1 / 24

Computational Thinking Showcase: Computing Concepts Across Curriculum

Computational Thinking Showcase: Computing Concepts Across Curriculum. PI: Vicki Allan vicki.allan@usu.edu Chad Mano chad.mano@usu.edu Donald Cooley donald.cooley@usu.edu. If you build it…. Why do we start out with programming?. Often we hope students will explore algorithms

sue
Download Presentation

Computational Thinking Showcase: Computing Concepts Across Curriculum

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Computational Thinking Showcase: Computing Concepts Across Curriculum • PI: Vicki Allan vicki.allan@usu.edu • Chad Manochad.mano@usu.edu • Donald Cooleydonald.cooley@usu.edu

  2. If you build it…

  3. Why do we start out with programming? Often we hope students will • explore algorithms • understand concepts • make associations • think about design • consider efficiency • get excited with the possibilities • But is it 95% “tedious” for 5% “ah ha”?

  4. More than “just programming” • Insanity: doing the same thing over and over and expecting a different result. • If you keep doing what you've been doing you'll keep getting what you've been getting.

  5. Idea • Interactive Learning Module ILM

  6. Discussion points • What is corresponding graph? What is an edge? What is a node?

  7. Why do computer scientists like graphs? • How do we use graphs to model problems? • Can you think of a problem that is appropriate for a graph?

  8. Modeling other problems

  9. Collaboration Try to design a map that requires five different colors. • Students loved trying it – especially when we told them it wasn’t possible. • Not easy to check. • Better if they could copy their design (so multiple attempts to color are possible) • Have them design their map via the computer (to get computer verification) or help with coloring.

  10. Designed by RET teacher

  11. Teachers • Liked the idea of using technology to teach technology. • Designed ILMs to meet curriculum guidelines • Customize existing ILMs • csilm becomes the glue to put various material in a single activity • Create ILMs from existing internet resources

  12. Discoveries • Students can go at their own rate – an advantage and a disadvantage • Allows one-on-one time with someone who is struggling • Teacher presentation is important • context of activity (5-10 minutes), • explanation of the main activity (the lead-in) (5-7 minutes), • transition to main activity that includes instructions (2-3 minutes), • main task (20-25 minutes), and • review of activity (3-4 minutes) • survey (3 minutes)

  13. Teachers… • Excellent insight as to what would work • Reading instructions • State mandates • Produce this output rather than follow these steps • What is computer science – different for each • Other requests • Liked the ability to pair questions with software and step through stages. • Want all software as an ILM • Automatic grading of responses

  14. Lessons Learned • The “community” we created of college professors with K-12 teachers and the teachers with each other was extremely valuable. • Being able to compensate teachers for participation is a huge advantage. With everything that requires their attention, paid time gives them a reason/resources to select this project.

  15. Results(116 middle schoolers) Which way would you prefer to learn new material: • ILM 47% • Reading 29% • Lecture 15% • Written homework 9% Well liked – but discovery learning is different

  16. What made the activity uninteresting? • 48% nothing • 11% reading • 7% taking the survey • 7 % lecture • 6% everything • memorizing, homework, easy, boring, long

  17. How well did the exercise help you to learn the material? • Extremely well 33% • Quite well 32% • OK 29% • Not very well 3% • Not at all 3%

  18. Computational Thinking Goals • closes the gap between what is learned in theory and its use • improves time-on-task and increases motivation even after failure • private - removes stigma of failure • provides a scaffolding for learning, giving cues, hints, and partial solutions • personalizes learning so that students can control the pace and the topics they pursue • exhibits infinite patience and provides a self-regulated approach to learning

  19. Methods • We create a community to plan and implement an exciting first exposure to computer science. • We create a set of Interactive Learning Modules which capture interesting computer science problems and challenge users to think creatively. • We foster the use of collaboration-based experiences throughout the computer science curriculum.

More Related