Managing Undergraduate Research – Lessons Learned

1. Managing Undergraduate Research – Lessons Learned Dave Musicant Carleton College Thursday, March 8, 2007

2. Who Am I? • Assoc Prof at Carleton College • Liberal arts: 1900 students • ~15 CS majors/year • Teaching: • AI, DB, DM, PL, CS 1 & 2 • My research: • Machine learning and data mining • Have advised 26 students, 12 projects • Currently: Enchilada • Environmental Chemistry Through Intelligent Atmospheric Data Analysis

3. Heavy debt to SIGCSE 2001 • Managing Undergraduate CS Research • James W. McGuffee, St. Edward’s University • Herbert L. Dershem, Hope College • Linda Lankewicz, The University of the South • Gary Lewandowski, Xavier University • Dian Lopez, University of Minnesota - Morris • Oberta A. Slotterbeck, Hiram College

4. My criteria for selecting students • Individual • Smart • Quick learners • Self-motivators • Group • Balanced levels among them • Can work well with me and others • Why groups? • Support • My time • Community

5. Finding the right projects • They know... • how to program, a bit • some basic algorithms • They don’t know... • nuances of my field • enough math • good software design • my tools • Programming projects work best... • but can’t publish just programming

6. The pace is going to be SLOW • Snail factors • Other demands • Procrastination • Learning it all for first time • What helps? • Signup for a year • Meet often • Email task lists • Bug tracking software • Partners • Reward per hour ($)

7. Watch their egos • Research can go wrong • Students blame themselves • ... or just don’t get rewards of success • Positive reinforcement important • Often • Students’ original ideas • Allow to pursue? • Evaluation • No grades • Discussion good