This study explores a liberatory epistemic virtue that is suitable for good learning as a form of liberating socially situated epistemic agents toward ideal virtuousness. First, I demonstrate that the weak neutralization of epistemically bad stereotypes is an end of good learning. Second, I argue that weak neutralization represents a liberatory epistemic virtue, the value of which derives from liberating us as socially situated learners from epistemic blindness to epistemic freedom. Third, I explicate two distinct forms (...) of epistemic transformation: constitutive and causal epistemic transformation. I argue that compared with the ideal conception of epistemic virtue, constitutive epistemic transformation that involves good learning has a transcendent value in light of agents constantly renewing their default epistemic status toward ideal virtuousness. (shrink)

AI is increasingly becoming based upon Internet-dependent systems to handle the massive amounts of data it requires to function effectively regardless of the availability of stable Internet connectivity in every affected community. As such, sustainable development (SD) for rural and mountain communities will require more than just equitable access to broadband Internet connection. It must also include a thorough means whereby to ensure that affected communities gain the education and tools necessary to engage inclusively with new technological advances, whether they (...) be focused on machine learning algorithms or community infrastructure, as they will be increasingly dependent upon the automational capabilities of AI. In this essay, an exploration will be conducted into the means whereby student-engaged learning (SEL) can effectively be utilized to provide targeted, inclusive education to rural and mountain communities regarding the implications of AI for SD. (shrink)

Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide (...) understanding misguided? In this paper, using the case of deep neural networks, I argue that it is not the complexity or black box nature of a model that limits how much understanding the model provides. Instead, it is a lack of scientific and empirical evidence supporting the link that connects a model to the target phenomenon that primarily prohibits understanding. (shrink)

What can we learn from cases of knowledge from falsehood? Critics of knowledge-first epistemology have argued that these cases provide us with good reason for rejecting the knowledge accounts of evidence, justification, and the norm of belief. I shall offer a limited defense of the knowledge-first approach to these matters. Knowledge from falsehood cases should undermine our confidence in like-from-like reasoning in epistemology. Just as we should be open to the idea that knowledge can come from non-knowledge, we should (...) be open to the idea that justified beliefs can come from unjustified beliefs. (shrink)

The use of AI algorithms in criminal trials has been the subject of very lively ethical and legal debates recently. While there are concerns over the lack of accuracy and the harmful biases that certain algorithms display, new algorithms seem more promising and might lead to more accurate legal decisions. Algorithms seem especially relevant for bail decisions, because such decisions involve statistical data to which human reasoners struggle to give adequate weight. While getting the right legal outcome is a strong (...) desideratum of criminal trials, advocates of the relational theory of procedural justice give us good reason to think that fairness and perceived fairness of legal procedures have a value that is independent from the outcome. According to this literature, one key aspect of fairness is trustworthiness. In this paper, I argue that using certain algorithms to assist bail decisions could increase three diferent aspects of judges’ trustworthiness: (1) actual trustworthiness, (2) rich trustworthiness, and (3) perceived trustworthiness. (shrink)

Good Thinking is a collection of papers about abilities, skills, and know-how and the distinctive but often overlooked—or explained away—role that these phenomena play in various foundational issues in epistemology and action theory. Each chapter, taken on its own, represents a fairly specific intervention into debates in (i) epistemic responsibility, (ii) the nature of inferential justification, and (iii) connections between inference and action. But taken collectively, these chapters constitute fragments of a larger mosaic of commitments about the explanatory priority (...) of abilities in normative theories. One distinctive argumentative strategy employed throughout Good Thinking is its placing special emphasis on what might be called “bad thinking”: defective judgments borne out of cognitive short-circuiting, incoherence or self-doubt, depression, or anxiety. The underlying motivation for this is that much of what we can learn about good thinking is only revealed at the margins, where thinking has in some respects gone bad without being entirely spoiled. (shrink)

Studies show that people we judge to have good character we also evaluate to be more attractive. I argue that in these cases, evaluative perceptual experiences represent morally admirable people as having positive (often intrinsic) value. Learning about a person's positive moral attributes often leads us to feel positive esteem for them. These feelings of positive esteem can come to partly constitute perceptual experiences. Such perceptual experiences evaluate the subject in an aesthetic way and seem to attribute aesthetic (...) qualities like 'beauty' to the object of perception. Moreover, these aesthetic qualities like 'beauty' represent the perceived to have various kinds of value. (shrink)

What might Adam Smith have learned from Jane Austen and other novelists of his moment? This paper finds and examines a serious problem at the center of Adam Smith’s moral psychology, stemming from an unacknowledged tension between the effort of the spectator to sympathize with the feelings of the agent and that of the agent to moderate her feelings. The agent’s efforts will result in her opacity to spectators, blocking their attempts to read her emotions. I argue that we can (...) resolve this tension by looking to developments in eighteenth-century literature, as perfected in the hands of Jane Austen. I focus on two techniques, focalization and free indirect style, and I show that the problems for spectatorship diminish when we see that good Smithian spectators are savvy readers. (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)

Abstract: People all over the world have been drinking tea for thousands of centuries, and for good reason. Many types of teas can help you stay healthy by boosting your immune system, reducing inflammation, and even preventing cancer and heart disease. There is sufficient material to show that regularly consuming tea can improve your health over the long term. A deep learning model that categorizes tea disorders has been completed. When focusing on the tea, we must also focus (...) on and take into account the diseases that harm it. The aim of this paper is to diagnose tea diseases based on a dataset containing 8000 picture and 8 classes .The model gave the final accuracy test with an F1-score of 99.41% in an estimated time 3 second, as with these results it proved its effectiveness and good ability in the classification test. (shrink)

Abstract: Lemons are an important fruit that have a wide range of uses and benefits, from culinary to health to household and beauty applications. Deep learning techniques have shown promising results in image classification tasks, including fruit quality detection. In this paper, we propose a convolutional neural network (CNN)-based approach for detecting the quality of lemons by analysing visual features such as colour and texture. The study aims to develop and train a deep learning model to classify lemons (...) based on their quality, evaluate the model's performance, compare it to traditional machine learning approaches, and identify key factors that affect the model's performance. The dataset used in the study consists of approximately 2533 images of lemons and an empty surface, divided into training, test, and validation data, and includes images of both good and bad quality lemons under different lighting conditions. The deep learning model achieved an accuracy of 99.74% on the test dataset and outperformed traditional machine learning approaches. The developed model has the potential to improve efficiency and accuracy in lemon quality control in the agriculture and food industry. (shrink)

In order to serve their citizens well, democracies must secure a number of epistemic goods. Take the truth, for example. If a democratic government wants to help its impoverished citizens improve their financial position, then elected officials will need to know what policies truly help those living in poverty. Because truth has such an important role in political decision-making, many defenders of democracy have highlighted the ways in which democratic procedures can lead to the truth. But there are also a (...) number of other epistemic goods – goods like evidence, intellectual virtue, epistemic justice, and empathetic understanding – that democracies can benefit from producing as well. In this teaching and learning guide, I chart a course through the literature that considers the importance of truth, along with these other political goods, for the healthy functioning of democracies. (shrink)

Philosophers and psychologists have argued that fiction can ethically educate us: fiction supposedly can make us better people. This view has been contested. It is, however, rarely argued that fiction can morally “corrupt” us. In this article, we focus on the alleged power of fiction to decrease one's prejudices and biases. We argue that if fiction has the power to change prejudices and biases for the better, then it can also have the opposite effect. We further argue that fictions are (...) more likely to be a bad influence than a good one. (shrink)

Pretendeu-se estudar a aquisição da virtude em Aristóteles a partir da interpretação de M. F. Burnyeat. Para esse, a virtude aristotélica exige dimensões cognitivas e emocionais, sendo que ao aprendiz não basta conhecer os princípios e as regras gerais da ação, mas deve ter internalizado, através do hábito, uma vontade de praticar ações nobres e justas. Compete ao sujeito virtuoso, portanto, ter o conhecimento do que é correto (the that), assim como, subsidiariamente, a justificativa do porquê é apropriada determinada ação (...) (the because). Da análise dessas variáveis, o autor procura esclarecer a figura conflituosa do akratic (incontinente) e do akalastos (perverso) e elucidar a hipótese do desenvolvimento moral. Concomitantemente este artigo pretende introduzir o problema criminológico da ideia de ressocialização ou da pena capital, entendendo ser o argumento aristotélico ainda influente para a filosofia da virtude e jurídica hodierna e necessário quando se discutem novos paradigmas éticos e jurídicos. (shrink)

In the Lunyu, Confucius remarks on the implausibility—or impossibility—of a life lacking in xin 信, reliability (2.22). In existing discussions of Confucian philosophy, this aspect of life is often eclipsed by greater emphasis on Confucian values such as ren 仁 (benevolence), li 禮 (propriety) and yi 義 (rightness). My discussion addresses this imbalance by focusing on reliability, extending current debates in two ways. First, it proposes that the common translation of xin as denoting coherence between a person’s words and deeds (...) is inadequate. The translation fails to capture the longer-term consistency in a person’s actions and behaviours in different circumstances across time. Second, it explores how the Lunyu passages discuss the processes of learning that prepare a person for reliable action. (shrink)

Of the four language skills, speaking is usually considered an indicator of proficiency in a language. As an EFL student, one should master speaking skill (Nazara, 2012). Unfortunately, most Afghan EFL undergraduates are not as good at speaking as they are in the other three English language skills (reading, writing and listening). Most Afghan undergraduate EFL learners are good at reading and writing, but in part of oral communication, they are not accurate and fluent (Zia & Sulan, 2015). (...) Hence, this study was conducted to investigate the factors that affect the Afghan undergraduate EFL learners’ speaking skill at Sayed Jamaluddin Afghani University Kunar, Afghanistan. The study specifically investigated the learning environment-related factors that affected student speaking skill. A mixed method was used for this study, i.e., quantitative (questionnaire) and qualitative (interview). The questionnaire data were descriptively analyzed in SPSS version 20 and presented in figures and tables. The interview data were thematically analyzed and presented. A total of 90 students (40 junior and 50 senior) were purposively selected and participated in this study. The findings revealed that large classes and the lack of basic facilities in the speaking classroom were some factors in the learning environment that affected the students speaking skill. The current study’s findings will hopefully help teachers and educators be attentive and creative in building a proper learning environment to reduce the factors that affect students’ speaking skill. (shrink)

At its strongest, Hume's problem of induction denies the existence of any well justified assumptionless inductive inference rule. At the weakest, it challenges our ability to articulate and apply good inductive inference rules. This paper examines an analysis that is closer to the latter camp. It reviews one answer to this problem drawn from the VC theorem in statistical learning theory and argues for its inadequacy. In particular, I show that it cannot be computed, in general, whether we (...) are in a situation where the VC theorem can be applied for the purpose we want it to. (shrink)

Mencius, referred to as second sage in Chinese philosophy history, grounds his theory about original goodness of human nature on psychological components by bringing in something new down ancient ages. Including the principles of virtuous action associated with Confucius to his doctrine, but by composing them along psychosocial development, he theorizes utterly out of the ordinary that makes all the difference to the school. In his argument stated a positive opinion, he explains the method of forming individuals' moral awareness by (...) means of inseparable integrity of feelings and thoughts, saying human being are born innately good. According to Mencius, heart-mind correlation is the motivational complement of inner incentives. Knowledge and virtue, which are extensions of inborn goodness, comprehended intuitively; then affective motives respond to circumstance, what is learned transmits to cognitive process and eventually behavior emerges. Comparing during the years of Warring State period he lived, in western geography Aristotle, who is one of the pioneers of Greek philosophy, argues deductive and inductive methods in mental activity. On the other hand, Mencius uses analogical reasoning throughout his self-titled work. This essay is an attempt to assert that most postulates of developmental theories, which have been considered an integral part of modern psychology, begin with Mencius in early era. Secondly, this study also aims to discuss the main paradigm of Mencius across emotivist-rationalist opposition, which keeps emotion above thought as well as reason above emotion. (shrink)

The role of emotions in mental life is the subject of longstanding controversy, spanning the history of ethics, moral psychology, and educational theory. This paper defends an account of love’s cognitive power. My starting point is Plato’s dialogue, the Symposium, in which we find the surprising claim that love aims at engendering moral virtue. I argue that this understanding affords love a crucial place in educational curricula, as engaging the emotions can motivate both cognitive achievement and moral development. I first (...) outline the state of the challenge between dominant rival theories regarding emotions in learning. Next, I demonstrate how Platonic virtue ethics offers the most tenable prospect for an education of reason and emotion. Third, I sketch three practical ways educators might constructively engage emotions in the classroom. I conclude that love’s virtue is its peerless power to motivate the creative and lateral thinking which leads to moral development. (shrink)

This paper addresses two specific and related questions the Buddhist neuroethics program raises for our traditional understanding of Buddhist ethics: Does affective neuroscience supply enough evidence that contempla- tive practices such as compassion meditation can enhance normal cognitive functioning? Can such an account advance the philosophical debate concerning freedom and determinism in a profitable direction? In response to the first question, I argue that dispositions such as empathy and altruism can in effect be understood in terms of the mechanisms that (...) regulate affective cognition. In response to the second question, I claim that moral agency is a type of achievement that comes with learning the norms of ethical con- duct, which are not tractable by specifically neurobiological mechanisms and processes (though, once learned, such norms would have their neural cor- relates when enacted). (shrink)

Governance encompasses the processes by which organizations are directed, controlled and held to account. It includes the authority, accountability, leadership, direction, and control exercised in an organization. Greatness can be achieved when good governance principles and practices are applied throughout the whole organization. Ethical Governance requires that public officials adhere to high moral standards while serving others. Authentic Governance entails the systematic process of continuous, gradual, and routine personal/corporate improvement, steering, and learning that lead to sustainable high personal/corporate (...) performance and excellence. Thus authentic governance represents the ability to discern right from wrong and the commitment to do what is right, good, and proper. Benevolent governance is perceived to be for benefit of the population as a whole. Sikhism, a panentheistic religion, originated in the Punjab province of the Indian subcontinent, during the 15th century. It is one of the youngest and fifth major world religions, founded by Guru Nanak. The fundamental beliefs of Sikhism have been enshrined in the sacred scripture, Sri Guru Granth Sahib [1-3]. These beliefs include faith in one universal creator, unity of all humankind, engaging in selfless service, striving for social justice for all, honest livelihood and ethical conduct while living a householder's life. Sri Guru Grant Sahib provides very useful insights for governance through religious or secular organizations, that address human rights, education, or diplomacy to end all forms of disparity/discrimination among people [4-5]. In this article, an attempt is made to understand how the doctrines of Sikhism encourage us for better governance and by which means. Whether these doctrines align with the above-mentioned forms of governance or conflict with these. It is pointed out the most of the attributes of good, ethical, authentic and benevolent governance are genuinely supported by the Sikh doctrines. The adherence to democratic and republican organizations, for providing high-quality governance, is encouraged in Sikh principles and practices. (shrink)

Langdellian “science” and its “formalism” ignore ways form permits and even creates freedom of choice. For example, as Wordsworth notes, though the weaver is restricted by what his form of loom can weave, the weaver may nonetheless choose what and how he weaves. Furthermore, the loom creates weaving possibilities that do not exist without it. Such freedom alongside form is often lost on lawyers, judges, and teachers trained primarily in Langdellian redacted appellate cases where “facts” and other framed matters often (...) wrongly appear as simply given. Similarly, in the context of their redacted appellate cases, many current students may only see constraint in IRAC (Issue-Rule-Application-Conclusion) and other thought forms rather than the fastidious freedoms such forms both provide and create. -/- Overlooking such freedoms is not only misleading in itself. It also misses the need to study how such freedoms are and should be exercised. When facts are simply presented as “given” and strategic and other choices go unrecorded and unnoticed in redacted appellate opinions, no thorough analysis of these overlooked subjects can occur. This is extremely troubling since such overlooked subjects are at the very heart of the lawyer’s craft. -/- Attempting to remedy such Langdellian shortcomings, this article explores, among other things, five basic levels of thought and the framing choices in such levels of thought: references, issues, rules, application of rules, and conclusions. Though often merely taken as “given” in redacted appellate opinions, a good grasp of reference assures that parties are in fact talking about the same matter or matters (the “reference”). It also increases the likelihood of ascertaining and properly framing all the relevant “facts” in a manner reasonably and ethically consistent with a client’s real interests. Similarly, focusing on flexibility of issue framing both brings necessary focus on what is important in the reference and, to the extent reasonable and ethical, again increases the likelihood of frames most consistent with a client’s real interests. A good grasp of applicable rules and how to frame and apply them on its face increases the likelihood of representing a client well. A good grasp of conclusions and how to frame and hedge them also does the same. -/- Grasping the multilevel complexities in play at these multiple levels pushes us beyond briefing redacted appellate cases to the much more difficult and stimulating work of exploring and teaching good legal thought at all its levels. Legal writing professors are pioneers in this regard and others in the academy can learn much from them. -/- Keywords: RIRAC, IRAC, CREAC, Reference, Issue, Analysis, Rule, Application, Conclusion, Frame, Framing, Metaphor, Concept, Category, Legal Thought, Legal Analysis, Rhetoric, Langdell, Wordsworth, Form, Formalism, Sonnet, Text. (shrink)

Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with least performance (...) of 69% accuracy. CNN has the best performance in the presence of large enough training dataset because of the presence of filter/ kernels which help to indentify patterns in text data regardless of their position in the sentence. We repeated the training again with just one-third of our data, at this point SVM comes with the best performance, the performance of CNN noticeably drops but still better than Multinomial Naive Bayes, the reason why SVM works best when we reduce the training data was because of its ability to look for a hyper-plane that creates a boundary between different classes of data so as to properly classify them, so we believed that getting the hyper-plane was more efficient when we reduce the dataset, hence reason for the good performance. Multinomial Naive Bayes have the least performance which we attributed to its assumption of independency between the features which sometimes does not hold true. We concluded that availability of data should be an important factor when choosing classifier for Natural Language Processing Text Classification task. CNN should be use in the presence of enough dataset, and SVM should be use when data is not enough. Multinomial Naive Bayes must not be trusted with state of the art NLP task due to its assumption of independency between the features . (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)

I formulate a resilient paradox about epistemic rationality, discuss and reject various solutions, and sketch a way out. The paradox exemplifies a tension between a wide range of views of epistemic justification, on the one hand, and enkratic requirements on rationality, on the other. According to the enkratic requirements, certain mismatched doxastic states are irrational, such as believing p, while believing that it is irrational for one to believe p. I focus on an evidentialist view of justification on which a (...) doxastic state regarding a proposition p is epistemically rational or justified just in case it tracks the degree to which one’s evidence supports p. If it is possible to have certain kinds of misleading evidence, then evidentialism and the enkratic requirements come into conflict. Yet, both have been defended as platitudinous. After discussing and rejecting three solutions, I sketch an account that rejects the enkratic requirements, while nevertheless explaining our sense that epistemic akrasia is a distinct kind of epistemic failure. Central to the account is distinguishing between two evaluative perspectives, one having to do with the relevant kind of success, the other having to do with manifesting good dispositions. The problem with akratic subjects, I argue, is that they manifest dispositions to fail to correctly respond to a special class of conclusive and conspicuous reasons. (shrink)

Previous research has assessed school facilities, administrative expenditures and curriculum and their relative contributions to students’ cognitive learning outcomes. This suggested the need to investigate further how these predictors may impact students’ affective and psychomotor outcomes. The current research studied the combined and relative prediction of school facilities, administrative expenses and curriculum on students’ overall cognitive, affective and psychomotor learning outcomes in public secondary schools. A cross-sectional research design was employed in this study, involving 87 school administrators and (...) a randomly selected group of 915 senior secondary class II (SS2) students. For data collection, we utilised the School Inputs Questionnaire (SIQ) and Educational Outcomes Questionnaire (EOQ), both developed by the researchers and validated through expert assessments, including content validity, Exploratory Factor Analysis (EFA) for dimensionality, Confirmatory Factor Analysis (CFA) for goodness of fit, and reliability using Cronbach's alpha. The results of these assessments demonstrated acceptable outcomes aligned with international standards. Hierarchical regression analysis was conducted to analyse the collected data. The findings indicated that enhancing the provision of quality school facilities, administrative expenses, and school curricula improved students' overall cognitive, affective, and psychomotor learning outcomes. Specifically, administrative expenses and school curriculum had significant predictive power for students’ overall cognitive, affective, and psychomotor learning outcomes. However, while school facilities significantly predicted students' overall, affective, and psychomotor dimensions, they did not significantly predict the cognitive dimension. These findings offer valuable insights for policymakers and educators aiming to enhance the educational quality in public secondary schools. (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)

Machine learning systems (MLS) that model low-level processes are the cornerstones of current AI systems. These ‘indirect’ learners are good at classifying kinds that are distinguished solely by their manifest physical properties. But the more a kind is a function of spatio-temporally extended properties — words, situation-types, social norms — the less likely an MLS will be able to track it. Systems that can interact with objects at the individual level, on the other hand, and that can sustain (...) this interaction, can learn responses to increasingly abstract properties, including representational ones. This representational capacity, arguably the mark of intelligence, then, is not available to current MLS’s. (shrink)

This study focuses on the step-to-step procedure in creating Facebook Social Learning Group (FBSLG) and the perception of students on using FBSLG as learning management tool. Descriptive method was employed in this study participated by two hundred eighty (280) teacher education students in Nueva Ecija University of Science and Technology – College of Education during the academic year 2020-2021 who were purposively selected based on the criteria set by the researcher. Five simple steps on creating FBSLG were discussed (...) by the researcher. Using the adapted survey questionnaire, the data revealed that the students strongly agreed on the four aspects of perception about FBSLG namely: pedagogical affordance, social affordance, technological affordance, and their overall perception on the platform. Some worries of the students on the platform were addressed like the safety of sharing ideas in the FBSLG and some technical difficulties were encountered. It is concluded that the FBSLG is a good platform of conducting classes during this time of pandemic, so the use of this platform to other subjects is highly recommended. (shrink)

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and react like humans. Some of the activities computers with artificial intelligence are designed for include, Speech, recognition, Learning, Planning and Problem solving. Deep learning is a collection of algorithms used in machine learning, It is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep (...) learning is a technique used to produce Pneumonia detection and classification models using x-ray imaging for rapid and easy detection and identification of pneumonia. In this thesis, we review ways and mechanisms to use deep learning techniques to produce a model for Pneumonia detection. The goal is find a good and effective way to detect pneumonia based on X-rays to help the chest doctor in decision-making easily and accuracy and speed. The model will be designed and implemented, including both Dataset of image and Pneumonia detection through the use of Deep learning algorithms based on neural networks. The test and evaluation will be applied to a range of chest x-ray images and the results will be presented in detail and discussed. This thesis uses deep learning to detect pneumonia and its classification. (shrink)

In this paper, a predictive artificial neural network (ANN) model was developed and validated for the purpose of prediction whether a watermelon is good or bad, the model was developed using JUSTNN software environment. Prediction is done based on some watermelon attributes that are chosen to be input data to the ANN. Attributes like color, density, sugar rate, and some others. The model went through multiple learning-validation cycles until the error is zero, so the model is 100% percent (...) accurate for the purpose of prediction whether good or bad the watermelon is. (shrink)

Two great problems of learning confront humanity: learning about the nature of the universe and about ourselves and other living things as a part of the universe, and learning how to become civilized or enlightened. The first problem was solved, in essence, in the 17th century, with the creation of modern science. But the second problem has not yet been solved. Solving the first problem without also solving the second puts us in a situation of great danger. (...) All our current global problems have arisen as a result. What we need to do, in response to this unprecedented crisis, is learn from our solution to the first problem how to solve the second one. This was the basic idea of the 18th century Enlightenment. Unfortunately, in carrying out this programme, the Enlightenment made three blunders, and it is this defective version of the Enlightenment programme, inherited from the past, that is still built into the institutional/intellectual structure of academic inquiry in the 21st century. In order to solve the second great problem of learning we need to correct the three blunders of the traditional Enlightenment. This involves changing the nature of social inquiry, so that social science becomes social methodology or social philosophy, concerned to help us build into social life the progress-achieving methods of aim-oriented rationality, arrived at by generalizing the progress-achieving methods of science. It also involves, more generally, bringing about a revolution in the nature of academic inquiry as a whole, so that it takes up its proper task of helping humanity learn how to become wiser by increasingly cooperatively rational means. The scientific task of improving knowledge and understanding of nature becomes a part of the broader task of improving global wisdom. The outcome would be what we so urgently need: a kind of inquiry rationally designed and devoted to helping us make progress towards a genuinely civilized world. We would succeed in doing what the Enlightenment tried but failed to do: learn from scientific progress how to go about making social progress towards as good a world as possible. (shrink)

Cumulative cultural knowledge [CCK], the knowledge we acquire via social learning and has been refined by previous generations, is of central importance to our species’ flourishing. Considering its importance, we should expect that our best epistemological theories can account for how this happens. Perhaps surprisingly, CCK and how we acquire it via cultural learning has only received little attention from social epistemologists. Here, I focus on how we should epistemically evaluate how agents acquire CCK. After sampling some reasons (...) why extant theories cannot account for CCK, I suggest that things aren’t as bleak as they might look. I explain how agents deserve epistemic credit for how CCK is transmitted in cultural learning by promoting a central need of their social group: The efficient and safe transmission of CCK. A good initial fit exists between this observation and Greco’s knowledge-economy framework. Ultimately, however, Greco’s account doesn’t straightforwardly account for CCK because of its strict focus on testimony. I point out two issues in the framework due to this focus. The resulting view advocates giving epistemic credit to agents when they act to promote their communities’ epistemic needs in the right way and highlights the various ways in which agents come to do this. (shrink)

Teachers in vocational education face two problems. (1) Learning involves the ability to transcend and modify learned knowledge to new circumstances. How should vocational education prepare students for future, unknown tasks? (2) Students should strive to produce work of good quality. How does vocational education help them develop their faculty of judgment to differentiate between better and worse quality? These two ques- tions are tightly interwoven. The paper compares the didactics of philosophy and sloyd. Both developed independently, but (...) their solutions to how one advances the capacity for reflective judgment are similar. Central to this capacity is not merely devising efficient means to work towards pre-existing aims, but to reflect in practice on what one’s aim are and should be. This implies reflection on what future problems, as well as solutions to them, demand of us cognitively, socially and morally. (shrink)

Abstract: Tomatoes are among the most popular vegetables in the world due to their frequent use in many dishes, which fall into many varieties in common and traditional foods, and due to their rich ingredients such as vitamins and minerals, so they are frequently used on a daily basis, When we focus our attention on this vegetable, we must also focus and take into consideration the diseases that affect this vegetable, a deep learning model that classifies tomato diseases has (...) been proposed. The aim of this paper is to diagnose tomato diseases based on a dataset containing 11000 picture and 11 classes. The model gave the final accuracy test with Accuracy (99.87%), F1-score (99.87%), Recall (99.87%), and Precision (99.88%) in an estimated time 1.36 second, as with these results it proved its effectiveness and good ability in the classification of the testing data. (shrink)

In their paper 'Reward is enough', Silver et al conjecture that the creation of sufficiently good reinforcement learning (RL) agents is a path to artificial general intelligence (AGI). We consider one aspect of intelligence Silver et al did not consider in their paper, namely, that aspect of intelligence involved in designing RL agents. If that is within human reach, then it should also be within AGI's reach. This raises the question: is there an RL environment which incentivises RL (...) agents to design RL agents? (shrink)

The ‘Wu xing’ belongs to Guodian bamboo slips texts, which were buried around 300 BCE and excavated in 1993. Its relation with Mengzi is widely investigated. Yet how it is philosophically related to Xunzi receives little attention. In this article, I illustrate a neglected relation between ‘Wu xing’ and Xunzi, by elucidating how shan 善 (goodness) is first raised in ‘Wu xing’ and developed by Xunzi into a concrete idea. Both ‘Wu xing’ and Xunzi propose that shan exists in action, (...) which boils down to the harmonious unity of the mind and body, and to secure the ideal relation between the mind and body requires constant learning and practicing, particularly, of rituals. Learning and practicing not only lead one to realize shan, but eventually to become a consummate practitioner of rituals, to use Xunzi’s words, to become a sage. (shrink)

Confucian education is best captured by the programme described in the Great Learning. Education is presented first as the process of self-cultivation for the sake of developing virtuous character. Self-cultivation then allows for virtue to be cultivated in the familial, social and international dimensions. My central thesis is that Confucianism can serve as a universal framework of educating people for the common good in its promotion of personal cultivation for the sake of human progress. On this account the (...) common good specifically refers to the social order accomplished by the virtuous behaviour found in the members of society. In this paper I argue that the Confucian notion of “lesser learning” sheds light on the concept of general education and the notion of “greater learning” improves our understanding of liberal education. Under this analysis the necessity of general education is assured although its importance should not be overly exaggerated. Furthermore, the objectives of liberal education deserve greater emphasis due to their historical importance and enduring relevance to promoting the common good of universal humanity. (shrink)

Value Sensitive Design (VSD) is an established method for integrating values into technical design. It has been applied to different technologies and, more recently, to artificial intelligence (AI). We argue that AI poses a number of challenges specific to VSD that require a somewhat modified VSD approach. Machine learning (ML), in particular, poses two challenges. First, humans may not understand how an AI system learns certain things. This requires paying attention to values such as transparency, explicability, and accountability. Second, (...) ML may lead to AI systems adapting in ways that ‘disembody’ the values embedded in them. To address this, we propose a threefold modified VSD approach: 1) integrating a known set of VSD principles (AI4SG) as design norms from which more specific design requirements can be derived; 2) distinguishing between values that are promoted and respected by the design to ensure outcomes that not only do no harm but also contribute to good; and 3) extending the VSD process to encompass the whole life cycle of an AI technology in order to monitor unintended value consequences and redesign as needed. We illustrate our VSD for AI approach with an example use case of a SARS-CoV-2 contact tracing app. (shrink)

This paper uses the fictional case of the ‘Babel fish’ to explore and illustrate the issues involved in the controversy about the use of cochlear implants in prelinguistically deaf children. Analysis of this controversy suggests that the development of genetic tests for deafness poses a serious threat to the continued flourishing of Deaf culture. I argue that the relationships between Deaf and hearing cultures that are revealed and constructed in debates about genetic testing are themselves deserving of ethical evaluation. Making (...) good policy about genetic testing for deafness will require addressing questions in political philosophy and anthropology about the value of culture and also thinking hard about what sorts of experiences and achievements make a human life worthwhile. (shrink)

his study aims to determine whether the application of brain-friendly learning through whole brain teaching gives a positive effect on the creative character of students, to know the response of the students against the application of brain-friendly learning through whole brain teaching, and to find out if the student response against the application of brain-friendly learning through whole brain teaching correlates positively with the creative character of students in learning mathematics. The research method used that is (...) quantitative. The instruments used, namely the now student response related application of brain-friendly learning through whole brain teaching, and sheets of observation about the creativity of students in learning mathematics after implementing this method. The correlation analysis with the results of the study showed that the value of the larger significance of the alpha values (5%) which means accepting and rejecting H0 Ha which means student response against the application of brain-friendly learning through whole brain teaching not correlated positively with the creative character of students in learning mathematics. The average student response score against this method is found on very good i.e. amounted to 85%. As for the observations of the creative character of the students, after this method is applied, the average score of 68% is found quite creative. (shrink)

This study sought to examine the factors affecting the Science, Technology, Engineering and Mathematics (STEM) students’ Mathematics performance in a modular distance learning at Notre Dame Village National High School (NDVNHS). In particular, the researcher was interested to determine if these factors had a significant effect on the students’ Pre-Calculus and General Mathematics performance considering the number of hours spent in modular learning. The period covered by the study was during the first semester of the school year 2020-2021. (...) The respondents were all 67 Grade 11 STEM students of NDVNHS. A quantitative research design was utilized particularly using Multivariate Analysis of Covariance (MANCOVA). The findings of the study revealed that majority of the STEM students had a good performance in their Mathematics subjects for the first semester. Also, the factors specifically type of motivation (intrinsic or extrinsic) and support system (parents, siblings, relatives, friends, or classmates) had statistically significant effect on their mathematics performance in the new normal considering the amount of time they spent in learning using modules. Moreover, there were statistically significant differences in both Pre-Calculus and General Mathematics performances between the type of motivation and support system when adjusted for the number of hours spent in modular learning. Based on the findings, the study concluded that the students’ motivation and support system can greatly affect their mathematics performance when controlling for the allocated time in modular learning. Especially in Pre-Calculus and General Mathematics, motivation and support system are important factors in learning using modules. In the new normal education, the students should increase their level of motivation as well as exposure in self-learning and be given full support towards the processes in the modular approach of distance learning. (shrink)

The Philippine educational system established alternative delivery modes of education, such as the Modified Work and Study Program, to eradicate student dropout incidence. This phenomenological study aims to probe the challenges and explore the coping mechanism of MWSP students in studying mathematics. The study was conducted at a public high school offering the program. Six students were chosen to participate in the study. Focus group discussion was utilized for the data gathering of the study. Results showed that mediocrity of resources (...) and conspicuous learning environment were the leading challenges that MWSP students encounter. Moreover, the coping mechanisms include good classroom management, utilization of concrete examples, time scheduling, steward support, motivational encouragement, and recreational and body relaxation. It is recommended that MWSP mathematics teachers integrate innovative strategies, provide more concrete contextualized examples, intensify the development of learning kits, and reinforce teaching and learning through supplementary materials. (shrink)

Discipline and interest are aspects of parenting that affect children’s behavior and academic performance. This study explores the parents’ disciplinary strategies to promote children’s learning interests. The researchers conducted this study due to society’s issue and observation that elementary pupils have a low interest in learning and manifested inappropriate behaviors inside and outside the classroom. The participants were the ten selected parents with children enrolled in 5th Grade in one of the private Catholic elementary schools in Pagadian City, (...) Philippines. A single case study was utilized. It was found that parents experienced challenges in disciplining their children to promote learning interests due to different kinds of behaviors that the children manifest. The participants identified the following behaviors: Too Much Screen Time in Playing Mobile Games and Being Disrespectful. Despite the challenges they have encountered, they were able to overcome those by implementing positive discipline, offering the problem to God, and effective communication to build good relationships with their children. It is important to be gentle and firm in implementing discipline to promote the learning interest of the pupils. Positive discipline inside the classroom allows the pupils to develop skills of responsibility, resiliency, and proper behavior with the use of positive and negative reinforcements that will motivate them to be interested in learning and excel academically. (shrink)

Following neo-Aristotelians Alasdair MacIntyre and Martha Nussbaum, we claim that humans are story-telling animals who learn from the stories of diverse others. Moral agents use rational emotions, such as compassion which is our focus here, to imaginatively reconstruct others’ thoughts, feelings and goals. In turn, this imaginative reconstruction plays a crucial role in deliberating and discerning how to act. A body of literature has developed in support of the role narrative artworks (i.e. novels and films) can play in allowing us (...) the opportunity to engage imaginatively and sympathetically with diverse characters and scenarios in a safe protected space that is created by the fictional world. By practising what Nussbaum calls a ‘loving attitude’, her version of ethical attention, we can form virtuous habits that lead to phronesis (practical wisdom). In this paper, and taking compassion as an illustrative focus, we examine the ways that students’ moral education might usefully develop from engaging with narrative artworks through Philosophy for Children (P4C), where philosophy is a praxis, conducted in a classroom setting using a Community of Inquiry (CoI). We argue that narrative artworks provide useful stimulus material to engage students, generate student questions, and motivate philosophical dialogue and the formation of good habits which, in turn, supports the argument for philosophy to be taught in schools. (shrink)

We consider an extended notion of reinforcement learning in which the environment can simulate the agent and base its outputs on the agent's hypothetical behavior. Since good performance usually requires paying attention to whatever things the environment's outputs are based on, we argue that for an agent to achieve on-average good performance across many such extended environments, it is necessary for the agent to self-reflect. Thus weighted-average performance over the space of all suitably well-behaved extended environments could (...) be considered a way of measuring how self-reflective an agent is. We give examples of extended environments and introduce a simple transformation which experimentally seems to increase some standard RL agents' performance in a certain type of extended environment. (shrink)

The paper continues my earlier Chat with OpenAI’s ChatGPT with a Focused LLM Experiment (FLEX). The idea is to conduct Large Language Model (LLM) based explorations of certain areas or concepts. The approach is based on crafting initial guiding prompts and then follow up with user prompts based on the LLMs’ responses. The goals include improving understanding of LLM capabilities and their limitations culminating in optimized prompts. The specific subjects explored as research subject matter include a) diagonalization techniques as practiced (...) by Cantor, Turing, Gödel, and the advances, such as the Forcing techniques introduced by Paul Cohen and later investigators, b) Knowledge Hierarchies & Mapping Exercises, c) Discussions of IJ Good’s Speculations Concerning the First Ultraintelligent Machine, AGI, and Super- intelligence. Results suggest variability between major models like ChatGPT-4, Llama-3, Cohere, Sonnet and Opus. Results also point to strong dependence on users’ preexisting knowledge and skill bases. The paper should be viewed as ’raw data’ rather than a polished authoritative reference. (shrink)

This essay narrates what I have learned from Søren Kierkegaard & John Dewey about teaching philosophy. It consists of three sections: 1) a Deweyan pragmatist’s translation of Kierkegaard’s religious insights on Christianity, as a way of life, into ethical insights on philosophy, as a way of life; 2) a brief description of the introductory course that I teach most frequently: Ethics, Happiness, & The Good Life; and 3) an exploration of three spiritual exercises from the course: a) self-cultivation by (...) means of writing in an Ethics Notebook, b) an “existential experiment” in which we practice one of Aristotle’s virtues for a week, and c) a 15-hour service-learning component. (shrink)

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and reacts like humans, some of the computer activities with artificial intelligence are designed to include speech, recognition, learning, planning and problem solving. Deep learning is a collection of algorithms used in machine learning, it is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep (...) learning is used as a technique to produce brain tumor detection and classification models using Magnetic Resonance Imaging (MRI) imaging for rapid and easy detection and identification of brain tumor. In this thesis, some ways and mechanisms will be reviewed to use deep learning techniques to produce a model for brain tumor detection. The goal is to find a good and effective way to detect brain tumor based on MRI to help the brain doctor in making decisions easily, accurately and rapidly. A recent report by the World Health Organization in February 2018 showed that the death rate from brain cancer or central nervous system (CNS) is the highest in the Asian continent. It is important to detect cancer early so that many of these lives can be saved. The model has been designed and implemented, including a dataset which consist of 10,000 images for brain tumor detection through the use of Deep learning algorithms based on neural networks. For testing, we have used our model, Inception, VGG16, MobileNet and ResNet models. The f-score accuracy we got for each model was as follows: Our model was 98.28, VGG16 was 99.86%, ResNet50 was 98.14%, MobileNet was 88,98%, and InceptionV3 was 99.88%. (shrink)