Scenario-based learning presentation from Chuck, Jen, and Staci

1. Successful Teaching Using
Computational Thinking via
Scenario Based Learning
Chuck Winer, Professor, Computer Information Technology and Graphics
Anastasia Trekles, Clinical Associate Professor, Instructional Technology
Jennifer Werner, Adjunct Professor of Computer Information Technology
and Instructional Designer, Community Healthcare Systems
Purdue University Calumet
Hammond, IN

3. Objectives
 Explain the concepts of Computational Thinking and
Scenario Based Learning as powerful tools for supporting
authentic student learning
 Discuss the benefits to serving as a Subject Matter Expert to
classrooms employing scenarios
 Demonstrate how teachers and businesses can work
together to bolster important critical thinking and problem-
solving skills in students
 Share the research produced from the ASSECT NSF grant,
including a Google Sites template and Computational
Thinking rubric

4. Background
 NSF grant project (ASSECT: Advancing the Successful IT
Student Through Enhanced Computational Thinking)
 Partnership of universities in five regions
 Marriage of Jeanette Wing’s Computational Thinking (CT)
with a framework for building instructional elements
 Focus on Scenario-Based Learning (SBL) combined with CT
to help teachers deliver engaging lessons that help students
develop important critical thinking skills within authentic
career-oriented situations

5. What exactly is Computational
Thinking?
 A problem-solving process
 A way of dealing with complexity
 A method of using available tools, including technology, in
logical ways to solve problems and answer questions
 ISTE’s definition:
http://www.youtube.com/watch?v=VFcUgSYyRPg&feature=y
outu.be
 Jeanette Wing’s description: http://youtu.be/C2Pq4N-iE4I

6. Problem-Based Learning Scenario-Based Learning
PBL vs. SBL
 Project or problem is often
already defined for the
student
 Solution may involve a
particular “right answer”
 Teacher guides students
toward the right answers
 Project may be contrived or
not based on real situations
 Exact problem details not
given; students define the
problem
 There is not necessarily a
right answer
 Teacher serves purely as a
facilitator and co-learner
 Project involves real outside
experts and situations

7. Examples of SBL/CT Scenarios
 Our list research-based scenarios can be found at
https://sites.google.com/site/workshopctandsblresourcesite/s
haring-our-research-experience
 Experiential Learning Center: http://learnpbl.com
 Computer Science Teachers Association:
http://csta.acm.org/Resources/sub/ResourceFiles/CompThin
king.pdf
 Examples from Ross Smith, a teacher trained in our
workshops:
 http://whoreallydiscoveredamerica.weebly.com
 https://sites.google.com/a/hammondacademy.org/middle-ages-
project/
 https://sites.google.com/a/hammondacademy.org/standard-of-
living2/

8. The CT Rubric
 Helps to assess computational thinking skills, including
logical thinking, strategizing, abstract thinking, procedural
thinking, and optimizing
 https://sites.google.com/site/workshopctandsblresourcesite/c
omputational-thinking-rubric

9. The Scenario-Building Template
 Workshop link with context and other information:
https://sites.google.com/site/workshopctandsblresourcesite
 Google Sites Scenario-building template:
https://sites.google.com/site/assectworkshop/home

10. Thank you!
 Chuck: winer@purduecal.edu
 Staci: atrekles@purdue.edu
 Jen: jencruse@hotmail.com