1,720,970 research outputs found
Conclusion Building Skills, Ethics and Human Autonomy within a Future of AI-Enhanced Learning
No full textIn developing this special collection, it has become clear that strategically integrating Generative AI into classroom practice accompanied by focused, robust professional development, is essential. These findings align with insights from The Shape of the Future report, which underscores the importance of educators becoming 'AI ready' by developing a deeper understanding of the distinctions between human intelligence and AI (Luckin, 2024). Equally important is incorporating the perspective and experiences of key stakeholders, including students and teachers, who will provide a balance in shaping and guiding these initiatives for outcomes that are both equitable and impactful. The integration of new professional development initiatives emphasise a move that upholds sound pedagogical principles and reinforces the capacity of educators as active agents of change in their choice to leverage Generative AI. This redistribution of agency is reinforced by Sharples (2023), who asserts that Generative AI should function within clear ethical boundaries, respecting human agency and the essential role of educators. Key aspects include empowering users with control over their data, ensuring transparency, and maintaining trust within educational settings. This approach promotes a balanced dynamic where educators retain autonomy in shaping AI-driven learning experiences, allowing AI to enhance rather than diminish their role
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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Metamorphic Frontiers: The Influence of Generative AI on Enhancing Student Employability
No full textThis chapter critically examines the dynamic interplay between Generative Artificial Intelligence (Gen AI) and the enhancement of student employability within the context of Higher Education Institutions (HEIs) in the United Kingdom (UK). Examining the transformative horizons introduced by Gen AI, the chapter explores its impact on the evolving landscape of skills development, career readiness, and the broader implications for students navigating the contemporary job market. It investigates the integration of Gen AI in educational frameworks, highlighting its role in fostering adaptive learning environments and preparing students for the demands of a technologically advanced workforce. Examining case studies and emerging best practices, the chapter unravels the ways in which Gen AI contributes to shaping the employability landscape in UK HEIs. Furthermore, the chapter offers valuable insights into the challenges and ethical considerations associated with the integration of Gen AI in higher education. It critically assesses the potential benefits and risks, providing a nuanced perspective on the ethical dimensions inherent in leveraging advanced technologies for educational purposes
Professional Readiness and Ethical Practices for AI Integration:Establishing a Framework for Staff Development
No full textThe focus on the use of Generative AI in educational settings has highlighted a need for new processes and policies, and a recognition that it will have a profound impact on teaching and learning. Significantly, discussions have foregrounded a necessity for staff training in order for educators to assist students in the ethical use of AI and also to help them realise the potential and limitations of the constantly changing technologies. However, whilst existing studies identify and acknowledge the importance of providing staff training opportunities, there is a lack of defined staff development. In response to the need for a structured approach to staff development, this chapter, acknowledging current literature and based on an ethically approved small-scale study conducted at a university in Northwest England, proposes the Professional Readiness and Ethical Practices for AI Integration (PREP-AI). The proposed framework offers a flexible tool for addressing AI literacy amongst educators that could be adapted for a range of educational contexts
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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How Did We Get Here?: A Brief History of Artificial Intelligence
No full textIn the last decade or so, AI has become an important mainstream technology. It has gone from the preserve of specialist research projects to being ubiquitous in consumer goods and industrial and medical applications. Generative AI is having a major impact in many fields because of its ability to produce text and images on demand. However, despite the promise of contemporary AI, there are also many concerns about its use. This chapter attempts to trace AI’s development to this point. AI has gone through several phases, from early attempts to build complex robots that attempted to replicate the intelligence and behaviours of humans, to today’s Generative AI systems, which learn behaviours from data. AI techniques have moved from hand-crafted models, informed by cognitive theories in disciplines such as psychology and linguistics, to machine learning models in which behaviour emerges from patterns seen in large data sets. To give a sense of some directions in which AI might be headed, consideration is given to how unpredictable AI systems should be managed, and the ethical issues around AI’s use of data. The chapter ends by outlining some of the benefits that AI could bring to fields such as education
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AI in Education: Balancing Innovation and Ethics
No full textTechnological advancement often outstrips institutional and regulatory processes. Novel technologies are adopted by individuals in a haphazard manner and become deeply entrenched in culture before suitable policies and guidance can be provided. As a community, educationalists must engage proactively with potentially transformational technologies, such as AI, and anticipate ethical challenges raised by their use. We must take care not to unduly stigmatise AI as a unique ethical threat. Many of the ethical issues highlighted by the current AI boom are neither new nor confined to discussions of AI; they are an inevitable consequence of the introduction of technology into social systems. Guidelines for the safe inclusion of AI in education can be derived from other areas of educational technology and from wider socio-technical domains. The chapter proposes a set of guidelines for the ethical use of AI in education that strives to balance the transformative potential of this technology with the rights of individuals and institutions. A critical element of this work is an emphasis on the necessity of involving end users in the requirements, design and deployment phases of AI
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