Results for 'Supervised Learning'

998 found
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  1. Implementation of Data Mining on a Secure Cloud Computing over a Web API using Supervised Machine Learning Algorithm.Tosin Ige - 2022 - International Journal of Advanced Computer Science and Applications 13 (5):1 - 4.
    Ever since the era of internet had ushered in cloud computing, there had been increase in the demand for the unlimited data available through cloud computing for data analysis, pattern recognition and technology advancement. With this also bring the problem of scalability, efficiency and security threat. This research paper focuses on how data can be dynamically mine in real time for pattern detection in a secure cloud computing environment using combination of decision tree algorithm and Random Forest over a restful (...)
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  2. Classification of Sign-Language Using Deep Learning - A Comparison between Inception and Xception models.Tanseem N. Abu-Jamie & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (8):9-19.
    there is a communication gap between hearing-impaired people and those with normal hearing, sign language is the main means of communication in the hearing-impaired population. Continuous sign language recognition, which can close the communication gap, is a difficult task since the ordered annotations are weakly supervised and there is no frame-level label. To solve this issue, we compare the accuracy of each model using two deep learning models, Inception and Xception . To that end, the purpose of this (...)
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  3. Predicting Whether Student will continue to Attend College or not using Deep Learning.Samy S. Abu-Naser, Qasem M. M. Zarandah, Moshera M. Elgohary, Zakaria K. D. AlKayyali, Bassem S. Abu-Nasser & Ashraf M. Taha - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (6):33-45.
    According to the literature review, there is much room for improvement of college student retention. The aim of this research is to evaluate the possibility of using deep and machine learning algorithms to predict whether students continue to attend college or will stop attending college. In this research a feature assessment is done on the dataset available from Kaggle depository. The performance of 20 learning supervised machine learning algorithms and one deep learning algorithm is evaluated. (...)
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  4.  67
    The University Teaching Opportunities Programme (UTOP): An Opportunity for Educators and Students to Learn from One Another.Jonathan Y. H. Sim - 2024 - Teaching Connections.
    Jonathan takes us through his experiences of being a mentor for UTOP (University Teaching Opportunities Programme), particularly how it enabled him to collaborate with his UTOP student mentees to design a learning activity in which students could think critically about AI-generated output.
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  5. Biology at Home: The Six Attributes of Home-based Biology Experiments (HBEs) for Remote Authentic Learning.Dave Arthur Robledo - 2021 - Psychology and Education 58 (4):4319-43123.
    Home-based biology experiments are activities that utilize household materials that have been adapted for the remote learning environment and are aligned to standard learning competencies. Recognizingthe households and kitchens as extensions of laboratories, HBEs can be used to deliver authentic learning experiences for the students at home. Furthermore, there are several attributes of HBEs that should be considered before the implementation of the activity. These attributes are, it is ethical and safe to perform, it produces tangible products, (...)
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  6. Prediction Heart Attack using Artificial Neural Networks (ANN).Ibrahim Younis, Mohammed S. Abu Nasser, Mohammed A. Hasaballah & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (10):36-41.
    Abstract Heart Attack is the Cardiovascular Disease (CVD) which causes the most deaths among CVDs. We collected a dataset from Kaggle website. In this paper, we propose an ANN model for the predicting whether a patient has a heart attack or not that. The dataset set consists of 9 features with 1000 samples. We split the dataset into training, validation, and testing. After training and validating the proposed model, we tested it with testing dataset. The proposed model reached an accuracy (...)
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  7. The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence.David Watson - 2019 - Minds and Machines 29 (3):417-440.
    Artificial intelligence has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative (...) learning methods—namely lasso penalties, bagging, and boosting—offer subtler, more interesting analogies to human reasoning as both an individual and a social phenomenon. Despite the temptation to fall back on anthropomorphic tropes when discussing AI, however, I conclude that such rhetoric is at best misleading and at worst downright dangerous. The impulse to humanize algorithms is an obstacle to properly conceptualizing the ethical challenges posed by emerging technologies. (shrink)
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  8. Breast Cancer Diagnosis and Survival Prediction Using JNN.Mohammed Ziyad Abu Shawarib, Ahmed Essam Abdel Latif, Bashir Essam El-Din Al-Zatmah & Samy S. Abu-Naser - 2020 - International Journal of Engineering and Information Systems (IJEAIS) 4 (10):23-30.
    Abstract: Breast cancer is reported to be the most common cancer type among women worldwide and it is the second highest women fatality rate amongst all cancer types. Notwithstanding all the progresses made in prevention and early intervention, early prognosis and survival prediction rates are still not sufficient. In this paper, we propose an ANN model which outperforms all the previous supervised learning methods by reaching 99.57 in terms of accuracy in Wisconsin Breast Cancer dataset. Experimental results on (...)
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  9. Comparing Artificial Neural Networks with Multiple Linear Regression for Forecasting Heavy Metal Content.Rachid El Chaal & Moulay Othman Aboutafail - 2022 - Acadlore Transactions on Geosciences 1 (1):2-11.
    This paper adopts two modeling tools, namely, multiple linear regression (MLR) and artificial neural networks (ANNs), to predict the concentrations of heavy metals (zinc, boron, and manganese) in surface waters of the Oued Inaouen watershed flowing towards Inaouen, using a set of physical-chemical parameters. XLStat was employed to perform multiple linear and nonlinear regressions, and Statista 10 was chosen to construct neural networks for modeling and prediction. The effectiveness of the ANN- and MLR-based stochastic models was assessed by the determination (...)
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  10. Evolving Self-taught Neural Networks: The Baldwin Effect and the Emergence of Intelligence.Nam Le - 2019 - In AISB Annual Convention 2019 -- 10th Symposium on AI & Games.
    The so-called Baldwin Effect generally says how learning, as a form of ontogenetic adaptation, can influence the process of phylogenetic adaptation, or evolution. This idea has also been taken into computation in which evolution and learning are used as computational metaphors, including evolving neural networks. This paper presents a technique called evolving self-taught neural networks – neural networks that can teach themselves without external supervision or reward. The self-taught neural network is intrinsically motivated. Moreover, the self-taught neural network (...)
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  11. Uncovering teacher's situation amidst the pandemic: Teacher's coping mechanisms, initiatives, constraints, and challenges encountered.Kevin Caratiquit & Lovely Jean Caratiquit - 2022 - International Journal of Social Sciences and Education Research 8 (3):288-298.
    This paper aimed to discover the coping, initiatives, constraints, and challenges public secondary school teachers encounter in the new normal education. The central question of this paper lies in "What are the adapting and coping mechanisms of teachers and students in the distance learning modality amidst the pandemic?". This paper used the qualitative research design and employed a phenomenological approach to investigate secondary public-school teachers' coping mechanisms and initiatives in the new normal education. This paper focused on twelve public (...)
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  12. The meaning of ‘reasonable’: Evidence from a corpus-linguistic study.Lucien Baumgartner & Markus Kneer - forthcoming - In Kevin P. Tobia (ed.), The Cambridge Handbook of Experimental Jurisprudence. Cambridge University Press.
    The reasonable person standard is key to both Criminal Law and Torts. What does and does not count as reasonable behavior and decision-making is frequently deter- mined by lay jurors. Hence, laypeople’s understanding of the term must be considered, especially whether they use it predominately in an evaluative fashion. In this corpus study based on supervised machine learning models, we investigate whether laypeople use the expression ‘reasonable’ mainly as a descriptive, an evaluative, or merely a value-associated term. We (...)
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  13. Instructional Leadership Practices of School Administrators: The Case of El Salvador City Division, Philippines.Ma Leah Lincuna & Manuel Caingcoy - 2020 - Commonwealth Journal of Academic Research 1 (2):12-32.
    School administrators are mandated to take the instructional leadership roles. On this premise, a study assessed the extent of instructional leadership practices of public elementary school administrators in El Salvador City Division, Philippines. Also, it explored their actual practices, challenges encountered, and the ways they overcome the challenges in practicing instructional leadership. It employed a mixed-method research design. It administered the adopted assessment tool on instructional leadership to 15 school administrators and 12 of them were involved in the individual interviews. (...)
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  14. Assessing Practice Teachers’ Culturally Responsive Teaching: The Role of Gender and Degree Programs in Competence Development.Manuel Caingcoy, Vivian Irish Lorenzo, Iris April Ramirez, Catherine Libertad, Romeo Pabiona Jr & Ruffie Marie Mier - 2022 - Iafor Journal of Cultural Studies 7 (1):21-35.
    Culturally Responsive Teaching (CRT) weaves together rigor and relevance while it improves student achievement and engagement. The Philippine Department of Education implemented Indigenous People’s education to respond to the demands for culturally responsive teaching. Teacher education graduates are expected to articulate the rootedness of education in sociocultural contexts in creating a learning environment that recognizes respect, connectedness, choice, personal relevance, challenges, engagement, authenticity, and effectiveness. Practice teachers need relevant exposure and immersion to fully develop their competence in CRT. This (...)
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  15.  83
    Response to Amihud Gilead.Iddo Landau - 2007 - Philosophy and Literature 31 (1):158-161.
    In lieu of an abstract, here is a brief excerpt of the content:Iddo Landau responds:I believe that there is much to learn from Gilead's arguments, and that his paper adds to the understanding of the themes presented in the original discussion. However, in the end I do not think that the claims I made are rebuffed.Gilead should be commended for expanding the discussion of the Mandarin thought experiment (henceforth: Mandarin) from the existentialist context, to which it was limited in my (...)
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  16. From Biological Synapses to "Intelligent" Robots.Birgitta Dresp-Langley - 2022 - Electronics 11:1-28.
    This selective review explores biologically inspired learning as a model for intelligent robot control and sensing technology on the basis of specific examples. Hebbian synaptic learning is discussed as a functionally relevant model for machine learning and intelligence, as explained on the basis of examples from the highly plastic biological neural networks of invertebrates and vertebrates. Its potential for adaptive learning and control without supervision, the generation of functional complexity, and control architectures based on self-organization is (...)
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  17. Citizen Science and Social Innovation: Mutual Relations, Barriers, Needs, and Development Factors.Andrzej Klimczuk, Egle Butkeviciene & Minela Kerla (eds.) - 2022 - Lausanne: Frontiers Media.
    Social innovations are usually understood as new ideas, initiatives, or solutions that make it possible to meet the challenges of societies in fields such as social security, education, employment, culture, health, environment, housing, and economic development. On the one hand, many citizen science activities serve to achieve scientific as well as social and educational goals. Thus, these actions are opening an arena for introducing social innovations. On the other hand, some social innovations are further developed, adapted, or altered after the (...)
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  18. A Coordinated Review of Chris Nwamuo’s Perspectives from the “Dynamics of International Communication.Iyorza Stanislaus - manuscript
    At the age of 70 years, Professor Chris Nwamuo is still breaking new grounds in the Theatre, Media and Communication disciplines, not only in the University of Calabar, but also in Cross River University of Technology (CRUTECH) in Cross River State Nigeria, Abia State University in Abia State, Nigeria and many other state, national and international higher institutions of learning. He is tireless in research, clinical in project supervision, stern in the resolution of academic knots and committed to teaching (...)
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  19. Bayesian Learning Models of Pain: A Call to Action.Abby Tabor & Christopher Burr - 2019 - Current Opinion in Behavioral Sciences 26:54-61.
    Learning is fundamentally about action, enabling the successful navigation of a changing and uncertain environment. The experience of pain is central to this process, indicating the need for a change in action so as to mitigate potential threat to bodily integrity. This review considers the application of Bayesian models of learning in pain that inherently accommodate uncertainty and action, which, we shall propose are essential in understanding learning in both acute and persistent cases of pain.
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  20. Machine Learning and Irresponsible Inference: Morally Assessing the Training Data for Image Recognition Systems.Owen C. King - 2019 - In Matteo Vincenzo D'Alfonso & Don Berkich (eds.), On the Cognitive, Ethical, and Scientific Dimensions of Artificial Intelligence. Springer Verlag. pp. 265-282.
    Just as humans can draw conclusions responsibly or irresponsibly, so too can computers. Machine learning systems that have been trained on data sets that include irresponsible judgments are likely to yield irresponsible predictions as outputs. In this paper I focus on a particular kind of inference a computer system might make: identification of the intentions with which a person acted on the basis of photographic evidence. Such inferences are liable to be morally objectionable, because of a way in which (...)
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  21. Supervision, Mentorship and Peer Networks: How Estonian Early Career Researchers Get (or Fail to Get) Support.Jaana Eigi, Katrin Velbaum, Endla Lõhkivi, Kadri Simm & Kristin Kokkov - 2018 - RT. A Journal on Research Policy and Evaluation 6 (1):01-16.
    The paper analyses issues related to supervision and support of early career researchers in Estonian academia. We use nine focus groups interviews conducted in 2015 with representatives of social sciences in order to identify early career researchers’ needs with respect to support, frustrations they may experience, and resources they may have for addressing them. Our crucial contribution is the identification of wider support networks of peers and colleagues that may compensate, partially or even fully, for failures of official supervision. On (...)
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  22. Institutional variables and the supervision of security in public secondary schools in Cross River State.Festus Obun Arop & Valentine Joseph Owan - 2018 - International Journal of Innovation in Educational Management (IJIEM) 2 (1):1-11.
    The purpose of this paper was to examine institutional variables and the supervision of security in secondary schools in Cross River State. The study specifically sought to determine whether there was a significant influence of school population, school type and school location, on the supervision of security in public secondary schools in Cross River State. Three null hypotheses were formulated accordingly to guide the study. 360 students and 120 teachers resulting in a total of 480 respondents, constituted the sample for (...)
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  23. Learning from Failure: Shame and Emotion Regulation in Virtue as Skill.Matt Stichter - 2020 - Ethical Theory and Moral Practice 23 (2):341-354.
    On an account of virtue as skill, virtues are acquired in the ways that skills are acquired. In this paper I focus on one implication of that account that is deserving of greater attention, which is that becoming more skillful requires learning from one’s failures, but that turns out to be especially challenging when dealing with moral failures. In skill acquisition, skills are improved by deliberate practice, where you strive to correct past mistakes and learn how to overcome your (...)
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  24. Supervision and Intervision in the Work of Educational Professionals.Irina Ivanyuk - 2018 - Psychology and Psychosocial Interventions 1:36-40.
    The article describes a comparative analysis of research on the approaches and peculiarities of the implementation of supervision and intervision in the professional activity of teachers abroad and in Ukraine. The concept of supervision and intervision in the work of teachers in the secondary school is revealed. The use of supervision and interference in the professional activity of teachers makes it possible to effectively prevent their emotional and professional burnout. It is noted that in Ukraine, for the first time, a (...)
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  25. Learning to Discriminate: The Perfect Proxy Problem in Artificially Intelligent Criminal Sentencing.Benjamin Davies & Thomas Douglas - 2022 - In Jesper Ryberg & Julian V. Roberts (eds.), Sentencing and Artificial Intelligence. Oxford: Oxford University Press.
    It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring that (...)
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  26. Modular Learning Efficiency: Learner’s Attitude and Performance Towards Self-Learning Modules.April Clarice C. Bacomo, Lucy P. Daculap, Mary Grace O. Ocampo, Crystalyn D. Paguia, Jupeth Pentang & Ronalyn M. Bautista - 2022 - IOER International Multidisciplinary Research Journal 4 (2):60-72.
    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 (...)
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  27. Networked Learning and Three Promises of Phenomenology.Lucy Osler - forthcoming - In Phenomenology in Action for Researching Networked Learning Experiences.
    In this chapter, I consider three ‘promises’ of bringing phenomenology into dialogue with networked learning. First, a ‘conceptual promise’, which draws attention to conceptual resources in phenomenology that can inspire and inform how we understand, conceive of, and uncover experiences of participants in networked learning activities and environments. Second, a ‘methodological promise’, which outlines a variety of ways that phenomenological methodologies and concepts can be put to use in empirical research in networked learning. And third, a ‘critical (...)
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  28. Supervision and Early Career Work Experiences of Estonian Humanities Researchers under the Conditions of Project-based Funding.Jaana Eigi, Pille Põiklik, Endla Lõhkivi & Katrin Velbaum - 2014 - Higher Education Policy 27 (4):453 - 468.
    We analyze a series of interviews with Estonian humanities researchers to explore topics related to the beginning of academic careers and the relationships with supervisors and mentors. We show how researchers strive to have meaningful relationships and produce what they consider quality research in the conditions of a system that is very strongly oriented towards internationalization and project-based funding, where their efforts are compromised by a lack of policies helping them establish a stable position in academia. Leaving researchers to face (...)
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  29. Perceptual learning and reasons‐responsiveness.Zoe Jenkin - 2022 - Noûs 57 (2):481-508.
    Perceptual experiences are not immediately responsive to reasons. You see a stick submerged in a glass of water as bent no matter how much you know about light refraction. Due to this isolation from reasons, perception is traditionally considered outside the scope of epistemic evaluability as justified or unjustified. Is perception really as independent from reasons as visual illusions make it out to be? I argue no, drawing on psychological evidence from perceptual learning. The flexibility of perceptual learning (...)
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  30. Perceptual Learning (Network for Sensory Research/University of York Perceptual Learning Workshop, Question One).Kevin Connolly, Dylan Bianchi, Craig French, Lana Kuhle & Andy MacGregor - manuscript
    This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: What is perceptual learning?
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  31. Learning and Business Incubation Processes and Their Impact on Improving the Performance of Business Incubators.Shehada Y. Rania, El Talla A. Suliman, J. Shobaki Mazen & Samy S. Abu-Naser - 2020 - International Journal of Academic Multidisciplinary Research (IJAMR) 4 (5):120-142.
    This study aimed to identify the learning and business incubation processes and their impact on developing the performance of business incubators in Gaza Strip, and the study relied on the descriptive analytical approach, and the study population consisted of all employees working in business incubators in Gaza Strip in addition to experts and consultants in incubators where their total number reached (62) individuals, and the researchers used the questionnaire as a main tool to collect data through the comprehensive survey (...)
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  32. Learning Organizations and Their Role in Achieving Organizational Excellence in the Palestinian Universities.Mazen J. Al Shobaki, Samy S. Abu Naser, Youssef M. Abu Amuna & Amal A. Al Hila - 2017 - International Journal of Digital Publication Technology 1 (2):40-85.
    The research aims to identify the learning organizations and their role in achieving organizational excellence in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) workers from the Palestinian universities was selected and the recovery (...)
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  33. Perceptual Learning Explains Two Candidates for Cognitive Penetration.Valtteri Arstila - 2016 - Erkenntnis 81 (6):1151-1172.
    The cognitive penetrability of perceptual experiences has been a long-standing topic of disagreement among philosophers and psychologists. Although the notion of cognitive penetrability itself has also been under dispute, the debate has mainly focused on the cases in which cognitive states allegedly penetrate perceptual experiences. This paper concerns the plausibility of two prominent cases. The first one originates from Susanna Siegel’s claim that perceptual experiences can represent natural kind properties. If this is true, then the concepts we possess change the (...)
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  34. Perceptual Learning and the Contents of Perception.Kevin Connolly - 2014 - Erkenntnis 79 (6):1407-1418.
    Suppose you have recently gained a disposition for recognizing a high-level kind property, like the property of being a wren. Wrens might look different to you now. According to the Phenomenal Contrast Argument, such cases of perceptual learning show that the contents of perception can include high-level kind properties such as the property of being a wren. I detail an alternative explanation for the different look of the wren: a shift in one’s attentional pattern onto other low-level properties. Philosophers (...)
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  35.  57
    Coordination in Social Learning: Expanding the Narrative on the Evolution of Social Norms.Müller Basil - forthcoming - European Journal for Philosophy of Science.
    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 (...)
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  36. The Relationship between Performance Standards and Achieving the Objectives of Supervision at the Islamic University in Gaza.Ashraf A. M. Salama, Mazen Al Shobaki, Samy S. Abu-Naser, Abed Alfetah M. AlFerjany & Youssef M. Abu Amuna - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 1 (10):89-101.
    The aim of the research is to identify the relationship between the performance criteria and the achievement of the objectives of supervision which is represented in the performance of the job at the Islamic University in Gaza Strip. To achieve the objectives of the research, the researchers used the descriptive analytical approach to collect information. The questionnaire consisted of (22) paragraphs distributed to three categories of employees of the Islamic University (senior management, faculty members, their assistants and members of the (...)
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  37. Learning Implicit Biases from Fiction.Kris Goffin & Stacie Friend - 2022 - Journal of Aesthetics and Art Criticism 80 (2):129-139.
    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 (...)
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  38. Pupils’ Learning Styles and Academic Performance in Modular Learning.June Albert V. Cavite & Maria Victoria A. Gonzaga - 2023 - International Journal of Multidisciplinary Educational Research and Innovation 1 (3): 72-88.
    This study assesses the student learning styles and academic performance in modular learning among Grade IV, V, and VI learners of Hindang Central School. This considered the learning styles and academic performance of the respondents in modular learning. A total of 252 learners from Hindang Central School participated as respondents in the evaluative method of research that consists of two parts questionnaires. This study used a modified survey questionnaire from the University of California at Merced, Student (...)
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  39. Machine Learning-Based Diabetes Prediction: Feature Analysis and Model Assessment.Fares Wael Al-Gharabawi & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (9):10-17.
    This study employs machine learning to predict diabetes using a Kaggle dataset with 13 features. Our three-layer model achieves an accuracy of 98.73% and an average error of 0.01%. Feature analysis identifies Age, Gender, Polyuria, Polydipsia, Visual blurring, sudden weight loss, partial paresis, delayed healing, irritability, Muscle stiffness, Alopecia, Genital thrush, Weakness, and Obesity as influential predictors. These findings have clinical significance for early diabetes risk assessment. While our research addresses gaps in the field, further work is needed to (...)
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  40. Amidst the Online Learning Modality: The Social Support and Its Relationship to the Anxiety of Senior High School Students.Jastine Joy Basilio, Twinkle Pangilinan, Jeremiah Joy Kalong & Jhoselle Tus - 2022 - Psychology Abd Education: A Multidisciplinary Journal 1 (1):1-6.
    Senior high school is known to be part of the newly implemented K-12 program in the Philippines' educational system. Hence, this program added two years to the academic learning program of students, which mainly focuses on different theoretical and vocational strands that aim to prepare and fully furnish the students for education and employment in the future. Due to adjustments to new online learning amidst the pandemic, students begin to experience various challenges, primarily social support and mental well-being. (...)
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  41. The Learning-Consciousness Connection.Jonathan Birch, Simona Ginsburg & Eva Jablonka - 2021 - Biology and Philosophy 36 (5):1-14.
    This is a response to the nine commentaries on our target article “Unlimited Associative Learning: A primer and some predictions”. Our responses are organized by theme rather than by author. We present a minimal functional architecture for Unlimited Associative Learning that aims to tie to together the list of capacities presented in the target article. We explain why we discount higher-order thought theories of consciousness. We respond to the criticism that we have overplayed the importance of learning (...)
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  42. Logical ignorance and logical learning.Richard Pettigrew - 2021 - Synthese 198 (10):9991-10020.
    According to certain normative theories in epistemology, rationality requires us to be logically omniscient. Yet this prescription clashes with our ordinary judgments of rationality. How should we resolve this tension? In this paper, I focus particularly on the logical omniscience requirement in Bayesian epistemology. Building on a key insight by Hacking :311–325, 1967), I develop a version of Bayesianism that permits logical ignorance. This includes: an account of the synchronic norms that govern a logically ignorant individual at any given time; (...)
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  43. Deep learning and synthetic media.Raphaël Millière - 2022 - Synthese 200 (3):1-27.
    Deep learning algorithms are rapidly changing the way in which audiovisual media can be produced. Synthetic audiovisual media generated with deep learning—often subsumed colloquially under the label “deepfakes”—have a number of impressive characteristics; they are increasingly trivial to produce, and can be indistinguishable from real sounds and images recorded with a sensor. Much attention has been dedicated to ethical concerns raised by this technological development. Here, I focus instead on a set of issues related to the notion of (...)
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  44. Learning to see.Boyd Millar - 2019 - Mind and Language 35 (5):601-620.
    The reports of individuals who have had their vision restored after a long period of blindness suggest that, immediately after regaining their vision, such individuals are not able to recognize shapes by vision alone. It is often assumed that the empirical literature on sight restoration tells us something important about the relationship between visual and tactile representations of shape. However, I maintain that, immediately after having their sight restored, at least some newly sighted individuals undergo visual experiences that instantiate basic (...)
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  45. Learning and Selection Processes.Marc Artiga - 2010 - Theoria 25 (2):197-209.
    In this paper I defend a teleological explanation of normativity, i. e., I argue that what an organism is supposed to do is determined by its etiological function. In particular, I present a teleological account of the normativity that arises in learning processes, and I defend it from some objections.
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  46. Learning from experience and conditionalization.Peter Brössel - 2023 - Philosophical Studies 180 (9):2797-2823.
    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 (...)
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  47. Perceptual Learning and Cognitive Penetration (Network for Sensory Research/University of York Perceptual Learning Workshop, Question Two).Kevin Connolly, Dylan Bianchi, Craig French, Lana Kuhle & Andy MacGregor - manuscript
    This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: Can perceptual experience be modified by reason?
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  48. Learning Computer Networks Using Intelligent Tutoring System.Mones M. Al-Hanjori, Mohammed Z. Shaath & Samy S. Abu Naser - 2017 - International Journal of Advanced Research and Development 2 (1).
    Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation of (...)
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  49. Learning Matters: The Role of Learning in Concept Acquisition.Eric Margolis & Stephen Laurence - 2011 - Mind and Language 26 (5):507-539.
    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 (...)
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  50. Perceptual Learning and Perceptual Phenomenology (Network for Sensory Research/University of York Perceptual Learning Workshop, Question Three).Kevin Connolly, Dylan Bianchi, Craig French, Lana Kuhle & Andy MacGregor - manuscript
    This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: How does perceptual learning alter perceptual phenomenology?
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