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\"School innovation expert John B. Nash demonstrates how design thinking can be adapted successfully by busy school leaders seeking student-centered solutions to a range of challenges\"-- Provided by publisher.

A frequently cited strategy for fostering science, technology, engineering, and mathematics (STEM) instructional improvements is creating communities where faculty can share and learn evidence-based teaching practices. Despite research-documented benefits, little is known about why (and with whom) faculty engage in teaching-related conversations, including those fostered by initiative communities. We explored how STEM faculty engage in teaching-related conversations, via analysis of faculty interviews and discussion networks, to identify factors potentially influencing teaching-related conversations over the life of an initiative. Our results suggest aspects that might inhibit STEM faculty from engaging in teaching-related conversations, including: 1) faculty members’ autonomy with teaching practices; 2) faculty members’ varied interests in teaching improvements; 3) varied degrees of support to engage in teaching-related conversations; and 4) a lack of inclusive and non-judgmental spaces to talk about teaching. We suggest that those fostering STEM faculty communities consider working with others across the institution to map the instructional improvement opportunities faculty may already take part in and attend to areas lacking support. Initiative leaders and designers should also elicit and build off faculty members’ teaching-related knowledge and concerns. We further suggest making conversational spaces inclusive and safe, to help faculty honestly share teaching-related challenges and insights. We recommend creating and fostering spaces that bring faculty together across department boundaries. Our study echoes prior research by drawing attention to administrative support for instructional improvement initiatives, which can foster and sustain opportunities for faculty to talk about teaching and learn instructional improvements.

Gamification refers to using game attributes in a non-gaming context. Health professions educators increasingly turn to gamification to optimize students’ learning outcomes. However, little is known about the concept of gamification and its possible working mechanisms. This review focused on empirical evidence for the effectiveness of gamification approaches and theoretical rationales for applying the chosen game attributes. We systematically searched multiple databases, and included all empirical studies evaluating the use of game attributes in health professions education. Of 5044 articles initially identified, 44 met the inclusion criteria. Negative outcomes for using gamification were not reported. Almost all studies included assessment attributes (n = 40), mostly in combination with conflict/challenge attributes (n = 27). Eight studies revealed that this specific combination had increased the use of the learning material, sometimes leading to improved learning outcomes. A relatively small number of studies was performed to explain mechanisms underlying the use of game attributes (n = 7). Our findings suggest that it is possible to improve learning outcomes in health professions education by using gamification, especially when employing game attributes that improve learning behaviours and attitudes towards learning. However, most studies lacked well-defined control groups and did not apply and/or report theory to understand underlying processes. Future research should clarify mechanisms underlying gamified educational interventions and explore theories that could explain the effects of these interventions on learning outcomes, using well-defined control groups, in a longitudinal way. In doing so, we can build on existing theories and gain a practical and comprehensive understanding of how to select the right game elements for the right educational context and the right type of student.

Professional development programs are based on different theories of how students learn and different theories of how teachers learn. Reviewers often sort programs according to design features such as program duration, intensity, or the use of specific techniques such as coaches or online lessons, but these categories do not illuminate the programs' underlying purpose or premises about teaching and teacher learning. This review sorts programs according to their underlying theories of action, which include (a) a main idea that teachers should learn and (b) a strategy for helping teachers enact that idea within their own ongoing systems of practice. Using rigorous research design standards, the review identifies 28 studies. Because studies differ in multiple ways, the review presents program effects graphically rather than statistically. Visual patterns suggest that many popular design features are not associated with program effectiveness. Furthermore, different main ideas are not differentially effective. However, the pedagogies used to facilitate enactment differ in their effectiveness. Finally, the review addresses the question of research design for studies of professional development and suggests that some widely favored research designs might adversely affect study outcomes.

In this book, eCoaching pioneer Marcia Rock draws on best-practice research and decades of experience to offer a blueprint for professional development that maximizes teacher and student growth. The eCoaching Continuum for Educators provides teachers, administrators, and other school professionals a step-by-step guide to the four connected, coordinated components of technology-enabled professional development: (1) studying theory and practice to build knowledge of specific content and pedagogy; (2) observing theory and practice to aid in the transfer of new knowledge to classroom practice; (3) one-on-one coaching to give teachers the feedback they need to improve classroom practice; and (4) group coaching to build capacity for identifying and solving problems of professional practice. Rock offers a practical approach for putting professional development where it can do the most good—in the classroom. You'll learn * Why technology is so well suited for authentic, job-embedded professional development * How to cultivate a culture in which the eCoaching continuum can have the greatest impact * Which technologies are the most useful for carrying out eCoaching in a variety of settings * How to capture and evaluate the impact of eCoaching on teachers and students The eCoaching Continuum for Educators integrates best practice in coaching for professional development with a detailed account of how teachers and other school professionals can use today's technologies to improve their practice and ensure their students are fully engaged and learning.

One of the things that we like to tell our students is that change is the only constant in healthcare. In my personal experience, managing change is difficult when done well and nearly impossible when done poorly. Life would be so much easier if we did not have to deal with continuous change in our personal and professional lives. The reason I bring this up is that the Journal of Health Administration Education is not immune to the need to change. In addition to the periodic change in editors and editorial direction, the journal has seen some significant changes. Less than 10 years ago, the journal and leadership of AUPHA made the decision to move from print to an open access format. This was an important step forward to give more faculty and programs access to the exceptional writing of our authors as we seek to improve teaching and learning in our discipline. A small but important chage is forthcoming in the listing of the academic affiliations of all co-authors on published manuscripts.

Pratham’s “Read India” initiative is a large-scale intervention to improve basic learning and arithmetic among children in primary school. It was started almost 10 years ago and has evolved considerably over time. Currently, this initiative uses two strategies. The first strategy is to work directly with village communities and local schools to improve children’s learning. “Learning camps” are organized in the local school or community for a period of 6–10 days at a time. Local village volunteers help to teach children who are organized in groups by their level of learning. These camps—intensive bursts of focused instruction—are repeated several times during the year. This model which has been rigourously evaluated shows that children’s learning levels improve significantly. The second strategy is to work with the government. This approach is used when school systems want to partner or collaborate with Pratham for improving basic learning. The key element here too is grouping children and teaching them from their level rather than by their grade. This approach also shows promising results. Independent evaluations and randomized control trials conducted on both models have indicated significant impact. Moving between the present set of conditions in India and past lessons, this case describes a decade-long journey of efforts to change teaching and learning at the ground level as well the efforts to bring about significant shifts in priority at the system level. The “Read India” case presented here contributes knowledge on strategies under which effective pedagogy can be brought to scale. It also discusses challenges of transforming instructional change in a context of low initial capacity at the school and system levels, where attention to rapid expansion of access to school had kept aside for a long time critical questions about teaching quality and learning outcomes. A second contribution of “Read India” to current knowledge on large-scale educational change relates to the role non-government actors such as Pratham can play in bringing effective pedagogy to scale to improve student learning.

This study aims to analyze the use of virtual reality and gamification in education by examining the existing literature. In addition to virtual reality, this study focuses on gamified virtual reality learning environments which refer to virtual reality learning environments that integrate gamification elements and mechanisms. Based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a systematic literature review was carried out. No limitations were set regarding educational level, type of study, subject, and publication year. The related articles were retrieved from 5 databases (ERIC, Google Scholar, IEEE, SCOPUS, and Web of Science). A total of 112 articles were included, 16 research questions were explored, and a thematic analysis was conducted. To evaluate the quality of the articles included, the Mixed Methods Appraisal Tool (MMAT) was used. According to the findings, gamification and virtual reality support several pedagogical theories and approaches. Their adoption to and integration into education can enrich and transform traditional teaching and learning and were assessed positively by students and teachers. Gamification elements significantly affected students’ achievements. In comparison to traditional learning environments, gamified virtual reality learning environments were more motivating, engaging, and interactive and offered more opportunities for personalized and collaborative learning. Through the realistic and interactive experiences offered, students’ immersion and social presence can be enhanced, knowledge acquisition can be improved, and material comprehension can be facilitated. Positive changes in student attitude, behavior, and mentality as well as improved cognitive, physical, and social–emotional development were observed. When using learning environments that integrate both virtual reality and gamification, students’ learning outcomes, motivation, engagement, and self-efficacy were increased. Additionally, students’ academic performance, active involvement, and satisfaction were improved. Students’ curiosity, imagination, focus, and interest were enhanced and their skills and competences were developed. Finally, gamified virtual reality emerged as an effective educational tool that can improve learning at all educational levels, subjects, and contexts.

We present results from a meta-analysis of 95 experimental and quasi-experimental pre-K–12 science, technology, engineering, and mathematics (STEM) professional development and curriculum programs, seeking to understand what content, activities, and formats relate to stronger student outcomes. Across rigorously conducted studies, we found an average weighted impact estimate of +0.21 standard deviations. Programs saw stronger outcomes when they helped teachers learn to use curriculum materials; focused on improving teachers’ content knowledge, pedagogical content knowledge, and/or understanding of how students learn; incorporated summer workshops; and included teacher meetings to troubleshoot and discuss classroom implementation. We discuss implications for policy and practice.

This study aims to develop an AI education policy for higher education by examining the perceptions and implications of text generative AI technologies. Data was collected from 457 students and 180 teachers and staff across various disciplines in Hong Kong universities, using both quantitative and qualitative research methods. Based on the findings, the study proposes an AI Ecological Education Policy Framework to address the multifaceted implications of AI integration in university teaching and learning. This framework is organized into three dimensions: Pedagogical, Governance, and Operational. The Pedagogical dimension concentrates on using AI to improve teaching and learning outcomes, while the Governance dimension tackles issues related to privacy, security, and accountability. The Operational dimension addresses matters concerning infrastructure and training. The framework fosters a nuanced understanding of the implications of AI integration in academic settings, ensuring that stakeholders are aware of their responsibilities and can take appropriate actions accordingly.HighlightsProposed AI Ecological Education Policy Framework for university teaching and learning.Three dimensions: Pedagogical, Governance, and Operational AI Policy Framework.Qualitative and quantitative data collected from students, teachers, and staff.Ten key areas identified for planning an AI policy in universities.Students should play an active role in drafting and implementing the policy.