1. Students designing online games for active learning sessions in chemistry courses
Brandon P. Eklund, Dylan Gilbertson, Joseph W. Inhofer, Jason D. Greenwood, Omar Mohamed, Peter L. Larsen, Xavier Prat-Resina
Center for Learning Innovation
University of Minnesota - Rochester

2. Context: University of Minnesota Rochester
Laptop Program
Active Learning
Degree in Health Science
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

3. Prat-Resina. Univ. Minnesota Rochester
Main idea
High level thinking
Learn web programming
Create games
Teach chemistry
2nd year Chem. Students
Navigate + Display
ChemEd X Data
Simple online activities
1st year Chem. Students
Memorize basic chemistry
Nomenclature
Acid/Base
Amino acids
Low-level thinking
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

4. Prat-Resina. Univ. Minnesota Rochester
Why gamification?
Our needs:
First-year students in chemistry need basic skills such as chemistry nomenclature, identifying the acid/basic character of compounds or, in biochemistry, memorize amino acids: low-order thinking (boring, repetitive… necessary)
Objectives:
Implementing online game-like activities for non-game tasks to increase engagement and retention
Challenges:
The best game engages: it is not boring and it is not frustrating.
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

5. Prat-Resina. Univ. Minnesota Rochester
Why programming?
Why should everyone learn web programing?
Programming promotes the development of higher mental functions
It makes students create, pay attention to detail and work on problem solving
Understand the web!
privacy + security
data ownership
Quiz yourself on “how the web works”:
Does Facebook know if…
I close the window?
Click on a picture?
Scroll down
When I erase a picture from Facebook. Does it disappear forever?
When I navigate as “incognito” who knows what sites I visit.
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

6. Prat-Resina. Univ. Minnesota Rochester
Why programming?
How?
Weekly seminar of 2nd year students: A project-based course
Each students ends the semester with at least one fully functional online activity
They take online tutorials at home. Bring questions to class
We only use basic action elements:
Click on buttons
Drag and drop
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

7. Example 1: Chemistry nomenclature
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

8. Prat-Resina. Univ. Minnesota Rochester
Example 2: Acid/Base
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

9. Example 3: multi-level nomenclature
Achievement: A leader board
Timed multiple choice (Progress: scaffold difficulty)
Right choice and speed is rewarded
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

10. ChemEd X Data for self-regulated learning
Scattered/Unstructured open data
Chem Ed X Data
Unstructured but easy to represent, parse and sort data
To prove/disprove a chemical statement
Data aligned with topics and compounds in undergraduate curriculum
Tagged with different levels of complexity
ChemEd X Data: Exposing Students to Open Scientific Data for Higher-Order Thinking and Self-Regulated Learning. B. Eklund and X. Prat-Resina. J. Chem. Educ. In press
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

11. High-order thinking and self-regulated learning
Unstructured data
Non-linear
Non-sequential
Open-ended
Skills required: Self-regulation
Self-evaluation
The web
Static, “precooked”
data
Remember  Understand  Apply  Analyze
Evaluate
Look at this graph
See what I want you to see
Explain how everything perfectly fits
Believe me
Choose some data
Represent it
Analyze it
Interpret it
Where can Computer Based Learning Environments (CBLE) be most useful?
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

12. ChemEd X Data for self-regulated learning
Sorting, filtering tables
Graphical representation
Selecting molecular families and
properties
Metadata for search
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

13. ChemEd X Data for self-regulated learning
Explanatory questions (pre-selected sets of data. One right answer).
“Why do these molecules show this trend for property X?”
Problem solving questions:(pre-selected sets of data. One right answer)
“If the heavier the molecule the larger the heat capacity. Why does the heat capacity decrease in the following set of data?”
Prove it: (open-ended)
Choose a set of molecules that prove that hydrogen bonds are stronger than dipole-dipole interaction but much weaker than ionic bonds.
Building knowledge: (open-ended)
Choose a set of data to describe what molecular properties have an influence in heat of combustion.
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

14. Conclusions: The good, the bad and the ugly
A win-win situation:
An opportunity to include programming in any undergraduate major
We obtain game-like activities targeting specific needs for our courses
The bad:
It is hard to have students learn web design and develop in one semester a platform that meets the quality to be used in class.
The ugly
Still, a very small portion of students (all male!) are interested in programming
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester

15. Prat-Resina. Univ. Minnesota Rochester
The team!
Brandon Eklund
Dylan Gilbertson
Joe Inhofer
Peter Larsen
Omar Mohamed
Jason Greenwood
Edulearn 2014
Prat-Resina. Univ. Minnesota Rochester