DOING MORE WITH LESS: USING ONLINE DATA SETS FOR INQUIRY-BASED LAB INSTRUCTION

Clovis Community College (CCC) is a new and fast-growing 2YC in Central California, accredited in 2015. Its geology program serves an average of 250 students per year in a growing number of combined lecture and lab sections (7, 12, and 15 respectively in the last 3 years). However, the 2019-2020 school year was the first in which there was a full-time geology faculty with official responsibility for program development; in the four years before that, geology courses were taught exclusively by a team of up to six adjuncts. With little formal coordination or budget, no lab coordinator on staff, limited access to tools or materials other than a rock collection, and official discouragement for field trips led by part-time faculty, many introductory geology lab exercises were not feasible. The geology teaching team therefore needed to develop exercises that made good use of lab time by exploiting its opportunities for peer teaching and high student-teacher contact, and avoiding “paper labs” without relying on the availability of many physical resources.

One productive approach we suggest is designing data-driven, inquiry-based lab activities that take advantage of the abundance of data and data visualization tools provided online by various scientific organizations (e.g. USGS Quake Map, Exoplanet Orbits Database, Paleobiology Database), as well as public data sets from published studies. Such exercises give students experience in manipulating and interpreting real data, including hypothesis generation, dealing with investigation constraints (e.g. outliers, detection limits, taphonomic biases), and other scientific practices. Students new to college-level science need intensive scaffolding to have an authentic science inquiry experience since they may have difficulty with a number of basic scientific practices, such as understanding what the data represents, reading graphs, manipulating numbers, estimating regression lines, and other analytical skills. However, this is a strength of this approach, because implementing data-analysis exercises as labs rather than homework encourages instructors to devote time to developing those skills. In this presentation, we will share several such activities and discuss scaffolding methods we have found useful for effective instruction in science practices.