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GEOG 155: GIS Data Acquisition & Management

Prompt Writing, Refinement, Evaluation

Reflection on Instructional Change:

I allowed students to optionally practice writing effective AI prompts. The assignments were optional or bonus points because I did not want to force students to use AI if they are not comfortable with AI or did not want to create an account with an AI website. As part of the class, students write many standard operating procedures (SoPs). In these assignments students practiced identifying audience needs and crafting concise, engaging instructions tailored to specific tasks. In the optional assignments I had them ask AI to write the SoPs, and then had them (1) evaluate the output generated by the AI, and (2) identify where it did well and where it failed with the directions it produced.

Students did NOT like using AI, often finding it very frustrating at the vagueness of directions provided, and commenting that correcting AI and constantly evaluating its output took more work than writing the SoP on their own. This is likely because GIS is not a common dataset in AI, and the tasks I have students perform are not cookie-cutter. Students also remarked at the invalid information returned by AI, with one student commenting "[u]sing AI for [finding GID datasets] provides you with a good start on the assignment but it does not respond perfectly according to the prompt, despite multiple refines of the original prompt to clarify. Some of the links seemed great while others were nonexistent or not clickable at all. Regardless, it would be important to go in and verify any sources provided through AI as well as the quality of data it finds."

In interacting with "ACUE Gen AI Course Activities: Writing Effective Prompts" I found that students had a greater appreciation of gen AI's limitations -- what it cannot do and what it does not do well. They learned that while the answer looked reasonable, they had to constantly check, verify, refine, and ultimately do it on their own. This helped engage critical thinking and problem-solving skills via a somewhat novel environment.

In the "Observe and Analyze" session my "aha" moment about my teaching is that my desire to be incredibly clear about expectations results in repetition.

Evidence of Instructional Change

evidence of instructional change
Screenshot of providing activity instruction for an option portion of a lab assignment	Screenshot of student submission from a bonus assignment, demonstrating prompt development	ACUE badge for "Empowering students to use AI responsibly"

Practice and Reflect Teaching and Learning with AI:

The ACUE course has changed teaching practices in challenging where I have students apply critical thinking, and in constantly evaluating the efficacy of AI's answers (they're still pretty trash most of the time). I use ChatGPT in class to have students practice prompts and to evaluate the results as a class. This allows them to see the process of evaluation modeled and implemented

Course Syllabus

Syllabus_GEOG155_F24.docx

Faculty Bio

faculty bio
	My name is Anna Klimaszewski-Patterson and I am an Associate Professor in the Department of Geography. Prior to going back to school to receive my degrees in Geography (B.A. from San Diego State, M.A.G from New Mexico State, and Ph.D. from the University of Nevada, Reno) I was a (mostly Web) programmer for 18+ years for companies ranging from start-ups to Fortune 100. I know Python, R, PHP, JavaScript, HTML/CSS, (and it's been a while, but also Perl, C, & C++, and enough Fortran and Visual Basic to read and tweak). I am a geospatial scientist, biogeographer, and paleoecologist with specializations in geovisual analytics, environmental change modeling, and human-environment interactions. My research focuses broadly on integrating quantitative field-based ecosystem observations with climate and environmental change simulations/geovisualizations.

Funding
	This work was supported by: US Department of Education Hispanic Serving Institution Project TECH4Equity US Department of Education Hispanic Serving Institution Project STEM4Equity P031C210012 *Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation or the US Department of Education.