Instructors in lab courses often find it difficult to simulate and discuss all phases of scientific inquiry during a single class period. For instance, individual lab groups may not be able to replicate experimental trials sufficiently in the time allotted, requiring instructors to compile data sets across lab groups before students can properly analyze and interpret results.Google Spreadsheets can circumvent this logistical barrier by allowing instructors to crowdsource the data aggregation and “cleaning” during class.
For example, Chad Hershock and Rachel Niemer, CRLT, teach a short-course for postdocs on college teaching in science and engineering. During a unit on converting traditional, “cookbook” lab exercises into inquiry-based activities, postdocs work in pairs to complete a sample lab protocol. All the pairs then enter their data into a single Google Spreadsheet, so that the class compiles a robust class data set in real time, without any cutting and pasting across files.
Instructors simply monitor the data as it accumulates, responding to problems as needed. In the same class meeting, each group can analyze the entire data set to test student-generated hypotheses and predictions brainstormed during a brief pre-lab discussion. Students then share and discuss visual representations of their findings within the Google Spreadsheet, connect results to underlying fundamental concepts, and reflect on their inquiry processes. This approach integrates more of the scientific method into a single classroom experience, rather than leaving the analysis and interpretation for students to complete in isolation after class.