The
sTEm-at Work Puzzle series is
on hiatus. It is likely the series will
return. However, as its slips out the
door heading toward Hyannis Port, today's FLATE FOCUS has a reminder of what
the puzzles are trying to do.

The
lack of specifics also directs the students to the plots intended message. This provides instructional avenues for proper
interpretation the graphic data as relative to magnitudes for variables in
context with the "story" that the graphic is presenting. It also directs student attention to the plot's
boundary conditions expectation. This
knowledge helps students understand the intended range of data that quantizes
the situation.
Finally, the puzzles present students with a situation where they must
reach a definitive (yes/no) conclusion.
A task that is hard to master since it also requires the continuous
development of the student's proper self assessment of their knowledge and skills
and then the confidence to make a public declaration of their conclusions. Success
with these skills, in turn, develops the student use of data as part of their
trouble shooting toolbox with the confidence that they will be able to move
through the problem's symptoms, compare that data with the acceptable range of
data, and then fix the problem.
Despite
the ever presence of flashy visual data in our 21st century world,
few people critically review data in any format. It is very important for technical educators to
provide students with opportunities to practice and develop their own strategies
for analyzing visual information. Data
presented in infographics typically showcase data bytes that an author wants
the audience to see from a single point of view. This snapshot brevity of infographics is
admirable however, the practice hides data that is often needed to think
creatively, troubleshoot, and solve problems. Educators should use exercises like the
STEM-at-Work puzzles because our instructional practices typically do not
always deal with challenging information and critical interpretations. A successful technician in any field must be
able to critically read, interpret, and trouble shoot a problem using scalar data
quickly and effectively. And so, like
Arnie, we'll be back!
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