarded exploration, including careful consideration of
competing approaches, and innovation, particularly extending the course
concepts. The data were provided by a local company (www.geotab.com)
and company data scientists introduced the project and visited the poster
fair where students presented their findings.
• Complex, real-world data: Concerted effort has been made throughout
all aspects of our courses, lectures, practice problems and assessments, to
expose students to a variety of data collected for a variety of purposes
with rich contexts. To incite students’ curiosity, we tried to use data that
were as close to their experiences and interests as possible. For a course
project we gave students the question “Is university education worth it?”,
which they were free to tackle from any angle they chose. Students were
pointed to survey microdata (e.g., Labour Force Survey, National
Graduates Survey, Canadian Income Survey, Census) collected from
Statistics Canada, the national statistical office, and accessed through our
institution’s data library. They had to explore these rich data sources,
potentially combining them with other ones, and extract relevant
information for addressing their questions.
• Collaborative work: Collaborative work was an integral expectation of
projects and problem solving in our courses. Students were given time to
work in teams in informal environments, in which the teaching team
supported student investigation and experimentation and encouraged
reflection on the process. Teaching assistants arranged students in
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