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This article presents a theoretical approach for studying the coordination of futures. Building off theories of temporality and action, the authors map three different modes of future making-protentions, trajectories, and temporal landscapes-that actors need to coordinate in order to make sense of action together. Using a wide range of empirical evidence, they then show that these modes of future-coordination are autonomous from each other, so that although they are connected, they can clash or move in disjointed directions in interaction. By focusing on the coordination and disjunctures of those three modes, the authors argue that sociologists can provide a methodological axis of comparison between cases; depict mechanisms through which other theoretical or empirical constructs-such as racism or late modernity-operate; and open a window into the ways in which people organize and coordinate their futures, a topic of inquiry in its own right. Adapted from the source document.

Purpose: The purpose of this paper is to challenge processes of organizational learning and innovation that are based on making use of, extrapolating, or adapting past experiences and knowledge, because such a strategy turns out to be incapable of dealing with the challenges of today's volatile, uncertain, complex and ambiguous environment. As a possible way out, a conceptual model is proposed that integrates organizational learning and innovation as a future-driven learning process and a future-making practice. Design/methodology/approach: This work is conceptual in nature, drawing on (both theoretical/philosophical and empirical) interdisciplinary concepts and evidence from a variety of fields, including organizational studies, organizational learning, innovation studies, systems theory and systems biology, as well as cognitive science. Findings: The author proposes a paradigm shift in organizational learning: from a future-oriented perspective, organizational learning can be viewed as an innovation process that is based on \"learning from the future as it emerges.\" A conceptual approach is presented that integrates future-oriented innovation and organizational learning as a future-making practice. It is based on learning from future potentials as a source for sustainable innovations. Both epistemological/ontological foundations and organizational implications are discussed. Originality/value: This paper introduces a new perspective on the role of future-oriented innovation in the context of organizational learning. It shows how organizational learning and innovation can be integrated and how shortcomings of absorptive capacity can be overcome by assuming a future-driven perspective. Furthermore, an epistemology of future knowledge/potentials and its applications for organizations is developed.

Background As the information age wanes, enabling the prevalence of the artificial intelligence age; expectations, responsibilities, and job definitions need to be redefined for those who provide services in healthcare. This study examined the perceptions of future physicians on the possible influences of artificial intelligence on medicine, and to determine the needs that might be helpful for curriculum restructuring. Methods A cross-sectional multi-centre study was conducted among medical students country-wide, where 3018 medical students participated. The instrument of the study was an online survey that was designed and distributed via a web-based service. Results Most of the medical students perceived artificial intelligence as an assistive technology that could facilitate physicians’ access to information (85.8%) and patients to healthcare (76.7%), and reduce errors (70.5%). However, half of the participants were worried about the possible reduction in the services of physicians, which could lead to unemployment (44.9%). Furthermore, it was agreed that using artificial intelligence in medicine could devalue the medical profession (58.6%), damage trust (45.5%), and negatively affect patient-physician relationships (42.7%). Moreover, nearly half of the participants affirmed that they could protect their professional confidentiality when using artificial intelligence applications (44.7%); whereas, 16.1% argued that artificial intelligence in medicine might cause violations of professional confidentiality. Of all the participants, only 6.0% stated that they were competent enough to inform patients about the features and risks of artificial intelligence. They further expressed that their educational gaps regarding their need for “knowledge and skills related to artificial intelligence applications” (96.2%), “applications for reducing medical errors” (95.8%), and “training to prevent and solve ethical problems that might arise as a result of using artificial intelligence applications” (93.8%). Conclusions The participants expressed a need for an update on the medical curriculum, according to necessities in transforming healthcare driven by artificial intelligence. The update should revolve around equipping future physicians with the knowledge and skills to effectively use artificial intelligence applications and ensure that professional values and rights are protected.

Massive pretrained language models have garnered attention and controversy due to their ability to generate humanlike responses: Attention due to their frequent indistinguishability from human-generated phraseology and narratives and controversy due to the fact that their convincingly presented arguments and facts are frequently simply false. Just how humanlike are these responses when it comes to dialogues about physics, in particular about the standard content of introductory physics courses? This case study explores that question by having ChatGPT, the preeminent language model in 2023, work through representative assessment content of an actual calculus-based physics course and grading the responses in the same way human responses would be graded. As it turns out, ChatGPT would narrowly pass this course while exhibiting many of the preconceptions and errors of a beginning learner. A discussion of possible consequences for teaching, testing, and physics education research is provided as a possible starter for more detailed studies and curricular efforts in the future.

In this paper, we investigate how highly ranked business schools construct their legitimacy claims by analysing their online organisational communication. We argue that in the case of higher education institutions in general, and business schools in particular, the discursive formation of these legitimacy claims is strongly connected to the future. Consequently, we utilise corpus-based discourse analysis of highly ranked business schools’ website communication by focusing on sentences containing the expression ‘future’. At first, we analysed the future-related language use to reveal the general future picture in the corpus. Furthermore, by combining qualitative and quantitative textual data, we identified six typical agency frames (i.e. preparing, shaping, adjusting, exploring, personal future, responsibility) about the future. By examining the co-occurrence of these frames, we were able to identify different discursive strategies. As we connected our findings to general societal phenomena we could interpret why and how business schools utilise these discursive strategies to (re)create and maintain their legitimacy.

Research on computer-supported collaborative learning (CSCL) has traditionally investigated how student-, group-, task-, and technological characteristics affect the processes and outcomes of collaboration. On the other hand, cognitive load theory has traditionally been used to study individual learning processes and to investigate instructional effects that are present during individual learning (e.g., expertise reversal effect). In this contribution we will argue that cognitive load theory can be applied to CSCL. By incorporating concepts such as collective working memory (i.e., individuals share the burden of information processing), mutual cognitive interdependence (i.e., individuals learn about each other’s expertise and become dependent on their partners’ expertise), and transaction costs (i.e., the burden placed on individuals working memory capacity when communicating and coordinating collaborative activities), collaborative cognitive load theory (CCLT) can be used to formulate testable hypotheses for pressing issues in CSCL research. The aim of this paper is to develop a research agenda to guide future CSCL research from a CCLT perspective. We highlight how variables associated with student-, group-, task-, and technological characteristics may be investigated using CCLT. We also address important steps CSCL research needs to make with respect to the measurement of variables and the methodologies used to analyze data.

In today's fast-paced, performance metrics–driven health care world, data-driven actions often squeeze out the imaginative space that visionary leadership requires. However, imagination—or what we term here dreaming—is not a luxury in leadership; it is a necessity. In a volatile, uncertain, complex, and ambiguous world, the ability to envision new possibilities can take us to new heights (Robinson).

In the twenty-first century, educators around the world are being told that they need to transform education systems to adapt young people for the challenges of a global digital knowledge economy. Too rarely, however, do we ask whether this future vision is robust, achievable or even desirable, whether alternative futures might be in development, and what other possible futures might demand of education. Drawing on ten years of research into educational innovation and socio-technical change, working with educators, researchers, digital industries, students and policy-makers, this book questions taken-for-granted assumptions about the future of education. Arguing that we have been working with too narrow a vision of the future, Keri Facer makes a case for recognizing the challenges that the next two decades may bring, including: the emergence of new relationships between humans and technology the opportunities and challenges of aging populations the development of new forms of knowledge and democracy the challenges of climate warming and environmental disruption the potential for radical economic and social inequalities. This book describes the potential for these developments to impact critical aspects of education - including adult-child relationships, social justice, curriculum design, community relationships and learning ecologies. Packed with examples from around the world and utilising vital research undertaken by the author while Research Director at the UK's Futurelab, the book helps to bring into focus the risks and opportunities for schools, students and societies over the coming two decades. It makes a powerful case for rethinking the relationship between education and social and technological change, and presents a set of key strategies for creating schools better able to meet the emerging needs of their students and communities. An important contribution to the debates surrounding edu

We are living in a time with unprecedented opportunities to communicate with others in authentic and compelling linguistically and culturally contextualized domains. In fact, language teachers today are faced with so many fascinating options for using technology to enhance language learning that it can be overwhelming. Even for those who are inclined to experiment with emerging technologies, it can be challenging to identify which resources, tools, or Web sites may best fit a particular lesson, activity, or goal. Many of the most compelling opportunities are situated within the same global social and technology trends that have become commonplace in our daily lives, including social media, artificial intelligence, big data, and augmented reality. This article addresses the extent to which technology‐mediated social interactions dominate our daily lives, how we can leverage those interactions to the benefit of our learners, and how we can engage them in learning experiences in ways that will encourage them to practice language extensively. Challenges Technology offers unprecedented opportunities to communicate with others in authentic and compelling, linguistically and culturally contextualized domains. How can we leverage learners’ technologically mediated and highly participatory culture and an array of quickly emerging technologies, including language learning media, artificial intelligence, big data, and augmented reality to enhance language teaching and learning?

There have been giant leaps in the field of education in the past 1–2 years.. Schools and colleges are transitioning online to provide more resources to their students. The COVID-19 pandemic has provided students more opportunities to learn and improve themselves at their own pace. Online proctoring services (part of assessment) are also on the rise, and AI-based proctoring systems (henceforth called as AIPS) have taken the market by storm. Online proctoring systems (henceforth called as OPS), in general, makes use of online tools to maintain the sanctity of the examination. While most of this software uses various modules, the sensitive information they collect raises concerns among the student community. There are various psychological, cultural and technological parameters need to be considered while developing AIPS. This paper systematically reviews existing AI and non-AI-based proctoring systems. Through the systematic search on Scopus, Web of Science and ERIC repositories, 43 paper were listed out from the year 2015 to 2021. We addressed 4 primary research questions which were focusing on existing architecture of AIPS, Parameters to be considered for AIPS, trends and Issues in AIPS and Future of AIPS. Our 360-degree analysis on OPS and AIPS reveals that security issues associated with AIPS are multiplying and are a cause of legitimate concern. Major issues include Security and Privacy concerns, ethical concerns, Trust in AI-based technology, lack of training among usage of technology, cost and many more. It is difficult to know whether the benefits of these Online Proctoring technologies outweigh their risks. The most reasonable conclusion we can reach in the present is that the ethical justification of these technologies and their various capabilities requires us to rigorously ensure that a balance is struck between the concerns with the possible benefits to the best of our abilities. To the best of our knowledge, there is no such analysis on AIPS and OPS. Our work further addresses the issues in AIPS in human and technological aspect. It also lists out key points and new technologies that have only recently been introduced but could significantly impact online education and OPS in the years to come.