Nesra Yannier, K. Crowley, Youngwook Do, S. Hudson, K. Koedinger
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引用次数: 2
Abstract
ABSTRACT Background Museum exhibits encourage exploration with physical materials typically with minimal signage or guidance. Ideally children get interactive support as they explore, but it is not always feasible to have knowledgeable staff regularly present. Technology-based interactive support can provide guidance to help learners achieve scientific understanding for how and why things work and engineering skills for designing and constructing useful artifacts and for solving important problems. We have developed an innovative AI-based technology, Intelligent Science Exhibits that provide interactive guidance to visitors of an inquiry-based science exhibit. Methods We used this technology to investigate alternative views of appropriate levels of guidance in exhibits. We contrasted visitor engagement and learning from interaction with an Intelligent Science Exhibit to a matched conventional exhibit. Findings We found evidence that the Intelligent Science Exhibit produces substantially better learning for both scientific and engineering outcomes, equivalent levels of self-reported enjoyment, and higher levels of engagement as measured by the length of time voluntarily spent at the exhibit. Contribution These findings show potential for transforming hands-on museum exhibits with intelligent science exhibits and more generally indicate how providing children with feedback on their predictions and scientific explanations enhances their learning and engagement.
期刊介绍:
Journal of the Learning Sciences (JLS) is one of the two official journals of the International Society of the Learning Sciences ( www.isls.org). JLS provides a multidisciplinary forum for research on education and learning that informs theories of how people learn and the design of learning environments. It publishes research that elucidates processes of learning, and the ways in which technologies, instructional practices, and learning environments can be designed to support learning in different contexts. JLS articles draw on theoretical frameworks from such diverse fields as cognitive science, sociocultural theory, educational psychology, computer science, and anthropology. Submissions are not limited to any particular research method, but must be based on rigorous analyses that present new insights into how people learn and/or how learning can be supported and enhanced. Successful submissions should position their argument within extant literature in the learning sciences. They should reflect the core practices and foci that have defined the learning sciences as a field: privileging design in methodology and pedagogy; emphasizing interdisciplinarity and methodological innovation; grounding research in real-world contexts; answering questions about learning process and mechanism, alongside outcomes; pursuing technological and pedagogical innovation; and maintaining a strong connection between research and practice.