Managing Undergraduate Research Lessons Learned Dave Musicant Carleton
- Slides: 7
Managing Undergraduate Research – Lessons Learned Dave Musicant Carleton College Thursday, March 8, 2007
Who Am I? n Assoc Prof at Carleton College q q n Teaching: q n Liberal arts: 1900 students ~15 CS majors/year AI, DB, DM, PL, CS 1 & 2 My research: q q q Machine learning and data mining Have advised 26 students, 12 projects Currently: Enchilada n Environmental Chemistry Through Intelligent Atmospheric Data Analysis
Heavy debt to SIGCSE 2001 n Managing Undergraduate CS Research q q q James W. Mc. Guffee, 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
My criteria for selecting students n Individual q q q n Group q q n Smart Quick learners Self-motivators Balanced levels among them Can work well with me and others Why groups? q q q Support My time Community
Finding the right projects n They know. . . q q n They don’t know. . . q q n how to program, a bit some basic algorithms nuances of my field enough math good software design my tools Programming projects work best. . . q but can’t publish just programming
The pace is going to be SLOW n Snail factors q q q n Other demands Procrastination Learning it all for first time What helps? q q q Signup for a year Meet often Email task lists n q q Bug tracking software Partners Reward per hour ($)
Watch their egos n Research can go wrong q q n Positive reinforcement important q n Often Students’ original ideas q n Students blame themselves. . . or just don’t get rewards of success Allow to pursue? Evaluation q q No grades Discussion good
