1. 1 Research Problem Microbiology students have trouble understanding bioinformatic tools available. They can follow the steps, but they don't really seem to understand what the bioinformatics tools are doing.

2. 2 Research Question Research Question: Does practice with simulated data sets for bioinformatic analysis, along with scaffolding techniques, help students understand bioinformatic analysis? Research Context: Senior students (~40) in their last semester of our course. Some have senioritis. Ages are 20-24 year olds. My question is interesting because: Many students have difficulty understanding complex tools used for analyzing large data sets and will miss apply them, creating invalid data. It is a growing area. There are few techniques for understanding. A model for approaching the teaching of complex problems may be developed that can be applied to many disciplines.

3. 3 Research Methodology Use a series of designed data sets A simple data set where we walk the students through using it Have them use the Darden technique A larger data set where we do incorrect answers to model trouble shooting Their generated data set where they do it on their own, instructor available as a life line. 3 Step performed What this step does sffinfo(sff=GQY1XT001.sff, flow=T) Extracts fasta, qual and flow data trim.flows separates data into bins based on your tags shhh.flows smooths flow files and translates to DNA sequence...

4. 4 Alignment of Research Question and Methodology Learning GoalAssessment Students will be able to critique filtering a analysis (i.e. trouble shoot poor data) Two-tier multiple choice quiz. Open- ended response to explain thinking Students will be able to critique a genome classification Two-tier multiple choice quiz. Open ended response to explain thinking Students will be able to successfully analyze a raw sff file and produce a species distribution from that file Students do a test analysis, in combination with a flow chart. Evaluate log of student commands Written report analysis Students will be more comfortable with the tools used in bioinformatics and be more confident applying them. Pre- and post-survey of students attitudes toward using bioinformatics to analyze data.