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Co-Designing Teaching Augmentation Tools to Support the Integration of Problem-Based Learning in K-12 Science

dc.contributor.advisorBiswas, Gautam
dc.creatorHutchins, Nicole Marie
dc.date.accessioned2022-12-13T18:02:52Z
dc.date.available2022-12-13T18:02:52Z
dc.date.created2022-12
dc.date.issued2022-08-26
dc.date.submittedDecember 2022
dc.identifier.urihttp://hdl.handle.net/1803/17821
dc.description.abstractThis dissertation presents three primary but related directions to explore how might we leverage advances in our understanding of how students combine learning of science and engineering in a computational thinking framework implemented in technology-enhanced learning environments to better support classroom teachers in implementing problem-based learning in their K-12 STEM classrooms. We first apply learning-analytics-based approaches to analyze and evaluate student learning and problem-solving processes over the course of a three-week, technology-enhanced, problem-based learning curriculum known as Science Projects Integrating Computing and Engineering (SPICE). Second, we apply a novel end-to-end participatory design technique to design and implement a teacher dashboard that systematically integrates experienced and inexperienced teachers’ insights, values, concerns, and preferences into the design and implementation of the instructor-support technology for problem-based learning in middle school science. This process leveraged results from the first manuscript to connect data visualizations of real student experiences and performance as they work in the SPICE environment. Finally, we conducted a series of simulations with experienced and inexperienced SPICE teachers to explore how teachers interpret feedback provided by the technology, and then translate them into actionable information using evidence-based customizations to update their lesson plans and classroom instruction. Addressing gaps in teacher-engaged participatory design provides for increased opportunities for researchers and system developers to gain a deep understanding of how AI and analytics-driven algorithmic results can inform student-centered pedagogical approaches (such as problem-based learning), how teachers with diverse backgrounds and student populations leverage these technologies to generate actionable information for their teaching, and how we can collectively address bias and promote equity by making the teachers more aware of student work and progress in these STEM curricular applications.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjecthuman-computer interaction, K-12 teaching, computational modeling
dc.titleCo-Designing Teaching Augmentation Tools to Support the Integration of Problem-Based Learning in K-12 Science
dc.typeThesis
dc.date.updated2022-12-13T18:02:52Z
dc.type.materialtext
thesis.degree.namePhD
thesis.degree.levelDoctoral
thesis.degree.disciplineComputer Science
thesis.degree.grantorVanderbilt University Graduate School
dc.creator.orcid0000-0002-7258-5023
dc.contributor.committeeChairBiswas, Gautam


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