Modularity theorists have challenged that there are, or could be, general learning mechanisms that explain theory-of-mind development. In response, supporters of the ‘scientific theory-theory’ account of theory-of-mind development have appealed to children's use of auxiliary hypotheses and probabilistic causal modeling. This article argues that these general learning mechanisms are not sufficient to meet the modularist's challenge. The article then explores an alternative domain-general learning mechanism by proposing that children grasp the concept belief through the progressive alignment of (...) relational structure that occurs as a result of structural-comparison. The article also explores the implications of the proposed account for Fodor's puzzle of conceptual learning. (shrink)

Biologists and philosophers of biology have argued that learning rules that do not lead organisms to play evolutionarily stable strategies (ESSes) in games will not be stable and thus not evolutionarily successful. This claim, however, stands at odds with the fact that learning generalization---a behavior that cannot lead to ESSes when modeled in games---is observed throughout the animal kingdom. In this paper, I use learning generalization to illustrate how previous analyses of the evolution of (...) class='Hi'>learning have gone wrong. It has been widely argued that the function of learning generalization is to allow for swift learning about novel stimuli. I show that in evolutionary game theoretic models learning generalization, despite leading to suboptimal behavior, can indeed speed learning. I further observe that previous analyses of the evolution of learning ignored the short term success of learning rules. If one drops this assumption, I argue, it can be shown that learning generalization will be expected to evolve in these models. I also use this analysis to show how ESS methodology can be misleading, and to reject previous justifications about ESS play derived from analyses of learning. (shrink)

In LOT 2: The Language of Thought Revisited, Jerry Fodor argues that concept learning of any kind—even for complex concepts—is simply impossible. In order to avoid the conclusion that all concepts, primitive and complex, are innate, he argues that concept acquisition depends on purely noncognitive biological processes. In this paper, we show (1) that Fodor fails to establish that concept learning is impossible, (2) that his own biological account of concept acquisition is unworkable, and (3) that there are (...) in fact many promising general models for explaining how concepts are learned. (shrink)

Children acquire complex concepts like DOG earlier than simple concepts like BROWN, even though our best neuroscientific theories suggest that learning the former is harder than learning the latter and, thus, should take more time (Werning 2010). This is the Complex- First Paradox. We present a novel solution to the Complex-First Paradox. Our solution builds on a generalization of Xu and Tenenbaum’s (2007) Bayesian model of word learning. By focusing on a rational theory of concept (...) class='Hi'>learning, we show that it is easier to infer the meaning of complex concepts than that of simple concepts. (shrink)

Learner’s attitude towards modular distance learning catches uncertainties as a world crisis occurs up to this point. As self-learning modules (SLMs) become a supplemental means of learning in new normal education, this study investigated efficiency towards the learners’ attitude and performance. Specifically, the study described the learners’ profile and their attitude and performance towards SLMs. It also ascertained the relationship between the learner’s profile with their attitude and performance, as well as the relationship between attitude and performance (...) relevant to SLMs. A descriptive-correlational research design was employed in the study with 88 non-randomly chosen participants from secondary schools in West Philippines. The learners’ GWA (general weighted average) was used to determine their performance and a survey questionnaire for their profile and attitude. Frequency counts, percentage, and Spearman’s rank correlation coefficient were used to analyze the data gathered with the aid of Jamovi software. Results revealed a strong correlation between attitude and performance, but there was no link between learner’s attitude and performance as to the learner’s profile. It was affirmed that attitude is a compelling factor that is related with performance. Hence, this research has broader ramifications that can direct the Bureau of Learning Delivery to orient the module writers to further contextualize the learning materials that can compound learner’s disposition and academic performance. (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)

Traditional accounts of the role of learning in evolution have concentrated upon its capacity as a source of fitness to individuals. In this paper I use a case study from invasive species biology—the role of conditioned taste aversion in mitigating the impact of cane toads on the native species of Northern Australia—to highlight a role for learning beyond this—as a source of evolvability to populations. This has two benefits. First, it highlights an otherwise under-appreciated role for learning (...) in evolution that does not rely on social learning as an inheritance channel nor “special” evolutionary processes such as genetic accommodation (both of which many are skeptical about). Second, and more significantly, it makes clear important and interesting parallels between learning and exploratory behaviour in development. These parallels motivate the applicability of results from existing research into learning and learning evolution to our understanding of the evolution of evolvability more generally. (shrink)

Online education has become an essential component of education. Thus, several factors, such as the student’s learning strategy and motivation, generally contribute to their academic success. This study investigates the relationship between learning strategies, motivation, and online learning environment among 150 first-year college students. Employing correlational design, the statistical findings of the study reveal that the r coefficient of 0.59 indicates a moderate positive correlation between the variables. The p-value of 0.00, which is less than 0.05, leads (...) to the decision to reject the null hypothesis. Hence, a significant relationship exists between learning strategies, motivation, and the online learning environment. (shrink)

Two great problems of learning confront humanity: learning about the nature of the universe and our place in it, and learning how to become civilized. 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. 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 that we have institutionalized in 20th century academic inquiry. 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. (shrink)

Much of our know-how is acquired through practice: we learn how to cook by cooking, how to write by writing, and how to dance by dancing. As Aristotle argues, however, this kind of learning is puzzling, since engaging in it seems to require possession of the very knowledge one seeks to obtain. After showing how a version of the puzzle arises from a set of attractive principles, I argue that the best solution is to hold that knowledge-how comes in (...) degrees, and through practice a person gradually learns how to do something. However, the two standard accounts of know-how in the literature, intellectualism and anti-intellectualism, cannot properly account for the distinctive way in which know-how is gradually acquired by practice, a process in which conceptual representations and practical abilities are intimately interwoven. Drawing on Gareth Evans's work, I outline an account that may do so, and use this account to distinguish between two forms of learning to explain why skill generally cannot be learnt through testimony, and requires practice. (shrink)

Bayesianism can be characterized as the following twofold position: (i) rational credences obey the probability calculus; (ii) rational learning, i.e., the updating of credences, is regulated by some form of conditionalization. While the formal aspect of various forms of conditionalization has been explored in detail, the philosophical application to learning from experience is still deeply problematic. Some philosophers have proposed to revise the epistemology of perception; others have provided new formal accounts of conditionalization that are more in line (...) with how we learn from perceptual experience. The current investigation argues that Bayesian epistemology is still incomplete; the epistemology of perception and the epistemology of rational reasoning have not been reconciled. (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)

[Edited from Conclusion section:] We have looked at various challenging issues to do with getting connectionism to cope with high-level cognitive activities such a reasoning and natural language understanding. The issues are to do with various facets of generalization that are not commonly noted. We have been concerned in particular with the special forms these issues take in the arena of propositional attitude processing. The main problems we have looked at are: (1) The need to construct explicit representations of (...) generalizations, not just generalize correctly to individual cases; (2) The need to be able to match two or more complex short-term information structures, to enable rapid generalization from recent examples rather than from long-term memories; (3) The need to represent and reason with anomalous combinations of concepts; (4) The need to perform embedded reasoning. This presents special problems for systems using non-concatenative representations (as in mainstream connectionist approaches). We also touched on vague quantification in attitude report complements. Neither this topic nor that of analogies between short-term structures (point 2) has been adequately addressed in the symbolic framework, let alone in connectionism. -/- The opportunities and problems covered are put forward as things worth being optimistic about or pessimistic about, respectively. They are not put forward as decisive arguments for or against connectionism. The hope is that this chapter contributes to a greater understanding of the connectionist/symbolist gap by presenting some unusual issues and by throwing new light on some well known ones. (shrink)

The first learning game to be developed to help students to develop and hone skills in constructing proofs in both the propositional and first-order predicate calculi. It comprises an autotelic (self-motivating) learning approach to assist students in developing skills and strategies of proof in the propositional and predicate calculus. The text of VALIDITY consists of a general introduction that describes earlier studies made of autotelic learning games, paying particular attention to work done at the Law School of (...) Yale University, called the ALL Project (Accelerated Learning of Logic). Following the introduction, the game of VALIDITY is described, first with reference to the propositional calculus, and then in connection with the first-order predicate calculus with identity. Sections in the text are devoted to discussions of the various rules of derivation employed in both calculi. Three appendices follow the main text; these provide a catalogue of sequents and theorems that have been proved for the propositional calculus and for the predicate calculus, and include suggestions for the classroom use of VALIDITY in university-level courses in mathematical logic. (shrink)

After generalizing the Archimedean property of real numbers in such a way as to make it adaptable to non-numeric structures, we demonstrate that the real numbers cannot be used to accurately measure non-Archimedean structures. We argue that, since an agent with Artificial General Intelligence (AGI) should have no problem engaging in tasks that inherently involve non-Archimedean rewards, and since traditional reinforcement learning rewards are real numbers, therefore traditional reinforcement learning probably will not lead to AGI. We indicate two (...) possible ways traditional reinforcement learning could be altered to remove this roadblock. (shrink)

The purpose of this study was to evaluate the differentiated learning training program at the mathematics subject teachers' meeting (MGMP). A descriptive quantitative approach was used to identify the successes of the program and areas that require improvement. The sample included 21 mathematics teachers in Sub Rayon 2 of Lebak District. The instruments used were questionnaires in which data on participants' responses to resource persons, materials, and suggestions for future activities were collected, and the results of direct observations. Data (...) analysis was carried out using descriptive statistical methods to describe the overall evaluation results. Based on the findings, it is expected to provide an in-depth view of the differentiated learning program, contribute to the development of the program in the future, and become a guideline for improving the quality of mathematics learning in the Lebak district. The results of this training program evaluation show that the differentiated learning training activities have been well implemented in MGMP Mathematics Sub Rayon 2 Lebak District. This is evidenced by the level of teacher satisfaction in participating in the training, the majority of which were at scores 4 and 5, namely agreeing and strongly agreeing. This was also the case with the resource persons, materials, and training facilities, and organization. It is hoped that in the future continue to carry out ongoing training related to differentiated learning by current needs and to improve the competence of mathematics teachers in particular, as well as teachers of other subjects in general. (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)

Theories of number concepts often suppose that the natural numbers are acquired as children learn to count and as they draw an induction based on their interpretation of the first few count words. In a bold critique of this general approach, Rips, Asmuth, Bloomfield [Rips, L., Asmuth, J. & Bloomfield, A.. Giving the boot to the bootstrap: How not to learn the natural numbers. Cognition, 101, B51–B60.] argue that such an inductive inference is consistent with a representational system that clearly (...) does not express the natural numbers and that possession of the natural numbers requires further principles that make the inductive inference superfluous. We argue that their critique is unsuccessful. Provided that children have access to a suitable initial system of representation, the sort of inductive inference that Rips et al. call into question can in fact facilitate the acquisition of larger integer concepts without the addition of any further principles. (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)

Does postulating skeptical theism undermine the claim that evil strongly confirms atheism over theism? According to Perrine and Wykstra, it does undermine the claim, because evil is no more likely on atheism than on skeptical theism. According to Draper, it does not undermine the claim, because evil is much more likely on atheism than on theism in general. I show that the probability facts alone do not resolve their disagreement, which ultimately rests on which updating procedure – conditionalizing or updating (...) on a conditional – fits both the evidence and how we ought to take that evidence into account. (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)

The use of social networks such as Facebook, Twitter, and YouTube in the society has become ubiquitous. The advent of communication technologies alongside other unification trends and notions such as media convergence and digital content allow the users of the social network to integrate these networks in their everyday life. There have been several attempts in the literature to investigate and explain the use of social networks such as Facebook and WhatsApp by university students in the Arab region. However, little (...) research has been done on how university students utilise online audiovisual materials in their academic activities in the UAE. This research aims to elucidate the use of YouTube as a learning aid for university students in the UAE. We adopt the technology acceptance model (TAM) as the theoretical framework for this investigation. A quantitative methodology is employed to answer the research question. Primary data consisting of 221 correspondents were analysed, covering patterns of using YouTube as an academic audiovisual learning aid. Statistical techniques including descriptive, correlations, regression tests were used to analyse the data. The study concluded that students use YouTube as a learning tool for their academic studies and enriching their general knowledge; and there is a positive relationship between the use of YouTube videos in academic settings and the students’ overall performance. This study can shed light for teachers, curriculum designers, government entities, and other stakeholders on how to best utilise and integrate the online technology — YouTube — as a learning aid. (shrink)

The goal of creating Artificial General Intelligence (AGI) – or in other words of creating Turing machines (modern computers) that can behave in a way that mimics human intelligence – has occupied AI researchers ever since the idea of AI was first proposed. One common theme in these discussions is the thesis that the ability of a machine to conduct convincing dialogues with human beings can serve as at least a sufficient criterion of AGI. We argue that this very ability (...) should be accepted also as a necessary condition of AGI, and we provide a description of the nature of human dialogue in particular and of human language in general against this background. We then argue that it is for mathematical reasons impossible to program a machine in such a way that it could master human dialogue behaviour in its full generality. This is (1) because there are no traditional explicitly designed mathematical models that could be used as a starting point for creating such programs; and (2) because even the sorts of automated models generated by using machine learning, which have been used successfully in areas such as machine translation, cannot be extended to cope with human dialogue. If this is so, then we can conclude that a Turing machine also cannot possess AGI, because it fails to fulfil a necessary condition thereof. At the same time, however, we acknowledge the potential of Turing machines to master dialogue behaviour in highly restricted contexts, where what is called “narrow” AI can still be of considerable utility. (shrink)

The goal of the study is to analyse the relation between students' digital learning and transversal skills, as well as between students' digital learning and virtues. In the correlative study, 73 teachers of Class 12 of general education institutions participated, filling out a questionnaire in the Google Docs environment. As a result of the theoretical analysis, the criteria for digital learning have been identified -access to digital technologies, cooperation, teachers’ digital competence and availability of activities in compliance (...) with cognitive engagement levels. The findings of the correlation analysis show that the availability of activities in compliance with cognitive engagement levels is the most important in the development of transversal skills,while in the inculcation of virtues -cooperation. The access to digital technologies has a statistically significant correlation with both transversal skills and virtues. The teachers’ digital competence promotes digital literacy and such virtues as responsibility and wisdom. The recommendations developed as part of the study include compilation and promotion of the positive experiences of digital learning at the state and local government level; continuous monitoring and feedback analysis of purposeful digital learning and educational quality at school and classroom level; the application of digital learning resources based on the offer of activities in compliance with the students' cognitive engagement levels at the personal level. Keywords:Digital technologies, cooperation, digital competence, cognitive engagement. (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)

Many teachers appreciate discussing teaching and learning with others, and participating in a community of others who are also excited about pedagogy. Many philosophy teachers find meetings such as the biannual AAPT workshop extremely valuable for this reason. But in between face-to-face meetings such as those, we can still participate in a community of teachers and learners, and even expand its borders quite widely, by engaging in activities under the general rubric of “open education.” Open education can mean many (...) things, from sharing one’s teaching materials openly with others, to using and revising those created by others, to asking students to create open educational materials, and more. In this article I discuss the benefits and possible drawbacks of such activities, and I argue that the former outweigh the latter. (shrink)

Generalized Darwinism models cultural development as an evolutionary process, where traits evolve through variation, selection, and inheritance. Inheritance describes either a discrete unit’s transmission or a mixing of traits. In this article, we compare classical models of cultural evolution and generalized population dynamics with respect to blending inheritance. We identify problems of these models and introduce our model, which combines relevant features of both. Blending is implemented as success-based social learning, which can be shown to be an optimal strategy.

Causal understanding is a defining characteristic of human cognition. Like many animals, human children learn to control their bodily movements and act effectively in the environment. Like a smaller subset of animals, children intervene: they learn to change the environment in targeted ways. Unlike other animals, children grow into adults with the causal reasoning skills to develop abstract theories, invent sophisticated technologies and imagine alternate pasts, distant futures and fictional worlds. In this Review, we explore the development of human-unique causal (...) learning and reasoning from evolutionary and ontogenetic perspectives. We frame our discussion using an ‘interventionist’ approach. First, we situate causal understanding in relation to cognitive abilities shared with non-human animals. We argue that human causal understanding is distinguished by its depersonalized (objective) and decontextualized (general) representations. Using this framework, we next review empirical findings on early human causal learning and reasoning and consider the naturalistic contexts that support its development. Then we explore connections to related abilities. We conclude with suggestions for ongoing collaboration between developmental, cross-cultural, computational, neural and evolutionary approaches to causal understanding. (shrink)

The new normal education requires learners to be independent in the learning process without face-to-face instruction. This study determined the home-based learning activities in relation to the academic achievement of Grade 6 learners in Plaridel North District, Municipality of Plaridel, Misamis Occidental. The descriptive-correlational design was used in the study. There were 135 students who served as respondents, selected through purposive and convenient sampling techniques. The researcher-made Home-Based Learning Activities Questionnaire was used as a research instrument in (...) determining the learners’ learning activities at home. Documentary analysis was made to determine the learners' academic achievement. Mean, Standard Deviation, Pearson Product-Moment Correlation Coefficient, and Regression Analysis were used as statistical tools in analyzing the data gathered. Results revealed that the respondents had a very high engagement in home-based learning activities, and their academic achievement was generally very satisfactory. The level of engagement in home-based learning activities was highly influential to the learners' academic achievement. The efforts extended for modular distance learning can determine what learners can achieve academically. (shrink)

[This is an edited and improved version of "You Are Not Your Brain: Against 'Teaching to the Brain'" previously published in *Review of Higher Education and Self-Learning* 5(15), Summer 2012.] Since educators are always looking for ways to improve their practice, and since empirical science is now accepted in our worldview as the final arbiter of truth, it is no surprise they have been lured toward cognitive neuroscience in hopes that discovering how the brain learns will provide a nutshell (...) explanation for student learning in general. I argue that identifying the person with the brain is scientism (not science), that the brain is not the person, and that it is the person who learns. In fact the brain only responds to the learning of embodied experience within the extra-neural network of intersubjective communications. Learning is a dynamic, cultural activity, not a neural program. Brain-based learning is unnecessary for educators and may be dangerous in that a culturally narrow ontology is taken for granted, thus restricting our creativity and imagination, and narrowing the human community. (shrink)

In response to paradigm shifts in education, teacher education institutions have increasingly adopted flexible learning modalities such as online courses, blended learning approaches, and personalized instruction to meet the diverse needs of students and prepare educators for the demands of modern classrooms. This study used a mixed-method research design to gain a comprehensive understanding of the flexible teaching and learning modalities it brought to mathematics teacher educators (MTEs) and learners in a state university in West Philippines. Since (...) ethical considerations preclude random sampling, the study comprised nonrandom participants using purposive sampling, where 189 learners were surveyed, and six MTEs and 16 learners were interviewed. A researcher-made interview guide was prepared to describe the flexible teaching and learning modalities and opportunities of the MTEs. Also, a researcher-made questionnaire was used to describe the learners’ general assessment of the flexible teaching and learning modalities in mathematics education. Quantitative data were gathered online, while qualitative data were gathered through interviews. Results showed that flexible teaching-learning approaches have implications for education, overcoming barriers, and promoting engagement. The findings highlight the importance of technology integration, inclusive assessment modalities, infrastructure support, and professional development opportunities in enhancing the quality and accessibility of flexible teaching and learning, ultimately leading to inclusive educational environments. Therefore, the educational institution must adopt flexible instructional modalities, emphasize diverse assessment methods, and personalize the learning experience by integrating online platforms and various assessments for effective mathematics instruction. (shrink)

This dissertation consists of five chapters, each written as independent research papers that are unified by an overarching concern regarding information privacy and machine learning-based artificial intelligence (AI). This dissertation addresses the issues concerning privacy and AI by responding to the following three main research questions (RQs): RQ1. ‘How does an AI system affect privacy?’; RQ2. ‘How effectively does the General Data Protection Regulation (GDPR) assess and address privacy issues concerning both individuals and groups?’; and RQ3. ‘How can the (...) value of privacy be embedded into systems?’ -/- To respond to the RQs, this dissertation adopts the privacy impact assessment (PIA) as the overall methodology. A PIA encompasses three distinct stages; the first, the analytical stage, concerns the analysis of how AI (particularly focusing on inference as a process that includes inferred information, AI models’ performance, and accessing information uncovered by AI models) impacts privacy. Second, the legal assessment stage concerns whether AI that processes personal information and develops models complies with the GDPR. Finally, the design requirements stage features proposals for design requirements for systems aimed at protecting privacy. Accordingly, this dissertation is structured in three parts, each corresponding to a specific stage of a PIA and responding to one of the RQs. -/- Part I, which addresses the first stage of the PIA, comprises three chapters that altogether respond to RQ1. Chapter 2 analyses how AI impacts the descriptive aspect of privacy; this part argues that AI challenges the current definitions of privacy and that the ‘source control’ and ‘actual access’ definitions of privacy, once revised in the face of counter-examples involving inferred information, converge. Chapter 3, which considers how AI impacts the normative aspect of privacy, particularly the value of privacy, argues that AI affects the social value of privacy, which depends on trust, as this dimension of privacy is constituted when AI models perform accurately. Chapter 4 examines how AI impacts the normative aspect of privacy, particularly the right to privacy, and it argues that, although accessing information uncovered by AI models raises concerns about the privacy of algorithmically designed groups, the right to privacy cannot be recognised for such groups. This is the disruptive feature of AI that has led to consideration of new approaches other than the traditional one, which involves recognising the right to privacy, to protect the privacy of these groups. Instead of recognising the right to privacy for algorithmically designed groups, this chapter suggests taking a moral principle for the moral obligation of protecting vulnerable groups within an ethics of vulnerability. -/- Part II concerns the second stage of the PIA and consists of one chapter that responds to RQ2. Chapter 5, in addition to evaluating whether AI that processes personal information and develops models complies with the GDPR, also assesses whether the GDPR adequately addresses the privacy issues raised by AI. It specifically focuses on group privacy and argues that GDPR has limitations in protecting the privacy of algorithmically designed groups and that the privacy of such vulnerable entities must be considered in the context of privacy and data protection. -/- Part III, which is related to the third stage of the PIA, also consists of one chapter that responds to RQ3. Chapter 6 proposes design requirements to protect privacy by integrating privacy into systems and argues that privacy is instrumentally valuable for the sake of autonomy. Accordingly, to embed the value of privacy into systems, design requirements are articulated through the translation of norms that promote and protect autonomy. (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)

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)

This work demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were shown to demonstrate model generality over (...) the video temporal dimension. Predicted captions were shown to generalize over video action, even in instances where the video scene changed dramatically. Model architecture changes are discussed to improve sentence grammar and correctness. (shrink)

Abstract: Rice is one of the most important staple crops in the world and serves as a staple food for more than half of the global population. It is a critical source of nutrition, providing carbohydrates, vitamins, and minerals to millions of people, particularly in Asia and Africa. This paper presents a study on using deep learning for the classification of different types of rice. The study focuses on five specific types of rice: Arborio, Basmati, Ipsala, Jasmine, and Karacadag. (...) A dataset of 75,000 images was collected and annotated, consisting of 15,000 images for each of the five types of rice. The deep learning system uses convolutional neural networks (CNNs) to classify images of rice grains based on their physical characteristics. The performance of the deep learning system was evaluated using metrics such as accuracy, precision, recall, and F1-score. The results show that the proposed deep learning system was able to achieve high accuracy in classifying the different types of rice, outperforming traditional image processing techniques. This study provides valuable insights into the potential of deep learning for classifying different types of rice and can be useful for applications such as quality control in rice processing industries and research in crop science. The large size of the dataset, 15,000 images for each type of rice, helped the deep learning system to learn the features of each type of rice, and increase the performance of the classifier. The attained overall accuracy of the proposed model (99.96%), Precision (99.96%), Recall (99.96%) and F1-score (99.96%). Thus, the proposed model proved that it leaned the five categories of rice and it can generalize these categories and it is effective. (shrink)

The results are interpreted in terms of a deficit in initial rule learning and subsequent generalization of these rules to new stimuli. Negative feedback is adequately processed at a neural level but this information is not used to improve behaviour on subsequent trials. As learning is degraded, the process of error detection at the moment of the actual response is diminished. Therefore, the current study demonstrates that disturbed error-monitoring processes play a central role in the often reported (...) learning deficits in individuals with PP. (shrink)

Quine has been charged with eliminating the normative dimension from his naturalized epistemology. The aim of the paper is to look at the role of empathy in Quine's language learning situation, which in its simplest form is constituted by the parent-child relation. We will explore the normativity of the role of empathy thereof by exploiting the sociality of the language learning situation. Since the sociality of Quine's notion of empathy is implicit, to explore the normativity expression thereof, we (...) will examine the explicit sociality of Wittgenstein's language learning situation-also constituted in its simplest form by the master-novice relation-and the normative character of it. By explicating the normativity of the calibrating role of the master and of rule following generally, we will parse the social dimensions of the empathizing role of the linguist in Quine's language learning situation. Finally, by examining the nature of normativity in empathizing, we will establish that the normativity of empathizing involved in Quine's language learning situation is socially grounded without denying its individual dimension. We will conclude that the normativity objection against Quine's naturalism thus stands refuted. (shrink)

Rescorla (Erkenntnis, 2020) has recently pointed out that the standard arguments for Bayesian Conditionalization assume that whenever I become certain of something, it is true. Most people would reject this assumption. In response, Rescorla offers an improved Dutch Book argument for Bayesian Conditionalization that does not make this assumption. My purpose in this paper is two-fold. First, I want to illuminate Rescorla’s new argument by giving a very general Dutch Book argument that applies to many cases of updating beyond those (...) covered by Conditionalization, and then showing how Rescorla’s version follows as a special case of that. Second, I want to show how to generalise R. A. Briggs and Richard Pettigrew’s Accuracy Dominance argument to avoid the assumption that Rescorla has identified (Briggs and Pettigrew in Noûs, 2018). In both cases, these arguments proceed by first establishing a very general reflection principle. (shrink)

Citizenship and marriage are legal statuses that generate numerous privileges and responsibilities. Legal doctrine and argument have analogized these statuses in passing: consider, for example, Ted Olson’s statement in the Hollingsworth v. Perry oral argument that denying the label “marriage” to gay unions “is like you were to say you can vote, you can travel, but you may not be a citizen.” However, the parallel between citizenship and marriage has rarely been investigated in depth. This paper investigates the marriage-citizenship parallel (...) with a particular focus on three questions prompted by recent developments in law and policy: -/- 1) Should we provide second-best statuses? Some couples — in particular gay and lesbian couples — have been offered permanent statuses, like civil unions, that bear legal privileges but fall short of full marriage equality. In contrast, similar differentiations within citizenship are generally resisted. The history of citizenship may presage the increasing unacceptability of differentiations within status in the gay marriage context. Meanwhile, the history of marriage equality efforts may help present-day citizenship advocates choose legal strategies. -/- 2) Should statuses be a gateway to rights? Some early gay rights advocates unsuccessfully argued that advocates should challenge the primacy of marriage, rather than seek access to the institution. Advocates attempting to expand the rights of current noncitizens face similar choices: should they seek to give current noncitizens greater access to citizenship, or challenge the reservation of important rights to citizens? -/- 3) Can status relationships be plural? Many critics of dual and multiple citizenship argued that allegiance to multiple states was immoral, unadministrable, or both. More recently, polygamous marriage has become a topic of legal and political discourse, first as a foil in anti-gay marriage arguments and later as a political possibility in its own right. I consider whether polygamous marriage advocates can profitably draw on arguments for multiple citizenship, and how multiple-citizenship advocates should responsibly respond to the analogy with polygamy. (shrink)

The study aimed to analyze lexical items underpinned in the textbooks used in the current teaching of ESP and GE. Using content analysis, a systematic evaluation of texts to examine nuances to bridge the gap between quantitative and qualitative data. This was such of importance, however, difficult to study due to issues of interest like in the study, frequency of lexical items in ESP, and GE textbooks. Results found 13,713 lexical items in Hospitality Management, 17,561 in Criminology, 4576 in Tourism, (...) 7167 in Marine Engineering, and 512 in Information Technology. Furthermore, the overall percentage of ESP lexical items fell in Tier 2 (with multiple-meaning while the least was in Tier 3, specifically on context-specific vocabulary. It is the core of vocabulary learning to ensure English language teaching. It is its goal to help learners better understand language, allowing them to understand others as they want to express themselves as well. This applies not only in speaking but also in writing and reading. Wilkins (1972, p. 111-112) stated that without grammar very little understanding can be acquired and without vocabulary there can be no learning at all. Thus, even without good grammar, so long as you equipped with useful words and expression, one can still manage to communicate. Lewis (1993) argued that “lexis is the heart of language” and that it develops a better fluency and expression in English. He also added the significance to the learners of acquiring a more productive vocabulary knowledge, also, their eagerness to develop their own personal vocabulary strategies. Thus, a proposed bridge model program was recommended to highlight the study findings using the lexicons found from the different respective courses. (shrink)

Consider a set of shuffled observations drawn from a fixed probability distribution over some instance domain. What enables learning of inductive generalizations which proceed from such a set of observations? The scenario is worthwhile because it epistemically characterizes most of machine learning. This kind of learning from observations is also inverse and ill-posed. What reduces the non-uniqueness of its result and, thus, its problematic epistemic justification, which stems from a one-to-many relation between the observations and many learnable (...) generalizations? The paper argues that this role belongs to any complexity regularization which satisfies Norton’s Material Theory of Induction (MTI) by localizing the inductive risk to facts in the given domain. A prime example of the localization is the Lottery Ticket Hypothesis (LTH) about overparameterized neural networks. The explanation of MTI’s role in complexity regularization of neural networks is provided by analyzing the stability of Empirical Risk Minimization (ERM), an inductive rule that controls the learning process and leads to an inductive generalization on the given set of observations. In cases where ERM might become asymptotically unstable, making the justification of the generalization by uniform convergence unavailable, LTH and MTI can be used to define a local stability. A priori, overparameterized neural networks are such cases and the combination of LTH and MTI can block ERM’s trivialization caused by equalizing the strengths of its inductive support for risk minimization. We bring closer the investigation of generalization in artificial neural networks and the study of inductive inference and show the division of labor between MTI and the optimality justifications (developed by Gerhard Schurz) in machine learning. (shrink)

Background Men with antisocial personality disorder show lifelong abnormalities in adaptive decision making guided by the weighing up of reward and punishment information. Among men with antisocial personality disorder, modifi cation of the behaviour of those with additional diagnoses of psychopathy seems particularly resistant to punishment. Methods We did a case-control functional MRI (fMRI) study in 50 men, of whom 12 were violent off enders with antisocial personality disorder and psychopathy, 20 were violent off enders with antisocial personality disorder but (...) not psychopathy, and 18 were healthy non-off enders. We used fMRI to measure brain activation associated with the representation of punishment or reward information during an event-related probabilistic response-reversal task, assessed with standard general linear-model-based analysis. Findings Offenders with antisocial personality disorder and psychopathy displayed discrete regions of increased activation in the posterior cingulate cortex and anterior insula in response to punished errors during the task reversal phase, and decreased activation to all correct rewarded responses in the superior temporal cortex. This finding was in contrast to results for off enders without psychopathy and healthy non-off enders. Interpretation Punishment prediction error signalling in off enders with antisocial personality disorder and psychopathy was highly atypical. This finding challenges the widely held view that such men are simply characterised by diminished neural sensitivity to punishment. Instead, this fi nding indicates altered organisation of the information processing system responsible for reinforcement learning and appropriate decision making. This difference between violent offenders with antisocial personality disorder with and without psychopathy has implications for the causes of these disorders and for treatment approaches. (shrink)

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

Matthias Mahlmann’s Mind and Rights (M&R) argues that the mentalist theory of moral cognition—premised on an approach to the mind most closely associated with generative linguistics—is the appropriate lens through which to understand moral judgment’s roots in the mind. Specifically, he argues that individuals possess an inborn moral faculty responsible for the principled generation of moral intuitions. These moral intuitions, once sufficiently abstracted, generalized, and universalized by individuals, gave rise to the idea of human rights embodied in such conventions as (...) the Universal Declaration of Human Rights. I am sympathetic to the fundamentals of this argument, particularly in the link between Universal Moral Grammar and the idea of human rights. I thus take my comments on M&R as an opportunity to preempt a topical challenge to the mentalist theory arising in statistical machine learning. Using M&R’s analytical theory of morality alongside the mentalist approach, I emphasize—through this preempted challenge—the significance of strong generative capacity in the moral domain, the distinction between actual acquisition of cognitive abilities and simulation of acquisition, and what Mahlmann calls the theory-dependence of data interpretation in machine learning modeling. (shrink)

Xuanzang (602–664) is famous for his legendary life, his important translation works, and also his Discourse on the Realisation of Consciousness-Only (Vijñapti-mātratā-siddhi, 成唯識論). This text, which is considered as a synthesis of Yogācāra thought, has been diversely interpreted by modern scholars and is still discussed, in particular about the status of external things. Nevertheless, this issue seems to be of little interest for Yogācāra thinkers compared to other topics such as the Noble Path, or else the three types of wisdom (...) (trividhā prajñā, 三慧): learning (śruta, 聞), reasoning (cintā, 思), and cultivating (bhāvanā, 修). As emphasized in recent research, this topic represents a major issue for Buddhist practitioners. In an attempt to analyse it in Xuanzang’s Discourse, and more generally in Yogācāra thought, this paper will first discuss Asaṅga’s and Vasubandhu’s thought on the three types of wisdom. Secondly, since it is important to replace the three types of wisdom in the general argumentation of Xuanzang’s Discourse, we will present the structure of his text which is modelled on a “path” leading progressively to Supreme Awakening. Then, we will present the main elements of the Noble Path and situate the three types of wisdom into it. Finally, we will explain that Xuanzang follows Asaṅga’s and Vasubandhu’s conceptions and eventually confirm the importance of the three types of wisdom in Yogācāra thought. (shrink)

Defenders of happiness surveys often claim that individuals are infallible judges of their own happiness. I argue that this claim is untrue. Happiness, like other emotions, has three features that make it vulnerable to introspective error: it is dispositional, it is intentional, and it is publically manifest. Other defenders of the survey method claim, more modestly, that individuals are in general reliable judges of their own happiness. I argue that this is probably true, but that it limits what happiness surveys (...) might tell us, for the very claim that people are reliable judges of their own happiness implies that we already have a measure of how happy they are, independent of self-reports. Happiness surveys may help us extend and refine this prior measure, but they cannot, on pain of unintelligibility, supplant it altogether. (shrink)

In contemporary healthcare, medical image categorization is essential for illness prediction, diagnosis, and therapy planning. The emergence of digital imaging technology has led to a significant increase in research into the use of machine learning (ML) techniques for the categorization of images in medical data. We provide a thorough summary of recent developments in this area in this review, using knowledge from the most recent research and cutting-edge methods.We begin by discussing the unique challenges and opportunities associated with medical (...) image classification, including the complexity of anatomical structures, variability in imaging modalities, and the need for interpretability and reliability in clinical settings. Subsequently, we survey a wide range of ML algorithms and techniques employed for medical image classification, including traditional methods such as support vector machines and k-nearest neighbors, as well as deep learning approaches like convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Furthermore, we examine key considerations in dataset preparation, feature extraction, and model evaluation specific to medical image classification tasks. We highlight the importance of large, annotated datasets, transfer learning, and data augmentation techniques in enhancing model performance and generalization. (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)

Abstract: Networking is one of the most important areas currently used for data transfer and enterprise management. It also includes the security aspect that enables us to protect our network to prevent hackers from accessing the organization's data. In this paper, we would like to learn what the network is and how it works. And what are the basics of the network since its emergence and know the mechanism of action components. After reading this paper - even if you do (...) not have a general background on networking - you will be able to manage your own network and be able to distribute and control your ip. (shrink)