The public release and surprising capacity of ChatGPT has brought AI-enabled text generation into the forefront for educators and academics. ChatGPT and similar text generation tools raise numerous questions for educational practitioners, policymakers, and researchers. We begin by first describing what large language models are and how they function, and then situate them in the history of technology’s complex interrelationship with literacy, cognition, and education. Finally, we discuss implications for the field.
To understand instruction during the spring 2020 transition to emergency distance learning (EDL), we surveyed a sample of instructors teaching undergraduate EDL courses at a large university in the southwest. We asked them how frequently they used and how confident they were in their ability to implement each of nine promising practices, both for their spring 2020 EDL course and a time when they previously taught the same course face-to-face (F2F). Using latent class analysis, we examined how behavioral frequencies and confidence clustered to form meaningful groups of instructors, how these groups differed across F2F and EDL contexts, and what predicted membership in EDL groupings. Results suggest that in the EDL context, instructors fell into one of three profiles in terms of how often they used promising practices: Highly Supportive, Instructor Centered, and More Detached. When moving from the F2F to EDL context, instructors tended to shift “down” in terms of their profile—for example, among F2F Highly Supportive instructors, 34% shifted to the EDL Instructor Centered profile and 30% shifted to the EDL More Detached Profile. Instructors who reported lower self-efficacy for EDL practices were also more likely to end up in the EDL More Detached profile. These results can assist universities in understanding instructors' needs in EDL, and what resources, professional development, and institutional practices may best support instructor and student experiences.
teacher learning and classroom practice. We define and discuss technologyrich environments, which encompass a complex combination of tools, curricula, contexts, and teachers. We will point out that technocentrist approaches (see discussion in Papert, 1990) persist in the classroom and note their counterproductive nature. We then conceptualize technological pedagogy within the framework of technological pedagogical content knowledge (TPACK) (Koehler & Mishra, 2009), which presents a useful way to situate technology and teacher knowledge. Finally, we broaden our view to examine technological contexts across a number of settings and the impact of sociocultural factors on the use of technology and the enactment of technological pedagogy. In exploring varied teaching contexts, we identify emerging characteristics that support or hinder teacher learning of technological pedagogy and implementation of high quality instruction. In particular, we examine barriers that teachers and schools are likely to confront in developing teacher technological pedagogy and practice. We consider both pre-service teacher education programs and in-service teacher professional development (PD), and their roles in promoting teacher technological pedagogy and improved classroom practice. We look at affordances in existing pre-service and in-service programs, and make recommendations for productive approaches to improve teacher technological pedagogy.
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