Strengthening Contexts for Scholarly Dialogue: Micro-Moments of Inclusive Excellence
Abstract
In consideration of the importance of advancing critical thinking skills, Halpern (2014) identified four essential practices: adopting habits of thoughtful deliberation, building proficiencies in analysis and inference, refining processes of knowledge transfer from familiar to novel environments, and reflecting on personal views. Critical thinking incorporates insightful understanding and evaluation, and it fosters associated judgments. It is central to advancing knowledge. When it is offered in a context of scholarly dialogue, critical thinking becomes the vehicle for personal understanding and shared debate. Even as it facilitates collective understanding, though, scholarly dialogue can foster disagreement and sometimes outright dissent. How best to fine tune shared knowledge and understandings has challenged academicians for generations (Damrosch, 1995). Often inciting the challenge are individuals’ beliefs about what sorts of reflections and ideas are legitimate; how they should be studied and understood; the fiscal implications of addressing them; and whether “the way we’ve always done it,” as an established precedent, ought to be valued and respected. In other words, efforts to advance collective understanding typically invite emotion, a rapidly experienced, neurologically mediated reaction (Byrne, 2015; Kahnemann, 2011) that will influence attending, remembering, and reasoning, and that can derail the fine tuning required for scholarly dialogue. Under challenging…
Read the paper
Related studies
- Knowledge Management Perspective of Generative Artificial Intelligence
- Navigating Generative Artificial Intelligence Promises and Perils for Knowledge and Creative Work
- Characterizing the evolving research on enterprise content management
- Large language models and multimodal foundation models for precision oncology
- From Generative AI to Extended Reality: Multidisciplinary Perspectives on the Challenges, Opportunities, and Future of Educational Computing
- Generative Artificial Intelligence: A New Engine for Advancing Environmental Science and Engineering
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.