1. Computer Science Outreach and Study: Difference in interest and ability raised in elementary students through “Computer Science Unplugged” supplemented with lectures and as standalone activities
By Bryan Gallo

2. Contents Introduction Background Information Outline of the Study
Inspiration
Types of Learning
Computer Science Unplugged
Outline of the Study
Performing outreach program
Binary Numbers
Searching Algorithms
Sorting Algorithms
Results
Conclusion

3. Introduction- Project Outline
Research computer science teaching methods for younger students
Computer Science Unplugged – collection of CS learning activities that do not use computers. Designed for younger students.
Goal - Contribute to the research on these learning activities. Particularly regarding supplementing the activities with lectures.
Method – CS outreach at an elementary school

4. Introduction – Case Specifics
Outreach offered at a Pittsburgh Intermediate School (Chartiers Valley)
3rd and 4th grade classes were interested in the program
The classes were split into two groups, separated by types of learning.
Each group had 3 forty-minute classes
All students took a survey before the first class and after the last

5. Background Information Inspiration for Project
High demand for computer science students
More classes are being offered to younger students
ACM K – 12 Task Force outlined learning objectives by age and grade level

6. Background Information Inspiration for Project
Grades 3–5: Upon completion of grade 5, students will:
1. Be comfortable using keyboards and other input and output devices, and reach an appropriate level of proficiency using the keyboard with correct fingering.
2. Discuss common uses of technology in daily life and the advantages and disadvantages those uses provide.
3. Discuss basic issues related to responsible use of technology and information, and describe personal consequences of inappropriate use.
4. Use general-purpose productivity tools and peripherals to support personal productivity, remediate skill deficits, and facilitate learning throughout the curriculum.
5. Use technology tools (e.g., multimedia authoring, presentation, Web tools, digital cameras, scanners) for individual and collaborative writing, communication, and publishing activities to create presentations for audiences inside and outside the classroom.
6. Use telecommunications efficiently to access remote information, communicate with others in support of direct and independent learning, and pursue personal interests.

7. Background Information Inspiration for Project
7. Use online resources (e.g., , online discussions, Web environments) to participate in collaborative problem-solving activities for the purpose of developing solutions or products for audiences inside and outside the classroom.
8. Use technology resources (e.g., calculators, data collection probes, videos, educational software) for problem-solving, self-directed learning, and extended learning activities.
9. Determine which technology is useful and select the appropriate tool(s) and technology resources to address a variety of tasks and problems.
10.Evaluate the accuracy, relevance, appropriateness, comprehensiveness, and bias that occur in electronic information sources.
11. Develop a simple understanding of an algorithm, such as text compression, search, or network routing, using computer-free exercises

8. Background Information Types of Learning
Activity Supplemented with Lecture
Introduced to the topics of the lesson and its applications
Listen to a lecture explaining the topic in detail covering how to complete the activity
Discuss results
Standalone Activity
Begin activity and address questions and issues as they come up

9. Background Information Computer Science Unplugged
Collection of computer science learning activities do not require computers or technical skills.
Developed by the CS Education Research Group at the University of Canterbury, New Zealand.
Has had the most success with students ages 5 – 12.
This project will take use three categories of the Computer Science Unplugged activities
Data representation
Searching
Sorting

10. Outreach Program CSU – Data Representation
Binary Numbers
Activity: Students will have cards with numbers on them to represent the bits.
Each “bit” follow an set of steps to represent the correct number
They learn the step by step process to convert binary to decimal
Goal: Introduction to following an algorithm, understanding an algorithm

11. Outreach Program CSU – Searching
Activity: Students will play a game of ‘battleship’ in which the ships appear in sorted order. They will use linear, binary, and hashing sorting algorithms to find their opponents battleship first.
Goal: Introduces the students to optimal algorithms and gives more practice following an algorithm.

15. Outreach Program CSU – Sorting
Activity: Students will learn bubble sort and quicksort algorithms to sort a set of weighted containers using a scale
Goal: Builds on optimal algorithms and following an algorithm.

17. Results Data Gathering
Topics of Comparison
Desire to continue learning about computer science
Understanding of Binary Numbers
Understanding of Searching Algorithms
Understanding of Sorting Algorithms
Fun had in the outreach

18. Results Questions #1 - 5 Supplemented with Lecture:
Before Mean: #.##
After Average: #.##
P-value: .##
Standalone Activity:
Before Mean: #.##
After Average: #.##
P-value: .##
Difference in teaching methods (Lecture - standalone):
Two-tailed p-value
T-value: .##
Difference in Means: #.##
95% confidence interval: (#.##,#.##)

19. Results Desire to continue learning
Supplemented with Lecture:
Before Average: 4.4
After Average: 4.8
P-value: .18
Standalone Activity:
Before Average: 4.0
After Average: 4.2
P-value: .61
Difference in teaching methods:
Two-tailed p value: .6752
T-value: .422
Difference in Means: .2
95% confidence interval: (-0.78,1.19)

20. Results Understanding of Binary Numbers
Supplemented with Lecture:
Before Average: 2.3
After Average: 4.8
P-value: <.0001
Standalone Activity:
Before Average: 1.1
After Average: 4.6
P-value: <.0001
Difference in teaching methods:
Two-tailed p value: .032
T-value:
Difference in Means: -.92
95% confidence interval: (-1.76,-0.08)

21. Results Understanding of Searching Algorithms
Supplemented with Lecture:
Before Average: 2.3
After Average: 4.7
P-value: <.0001
Standalone Activity:
Before Average: 1.1
After Average: 4.5
P-value: <.0001
Difference in teaching methods:
Two-tailed p value: .027
T-value: 2.309
Difference in Means: -.97
95% confidence interval: (-1.82,-0.12)

22. Results Understanding of Sorting Algorithms
Supplemented with Lecture:
Before Average: 2.4
After Average: 4.6
P-value: <.0001
Standalone Activity:
Before Average: 1.2
After Average: 4.5
P-value: <.0001
Difference in teaching methods:
Two-tailed p value: .008
T-value: 2.812
Difference in Means: -1.18
95% confidence interval: (-2.02,-.33)

23. Results Computer Science is fun
Supplemented with Lecture:
Before Average: 4.2
After Average: 4.7
P-value: .0405
Standalone Activity:
Before Average: 3.6
After Average:4.7
P-value: .0015
Difference in teaching methods:
Two-tailed p value: .2105
T-value: 1.276
Difference in Means: -.6
95% confidence interval: (-1.55,.35)

24. Conclusion – Summary of Data
Questions compared
Desire to continue learning about computer science
No Significant Conclusion
Understanding of Binary Numbers
Both groups said they had a better understanding of binary numbers after the outreach
more than 95% confident the standalone activity group expressed a better understanding
Understanding of Searching Algorithms
Understanding of Sorting Algorithms
Fun had in the outreach

25. Conclusion – Observations
Outreach benefitted individuals more than others
Standalone Activity group struggled more than lecture group
By the end I saw more engagement from activity class
Some in the activity class gave up or couldn’t grasp concept and didn’t gain much from the activity
Future work
Explore other methods of data gathering with younger students
Test aptitude and compare it to interest survey

26. References
Hauswirth Matthias. Moving from Visualization for Teaching to Visualization for Learning. University of Lugano. Web. 24 Sept Print.
Lambert, Lynn. and Guiffre, Heather. “Computer Science Outreach in Elementary School” Journal of Computing Sciences in Colleges 24.3 (2009)
Thies, Renate, and Jan Vahrenhold On plugging “unplugged” into CS classes. Proceeding of the 44th ACM technical symposium on Computer science education - SIGCSE ’13:
Prince, M. (2004), Does Active Learning Work? A Review of the Research. Journal of Engineering Education, 93: 223–231.
Scott Freeman, Sarah L. Eddy, Miles McDonough, Michelle K. Smith, Nnadozie Okoroafor, Hannah Jordt, and Mary Pat Wenderoth. Active learning increases student performance in science, engineering, and mathematics. PNAS (23) ; May 12, 2014.
 Computer Science: A Curriculum For Schools. 1st ed. Computing at School Working Group, Print.               
Computer Science: A A Model Curriculum For K-12 Computer Science: Final Report Of The ACM K-12 Task Force Curriculum Committee. 1st ed. CSTA, Web. 18 Sept
 Bell, Tim, and Heidi Newton Using Computer Science Unplugged as a teaching tool. Improving Computer Science Education: 1-18.
Thies, R a, and J B Vahrenhold Reflections on outreach programs in CS classes: Learning objectives for “unplugged” activities. SIGCSE12 Proceedings of the 43rd ACM Technical Symposium on Computer Science Education: