The Benefits of Peer Instruction and Collaborative Study in Acquisition of Data Analysis Skills

 

Lakshmi Chilukuri

Tested Studies in Laboratory Teaching, 2013, Volume 34

Poster file:

Abstract

The development of sound quantitative reasoning skills is a very important learning goal for the undergraduate Biology labs at UCSD. Achievement of this goal is part of two other learning goals: developing strong critical thinking skills and proficiency in scientific writing. However, analysis of numerical data is not nearly as intuitive for students as managing descriptive data and mastery of complex data sets and can be a daunting task. To make this goal achievable, I have incorporated a very structured and interactive learning module to promote practice and retention of quantitative skills in the context of ongoing lab experiments. In this approach, students work with three incrementally challenging datasets to gauge, improve, and test their competence in quantitative reasoning. The first data set is the simplest and allows them to determine their baseline skill levels while the final data set is related to authentic research conducted in our lab and is the most complex of the series. The centerpiece of this strategy is an intensive and highly interactive data analysis workshop in which students work in pairs to organize, analyze, and summarize a moderately complex data set using a spreadsheet program, such as Excelâ„¢, with subsequent independent work. The format of the workshop promotes healthy dialogue between students and between students and instructor while the students are in the learning process. This provides the opportunities to answer questions in real time, gauge student understanding before misconceptions set in, and monitor and guide work as it proceeds to avoid frustration and fatigue. This approach has the advantage that it can be readily adapted to any desired level of quantitative complexity.

Keywords:  data analysis, peer instruction

University of North Carolina, Chapel Hill (2012)