Driving Interdisciplinary Collaboration through Adapted Conjecture Mapping: A Case Study with the PECAS Mediator

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dc.contributor.authorChang, Michael Alan
dc.contributor.authorMagana, Alejandra
dc.contributor.authorBenes, Bedrich
dc.contributor.authorKao, Dominic
dc.contributor.authorFusco, Judith
dc.date.accessioned2022-05-31T18:02:30Z
dc.date.available2022-05-31T18:02:30Z
dc.date.issued2022-05
dc.description.abstractIn this report, we demonstrate how an interdisciplinary team of computer science and learning sciences researchers utilize an adapted conjecture mapping tool during a collaborative problem-solving session. The session is documented through an edited “Dialogue” format, which captures the process of conjecture map construction and subsequent reflection. We find that creating the conjecture map collaboratively surfaces a key tension: while learning sciences theory often highlights the nuanced and complex relational nature of learning, even the most cutting-edge computing techniques struggle to discern these nuances. Articulating this tension proved to be highly generative, enabling the researchers to discuss how considering impacted community members as a critical “part of the solution” may lead to a socio-technical tool which supports desired learning outcomes, despite limitations in learning theory and technical capability. Ultimately, the process of developing the conjecture map directed researchers towards a precise discussion about how they would need to engage impacted community members (e.g., teachers) in a co-design process.en_US
dc.description.sponsorshipThis material is based upon work supported by the National Science Foundation under grant 2021159. 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.en_US
dc.identifier.otherDOI: https://doi.org/10.51388/20.500.12265/156
dc.identifier.urihttp://hdl.handle.net/20.500.12265/156
dc.language.isoen_USen_US
dc.publisherDigital Promiseen_US
dc.subjectconjecture mapsen_US
dc.subjectcollaborationen_US
dc.subjectlearning sciencesen_US
dc.subjectcomputer scienceen_US
dc.subjectdesign-based researchen_US
dc.subjectartificial intelligenceen_US
dc.subjectinterdisciplinaryen_US
dc.titleDriving Interdisciplinary Collaboration through Adapted Conjecture Mapping: A Case Study with the PECAS Mediatoren_US
dc.typeTechnical Reporten_US

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