There are (at least) three approaches to quantifying information. The first, algorithmic information or Kolmogorov complexity, takes events as strings and, given a universal Turing machine, quantifies the information content of a string as the length of the shortest program producing it [1]. The second, Shannon information, takes events as belonging to ensembles and quantifies the information resulting from observing the given event in terms of the number of alternate events that have been ruled out [2]. The third, statistical (...) class='Hi'>learning theory, has introduced measures of capacity that control (in part) the expected risk of classifiers [3]. These capacities quantify the expectations regarding future data that learning algorithms embed into classifiers. Solomonoff and Hutter have applied algorithmic information to prove remarkable results on universal induction. Shannon information provides the mathematical foundation for communication and coding theory. However, both approaches have shortcomings. Algorithmic information is not computable, severely limiting its practical usefulness. Shannon information refers to ensembles rather than actual events: it makes no sense to compute the Shannon information of a single string – or rather, there are many answers to this question depending on how a related ensemble is constructed. Although there are asymptotic results linking algorithmic and Shannon information, it is unsatisfying that there is such a large gap – a difference in kind – between the two measures. This note describes a new method of quantifying information, effective information, that links algorithmic information to Shannon information, and also links both to capacities arising in statistical learning theory [4, 5]. After introducing the measure, we show that it provides a non-universal analog of Kolmogorov complexity. We then apply it to derive basic capacities in statistical learning theory: empirical VC-entropy and empirical Rademacher complexity. A nice byproduct of our approach is an interpretation of the explanatory power of a learning algorithm in terms of the number of hypotheses it falsifies [6], counted in two different ways for the two capacities. We also discuss how effective information relates to information gain, Shannon and mutual information. (shrink)

An important problem with machine learning is that when label number n>2, it is very difficult to construct and optimize a group of learning functions, and we wish that optimized learning functions are still useful when prior distribution P(x) (where x is an instance) is changed. To resolve this problem, the semantic information G theory, Logical Bayesian Inference (LBI), and a group of Channel Matching (CM) algorithms together form a systematic solution. MultilabelMultilabel A semantic channel in the (...) G theory consists of a group of truth functions or membership functions. In comparison with likelihood functions, Bayesian posteriors, and Logistic functions used by popular methods, membership functions can be more conveniently used as learning functions without the above problem. In Logical Bayesian Inference (LBI), every label’s learning is independent. For Multilabel learning, we can directly obtain a group of optimized membership functions from a big enough sample with labels, without preparing different samples for different labels. A group of Channel Matching (CM) algorithms are developed for machine learning. For the Maximum Mutual Information (MMI) classification of three classes with Gaussian distributions on a two-dimensional feature space, 2-3 iterations can make mutual information between three classes and three labels surpass 99% of the MMI for most initial partitions. For mixture models, the Expectation-Maxmization (EM) algorithm is improved and becomes the CM-EM algorithm, which can outperform the EM algorithm when mixture ratios are imbalanced, or local convergence exists. The CM iteration algorithm needs to combine neural networks for MMI classifications on high-dimensional feature spaces. LBI needs further studies for the unification of statistics and logic. (shrink)

At the beginning of 2020, the world was experiencing the Covid-19 pandemic, and Indonesia was no exception. The occurrence of this affects the learning system in Indonesia, the learning system that was originally face-to-face was forced to online form, in this case the teachers are required to provide a creative, efficient and optimal learning system for students. So the purpose of this study is to find out the difference in the average learning result of elementary school (...) students during the pandemic. The method used in this study is quantitative with a posttest-only control group design. The population in this study were grade 4 elementary school students in Majalengka district, Indonesia. There were 64 samples and was taken by purposive sampling. The results of this study are that there are differences in the average student learning results where students who study with the hybrid learning system are higher than the face-to-face learning system. The hybrid learning system is very reliable in the 4.0 era as well as learning during the Covid-19 pandemic. However, for the record, it is necessary to look at the facilities and infrastructure considering that this system relies on technology, it is necessary to understand and be able to control the learning media for both teachers and students so that learning outcomes can be optimal and minimize the occurrence of obstacles. The present study revealed the implementation of 21st century learning. (shrink)

Complex constraints like conditionals ('If A, then B') and probabilistic constraints ('The probability that A is p') pose problems for Bayesian theories of learning. Since these propositions do not express constraints on outcomes, agents cannot simply conditionalize on the new information. Furthermore, a natural extension of conditionalization, relative information minimization, leads to many counterintuitive predictions, evidenced by the sundowners problem and the Judy Benjamin problem. Building on the notion of a `paradigm shift' and empirical research in psychology and economics, (...) I argue that the model of hypothesis testing can explain how people learn complex, theory-laden propositions like conditionals and probability constraints. Theories are formalized as probability distributions over a set of possible outcomes and theory change is triggered by a constraint which is incompatible with the initial theory. This leads agents to consult a higher order probability function, or a 'prior over priors,' to choose the most likely alternative theory which satisfies the constraint. The hypothesis testing model is applied to three examples: learning a simple probabilistic constraint involving coin bias, the sundowners problem for conditional learning, and the Judy Benjamin problem for learning conditional probability constraints. (shrink)

Alternative Learning System (ALS) has been adopted in Philippine basic education, yet there is no academic institution in the region prepares ALS teachers in teaching life skills. ALS teachers graduated from different programs of teacher education for formal education. In response, an extension project was conceptualized and implemented to enhance the teaching capacity and effectiveness of ALS teachers. Case study was conducted to evaluate the effectiveness of the project. It explored the transfer of life skills among ALS teachers. Data (...) were collected from multiple sources. Interview and written responses, and feedbacks were analyzed using thematic narrative analysis. Other data were analyzed using document and descriptive analyses. The project had achieved its objectives and rated best by participants. These indicate that the project was implemented effectively and successfully. ALS teachers have acquired life skills and transferred them to others. Thus, the project has made a difference in the lives of these teachers. (shrink)

In recent years, educational institutions have started using the tools of commercial data analytics in higher education. By gathering information about students as they navigate campus information systems, learning analytics “uses analytic techniques to help target instructional, curricular, and support resources” to examine student learning behaviors and change students’ learning environments. As a result, the information educators and educational institutions have at their disposal is no longer demarcated by course content and assessments, and old boundaries between information (...) used for assessment and information about how students live and work are blurring. Our goal in this paper is to provide a systematic discussion of the ways in which privacy and learning analytics conflict and to provide a framework for understanding those conflicts. -/- We argue that there are five crucial issues about student privacy that we must address in order to ensure that whatever the laudable goals and gains of learning analytics, they are commensurate with respecting students’ privacy and associated rights, including (but not limited to) autonomy interests. First, we argue that we must distinguish among different entities with respect to whom students have, or lack, privacy. Second, we argue that we need clear criteria for what information may justifiably be collected in the name of learning analytics. Third, we need to address whether purported consequences of learning analytics (e.g., better learning outcomes) are justified and what the distributions of those consequences are. Fourth, we argue that regardless of how robust the benefits of learning analytics turn out to be, students have important autonomy interests in how information about them is collected. Finally, we argue that it is an open question whether the goods that justify higher education are advanced by learning analytics, or whether collection of information actually runs counter to those goods. (shrink)

A nation’s economy runs on the knowledge and skills of its people.Quality assurance mechanisms for higher education institutions must take cognizance of the graduates' acquisition of skills to become productive and contributory for societal development. The study is a quantitative survey assessing the attainment of the immediate program learning outcomes of the graduating Bachelor of Science in Information Technology of one campus of a public higher education institution in the Philippines. It also assessed the introspection and level of satisfaction (...) of the graduates in their studies. Findings disclosed that the graduates have a high level of attainment of the program's learning outcomes and a high level of satisfaction. The high school where the respondents graduated is the single variable that defined the difference in attainment of program intended learning outcomes. As to the graduates' introspections, themost significant percentage of them learned the program from family, relatives, and friends. Reasons for pursuing the degree program are because of parents’ influence, prestige of IT profession. Meanwhile, the university's reputation, affordable tuition fees, and proximity to home were the factors affecting the enrolment in the BSIT program. The findings will be the basis for strategic program interventions of the program. (shrink)

The key assumption behind evolutionary epistemology is that animals are active learners or ‘knowers’. In the present study, I updated the concept of natural learning, developed by Henry Plotkin and John Odling-Smee, by expanding it from the animal-only territory to the biosphere-as-a-whole territory. In the new interpretation of natural learning the concept of biological information, guided by Peter Corning’s concept of “control information”, becomes the ‘glue’ holding the organism–environment interactions together. The control information guides biological systems, from bacteria (...) to ecosystems, in the process of natural learning executed by the universal algorithm. This algorithm, summarized by the acronym IGPT (information-gain-process-translate) incorporates natural cognitive methods including sensing/perception, memory, communication, and decision-making. Finally, the biosphere becomes the distributed network of communicative interactions between biological systems termed the interactome. The concept of interactome is based on Gregory Bateson’s natural epistemology known as the “ecology of mind”. Mimicking Bateson’s approach, the interactome may also be designated “physiology of mind”—the principle behind regulating the biosphere homeostasis. (shrink)

Higher education institutions are mining and analyzing student data to effect educational, political, and managerial outcomes. Done under the banner of “learning analytics,” this work can—and often does—surface sensitive data and information about, inter alia, a student’s demographics, academic performance, offline and online movements, physical fitness, mental wellbeing, and social network. With these data, institutions and third parties are able to describe student life, predict future behaviors, and intervene to address academic or other barriers to student success (however defined). (...) Learning analytics, consequently, raise serious issues concerning student privacy, autonomy, and the appropriate flow of student data. We argue that issues around privacy lead to valid questions about the degree to which students should trust their institution to use learning analytics data and other artifacts (algorithms, predictive scores) with their interests in mind. We argue that higher education institutions are paradigms of information fiduciaries. As such, colleges and universities have a special responsibility to their students. In this article, we use the information fiduciary concept to analyze cases when learning analytics violate an institution’s responsibility to its students. (shrink)

Purpose:The research aims to see the effect of using digital books based on the RANDAI learning model on students' problem-solving skills and information literacy in biology learning. -/- Theoritical Framework: The integration of local wisdom will make the material more contextual so that learning becomes more meaningful. Digital books that are integrated with local wisdom can be concretized through digital books based on the RANDAI learning model. -/- Methodology:The study was conducted at a secondary school in (...) the province of West Sumatra, Indonesia. The learning applied in this study uses the theoretical framework of the RANDAI model (Reciting, Analyzing the problem, Narrating the solution, Doing the solution, Assessing the solution, and Implementing the solution) which is problem-based learning integrated with local wisdom. Data collection was carried out through a test referring to Polya's problem-solving skills while for information literacy using a questionnaire referring to the Association of College and Research Library indicators. Data were analyzed using a parametric t-test and n-gain analysis. -/- Result and discussion: This study found that problem-solving skills and information literacy through learning with the RANDAI learning model assisted by digital books can promote students' problem-solving skills in science learning. -/- Conclusion: the RANDAI learning model with the help of digital books has an effect on the problem-solving abilities and information literacy of high school students. (shrink)

A new trend in deep learning, represented by Mutual Information Neural Estimation (MINE) and Information Noise Contrast Estimation (InfoNCE), is emerging. In this trend, similarity functions and Estimated Mutual Information (EMI) are used as learning and objective functions. Coincidentally, EMI is essentially the same as Semantic Mutual Information (SeMI) proposed by the author 30 years ago. This paper first reviews the evolutionary histories of semantic information measures and learning functions. Then, it briefly introduces the author’s semantic information (...) G theory with the rate-fidelity function R(G) (G denotes SeMI, and R(G) extends R(D)) and its applications to multi-label learning, the maximum Mutual Information (MI) classification, and mixture models. Then it discusses how we should understand the relationship between SeMI and Shannon’s MI, two generalized entropies (fuzzy entropy and coverage entropy), Autoencoders, Gibbs distributions, and partition functions from the perspective of the R(G) function or the G theory. An important conclusion is that mixture models and Restricted Boltzmann Machines converge because SeMI is maximized, and Shannon’s MI is minimized, making information efficiency G/R close to 1. A potential opportunity is to simplify deep learning by using Gaussian channel mixture models for pre-training deep neural networks’ latent layers without considering gradients. It also discusses how the SeMI measure is used as the reward function (reflecting purposiveness) for reinforcement learning. The G theory helps interpret deep learning but is far from enough. Combining semantic information theory and deep learning will accelerate their development. (shrink)

Abstract: This paper examined the use of educational management information system in distance learning education University of Lagos. Descriptive Survey research method was adopted for the purpose of this study. A total of one hundred and twenty students participated and returned questionnaire were found useful for analysis. The test of hypothesis was done using simple percentage. This article revealed that EMIS will help to properly measure and evaluate the performance of distance learning education University of Lagos, that EMIS (...) is useful for effective planning of distance learning education University of Lagos and that there is a significant relationship between EMIS and quality Distance education delivery in University of Lagos. There is need for reengineering and integration of Education management information system with learning management system software in University of Lagos. (shrink)

We argue that the core social being system is unlike other core systems in that it participates in frequent, widespread learning. As a result, the social being system is less constant throughout the lifespan and less informationally encapsulated than other core systems. This learning supports the development of the precursors of bias, but also provides avenues for preempting it.

The research aims to identify the learning organizations and their role in achieving organizational excellence in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) workers from the Palestinian universities was selected and the recovery (...) rate was (69.2%). Statistical analysis (SPSS) program was used for analysis and processing the data. The research found the following results: there is a fair degree of approval on "cognitive dimension", there is a high approval about the importance of "organizational dimension", there is moderately consent of the importance of "Community dimension", there is a large degree of consent about the importance of axis of the "leadership excellence", there is a large degree of consent about the importance of axis of the "service-excellence", there is a fair degree approval about the importance of the axis of "cognitive excellence", and there is a moderately consent of the importance of "Organizational Excellence". The research found a group of recommendations including: the need to develop appropriate strategies for the University, employ modern technology in information systems, in addition to provide appropriate environment that achieve learning organizations, develop technological infrastructure, adopt universities for knowledge management in the academic and administrative departments because knowledge is the core of the work of these departments, create technological incubators in universities to adopt excellence academic research projects, and protected them, support them, and market them. Establishing of centers of excellence for scientific research in the university.The need for cooperation and coordination between local, Arab and international universities for the exchange of knowledge, information, and participation programs and training courses, as it provides an opportunity to develop the capabilities and skills of personnel and expertise. (shrink)

Extended and distributed cognition theories argue that human cognitive systems sometimes include non-biological objects. On these views, the physical supervenience base of cognitive systems is thus not the biological brain or even the embodied organism, but an organism-plus-artifacts. In this paper, we provide a novel account of the implications of these views for learning, education, and assessment. We start by conceptualising how we learn to assemble extended cognitive systems by internalising cultural norms and practices. Having a better grip on (...) how extended cognitive systems are assembled, we focus on the question: If our cognition extends, how should we educate and assess such extended cognitive systems? We suggest various ways to minimize possible negative effects of extending one’s cognition and to efficiently find and organise (online) information by adopting a virtue epistemology approach. Educational and assessment implications are foregrounded, particularly in the case of Danish students’ use of the Internet during exams. (shrink)

It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring that (...) the resulting predictive model does not use race as an explicit predictor. However, if race is correlated with measured recidivism in the training data, the ML tool may ‘learn’ a perfect proxy for race. If such a proxy is found, the exclusion of race would do nothing to weaken the correlation between risk (mis)classifications and race. Is this a problem? We argue that, on some explanations of the wrongness of discrimination, it is. On these explanations, the use of an ML tool that perfectly proxies race would (likely) be more wrong than the use of a traditional tool that imperfectly proxies race. Indeed, on some views, use of a perfect proxy for race is plausibly as wrong as explicit racial profiling. We end by drawing out four implications of our arguments. (shrink)

Starting from a philosophical perspective, which states that the living structures are actually a combination between matter and information, this article presents the results on an analysis of the bipolar information-matter structure of the human organism, distinguishing three fundamental circuits for its survival, which demonstrates and supports this statement, as a base for further development of the informational model of consciousness to a general informational model of the human organism. For this, it was examined the Informational System of the Human (...) Body and its components from the perspective of the physics/information/neurosciences concepts, showing specific functions of each of them, highlighting the correspondence of these centers with brain support areas and with their projections in consciousness, which are: Center of Acquisition and Storing of Information (CASI) reflected in consciousness as memory, Center of Decision and Command (CDC) (decision), Info-Emotional Center (IES) (emotions), Maintenance Informational System (MIS) (personal status), Genetic Transmission System (GTS) (associativity/genetic transmission) and Info Genetic Generator (IGG) related by the body development and inherited behaviors. The Info Connection (IC), detected in consciousness as trust and confidence can explain the Near-Death Experiences (NDEs) and associated phenomena. This connection is antientropic and informational, because from the multitude of uncertain possibilities is selected a certain one, helping/supporting the survival and life. The human body appears therefore as a bipolar structure, connected to two poles: information and matter. It is argued that the survival, which is the main objective of the organism, is complied in three main ways, by means of: (i) the reactive operation for adaptation by attitude; (ii) the info-genetic integration of information by epigenetic processes and genetic transmission of information for species survival, both circuits (i) and (ii) being associated to the information pole; (iii) maintenance of the material body (defined as informed matter) and its functions, associated to the matter pole of the organism. It results therefore that the informational system of the human body is supported by seven informational circuits formed by the neuro-connections between the specific zones of the brain corresponding to the informational subsystems, the cognitive centers, the sensors, transducers and execution (motor/mobile) elements. The fundamental informational circuits assuring the survival are the reactive circuit, expressible by attitude, the epigenetic/genetic circuit, absorbing and codifying information to be transmitted to the next generations, and the metabolic circuit, connected to matter (matter pole). The presented analysis allows to extend the informational modeling of consciousness to an Informational Model of Consciousness and Organism, fully describing the composition/functions of the organism in terms of information/matter and neurosciences concept. (shrink)

In this chapter, I consider three ‘promises’ of bringing phenomenology into dialogue with networked learning. First, a ‘conceptual promise’, which draws attention to conceptual resources in phenomenology that can inspire and inform how we understand, conceive of, and uncover experiences of participants in networked learning activities and environments. Second, a ‘methodological promise’, which outlines a variety of ways that phenomenological methodologies and concepts can be put to use in empirical research in networked learning. And third, a ‘critical (...) promise’, which suggests how work done in the realm of critical phenomenology is complementary to and useful for exploring the social justice and emancipatory aims of networked learning researchers. Through this framework, I reflect upon multiple ways in which phenomenology has and might continue to fruitfully inform and shape networked learning research. In doing so, I emphasise that deploying phenomenology in the context of networked learning not only enriches our understanding of networked learning but that phenomenology itself is enriched through testing, finetuning, and expanding its methods, concepts, and understanding, as well as unveiling its own limitations and constraints. (shrink)

Purpose. The purpose of this study is to investigate how professionals learn from varying experiences with errors in health-care digitalization and develop and use negative knowledge and digital ignorance in efforts to improve digitalized health care. Design/methodology/approach. A two-year qualitative field study was conducted in the context of a public health-care organization working with digital patient communication. The data consisted of participant observation, semistructured interviews and document data. Inductive coding and a theoretically informed generation of themes were applied. Findings. The (...) findings show that both health-care and digital communication professionals learn through experiences with digital “rule-” and “knowledge-based” errors in patient communication and develop negative knowledge and awareness of digital ignorance. In their joint efforts, they use negative knowledge to “bend the rules” and to explore digital ignorance in efforts to improve patient communication. Originality/value. This study provides insight into the importance of collaboration between professionals with varying experience of errors in digitalizing patient communication. Such collaboration is required to acknowledge own shortcomings and create complementary negative knowledge to improve digital patient communication. This is particularly important when working with innovative digitalization in health care. (shrink)

The author has extensive law enforcement experience and the paper is intended to provoke thought on the use of technology as it pertains to information sharing between the police and the private sector. -/- As the world edges closer and closer to the convergence of man and machine, the human capacity to retrieve information is increasing by leaps and bounds. We are on the verge of knowing everything and anything there is to know, and literally in the blink of an (...) eye! -/- This means that police will have the capacity to learn everything about everyone with the only restriction being privacy legislation. But it also means that those involved in immoral, unlawful or illegal activity will have that same capacity and with no such restriction. ‘Bad Brother’ may be far more dangerous than ‘Big Brother!' -/- The global community requires a secure and credible system to retrieve and assess all of the information ‘generally available to the public.' A system that will strive to keep ‘Big Brother’ in check and ‘Bad Brother’ out, all the while providing a means of alerting citizens to genuine risks or to dangerous people. Such as system would help diffuse the systemic inaccurate and harmful profiling that is often based on rumours and innuendo. -/- There is an identified public-private partnership opportunity. A chance to work with privacy advocate groups and background checking private companies to define, design and deliver on something that will be of immense benefit to citizens around the globe. -/- We have an opportunity to create something that will work to ensure that only the best information gets used and in a moralistic, lawful and legal way! Technology continues to move forward at incomprehensible speeds – failure to act could have serious consequences. (shrink)

The idea that fictions may educate us is an old one, as is the view that they distort the truth and mislead us. While there is a long tradition of passionate assertion in this debate, systematic arguments are a recent development, and the idea of empirically testing is particularly novel. Our aim in this chapter is to provide clarity about what is at stake in this debate, what the options are, and how empirical work does or might bear on its (...) resolution. We distinguish between merely influencing people’s opinions and providing genuine learning, where the latter requires that the source of the change in opinion should be reliable. Other important ideas here are the extent to which authors of fiction may be considered to provide testimony, or something like it, and the possibility of recognizing an unstated purpose in the project of the fictional work. We ask whether fictions can furnish us not merely with ideas but with reasons for believing them, perhaps by constituting thought experiments. We consider whether the focus should be on understanding rather than on knowledge, and whether fictions can inform us about the qualities of another’s experiences. We briefly describe some experimental work of recent decades and suggest that the evidence for learning from fiction is currently meagre. (shrink)

There remains no consensus among social scientists as to how to measure and understand forms of information deprivation such as misinformation. Machine learning and statistical analyses of information deprivation typically contain problematic operationalizations which are too often biased towards epistemic elites' conceptions that can undermine their empirical adequacy. A mature science of information deprivation should include considerable citizen involvement that is sensitive to the value-ladenness of information quality and that doing so may improve the predictive and explanatory power of (...) extant models. (shrink)

According to standard rational choice theory, as commonly used in political science and economics, an agent's fundamental preferences are exogenously fixed, and any preference change over decision options is due to Bayesian information learning. Although elegant and parsimonious, such a model fails to account for preference change driven by experiences or psychological changes distinct from information learning. We develop a model of non-informational preference change. Alternatives are modelled as points in some multidimensional space, only some of whose dimensions (...) play a role in shaping the agentís preferences. Any change in these "motivationally salient" dimensions can change the agent's preferences. How it does so is described by a new representation theorem. Our model not only captures a wide range of frequently observed phenomena, but also generalizes some standard representations of preferences in political science and economics. (shrink)

There has recently been an explosion of formal models of signalling, which have been developed to learn about different aspects of meaning. This paper discusses whether that success can also be used to provide an original naturalistic theory of meaning in terms of information or some related notion. In particular, it argues that, although these models can teach us a lot about different aspects of content, at the moment they fail to support the idea that meaning just is some kind (...) of information. As an alternative, I suggest a more modest approach to the relationship between informational notions used in models and semantic properties in the natural world. (shrink)

This article assesses how autonomy and machine learning impact the existential risk of nuclear war. It situates the problem of cyber security, which proceeds by stealth, within the larger context of nuclear deterrence, which is effective when it functions with transparency and credibility. Cyber vulnerabilities poses new weaknesses to the strategic stability provided by nuclear deterrence. This article offers best practices for the use of computer and information technologies integrated into nuclear weapons systems. Focusing on nuclear command and control, (...) avoiding autonomy and machine learning is recommended as one means to reduce the existential risk of unintended nuclear conflict. (shrink)

Objectives: Machine learning (ML) has the potential to facilitate “continual learning” in medicine, in which an ML system continues to evolve in response to exposure to new data over time, even after being deployed in a clinical setting. In this article, we provide a tutorial on the range of ethical issues raised by the use of such “adaptive” ML systems in medicine that have, thus far, been neglected in the literature. -/- Target audience: The target audiences for this (...) tutorial are the developers of ML AI systems, healthcare regulators, the broader medical informatics community, and practicing clinicians. -/- Scope: Discussions of adaptive ML systems to date have overlooked the distinction between 2 sorts of variance that such systems may exhibit—diachronic evolution (change over time) and synchronic variation (difference between cotemporaneous instantiations of the algorithm at different sites)—and underestimated the significance of the latter. We highlight the challenges that diachronic evolution and synchronic variation present for the quality of patient care, informed consent, and equity, and discuss the complex ethical trade-offs involved in the design of such systems. (shrink)

Learning from contemporary natural, formal, and social sciences, especially from current biology, as well as from humanities, particularly contemporary philosophy of nature, requires updates of our old definitions of cognition and intelligence. The result of current insights into basal cognition of single cells and evolution of multicellular cognitive systems within the framework of extended evolutionary synthesis (EES) helps us better to understand mechanisms of cognition and intelligence as they appear in nature. New understanding of information and processes of physical (...) (morphological) computation contribute to novel possibilities that can be used to inspire the development of abiotic cognitive systems (cognitive robotics), cognitive computing and artificial intelligence. (shrink)

This work investigates one of the most widespread yet elusive ideas about our experience of art: the idea that there is something cognitively valuable in engaging with great artworks, or, in other words, that we learn from them. This claim and the age-old controversy that surrounds it are reconsidered in light of the psychological and neuroscientific literature on learning, in one of the first systematic efforts to bridge the gap between philosophical and scientific inquiries on the topic. The work (...) has five chapters. Chapter 1 lays down its conceptual bases: it explains what learning is taken to be in the current philosophical debate and it points out how Bayesian cognitive science (particularly in its predictive processing formulations) might be well-suited to capture the kind of learning involved in our engagement with the arts. The following chapters test this latter hypothesis with respect to particular art forms, namely literature and literary language (Chapter 2), narrative (Chapter 3), and visual art, music and motor activities (Chapter 4). The fine-grained discussions conducted in each of these areas will enable us to see that the relationship between art and learning is indeed fundamental and pervasive. The final chapter (Chapter 5) examines the consequences of this fact for our understanding of the role of art in our epistemic practices, its ultimate usefulness and value, and its place in the interdisciplinary study of the human mind. The upshot is a novel and wide-ranging picture, both philosophically informed and empirically sound, that bypasses many of the problems and dead ends of the current philosophical debate on the topic and captures the deep sense in which art and learning are interrelated. (shrink)

Reading have always been a very important activity, which further paves the way for excellence in life both academically and non-academically. It is a fundamental skill that unlocks learning and provides individual’s benefits. Reading habit and attitude become an interest topic to discuss because it can be the key success in learning. This study aimed to examine the reading habits and attitudes of big city residents in Pakistan towards books with Chinese themes, available in Chinese, English, or Urdu (...) language. Using a survey design and simple random sampling, data was collected from 300 respondents through a pre-tested questionnaire based on Smith's (1991) Adult Survey of Reading Attitude. The study analyzed data from 11 online bookstores and publishers in Pakistan used to provide recent insights. We used two keywords (China, Chinese: چائ نا , چائ ن یز ) to collect data from online bookstores. The results of the study, with a reliability test score of 0.79, showed that the participants had a positive attitude towards reading Chinese themed books. The findings of this study can inform the development of educational programs to enhance reading skills and cultural understanding for users of Chinese-themed books in Pakistan. (shrink)

According to certain normative theories in epistemology, rationality requires us to be logically omniscient. Yet this prescription clashes with our ordinary judgments of rationality. How should we resolve this tension? In this paper, I focus particularly on the logical omniscience requirement in Bayesian epistemology. Building on a key insight by Hacking :311–325, 1967), I develop a version of Bayesianism that permits logical ignorance. This includes: an account of the synchronic norms that govern a logically ignorant individual at any given time; (...) an account of how we reduce our logical ignorance by learning logical facts and how we should update our credences in response to such evidence; and an account of when logical ignorance is irrational and when it isn’t. At the end, I explain why the requirement of logical omniscience remains true of ideal agents with no computational, processing, or storage limitations. (shrink)

Information is a central notion for cognitive sciences and neurosciences, but there is no agreement on what it means for a cognitive system to acquire information about its surroundings. In this paper, we approximate three influential views on information: the one at play in ecological psychology, which is sometimes called information for action; the notion of information as covariance as developed by some enactivists, and the idea of information as minimization of uncertainty as presented by Shannon. Our main thesis is (...) that information for action can be construed as covariant information, and that learning to perceive covariant information is a matter of minimizing uncertainty through skilled performance. We argue that the agent’s cognitive system conveys information for acting in an environment by minimizing uncertainty about how to achieve her intended goals in that environment. We conclude by reviewing empirical findings that support our view and by showing how direct learning, seen as instance of ecological rationality at work, is how mere possibilities for action are turned into embodied know-how. Finally, we indicate the affinity between direct learning and sense-making activity. (shrink)

Delicate Tissue Tumors (STT) are a type of sarcoma found in tissues that interface, backing, and encompass body structures. Due to their shallow recurrence in the body and their extraordinary variety, they seem, by all accounts, to be heterogeneous when seen through Magnetic Resonance Imaging (MRI). They are effortlessly mistaken for different infections, for example, fibro adenoma mammae, lymphadenopathy, and struma nodosa, and these indicative blunders have an extensive unfavorable impact on the clinical treatment cycle of patients. Analysts have proposed (...) a few AI models to characterize cancers, however none have sufficiently tended to this misdiagnosis issue. Likewise, comparative investigations that have proposed models for assessment of such cancers generally don't think about the heterogeneity and the size of the information. Thusly, we propose an AI based approach which joins another strategy of pre handling the information for highlights change, resampling methods to dispense with the predisposition and the deviation of precariousness and performing classifier tests in light of the and Deep learning Algorithm as Artificial brain organization. -/- Tumors (STT). (shrink)

The research aims to identify the trends of Palestinian higher educational institutions in Gaza Strip as learning organizations from the perspective of senior management in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) employees (...) from the Palestinian universities was selected and the recovery rate was (69.2%). Statistical analysis (SPSS) program was used for analysis and processing the data. The study found the following results: There is an agreement about: the importance of the focus of "organizational structure" with an average approval, the importance of "technological infrastructure" axis with high approval, and the importance of "strategic" with an average approval. The results concluded that the study sample agree on the importance of "organizational dimension" highly. The results showed that the sample believe that the "strategic leadership" level in the universities got medium-approval. There is a fair level agreement about the axis of interest "teams / committees". There is an agreement about the importance of the "human dimension" moderately. The results showed that the sample is highly agreed about the importance of focus of the "knowledge management", and the focus of the "continuing education". They agreed weakly to somewhat about the importance of the focus of "scientific research", moderately agree about the importance of the center of "institutional culture", agree moderately on the importance of "cognitive dimension". The results showed that the sample largely agree on the importance of the focus of "strategic partnerships and alliances". They agree highly on the axis "keep up with the labor market" and on the focus of the importance of "technology incubators". The results showed that the sample moderately agree about the importance of the theme on "consulting and training", the importance of the focus of "social responsibility", and the focus of the "Community dimension". The study found a group of recommendations including: there is a need to provide suitable environment that achieve learning organizations. There is a need to develop the technological infrastructure (hardware, software, networks, databases, and human skills) because of the great advantages that they offer. The universities need to adopt knowledge management in the academic and administrative departments because knowledge is the core of the work of these departments. The establishment of technology incubators in universities to adopt outstanding university research projects, to protect, to supports, and to market them; furthermore, to develop the capabilities and skills of employees in the field of information technology. (shrink)

Psychopathy is increasingly in the public eye. However, it is yet to be fully and effectively understood. Within the context of the DSM-IV, for example, it is best regarded as a complex family of disorders. The upside is that this family can be tightly related along common dimensions. Characteristic marks of psychopaths include a lack of guilt and remorse for paradigm case immoral actions, leading to the common conception of psychopathy rooted in affective dysfunctions. An adequate portrait of psychopathy is (...) much more complicated, however. Though some neural regions and corresponding functions are commonly indicated, they range across those responsible for action planning and learning, as well as emotional processes. Accordingly, a complete fine-grained map of all neural mechanisms responsible for psychopathy has not been realized, and even if it were, such a map would have limited utility outside of the context of surgical or chemical intervention. The utility of a neural-level understanding of psychopathy is further limited by the fact that it is only applicable in the clinical identification of individual subjects, and the neuro-chemical/biological correction of those subjects after they are positively identified as psychopaths. On the other hand, an information processing model of moral cognition provides for wider-ranging applications. The theoretical and practical implications for such a feasible working model of psychopathic personalities are assessed. Finally, this chapter raises the possibility of directed modification of social-environmental factors discouraging the development of psychopathic personalities in the first place, modifications which are also open to simulation and testing in terms of the same model of moral cognition. (shrink)

Looking out of Information Science (IS) it´s a dangerous attempt to compare this relative new science direct with Philosophy. Here you find a first circumspective trial of an investigation of the traditionally named “queen of science”, Philosophy, two thousand years old and - direct opposite - the only a half century old Information Science. For me it is till now not yet clear how to do this in a serious scientific manner. I worked in Applied Informatics for 30 years and (...) make Information Science since about 15 years. Here I dare to publish for first time the results. SOKRATES (469 – 399 b.Chr.), PLATON (428/27- 348/47 b.Chr.) und ARISTOTELES (384 - 322 b.Chr.) as inventors of our traditional occidental Philosophy, have founded the search of the sense of our Human Life, Thinking and Acting as an own science. They set the Joy of Life on top of their way of thinking. PLATON has separated this special new thinking from the „Sophists“ who had a very good public image too at his time. But they were thinking more about common business facts and knowledge only. Today we would call them manufacturer, qualified skilled workers or even bachelors of special sciences. Philosophy has (since over 20 centuries) till today first of all the smart and high duty to serve Religion and Ethics as mental, spirit- and language-grounded science-base. In other direction it was used to overthink our whole surrounding nature theoretically and completely by our best Human Mind. It´s our traditional science on our mental highest level. All sciences can be related by Philosophy. That´s possible by our human ability to Learn, Think, Understand and finally Know any interesting new fact. Where and how do we have now to integrate this new own science Information Science? We search consciously term-oriented and make an abstract science-theoretical comparison to find answers and definitions. (shrink)

This manuscript introduces I-Three Learning Model (ITLM) intervention to build competency among scholastically backward children by facilitating easy input, processing and output of information. Child receives information through sensory pathways, learning ability is the capacity of the children to collect, process, retain and retrieve information. Children are unique in mental maturity and learning ability. The reasoning is influenced by the auditory, visual, kinaesthetic and tactile inputs. The competency of children with poor social and emotional skills, learning (...) adjustment and academic performance can be improved by enriching their abilities connected to attention, self-learning, logical thinking, reasoning, adjustment, confidence, comprehension and problem-solving. This manuscript is both descriptive and exploratory in nature. On the basis of standard Psychological Assessment, a child studying in the eight standard aged 14 years is identified to be poor in social and emotional skills, learning adjustment and academic performance. This case study is carried to derive the findings of these objectives and establishes that ITLM intervention has certainly improved the capacity of receiving, processing and retrieving information in the children and recommends for the usage of a model for building competency of scholastically backward students. (shrink)

The research aims to design a proposed model of learning organizations as an entry point to achieve organizational excellence in the Palestinian universities of Gaza Strip. A random sample of workers were selected from the Palestinian universities consist of (286) employees at recovery rate of (70.3%). The study concluded with a set of results the most important of which: there is a statistically significant relationship between the components of learning organizations and achieving organizational excellence in the Palestinian universities (...) of Gaza Strip from the standpoint of the faculty members. One of the main recommendations of the study: establish the concept of learning organization in leaders and staff of the university through the establishment of specialized courses, and workshops. Turning the status of the university into a learning organization as a strategic objective and the performance of managers are measurement accordingly. Organize visits of the leaders of the university a to the top organizations in this field and to take advantage of their experience and encourage deans and heads of departments to involve their employees in the information on global trends and trends in learning organization through regular meetings. (shrink)

Abstract: A corn crop typically refers to a large-scale cultivation of corn (also known as maize) for commercial purposes such as food production, animal feed, and industrial uses. Corn is one of the most widely grown crops in the world, and it is a major staple food for many cultures. Corn crops are grown in various regions of the world with different climates, soil types, and farming practices. In the United States, for example, the Midwest is known as the "Corn (...) Belt" due to its extensive corn production. Corn crops can be grown using a variety of methods, including conventional tillage, no-till farming, and the use of genetically modified crops. Due to its importance, there is a need for discovering the corn diseases and treating them. The aim of this study is to propose a deep learning model for the classification of corn leaf diseases based on Convolutional Neural Network. A model for classifying maize diseases was developed using a dataset for classifying Corn diseases that contains 4 classes of disease. The dataset was collected from Keggel website. The proposed model was trained, validated, and tested. The F1-score (99.83%), Recall (99.83%), precision (99.83%), Accuracy (99.83%). (shrink)

In everyday life it is often important to have a mental model of the knowledge, beliefs, desires, and intentions of other people. Sometimes it is even useful to to have a correct model of their model of our own mental states: a second-order Theory of Mind. In order to investigate to what extent adults use and acquire complex skills and strategies in the domains of Theory of Mind and the related skill of natural language use, we conducted an experiment. It (...) was based on a strategic game of imperfect information, in which it was beneficial for participants to have a good mental model of their opponent, and more specifically, to use second-order Theory of Mind. It was also beneficial for them to be aware of pragmatic inferences and of the possibility to choose between logical and pragmatic language use. We found that most participants did not seem to acquire these complex skills during the experiment when being exposed to the game for a number of different trials. Nevertheless, some participants did make use of advanced cognitive skills such as second-order Theory of Mind and appropriate choices between logical and pragmatic language use from the beginning. Thus, the results differ markedly from previous research. (shrink)

Without doubt, there is a widespread usage of visualisations in science. However, what exactly the _epistemic status_ of these visual representations in science may be remains an open question. In the following, I will argue that at least some scientific visualisations are indispensible for our cognitive processes. My thesis will be that, with regard to the activity of _learning_, visual representations are of relevance in the sense of contributing to the aim of _scientific_ _understanding_. Taking into account that understanding can (...) be regarded as an epistemic desideratum in its own right, I will argue that, at least in some instances, no understanding can be achieved without the aid of visualisations. Consequently, they are of crucial importance in this process. Moreover, to support this thesis we will make use of some findings in educational psychology. (shrink)

Information and Communication Technologies, ICTs, has now for decades being increasingly taken into use for higher education, enabling distance learning, e-learning and online learning, mainly in parallel to mainstream educational practise. The concept Blended learning (BL) aims at the integration of ICTs with these existing educational practices. The term is frequently used, but there is no agreed-upon definition. The general aim of this dissertation is to identify new possible perspectives on ICTs and access to higher education, (...) for negotiating the dichotomy between campus-based and ICT-enabled education. The access options of BL are in focus for this dissertation, although BL is generally seen as a campus phenomenon, and shares a place perspective. The main research questions in the dissertation are 1) how BL can be understood in the context of increased access to education, moreover, (2) how time can be work as a more constructive perspective for designing ICTs in education, compared to place. The dissertation comprises five articles. The first is conceptual and concentrates on place and time in blended learning, and forms a time-based model and perspective, drawing on the tension between synchronous and asynchronous modalities instead of a place-based center-periphery model. The following article examines the differences between North American and European use of the term BL, in education and research, and finds that BL is not much used by European researchers, although the term is frequently used in educational environments. Two design and intervention studies, articles 3 and 4, make experiments using the BL time-based model. In article 3, a group of untraditional learners at a learning centre in Arvidsjaur attends a synchronous co-located study circle group and participates in an asynchronous and global Massive Open Online Course (MOOC). In article 4, nine students in a preparatory year for entering engineering studies volunteer and participate in a pilot distance course experiment, where prevention of procrastination is a high priority. For this, agile framework theory, constructivist learning theory and the time-based model are used in design and analysis. The last article (5) reconnects learning to place by discussing and adapting Triple- and Quadruple Helix theory for regional development in the knowledge society to four regional European cases. At the end of the synthesis, an outline of the access affordances with the time-based model is given, drawing on Adam’s timescape theory. The discussion of ICT integration into education is made drawing on Floridi’s Philosophy of Information, which provides many tools to view discourses of ICTs in education critically, and also envisions the concept of e-ducation in the infosphere, where other blend issues appear connected to weak artificial intelligence and the pervasive power of ICTs. (shrink)

Abstract: Fish are important for both nutritional and economic reasons. They are a good source of protein, vitamins, and minerals and play a significant role in human diets, especially in coastal and island communities. In addition, fishing and fish farming are major industries that provide employment and income for millions of people worldwide. Moreover, fish play a critical role in marine ecosystems, serving as prey for larger predators and helping to maintain the balance of aquatic food chains. Overall, fish play (...) a vital role in supporting human well-being and the health of our planet. . Fishes have a lots of types such that: Red Mullet, Sea Bass, Striped Red Mullet and Shrimp. Each of them has its own shape and characteristics that differ from other types. We proposed a system that recognize nine types of fishes using deep learning. We trained the model with a dataset that contain 9000 images that were slit into 6300 images for training, 1350 for validation and 1350 for testing. The proposed model achieved accuracy (99.68%), precision (99.69%), recall (99.68%), and f1-score (99.68%). This indicates that our proposed model can effectively predicate and classify different types of fish with very high accuracy. (shrink)

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial (deep learning, robotics), natural sciences (neuroscience, cognitive science, biology), and philosophy (philosophy of computing, philosophy of mind, natural philosophy). The question (...) is, what at this stage of the development the inspiration from nature, specifically its computational models such as info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach human-level intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

In this paper, we investigated multiple machine learning classifiers which are, Multinomial Naive Bayes, Support Vector Machine, Decision Tree, K Nearest Neighbors, and Random Forest in a text classification problem. The data we used contains real and fake job posts. We cleaned and pre-processed our data, then we applied TF-IDF for feature extraction. After we implemented the classifiers, we trained and evaluated them. Evaluation metrics used are precision, recall, f-measure, and accuracy. For each classifier, results were summarized and compared (...) with others. (shrink)

An influential objection to the epistemic power of the imagination holds that it is uninformative. You cannot get more out of the imagination than you put into it, and therefore learning from the imagination is impossible. This paper argues, against this view, that the imagination is robustly informative. Moreover, it defends a novel account of how the imagination informs, according to which the imagination is informative in virtue of its analog representational format. The core idea is that analog representations (...) represent relations ‘for free,’ and this explains how the imagination can contain more information than is put into it. This account makes important contributions to both philosophy of mind, by showing how the imagination can generate new content that is not represented by a subject’s antecedent mental states, and epistemology, by showing how the imagination can generate new justification that is not conferred by a subject’s antecedent evidence. (shrink)

Sometimes it’s reasonable to reduce confidence in a proposition in response to gaining etiological information. Suppose, for example, a theist learns that her theism is ‘due to’ her religious upbringing. There is a clear range of cases where it would be reasonable for her to respond by slightly decreasing her confidence in God’s existence. So long as reasonability and justification are distinct, this reasonability claim would appear consistent with the thesis that this kind of etiological information cannot, all by itself, (...) affect one’s justification. In what follows, I argue that this is mistaken. For, even if reasonability and justification are distinct, the reasonability of decreasing confidence in response to etiological information must be explained in terms of a decrease in justification. The argument to follow threatens not only the stronger thesis that etiological information never defeats justification but the substantially weaker thesis, advocated by various authors, that justification is defeated by etiological information in only a limited range of circumstances. I go on to show how the arguments en route to this conclusion have much wider epistemological ramifications. (shrink)

In this study, we consider that enabling young people to experience direct contact with nearby natural environments can positively influence their knowledge and feelings about the biodiversity that occurs there, contributing to its protection and conservation for current and future generations. In this study, we explore how teenagers (n = 17) aged between 13 and 17 years old describe and perceive the nearby natural environment before and after an interpretive trail in Una, Bahia, Brazil. Participants were asked to draw the (...) Atlantic Forest with colored pencils on white paper and, based on the drawing, they answered the following questions: “What is in your drawing? and “What is happening in your drawing?,” in addition to other information such as the title of the drawing, difficulty of the activity, and sociodemographic aspects. Content analysis was used to analyze the information collected. From the drawings and responses of the participants, categories related to knowledge, experiences, and types of relationships with the visited place emerged. (shrink)

A shared narrative in the literature on the evolution of cooperation maintains that social _learning_ evolves early to allow for the transmission of cumulative culture. Social _norms_, whilst present at the outset, only rise to prominence later on, mainly to stabilise cooperation against the threat of defection. In contrast, I argue that once we consider insights from social epistemology, an expansion of this narrative presents itself: An interesting kind of social norm — an epistemic coordination norm — was operative in (...) early and important instances of specialised social learning. I show how there’s a need for such norms in two key social learning strategies and explain how this need is constituted. In assessor-teaching (e.g. Castro et al., 2019b, 2021), epistemic coordination norms allow agents to coordinate around the _content_ of social learning, i.e., what is to be known and how this is to be done. These norms also allow agents to coordinate around the form of cultural learning in what’s sometimes called strategic social learning (Laland, 2004; Hoppitt & Laland, 2013; Heyes, 2018, Chap. 5) and elsewhere. Broadly speaking, this concerns how cultural learning is organised within the social group. The upshot is that the evolution of social learning and social norms are intertwined in important and underappreciated ways from early on. The above matters as it informs our views about the evolution of social norms more generally. Truly _social_ norms emerged to coordinate a plurality of complex behaviours and interactions, amongst them specialised social learning. I substantiate this view by contrasting it with Jonathan Birch’s views on the evolution of norms. What results is a general but cohesive narrative on the early evolution of social norms. (shrink)

Students with high motivation to learn English as a second language become efficient language learners and ultimately acquire second language proficiency. However, demotivation in learning English as a second language remains to be a serious challenge. Thus, research-based information is needed to shed light in unravelling the factors of demotivation among second language learners and to guide teachers in putting forward practical solutions to increase students’ motivation in second language learning. This study was conducted to find out the (...) specific factors that hinder students’ desire to learn English as a second language. The researcher used descriptive research design and involved 1,302 students of Palawan State University Cuyo Campus selected through random sampling. Demotivating factors were measured using a modified questionnaire with reliability index of 0.85. Students’ self-confidence, learning content and context, focus of teaching and school facilities are revealed as demotivation to second language learning. The findings of this study may guide English teachers in designing teaching-learning contexts that are interesting and can boost student’s confidence in using English as a second language. It is also beneficial to policymakers and curriculum developers so that necessary policies may be implemented to improve school facilities, teaching strategies, and learning content and context. (shrink)

Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. The aim of this study is to develop a deep learning model to predict the gender from retinal fundus images. The proposed model was based on the Xception pre-trained model. The proposed model was trained on 20,000 retinal fundus images from Kaggle depository. The dataset was preprocessed them split into three datasets (training, validation, Testing). After training and cross-validating the (...) proposed model, it was evaluated using the testing dataset. The result of testing, the area under receiver operating characteristic curve (AUROC) of the model was 0.99, precision, recall, f1-score and accuracy were 99%, precision, recall, f1-score and accuracy were 96.83%, 96.83%, 96.82% and 96.83% respectively.. Clinicians are presently unaware of dissimilar retinal feature variants between females and males, stressing the importance of model explain ability for the prediction of gender from retinal fundus images. The proposed deep learning may enable clinician-driven automated discovery of novel visions and disease biomarkers. (shrink)