Learning Sciences Research
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Browsing Learning Sciences Research by Subject "computer science"
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Item Ambitious Mashups: Reflections on a Decade of Cyberlearning Research(Digital Promise, 2020-09) Center for Innovative Research in CyberlearningThis report reflects on progress from over eight years of research projects in the cyberlearning community. The community involved computer scientists and learning scientists who received NSF awards to investigate the design of more equitable learning experiences with emerging technology—focusing on developing the learning theories and technologies that are likely to become important within 5-10 years. In early 2020, the Center for Innovative Research in Cyberlearning's team analyzed the portfolio of past and current projects in this community, and convened a panel of experts to reflect on important trends and issues, including artificial intelligence and learning; learning theories; research methods; out-of-school-time learning; and trends at NSF and beyond.Item Driving Interdisciplinary Collaboration through Adapted Conjecture Mapping: A Case Study with the PECAS Mediator(Digital Promise, 2022-05) Chang, Michael Alan; Magana, Alejandra; Benes, Bedrich; Kao, Dominic; Fusco, JudithIn 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.