0 Analyzing Programming Projects

Stuart Hanson, University of Wisconsin - Parkside

"This paper presents the results of student surveys administered after each programming project for multiple sections of two courses: CS2, and Data Structures and Algorithms." They "analyze the data in terms of engagement, frustration and niftiness (from abstract)."

The survey was administered on the due date of each assignment, 4 semesters of data for CS1 and CS2, 3 semesters of data of Data Structures and Algorithms and CS0 data from another institution. Class sizes varied from a low of 6 to a high of 30.

Engagement and frustration
positive correlation in CS2, small negative correlation between engagement and frustration means (the more challenge, the less frustration) and no clear correlation for this difference.

Niftiness = engagement - frustration
- distinguishes nicely among projects with large differences in two values.
- flawed in that it doesn't distinguish among projects where engagement and frustration are approximately equal.

Worst assignments
- all were "borrowed"
- all had instructor related problems

1. bad data set
2. major writing component that the instructor did not adequately discuss.
3. assumed (java i/o) background that students did not have.

I would also like to add to the list: Uniquely designed problems/assignments that were not tested by the instructor or TA. These ultimately end up being a 'rollercoaster' ride for the students with a negative thrill factor ...

Refining assignments work

• worst assignments were all first timers
• best assignments were all old timers