2,465 research outputs found

    Influence of Preaching’s Rhetorical Appeal on Evangelical Listeners’ Motivation

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    Preaching is a form of rhetorical narratology aimed at persuading its audience via sermons to experience a renewal of the mind and the transformation of their life. While previous research established the fact that listeners comprehend sermons through their rhetorical appeal, it has been unclear how this has motivated evangelical listeners to act. The purpose of this qualitative narrative study was to explore how the rhetorical appeal of preaching influences evangelical listeners’ motivation at evangelical churches in Savannah, Georgia. A comprehensive approach to exploring a sermon’s rhetorical appeal was utilized by focusing jointly on individual perception and social context. The Narrative Transportation Theory served as the theoretical framework, and 34 participants from six churches were interviewed to reach saturation. The findings showed that the rhetorical appeal embedded in preaching, plus its narrative essence, influences evangelical listener motivation. In addition, listeners subconsciously understand that aspects of rhetoric and narrative work together in sermons to influence their motivation. This study specifically identified three themes, seven categories, 13 conditions, and 32 codes relevant for rhetorical appeal to be effective and to help motivation occur. The three themes of Relatability, Applicability, and Engagement were aligned with Ethos, Logos, and Pathos, and then integrated with Environmental, Cognitive, and Behavioral functions, to create the Sermon Listener Motivation Triangle. This study’s corroboration of preaching’s collaborative nature between the perfectly divine and the imperfectly human is shared in hopes of helping speakers prepare scripturally authentic sermons and communicate in engaging ways that inspire change

    UMSL Bulletin 2023-2024

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    The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp

    Redefining Disproportionate Arrest Rates: An Exploratory Quasi-Experiment that Reassesses the Role of Skin Tone

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    The New York Times reported that Black Lives Matter was the third most-read subject of 2020. These articles brought to the forefront the question of disparity in arrest rates for darker-skinned people. Questioning arrest disparity is understandable because virtually everything known about disproportionate arrest rates has been a guess, and virtually all prior research on disproportionate arrest rates is questionable because of improper benchmarking (the denominator effect). Current research has highlighted the need to switch from demographic data to skin tone data and start over on disproportionate arrest rate research; therefore, this study explored the relationship between skin tone and disproportionate arrest rates. This study also sought to determine which of the three theories surrounding disproportionate arrests is most predictive of disproportionate rates. The current theories are that disproportionate arrests increase as skin tone gets darker (stereotype threat theory), disproportionate rates are different for Black and Brown people (self-categorization theory), or disproportionate rates apply equally across all darker skin colors (social dominance theory). This study used a quantitative exploratory quasi-experimental design using linear spline regression to analyze arrest rates in Alachua County, Florida, before and after the county’s mandate to reduce arrests as much as possible during the COVID-19 pandemic to protect the prison population. The study was exploratory as no previous study has used skin tone analysis to examine arrest disparity. The findings of this study redefines the understanding of the existence and nature of disparities in arrest rates and offer a solid foundation for additional studies about the relationship between disproportionate arrest rates and skin color

    Climate Change and Critical Agrarian Studies

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    Climate change is perhaps the greatest threat to humanity today and plays out as a cruel engine of myriad forms of injustice, violence and destruction. The effects of climate change from human-made emissions of greenhouse gases are devastating and accelerating; yet are uncertain and uneven both in terms of geography and socio-economic impacts. Emerging from the dynamics of capitalism since the industrial revolution — as well as industrialisation under state-led socialism — the consequences of climate change are especially profound for the countryside and its inhabitants. The book interrogates the narratives and strategies that frame climate change and examines the institutionalised responses in agrarian settings, highlighting what exclusions and inclusions result. It explores how different people — in relation to class and other co-constituted axes of social difference such as gender, race, ethnicity, age and occupation — are affected by climate change, as well as the climate adaptation and mitigation responses being implemented in rural areas. The book in turn explores how climate change – and the responses to it - affect processes of social differentiation, trajectories of accumulation and in turn agrarian politics. Finally, the book examines what strategies are required to confront climate change, and the underlying political-economic dynamics that cause it, reflecting on what this means for agrarian struggles across the world. The 26 chapters in this volume explore how the relationship between capitalism and climate change plays out in the rural world and, in particular, the way agrarian struggles connect with the huge challenge of climate change. Through a huge variety of case studies alongside more conceptual chapters, the book makes the often-missing connection between climate change and critical agrarian studies. The book argues that making the connection between climate and agrarian justice is crucial

    Developing great teachers through professional development: a comparative international case study in England, Israel, South Korea, and Turkey

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    This comparative international case study explores teacher quality, that is, how teachers, who are regarded as great, train and develop. In particular, the thesis investigates ways in which participation in professional development programmes contributes to teachers’ professional knowledge and the personal virtues involved in teaching chemistry at secondary school level in England, Israel, South Korea, and Turkey as case study nations. The study employs a comparative case study approach. Empirical data collection was preceded by a document analysis and a comprehensive literature review which revealed three themes, namely community of practice, pedagogical content knowledge, and professional beliefs and virtues as impacting teachers in becoming great teachers. These themes were explored in practice utilising qualitative data collection methods, namely semi structured interviews with science teachers (mainly chemistry) who participated in professional development programmes and through observing lessons and professional development activities of teachers teaching science to 14-18-year-olds. Data was collected in South Korea, Israel, Turkey, and the United Kingdom (England) over a 1-year period. A volunteer sample of 40 science teachers (10 teachers for each country) were interviewed. Ten professional development activities were observed. The total length of observed PD activities was 1500 minutes. Nine science teachers were observed in four countries. The total length of observed lessons was 525 minutes. Four focus group interviews with the participation of 18 teachers were conducted. Thematic analysis was used to analyse the data. The data shows that great teacher appears differently in the four nations. A great teacher is identified variously as an amalgamation of a lifelong learner (South Korea), a moral exemplar (Turkey), a reflective practitioner (England), and an educator (Israel). Great teachers as lifelong learners promote students’ practical wisdom and wise decision-making ability, skills which are required to live a good life. Moral exemplars transmit their personal moral values to their students. Reflective practitioner teachers demonstrate intellectual and performance virtues in practice. As educators, great teachers motivate their students to be good human beings. The results of the study reveal that practical wisdom is an essential lens for making teachers educationally wise people. Great teacher is perceived to empower practical wisdom, which helps teachers establish mutual understanding and let them have more space to draw ii upon intellectual, social, moral and performance virtues through collaboration, mutual engagement and sharing in community of practice. The teachers in the study who participated in community-based professional development programmes enhanced the intellectual, moral, performance, and social virtues, pedagogical content knowledge associated with being a great teacher. The study finds that nations whose educational systems build strong connections between teachers through development and application of learning communities tend to generate a higher proportion of great teachers and that those teachers have positive and extensive influences on each other’s intellectual and personal development. This research also found that one of the most important dispositions that enable teachers to become responsible for students' learning is passion in science teaching. The teachers' passion, motivation, and love for teaching helped them to expand their professional knowledge and techniques of instruction in distinctive manners. The character traits that a great teacher must possess should receive a lot of consideration. Emphasise also should be on developing character strengths in the professional development. Community of practice has potential to achieve this through mutual engagement, shared repertoire and joint enterprise. The research emphasizes the vital role of teachers' passion for science teaching in enabling them to take responsibility for their students' learning. It advocates for the development of character strengths in teacher professional development, particularly through the cultivation of community of practice, characterized by mutual engagement, shared repertoire, and joint enterprise. This comparative study offers valuable insights into the dynamic interplay of teacher development, enhancing the quality of education across diverse contexts

    Patterns and Variation in English Language Discourse

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    The publication is reviewed post-conference proceedings from the international 9th Brno Conference on Linguistics Studies in English, held on 16–17 September 2021 and organised by the Faculty of Education, Masaryk University in Brno. The papers revolve around the themes of patterns and variation in specialised discourses (namely the media, academic, business, tourism, educational and learner discourses), effective interaction between the addressor and addressees and the current trends and development in specialised discourses. The principal methodological perspectives are the comparative approach involving discourses in English and another language, critical and corpus analysis, as well as identification of pragmatic strategies and appropriate rhetorical means. The authors of papers are researchers from the Czech Republic, Italy, Luxembourg, Serbia and Georgia

    UMSL Bulletin 2022-2023

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    The 2022-2023 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1087/thumbnail.jp

    Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation

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    Trustworthy Artificial Intelligence (AI) is based on seven technical requirements sustained over three main pillars that should be met throughout the system's entire life cycle: it should be (1) lawful, (2) ethical, and (3) robust, both from a technical and a social perspective. However, attaining truly trustworthy AI concerns a wider vision that comprises the trustworthiness of all processes and actors that are part of the system's life cycle, and considers previous aspects from different lenses. A more holistic vision contemplates four essential axes: the global principles for ethical use and development of AI-based systems, a philosophical take on AI ethics, a risk-based approach to AI regulation, and the mentioned pillars and requirements. The seven requirements (human agency and oversight; robustness and safety; privacy and data governance; transparency; diversity, non-discrimination and fairness; societal and environmental wellbeing; and accountability) are analyzed from a triple perspective: What each requirement for trustworthy AI is, Why it is needed, and How each requirement can be implemented in practice. On the other hand, a practical approach to implement trustworthy AI systems allows defining the concept of responsibility of AI-based systems facing the law, through a given auditing process. Therefore, a responsible AI system is the resulting notion we introduce in this work, and a concept of utmost necessity that can be realized through auditing processes, subject to the challenges posed by the use of regulatory sandboxes. Our multidisciplinary vision of trustworthy AI culminates in a debate on the diverging views published lately about the future of AI. Our reflections in this matter conclude that regulation is a key for reaching a consensus among these views, and that trustworthy and responsible AI systems will be crucial for the present and future of our society.Comment: 30 pages, 5 figures, under second revie

    Current and Future Challenges in Knowledge Representation and Reasoning

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    Knowledge Representation and Reasoning is a central, longstanding, and active area of Artificial Intelligence. Over the years it has evolved significantly; more recently it has been challenged and complemented by research in areas such as machine learning and reasoning under uncertainty. In July 2022 a Dagstuhl Perspectives workshop was held on Knowledge Representation and Reasoning. The goal of the workshop was to describe the state of the art in the field, including its relation with other areas, its shortcomings and strengths, together with recommendations for future progress. We developed this manifesto based on the presentations, panels, working groups, and discussions that took place at the Dagstuhl Workshop. It is a declaration of our views on Knowledge Representation: its origins, goals, milestones, and current foci; its relation to other disciplines, especially to Artificial Intelligence; and on its challenges, along with key priorities for the next decade

    “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

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    Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts
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