This paper provides a broad bibliometric overview of the important conceptual advances that have been published during COVID-19 within “e-learning in higher education.” E-learning as a concept has been widely used in the academic and professional communities and has been approved as an educational approach during COVID-19. This article starts with a literature review of e-learning. Diverse subjects have appeared on the topic of e-learning, which is indicative of the dynamic and multidisciplinary nature of the field. (...) These include analyses of the most influential authors, of models and networks for bibliometric analysis, and progress towards the current research within the most critical areas. A bibliometric review analyzes data of 602 studies published in the Web of Science database to fully understand this field. The data were examined using VOSviewer, CiteSpace, and KnowledgeMatrix Plus to extract networks and bibliometric indicators about keywords, authors, organizations, and countries. The study concluded with several results within higher education. Many converging words or sub-fields of e-learning in higher education included distance learning, distance learning, interactive learning, online learning, virtual learning, computer-based learning, digital learning, and blended learning. This research is mainly focused on pedagogical techniques, particularly e-learning and collaborative learning, but these are not the only trends developing in this area. The sub-fields of artificial intelligence, machine learning, and deep learning constitute new research directions for e-learning in light of COVID-19 and are suggestive of new approaches for further analysis. (shrink)

How do we find out whether someone is conscious of some information or not? A simple answer is “We just ask them”! However, things are not so simple. Here, we review recent developments in the use of subjective and objective methods in implicit learning research and discuss the highly complex methodological problems that their use raises in the domain.

This article outlines the context in which General National Vocational Qualifications (GNVQs) have been developed with particular reference to the independent learning dimension of their principles and practice. It provides an overview of the problems associated with the GNVQ approach from the literature and from a study by the authors of twelve post-16 institutions in the process of implementing Advanced GNVQ programmes. It analyses the dimensions of independent learning and argues that GNVQs provide a hybrid learner experience in (...) which autonomy in the organisation of the individual learning process is mediated by a heavily prescribed GNVQ framework. The article concludes by locating this paradox in four central dilemmas characterising post-16 curricular policy in the UK. (shrink)

I contrast the “data fitting” vs “data interpreting” approaches to data science along three dimensions: Expediency, Transparency, and Explainability. “Data fitting” is driven by the faith that the secret to rational decisions lies in the data itself. In contrast, the data-interpreting school views data, not as a sole source of knowledge but as an auxiliary means for interpreting reality, and “reality” stands for the processes that generate the data. I argue for restoring balance to data science through a task-dependent symbiosis (...) of fitting and interpreting, guided by the Logic of Causation. (shrink)

While the need to protect vulnerable research participants is universal, conceptual challenges with the notion of vulnerability may result in the under or over-protection of participants. Ethics review bodies making assumptions about who is vulnerable and in what circumstance can be viewed as paternalistic if they do not consider participant viewpoints. Our study focuses on participant vulnerability in Scholarship of Teaching and Learning (SoTL) research. We aim to illuminate students’ views on participant vulnerability to contribute to critical (...) analysis of the role and processes of ethics review. Additionally, we aim to highlight the importance of seeking the views of participant communities, especially in research environments beyond ethics review’s medical origins. Thirty-four students from a health-related faculty at a university in Aotearoa New Zealand, participated in five focus groups. Participants discussed factors affecting their potential participation in research drawing upon a series of vignettes based on examples of published SoTL projects. Themes, generated using reflexive thematic analysis, built a participant-informed picture of vulnerability. Findings indicate that students do not generally consider themselves vulnerable and instead consider participation in SoTL research through an agentic lens. Students expect that participation will be voluntary, not negatively impact their grades, and not single them out so that others could judge them. Our study also highlights the value students place on relationships with one another and teaching staff and the implications these have for SoTL research participation and future professional practice. This research challenges research ethics committees to think further about vulnerability in the context of SoTL whilst highlighting the importance of providing opportunities for research participants more broadly to explore and vocalize their views as members of participant communities. (shrink)

TLRP's generic phase is believed to have been the largest ever UK investment in educational research. This paper describes the critique from which TLRP emerged, its strategic positioning and the roles of successive directors and their teams in its development. The paper offers an early stock take of TLRP's achievements from the perspective of the last Programme Director. The efficacy of the form of the Programme, once likened to 'a glider made of jelly', is discussed.

In this article we attempt to answer the question of how the ethical and conceptual framework (ECF) for a learning health‐care system (LHS) affects some of the main controversies in research ethics by addressing five key problems of research ethics: (a) What is the difference between practice and research? (b) What is the relationship between research ethics and clinical ethics? (c) What is the ethical relevance of the principle of clinical equipoise? (d) Does participation in (...) research require a higher standard of informed consent than the practice of medicine? and (e) What ethical principle should take precedence in medicine? These questions allow us to construct two opposite idealized positions on the distinction between research and practice: the integration model and the segregation model of research and practice. We then compare the ECF for an LHS with these two idealized positions. We argue that the ECF for a LHS does not, in fact, solve these problems, but that it is a third, separate position in the relationship between research ethics and clinical ethics. Moreover, we suggest that the ECF for a LHS raises new ethical problems that require additional ethical analysis and justification. Our article contributes to the discussion on the relationship between research ethics and clinical ethics, revealing that although a learning health‐care system may significantly change the landscape of health care, some ethical dilemmas still require resolving on both theoretical and policy‐making levels. (shrink)

The purpose of this review study is to explore the existing research focusing on the impact of foreign language learning among healthy seniors on their cognitive functions from the positive psychology perspective. The methods are based on a literature review of available sources found on the research topic in two acknowledged databases: Web of Science and Scopus. The search period was not limited by any time period since there are not many studies on this topic. Altogether seven (...) original studies were detected. The findings of this review study thus reveal that foreign language learning (FLL) has a positive impact on the maintenance and/or enhancement of cognitive abilities irrespective of age. In addition, the FLL courses seem to offer new opportunities for healthy seniors in the area of socializing and integration into society, which consequently may positively affect their overall well-being. Furthermore, the research shows that it is partly through the stimulation of social well-being that the cognitive effects of FLL might be observed. Cognitive aspects of older age are to be further investigated, including the importance of learning a foreign language, as basically all research conducted proves at least some maintenance or even improvement of cognitive functions of older people when starting intensive language training. (shrink)

Industry involvement in the machine learning (ML) community seems to be increasing. However, the quantitative scale and ethical implications of this influence are rather unknown. For this purpose, we have not only carried out an informed ethical analysis of the field, but have inspected all papers of the main ML conferences NeurIPS, CVPR, and ICML of the last 5 years—almost 11,000 papers in total. Our statistical approach focuses on conflicts of interest, innovation, and gender equality. We have obtained four (...) main findings. (1) Academic–corporate collaborations are growing in numbers. At the same time, we found that conflicts of interest are rarely disclosed. (2) Industry papers amply mention terms that relate to particular trending machine learning topics earlier than academia does. (3) Industry papers are not lagging behind academic papers with regard to how often they mention keywords that are proxies for social impact considerations. (4) Finally, we demonstrate that industry papers fall short of their academic counterparts with respect to the ratio of gender diversity. We believe that this work is a starting point for an informed debate within and outside of the ML community. (shrink)

The development of computer science has raised ethical concerns regarding the potential negative impacts of machine learning tools on people and society. Some examples are pornographic deepfakes used as weapons of war against women; pattern recognition designed to uncover sexual orientation; and misuse of data and deep learning by private companies to influence democratic elections. We contend that these three examples are cases of automated evil. In this article, we defend that the concept of forbidden knowledge can help (...) to inform a coherent ethical framework in the context of machine learning research. We conclude that restricting generalised access to extensive data and limiting access to ready-to-use codes would mitigate potential harms caused by machine learning tools. In addition, the notions of intersectionality and interdisciplinarity should be systematically introduced in data and computer science research. (shrink)

Effective stress management strategies correlate with improved academic performance in college students, yet inconsistent findings in existing research warrant further investigation. This study explored the intricate interplay between stress levels, coping strategies, and academic achievement in HyFlex learningenvironments. A stratified random sample of 111 students from five specializations within the Bachelor of Secondary Education program participated. Utilizing a descriptive-correlational design, data were collected through validated self-report questionnaires and a weighted general average. Subsequent descriptive statistics and bivariate correlation analysis revealed (...) moderate stress levels among participants who preferred task-oriented coping strategies. Interestingly, a significant positive association was observed between stress levels and academic achievement and emotion-oriented coping strategies, while a negative correlation emerged between stress and task-oriented coping strategies. Avoidance-oriented coping strategies, conversely, displayed a significant negative association with academic success. These findings underscore the crucial role of educational institutions in providing robust support mechanisms for stress management and cultivating a task-focused learning environment to optimize student well-being and academic performance within the HyFlex model. (shrink)

Responsible research practices are critical to maintaining integrity in research and the provision of institutional trainings is an important means of promoting research integrity. However, studies show contrasting results on the efficacy of institutional training and that these approaches may not be fully effective in promoting research integrity among individuals and improving the overall climate in research integrity. Therefore, a more comprehensive multi-dimensional learning strategy seems to be needed. This includes continuous and tailored training (...) at different institutional levels, the incorporation of training sessions focusing on the development of the moral character of researchers, and the use of different mentoring practices. With this comprehensive approach, research institutions can foster a culture of integrity in research, improve the overall research integrity climate and promote responsible research practices by individuals. (shrink)

The term robustness is ubiquitous in modern Machine Learning (ML). However, its meaning varies depending on context and community. Researchers either focus on narrow technical definitions, such as adversarial robustness, natural distribution shifts, and performativity, or they simply leave open what exactly they mean by robustness. In this paper, we provide a conceptual analysis of the term robustness, with the aim to develop a common language, that allows us to weave together different strands of robustness research. We define (...) robustness as the relative stability of a robustness target with respect to specific interventions on a modifier. Our account captures the various sub-types of robustness that are discussed in the research literature, including robustness to distribution shifts, prediction robustness, or the robustness of algorithmic explanations. Finally, we delineate robustness from adjacent key concepts in ML, such as extrapolation, generalization, and uncertainty, and establish it as an independent epistemic concept. (shrink)

BackgroundProblem-Based Learning is an instructional method of hands-on, active learning centered on investigating and resolving messy, real-world problems. This study aims to systematically analyze the current status and hotspots of PBL research and provide insights for research in the field.MethodsProblem-based learning-related publications were retrieved from the Web of Science Core Collection using “Problem-Based Learning”. Annual publications, countries, institutions, authors, journals, references, and keywords in the field were visually analyzed using the R, VOSviewer, and Microsoft (...) Excel 2019 software.ResultsA total of 2,790 articles and reviews were analyzed, with a steady increase in publications in the field of PBL. Overall, the United States was the major contributor to the study of PBL. Van Der Vleuten CPM was the key researcher in this field. Moreover, most of the publications were published in Medical Education. Keyword analysis showed that current research hotspots focus on the extensions of PBL teaching mode, application of PBL teaching method, and reform of PBL.ConclusionResearch on PBL is flourishing. Cooperation and exchange between countries and institutions should be strengthened in the future. These findings will provide a better understanding of the state of PBL research and inform future research ideas. (shrink)

The paper adopts an inter-theoretical socio-cultural and -material perspective on the relationship between human + machine learning to propose a new way to investigate the human + machine assistive assemblages emerging in professional work (e.g. medicine, architecture, design and engineering). Its starting point is Hutchins’s (1995a) concept of ‘distributed cognition’ and his argument that his concept of ‘cultural ecosystems’ constitutes a unit of analysis to investigate collective human + machine working and learning (Hutchins, Philos Psychol 27:39–49, 2013). It (...) argues that: (i) the former offers a way to reveal the cultural constitution of and enactment of human + machine cognition and, in the process, the limitations of the computational and connectionist assumptions about learning that underpin, respectively, good old-fashioned AI and deep learning; and (2) the latter offers a way to identify, when amplified with insights from Socio-Materialism and Cultural-Historical Activity Theory, how ML is further rearranging and reorganising the distributed basis of cognition in assistive assemblages. The paper concludes by outlining a set of conjectures researchers that could use to guide their investigations into the ongoing design and deployment of HL + ML assemblages and challenges associated with the interaction between HL + ML. (shrink)

This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: What is perceptual learning?

The philosophical debate around the impact of machine learning in science is often framed in terms of a choice between AI and classical methods as mutually exclusive alternatives involving difficult epistemological trade-offs. A common worry regarding machine learning methods specifically is that they lead to opaque models that make predictions but do not lead to explanation or understanding. Focusing on the field of molecular biology, I argue that in practice machine learning is often used with explanatory aims. (...) More specifically, I argue that machine learning can be tightly integrated with other, more traditional, research methods and in a clear sense can contribute to insight into the causal processes underlying phenomena of interest to biologists. One could even say that machine learning is not the end of theory in important areas of biology, as has been argued, but rather a new beginning. I support these claims with a detailed discussion of a case study involving gene regulation by microRNAs. (shrink)

Research examining Service-Learning in Physical Education Teacher Education is ample. However, long-term investigations are still scarce and literature demands the application of this type of design to uncover the effects of SL on the long run. This study followed a longitudinal quantitative approach; thus, the participants completed the Civic Attitudes and Skills Questionnaire in three occasions. Results show that there exist significant differences between mean values of the global outcomes of the CASQ; concretely, there was an improvement in (...) the first interval followed by a decrease in the second period. Regarding the different dimensions of the CASQ, leadership skills, attitudes towards social justice and attitudes towards diversity showed significant differences too. This research leads towards better understanding of methodological strategies promoting quality education, positing SL as an adequate possibility in this respect, also in the long term. (shrink)

Phenomenology has been with us for many years, and yet grasping phenomenology remains a difficult task. Heidegger, too, experienced this difficulty and devoted much of his teaching to the challenge of working phenomenologically. This article draws on aspects of Heidegger’s commentary in progressing the teaching and learning of phenomenology, especially as this pertains to research in fields such as education. Central to this task is elucidation of what I believe to be the most important feature of phenomenology—what Heidegger (...) referred to as the ‘starting point’ of phenomenology. I have written this article in the manner of a phenomenological workshop with the intention of inviting the reader to engage experientially with this starting point. (shrink)

The COVID-19 pandemic posed many ethical and practical challenges for academic research. Some of these have been documented, particularly in relation to health research, but less attention has been paid to the dilemmas encountered by educational and social science research. Given that pandemics are predicted to be more frequent, it is vital to understand how to continue crucial research in schools and other learning communities. This article therefore focuses specifically on research ethics in educational (...) and social science during the pandemic of 2020–2022. The research involved interviews and workshops with University College London (UCL) academics, professional staff and graduate students and encompassed those involved in reviewing ethics applications, researchers dealing with ethics in projects that continued despite disruptions caused by COVID-19, and successful research projects specifically designed to study the effects of COVID-19 in various contexts. The article discusses some of the crucial knowledge and practical experiences that were accumulated. The operational and epistemological lessons learned from this particular institution may have wider relevance to research ethics processes in higher education environments where academics and students are grappling with post-COVID-19 ethical dilemmas and inform broader debates about how research institutions can build institutional knowledge to improve practices of ethics review at the times of health emergencies in future. Our evidence points to the significance of inter- and multidisciplinary, collaborative approaches that flatten institutional hierarchies and to the crucial role played by professional staff. In addition, we argue that ethics review processes must be underpinned by critical debates about wider issues of unequal power relationships between research partners, the nature of knowledge production, ownership and utilisation. To enhance equity and epistemic justice in research practices, ethics education should be an ongoing integral part of research ethics within research institutions. (shrink)

The Covid-19 pandemic has led to an unprecedented acceleration of research. Thousands of papers have been published in a very short time across a wide range of academic disciplines. This has already led to instances of research misconduct and articles have been withdrawn from prominent journals very soon after being published. It has also led to calls for the relaxation of generally accepted research ethics rules and rules concerning the protection of personal data during what is claimed (...) to be an exceptional time of crisis where research need to be speeded up and not hampered by rules more suitable to normal times. This chapter will outline some areas of research where there have been calls for the relaxation of research ethics rules, e.g. challenge studies in vaccine development, use of personal health data in epidemiology and the use of data from contact tracing apps. It will explicate and analyse the arguments presented for allowing such relaxation in exceptional times of crisis from a philosophical point of view. And it will ask to what extent the Covid-19 pandemic is an exceptional time of crisis in comparison with other important historical moments in medical research, and how the calls for exception relaxation of general rules fit with the history of research ethics and regulation. It will be argued that (1) the Covid-19 pandemic is far less exceptional than it initially appears, (2) the arguments for a relaxation of research ethics and data protection rules are less than convincing, and (3) the lesson we should really learn from Covid-19 is that adherence to a well justified set of rules can act as a protection against false exceptionalism and a counter to the temptation to bend the rules in crises. (shrink)

This article illustrates the process of applied critical realist research using a case study of political decision-making in transport. Critical realism is often used to analyse socio-political cha...

This paper provides an empirical and conceptual account on seeing machine learning models as part of a sociotechnical system to identify relevant vulnerabilities emerging in the context of use. As ML is increasingly adopted in socially sensitive and safety-critical domains, many ML applications end up not delivering on their promises, and contributing to new forms of algorithmic harm. There is still a lack of empirical insights as well as conceptual tools and frameworks to properly understand and design for the (...) impact of ML models in their sociotechnical context. In this paper, we follow a design science research approach to work towards such insights and tools. We center our study in the financial industry, where we first empirically map recently emerging MLOps practices to govern ML applications, and corroborate our insights with recent literature. We then perform an integrative literature research to identify a long list of vulnerabilities that emerge in the sociotechnical context of ML applications, and we theorize these along eight dimensions. We then perform semi-structured interviews in two real-world use cases and across a broad set of relevant actors and organizations, to validate the conceptual dimensions and identify challenges to address sociotechnical vulnerabilities in the design and governance of ML-based systems. The paper proposes a set of guidelines to proactively and integrally address both the dimensions of sociotechnical vulnerability, as well as the challenges identified in the empirical use case research, in the organization of MLOps practices. (shrink)

Recent controversies about the level of replicability of behavioral research analyzed using statistical inference have cast interest in developing more efficient techniques for analyzing the results of psychological experiments. Here we claim that complementing the analytical workflow of psychological experiments with Machine Learning-based analysis will both maximize accuracy and minimize replicability issues. As compared to statistical inference, ML analysis of experimental data is model agnostic and primarily focused on prediction rather than inference. We also highlight some potential pitfalls (...) resulting from adoption of Machine Learning based experiment analysis. If not properly used it can lead to over-optimistic accuracy estimates similarly observed using statistical inference. Remedies to such pitfalls are also presented such and building model based on cross validation and the use of ensemble models. ML models are typically regarded as black boxes and we will discuss strategies aimed at rendering more transparent the predictions. (shrink)

The general process view of learning, which guided research into learning for the first half of this century, has come under attack in recent years from several quarters. One form of criticism has come from proponents of the so-called biological boundaries approach to learning. These theorists have presented a variety of data showing that supposedly general laws of learning may in fact be limited in their applicability to different species and learning tasks, and they (...) argue that the limitations are drawn by the nature of each species' adaptation to the particular requirements of its natural environment. The biological boundaries approach has served an important critical function in the move away from general process learning theory, but it is limited in its ability to provide an alternative to the general process approach. In particular, the biological boundaries approach lacks generality, it is in some respects subservient to the general process tradition, and its ecological content is in too many cases limited toex post factoadaptive explanations of learning skills. A contrasting, ecological approach to learning, which can provide a true alternative to general process theory, is presented. The ecological approach begins by providing an ecological task description for naturally occurring instances of learning; this step answers the question:Whatdoes this animal learn to do? The next step is an analysis of the means by which learning occurs in the course of development, answering the question:Howdoes the animal learn to do this? On the basis of such analyses, local principles of adaptation are formulated to account for the learning abilities of individual species. More global principles are sought by generalization among these local principles and may form the basis for a general ecological theory of learning. (shrink)

In this paper, I examine why moral exemplars are useful and even necessary in moral education despite several critiques from researchers and educators. To support my point, I review recent AI research demonstrating that exemplar-based learning is superior to rule-based learning in model performance in training neural networks, such as large language models. I particularly focus on why education aiming at promoting the development of multifaceted moral functioning can be done effectively by using exemplars, which is similar (...) to exemplar-based learning in AI model training. Furthermore, I discuss the potential limitations and issues related to exemplar-applied moral education with findings from recent studies in AI research raising concerns about model biases and toxic outcomes. I attempt to propose ways to address the concerns regarding employing moral exemplars as well. As remedies, I suggest that autonomy-supporting deliberative and reflective learning processes should be utilized. Furthermore, based on the discussion, I examine how macroscopic socio-cultural aspects influence the effectiveness of exemplar-applied moral education. Suggestions for moral educators and future directions for research in moral education are briefly discussed. (shrink)

The application of artificial intelligence and machine learning technologies in healthcare have immense potential to improve the care of patients. While there are some emerging practices surro...

Bayesian reverse-engineering is a research strategy for developing three-level explanations of behavior and cognition. Starting from a computational-level analysis of behavior and cognition as optimal probabilistic inference, Bayesian reverse-engineers apply numerous tweaks and heuristics to formulate testable hypotheses at the algorithmic and implementational levels. In so doing, they exploit recent technological advances in Bayesian artificial intelligence, machine learning, and statistics, but also consider established principles from cognitive psychology and neuroscience. Although these tweaks and heuristics are highly pragmatic in (...) character and are often deployed unsystematically, Bayesian reverse-engineering avoids several important worries that have been raised about the explanatory credentials of Bayesian cognitive science: the worry that the lower levels of analysis are being ignored altogether; the challenge that the mathematical models being developed are unfalsifiable; and the charge that the terms ‘optimal’ and ‘rational’ have lost their customary normative force. But while Bayesian reverse-engineering is therefore a viable and productive research strategy, it is also no fool-proof recipe for explanatory success. (shrink)

Due to the variety of research ethics and integrity training formats it may be challenging to use a common instrument to monitor and evaluate the development of competencies and learning progress as well as determine the effectiveness of the training. The present study scrutinises the use of learning diaries as one possible measure to evaluate the development of ethics competencies. The aim of the study was to increase understanding about how learning diaries capture development of (...) class='Hi'>research ethics and integrity competencies of participants and explore the use of diaries as a measure of training effectiveness. In the evaluative case study, a micro-credential programme was used as the context of the study and data was analysed using deductive content analysis. As a result, we outline criteria for analysis to be used in ethics training programmes for learning diaries. Results indicated that learning diaries submitted in the forum format (compared to individual submissions) provide peer support, so learners display more content knowledge on high levels of reflection and understanding. Submitting learning diaries over a longer period and making submissions repeatedly can improve writing and reflection competencies. The quality of learning diary entries may also depend on learner characteristics, such as commitment and motivation. Keeping a learning diary can help retain obtained competencies over a longer period. The article ends with a set of recommendations for implementing learning diaries as one measure of evaluation. (shrink)

Varying conceptions of and purposes for dialogue exist. Recent dialogic theorists and advocates urge exploration of forms of dialogue for learning and applying relational responsibilities within stakeholder networks. A related phenomenon has been the recent emergence of multi-stakeholder dialogues that involve parties significantly affected by major issues or concerns, such as environmental sustainability, that have complex and wide-spread implications. The extent to which these recent multi-stakeholder dialogues assume anything resembling the relationship or caring and the learning potentials of (...) dialogic goals and processes suggested by recent advocates, however, can certainly be questioned. This article explores potential directions for research on enhanced forms of multi-stakeholder dialogues that emphasize goals of dialogic learning, relationship building, and business social responsiveness within a more reflective practice of corporate citizenship. Many issues and questions concerning appropriate antecedents, processes, and outcomes for these enhanced multi-stakeholder dialogues are raised and discussed. (shrink)

The study aimed to identify E- Learning strategies and their relation to the efficiency of research performance in foreign and Palestinian universities (University of Ottawa, Munster, Suez Canal, Al-Azhar, Islamic, Al-Aqsa). The analytical descriptive approach was used for this purpose, and relying on the questionnaire as a main tool for data collection. The study society is from the senior management, where the number of senior management in the universities in question is 206. The random stratified sample was selected (...) and (SPSS) was used for statistical data analysis. The study found a significant relationship between E- Learning strategies and the efficiency of research performance in universities. It also reached the participation of senior management in the research that develops the university performance in the Palestinian universities. The senior management indicated that they do not care to follow the policies of implementing the development of scientific research. While the senior management in foreign universities indicated that they are interested in following up the policies of implementing the development of scientific research. The study also showed that senior management in Palestinian universities does not care about providing the appropriate budget for E- Learning. The study recommended that the senior management of Palestinian universities should provide an E- Learning budget and encourage employees to continue using E- Learning strategies. The administration in the Palestinian universities should adopt and support outstanding research, and the need to encourage interest in the implementation of policies for the development of scientific research. (shrink)

This paper describes a novel perspective on the foundations of mathematics: how mathematics may be seen to be largely about “information compression via the matching and unification of patterns”. That is itself a novel approach to IC, couched in terms of nonmathematical primitives, as is necessary in any investigation of the foundations of mathematics. This new perspective on the foundations of mathematics reflects the facts that mathematics is almost exclusively the product of human brains, and has been developed, as an (...) aid to human thinking, mathematics is likely to be consonant with much evidence for the importance of IC in human learning, perception, and cognition. This perspective on the foundations of mathematics has grown out of a long-term programme of research developing the SP Theory of Intelligence and its realization in the SP Computer Model, a system in which a generalised version of ICMUP—the powerful concept of SP-multiple-alignment—plays a central role. This paper shows with an example how mathematics, without any special provision, may achieve compression of information. Then, it describes examples showing how variants of ICMUP may be seen in widely used structures and operations in mathematics. Examples are also given to show how several aspects of the mathematics-related disciplines of logic and computing may be understood as ICMUP. Also discussed is the intimate relation between IC and concepts of probability, with arguments that there are advantages in approaching AI, cognitive science, and concepts of probability via ICMUP. Also discussed is how the close relation between IC and concepts of probability relates to the established view that some parts of mathematics are intrinsically probabilistic, and how that latter view may be reconciled with the all-or-nothing, “exact,” forms of calculation or inference that are familiar in mathematics and logic. There are many potential benefits and applications of the mathematics-as-IC perspective. (shrink)

This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: Can perceptual experience be modified by reason?

The findings of this article reveal that the development of the independent learning model in the American literature curriculum positively impacts teachers’ job psychological satisfaction. This study highlights the contribution of autonomous learning mode in empowering students’ subjective status and enhancing their initiative, consequently reducing teachers’ psychological pressure and improving their overall satisfaction with their work. Contribution: The results of this study hold implications for scholars in the field, particularly those engaged in practical theology and religious educational studies.

This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: How does perceptual learning alter the contents of perception?

This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: How does perceptual learning alter perceptual phenomenology?

This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: How is perceptual learning coordinated with action?

A special report of The Hastings Center and the Association of American Medical Colleges addressed the ethical oversight of learning health systems, which seek to combine high‐quality patient care with routine data collection aimed at improving patient outcomes. The report contained two position papers, authored by a number of distinguished bioethicists, and several commentaries. The position papers urged two changes. First, they urged a rethinking of our approach to the regulation of human subjects research, so as to make (...) it easier in the future for learning health systems to function well. Second, they argued that the rethinking required dispensing with a strict distinction between research and therapy, which has been a major tenet of bioethics since the Belmont Report, which explicated basic ethical principles governing human subjects research. We fully support the objectives of the authors, and we agree that the learning health system is an important advance that serves patients well. Unnecessary regulatory burden ought not impede this progress. We disagree, however, that the best way to bring about these needed changes in the regulatory environment is to reject the basic distinction between research and treatment. Unfortunately, we find the arguments in favor of that strategy to be, in places, reminiscent of what we take to be basic conceptual errors that hampered the ethical understanding of human subjects research prior to adoption of the Belmont Report. To see why one need not reject the research‐treatment distinction in order to promote learning health systems, we first investigate in some detail the arguments offered for eliminating the distinction. We next turn to an issue not addressed by those authors, namely, the relationship between the physician or investigator and the patient or subject, to illustrate why the distinction is important and what is lost if it is jettisoned. (shrink)

Research ethics education has taken many forms since federal funding agencies issued regulatory guidance directing those supported by these agencies to complete required training. In the absence of a standard training approach among institutions such as universities, the design and content of courses, workshops, and seminars varies widely. Here we describe a southwestern United States research university program that employed six teaching strategies to assist students in deep learning of ethical principles and behavior. Our purpose was to (...) determine how these strategies impact understanding and empowerment among an interdisciplinary group of graduate students. Results suggested that deep learning design can result in learning that requires students not only to remember and understand key ethics concepts but also to analyze and apply them in a broader ethical domain. Key findings inform design and delivery of future research ethics courses for instructional designers and instructors in higher education. (shrink)