This project studies learning at an innovative museum exhibit about climate change: A Climate of Hope at the Natural History Museum of Utah. By studying learning at A Climate of Hope-which offers a counternarrative to educational experiences that scare, polarize, and/or exclude-we work towards dismantling the current "spiral of silence" around climate change. This project targets two key groups: diverse learners from the general Utah population and learners from historically marginalized communities at the frontlines of climate change. By studying learning processes among these learners in response to frames used in the exhibit, we aim to build knowledge through two key efforts: 1) clarifying theory to explain learning of climate change in informal STEM learning (ISL) settings, specifically by parsing influences of knowledge, emotion, and identity; and 2) generating explanatory theory about how and why framing can support learning. Towards advancing ISL practice, we aim to: 1) explore potential of framing strategies for climate justice advocacy of frontline communities; and, 2) use our empirical, community-engaged research to refine A Climate of Hope. Interdisciplinary, mixed-methods research will occur in two phases, leading in parallel to exhibit refinement and knowledge building. This project aims to advance the field of ISL, as learning processes around climate change remain only partially understood, with this lack of clarity presenting major problems for ISL institutions, such as museums.
The student will contribute in key ways to learning sciences research at the Natural History Museum of Utah (NHMU). They will learn how to collect, organize, clean, and analyze a variety of qualitative and quantitative data. They will collaborate with the Curator of Learning Sciences on a research project studying visitor learning at A Climate of Hope. Specific tasks will include: preparing data collection equipment, supporting audio and video data collection within the exhibit, conducting interviews with Museum visitors, recording observational data through audio or video, transcribing audio and video data, cleaning survey data, and learning to analyze both qualitative and quantitative data with innovative methods. The student might be asked to contribute to the design of new interventions and tools to pilot with visitors at the Museum, with the support of the Curator of Learning Sciences. This is a unique opportunity to work in the Museum while developing skills in data collection and analysis, as well as imagining new ways and opportunities to support learning at the NHMU. Additionally, the student will select a specific line of inquiry within the larger project to pursue over the course of the summer. The project PI will support the student in developing a specific research question and selecting data from the larger dataset to use to answer that question.
Student Learning Outcomes and Benefits
By the end of this program, the student will be able to: 1) Enact key parts of a learning sciences research project, from inception to data collection to data analysis; 2) Use established qualitative methods of analysis to identify meaningful patterns in audio, video, and text-based data; 3) Use descriptive quantitative analytic methods to summarize trends and patterns; 4) Engage comfortably and professionally with Museum visitors in the context of implementing a learning sciences research study; 5) Develop a strong understanding of how museums operate and how learning sciences research can be conducted in informal learning settings, like museums.
My mentoring is grounded in strong, trusting relationships and a responsiveness to students' interests and needs. While every case of mentoring is slightly different depending on the student, across all mentoring, I aim to develop strong relationships with students, so that our collaborative work is built on trust. Early on in mentoring, I work to understand students' needs, interests, and life experiences, so that I can create a space where they will thrive and achieve the goals that they set out to achieve. In this project, the student can expect to meet with me a few times per week to check in about the project. They can also expect to work alongside me in an apprenticeship model, where they learn skills such as data collection, management, and analysis. By the end of the project, I hope for us to be writing collaboratively on the outcomes of this research.