EXPANDING THE REACH OF A NSF COMMUNITY FACILITY: EXPERIENTIAL LEARNING THROUGH REMOTE-CONTROL OF AN ANALYTICAL INSTRUMENT

Access to computer-controlled, state-of-the-art analytical tools for the geologist via the internet is becoming increasingly more feasible. Theoretically, this allows researchers to use these tools remotely, eliminating costs of travel and lodging and opening up new opportunities, particularly for underrepresented groups. The ASU Secondary Ion Mass Spectrometry (SIMS) NSF Community Facility is home to one such analytical tool and presents a unique opportunity for improving pedagogical practices, diversity and collaboration in research methodologies. SIMS instrumentation is expensive and uncommon. Remote, around-the-clock access would provide beneficial economies of scale.

While in-person training under the guidance of the resident subject matter expert is straightforward, how might this training be enhanced for remote users? To answer this, we examine our in situ training and consider modifications to maximize learning and research outcomes for our virtual visitors. The goal is to have users transition from being passive observers to active learners by designing the training using proven instructional design theories, such as Kolb’s (2014) Experiential Learning Theory, in tandem with a flipped classroom model.

SIMS is used for microanalyses of trace elements and determination of certain isotope ratios, thus, an example of a learning objective would be to have learners evaluate which analysis protocol is best suited for a particular study. Such protocols might include the use of high mass resolution or energy filtering to remove interfering species.

Pre-knowledge of different SIMS analyses is required. Thus, it will be important to develop a variety of lessons using a flipped classroom methodology for new users to maximize efficiencies. We have first-generation versions of selected lessons: 1) preparing a sample for SIMS analysis, 2) aligning the primary and secondary ion beams, 3) achieving high mass resolution, and 4) using SIMS in ion microscope mode. Critical next steps include trial runs with remote users and development of assessment tools that will determine the efficacy of the training.

Kolb, D. A. (2014). Experiential learning: Experience as the source of learning and development. FT press.