Innovative Practices in Computer Science Barbara Ericson Georgia Institute of Technology CCLI Conference Aug 2008

Innovative Practices  Alice  Games  Media Computation  Robotics

Main Questions  How has the approach been assessed and what were the results?  What are the strengths and weaknesses of the approach?  How does the approach work with majors and non-majors?  What are the barriers to adoption of the approach?

What is Alice?  Free development environment From Carnegie Mellon University Available from  Used to create 3D movies and games  Used to teach object-oriented programming Without the frustration of syntax errors  using drag-and-drop programming

Alice Assessment  Used as a pre CS1 for "at risk" CS majors at Ithaca College (Wanda Dann) and St. Joseph's University (Stephen Cooper) (n=25) SIGCSE'00 compared to a non treated "at risk" control group (n=30) and a not "at risk" control group (n=52) "high risk" – lack of programming experience and weak math skills better grades for the treatment group in CS1 (about 1 grade higher (3.0 versus 1.9) higher retention in CS1 (88%) than both control groups  "at risk" (47%) and not "at risk" (75%) higher retention through 2 nd year (88%) vs (15% for "high risk")  Open questions Would any intervention for the "at risk" group had the same success? How well would it work for CS1?

Alice Strengths and Weaknesses  Advantages Used for teaching computing concepts without the frustration of syntax Can be used to develop animations and games  creative and open-ended assignments  Disadvantages Doesn't cover all CS1 topics Steep learning curve for getting started Doesn't work well on all machines Perceived as not "real"

What do we mean by Games?  Types 2D arcade style games 3D computer games  first person shooter  Wii-type interactive games  simulation games Role playing games Board games

Games Assessment  Games as a context for CS1-CS3 Jessica Bayliss, Rochester Institute of Technology, RAPT program, SIGCSE'06  48 individuals in a distance first summer course (2 female and 5 minorities)  34 passed (only 37 took exam) (about 30% WDF)  reports that students were highly engaged in the course, but not everyone wants to make games  Games as a context for a general education course for non- majors, GDCSE’08 Jim Whitehead, Un. of Calif, Santa Cruz  two years with a total of 212 students (20% female)  each year about 1-3 students switch to a game design degree  81% rate the course good to excellent

Games Strengths and Weaknesses  Strengths Attractive context for some majors and non-majors  does increase enrollment in some courses Can teach many computing concepts in this context  CS1, CS2, machine learning, AI, graphics, etc  Weaknesses Doesn't appeal to many women and some men Steep learning curve for instructors Need a library of games and game consoles Game design degrees may limit job opportunities

linked listcollage What is Media Computation?  Writing programs that manipulate media to teach computing concepts iteration as a way to modify all pixels in a picture to negate the picture conditionals as a way to remove red eye from a picture or to do chromakey Covers CS1 and CS2 topics  Developed by Dr. Mark Guzdial at Georgia Tech

Media Computation Assessment  Used as a CS1 for non-majors (Georgia Tech) or as a pre CS1 (Gainesville College), SIGCSE'04 majority female (53.8% Tech and 69.2% Gainesville) improvement on success in course  from 71.2% to 86%-90% at Georgia Tech (n=818)  from 70.2% to 77% - 90% at Gainesville (n=81) 68% of students enjoyed the class and 42-50% wanted to take an additional media computation course (versus 23-31% for a CS course) (3.5% in a pre-course survey)  Used as a CS1 at Columbus State University With "traditional" CS1 sections as control (Lewis and Loftus)  better success and satisfaction with course with Media Computation  no difference in CS2

Media Comp Strengths and Weaknesses  Strengths succeeds with women encourages creativity programs have concrete results has proven successful at many institutions with different instructors  and for large numbers of students  Weaknesses pushback from departments (not "real" CS)  not how I learned it misconception that it is easier than traditional CS  if it is fun they can't be learning CS sound cards needed in machines to do sound processing

What do I mean by Robots?  Institute for personal robotics at Georgia Tech and Bryn Mawr funded by Microsoft Research  CS1 at Georgia Tech and Bryn Mawr robot with camera (includes Media Computation)

Robot Assessment  Two semesters trial (Georgia Tech majors and Bryn Mawr undeclared majors) 90.87% success rate students enjoyed the robots reported the class being about computer science found the homework challenging a final exam comparison at Georgia Tech showed that the robot course students did better on most questions  but, mostly CS majors in robot class and non-majors in traditional Jump in students taking CS2 at Byrn Mawr  2-6 usual pre robots and now post robots

Robots Strengths and Weaknesses  Strengths Helps retain students in CS1 Helps attract students to CS2  Weaknesses Cost ($150 currently) robots have limited ability