We linked between the social-psychology and experimental-philosophy paradigms for the study of folk intuitions and beliefs regarding the concept of free will to answer three questions: (1) what intuitions do people have about free-will and determinism? (2) do free will beliefs predict differences in free-will and determinism intuitions? and (3) is there more to free-will and determinism than experiencing certainty or uncertainty about the nature of the universe? Overall, laypersons viewed the universe as allowing for human indeterminism, and they (...) did so with certainty. Examining intuitions of prosociality, future-orientation, learning, meaningfulness, human uniqueness, and well-being, ratings were highest in the indeterministic universe condition and lowest in the deterministic universe condition, both significantly different from the uncertain universe condition. Participants’ free will beliefs had only weak impact on realism, happiness, and learning intuitions, but did not reverse the general intuition favoring indeterminism, and showed no impact on other intuitions. (shrink)

The Morris water maze has been put forward in the philosophy of neuroscience as an example of an experimental arrangement that may be used to delineate the cognitive faculty of spatial memory (e.g., Craver and Darden, Theory and method in the neurosciences, University of Pittsburgh Press, Pittsburgh, 2001; Craver, Explaining the brain: Mechanisms and the mosaic unity of neuroscience, Oxford University Press, Oxford, 2007). However, in the experimental and review literature on the water maze throughout the history of (...) its use, we encounter numerous responses to the question of “what” phenomenon it circumscribes ranging from cognitive functions (e.g., “spatial learning”, “spatial navigation”), to representational changes (e.g., “cognitive map formation”) to terms that appear to refer exclusively to observable changes in behavior (e.g., “water maze performance”). To date philosophical analyses of the water maze have not been directed at sorting out what phenomenon the device delineates nor the sources of the different answers to the question of what. I undertake both of these tasks in this paper. I begin with an analysis of Morris’s first published research study using the water maze and demonstrate that he emerged from it with an experimental learning paradigm that at best circumscribed a discrete set of observable changes in behavior. However, it delineated neither a discrete set of representational changes nor a discrete cognitive function. I cite this in combination with a reductionist-oriented research agenda in cellular and molecular neurobiology dating back to the 1980s as two sources of the lack of consistency across the history of the experimental and review literature as to what is under study in the water maze. (shrink)

Descriptive accounts of the nature of explanation in neuroscience and the global goals of such explanation have recently proliferated in the philosophy of neuroscience and with them new understandings of the experimental practices of neuroscientists have emerged. In this paper, I consider two models of such practices; one that takes them to be reductive; another that takes them to be integrative. I investigate those areas of the neuroscience of learning and memory from which the examples used to substantiate (...) these models are culled, and argue that the multiplicity of experimental protocols used in these research areas presents specific challenges for both models. In my view, these challenges have been overlooked largely because philosophers have hitherto failed to pay sufficient attention to fundamental features of experimental practice. I demonstrate that when we do pay attention to such features, evidence for reduction and integrative unity in neuroscience is simply not borne out. I end by suggesting some new directions for the philosophy of neuroscience that pertain to taking a closer look at the nature of neuroscientific experiments. (shrink)

Until recently, experimental philosophy has been associated with the questionnaire-based study of intuitions; however, experimental philosophers now adapt a wide range of empirical methods for new philosophical purposes. New methods include paradigms for behavioural experiments from across the social sciences as well as computational methods from the digital humanities that can process large bodies of text and evidence. This book offers an accessible overview of these exciting innovations. The volume brings together established and emerging research leaders from several (...) areas of experimental philosophy to explore how new empirical methods can contribute to philosophical debates. Each chapter presents one or several methods new to experimental philosophy, demonstrating their application in a key area of philosophy and discussing their strengths and limitations. Methods covered include eye tracking, virtual reality technology, neuroimaging, statistical learning, and experimental economics as well as corpus linguistics, visualisation techniques and data and text mining. The volume explores their use in moral philosophy and moral psychology, epistemology, philosophy of science, metaphysics, philosophy of language, philosophy of mind and the history of ideas. Methodological Advances in Experimental Philosophy is essential reading for undergraduates, graduate students and researchers working in experimental philosophy. (shrink)

As our epistemic ambitions grow, the common and scientific endeavours are becoming increasingly dependent on Machine Learning (ML). The field rests on a single experimental paradigm, which consists of splitting the available data into a training and testing set and using the latter to measure how well the trained ML model generalises to unseen samples. If the model reaches acceptable accuracy, an a posteriori contract comes into effect between humans and the model, supposedly allowing its deployment to (...) target environments. Yet the latter part of the contract depends on human inductive predictions or generalisations, which infer a uniformity between the trained ML model and the targets. The paper asks how we justify the contract between human and machine learning. It is argued that the justification becomes a pressing issue when we use ML to reach ‘elsewheres’ in space and time or deploy ML models in non-benign environments. The paper argues that the only viable version of the contract can be based on optimality (instead of on reliability which cannot be justified without circularity) and aligns this position with Schurz’s optimality justification. It is shown that when dealing with inaccessible/unstable ground-truths (‘elsewheres’ and non-benign targets), the optimality justification undergoes a slight change, which should reflect critically on our epistemic ambitions. Therefore, the study of ML robustness should involve not only heuristics that lead to acceptable accuracies on testing sets. The justification of human inductive predictions or generalisations about the uniformity between ML models and targets should be included as well. Without it, the assumptions about inductive risk minimisation in ML are not addressed in full. (shrink)

An experimental paradigm that purports to test young children’s understanding of social norms is examined. The paradigm models norms on Searle’s notion of a constitutive rule. The experiments and the reasons provided for their design are discussed. It is argued that the experiments do not provide direct evidence about the development of social norms and that the concepts of a social norm and constitutive rule are distinct. The experimental data are re-interpreted, and suggestions for how to (...) deal with the present criticism are presented that do not require abandoning the paradigm as such. Then the conception of normativity that underlies the experimental paradigm is rejected and an alternative view is put forward. It is argued that normativity emerges from interaction and engagement, and that learning to comply with social norms involves understanding the distinction between their content, enforcement, and acceptance. As opposed to rule-based accounts that picture the development of an understanding of social norms as one-directional and based in enforcement, the present view emphasizes that normativity is situated, reciprocal, and interactive. (shrink)

This chapter aims to narrow the gap between how Responsible Research and Innovation (RRI) is conceived of in European Commission policy circles and how it is conceived of in scholarly circles. The policy view of RRI and the scholarly view of RRI each have their strengths and weaknesses and both would be better off if coupled to the other. Large and pertinent differences between Scott's High Modernist projects and pRRI, however, perhaps weigh heavier than do the aforementioned similarities. In the (...) policy literature, people see that a straightforwardly optimistic approach to RRI can be found, which simultaneously is very explicit and universalist about what it means to be responsible—see the definition of RRI. Arguably, most of the discrepancies between aRRI and pRRI above can be explained in terms of two more parameters, along which the two can be differentiated—one somewhat philosophical, and one very down-to-earth. (shrink)

Advances in Artificial Intelligence (AI) have driven the evolution of reasoning in modern AI models, particularly with the development of Large Language Models (LLMs) and their "Think and Answer" paradigm. This paper explores the influence of human reinforcement on AI reasoning and its potential to enhance decision-making through dynamic human interaction. It analyzes the roots of bias and fairness in AI, arguing that these issues often stem from human data and reflect inherent human biases. The paper is structured as (...) follows: first, it frames reasoning as a mechanism for ethical reflection, grounded in dynamic learning and feedback loops; second, it discusses how scaling laws suggest that reinforcement learning (RL) can mitigate biases and promote fairness; third, it examines how RL allows models to view algorithmic bias and fairness as approximation problems. Through an experimental study, the paper demonstrates how AI models, empowered by RL, have successfully identified biases across various domains, including gender and socio-economic contexts, highlighting how reasoning improves algorithmic fairness. Ultimately, this work emphasizes the role of RL in mitigating algorithmic bias and enhancing fairness in AI systems. (shrink)

In the presently unfolding deepfake era, previously unrelated algorithmic superintelligence possibility claims cannot be scientifically analyzed in isolation anymore due to the connected inevitable epistemic interactions that have already commenced. For instance, deep-learning (DL) related algorithmic supremacy claims may intrinsically compete with both neuro-symbolic (NS) algorithmic and further quantum (Q) algorithmic superintelligence achievement claims. Concurrently, a variety of experimental combinations of DL, NS and Q directions are conceivable. While research on these three illustrative variants did not yet offer (...) any clear mutually applicable scientific definition of a purported supremacy level framed as goal, the currently most robust scientific evaluation frameworks would i.a. require a joint testing against pre-existing non-algorithmic supremacy baselines such as e.g. conscious supremacy and cellular supremacy. This autodidactic paper explains why, for scientific reasons, all algorithmic superintelligence achievement claims in the deepfake era can be condensed and subjected to a joint scientific evaluation framework comprising multiple successive civilization-level tasks of epistemic tunneling (ET). In light of this elusive requirement, recent claims of science automation are spurious and misleading. It is vital not to misapprehend algorithmic epistemic dark matter (EDM) mining and epistemic dark energy (EDE) generation as paradigm-shifting ET events. (shrink)

Two questions should be considered when assessing the Kantian dimensions of Kuhn’s thought. First, was Kuhn himself a Kantian? Second, did Kuhn have an influence on later Kantians and neo-Kantians? Kuhn mentioned Kant as an inspiration, and his focus on explanatory frameworks and on the conditions of knowledge appear Kantian. But Kuhn’s emphasis on learning; on activities of symbolization; on paradigms as practical, not just theoretical; and on the social and community aspects of scientific research as constitutive of scientific (...) reasoning, are all outside the Kantian perspective. Kuhn’s admiration for Kant is tempered by his desire to understand the processes of learning, of initiation into a scientific community, of experimentation using instruments, and of persuasion, drawing on the work of familiar influences, including Piaget, Koyré, and Wittgenstein, and less familiar ones, including Langer, Demos, and Frank. Both Kuhn and Kant were interested in the question: what is the status of science, and what is the role of the scientist in its development and justification? But Kuhn presents science in a much more messy, historically contingent, and socially charged way than Kant does. The paper’s conclusion evaluates Kuhn’s reception among researchers including Richardson and Friedman, assessing the prospects for future work. (shrink)

Learner-centered approaches have emerged as the fundamental pillar of effective pedagogy in the rapidly evolving landscape of 21st century education. This paradigm shift places the learner at the heart of the educational process, recognizing their diverse needs and aspirations. Consequently, the achievements of learners have become crucial indicators of institutional success. While extensive research has focused on student affairs and services, limited attention has been given to understanding the impact of administration on realizing the objectives of these support systems. (...) This study aims to investigate the relationship between the administration of learner-centered academic support systems and the attainment of desired outcomes in student affairs and services within higher education institutions in the Philippines. Utilizing a non-experimental correlational quantitative research design, a sample of three hundred fifty university students from various academic disciplines was randomly selected as participants. The findings demonstrate a strong positive correlation between the administration of learner-centered academic support systems and the achievement of desired outcomes in student affairs and services. As a result, the null hypothesis was rejected based on statistical analysis employing Pearson Correlation (r). These findings highlight the significant impact that learner-centered academic support system administration has on the realization of objectives in student affairs and services within the contemporary higher educational setting. To ensure sustained best practices in student development, it is imperative for the administration to foster collaboration with internal stakeholders and external partners. Recognizing that students are the focal point of instruction, their performance serves as a reflection of the institution’s commitment to providing quality education. By aligning administrative efforts with the evolving needs of students, institutions can enhance student affairs and services and create an optimal learning environment in the 21st century. (shrink)

We often remember in the company of others. In particular, we routinely collaborate with friends, family, or colleagues to remember shared experiences. But surprisingly, in the experimental collaborative recall paradigm, collaborative groups remember less than their potential, an effect termed collaborative inhibition. Rajaram and Pereira-Pasarin (2010) argued that the effects of collaboration on recall are determined by “pre-collaborative” factors. We studied the role of 2 pre-collaborative factors—shared encoding and group relationship—in determining the costs and benefits of collaborative recall. (...) In Experiment 1, we compared groups of strangers who encoded alone versus together, before collaborating to recall. In Experiment 2, we compared groups of friends who encoded alone versus together, before collaborating to recall. We found that shared encoding abolished collaborative inhibition in both Experiments 1 and 2. But prior relationship did not influence collaborative inhibition over and above the effects of shared encoding. Regardless of encoding condition, collaborative group recall contained fewer intrusions than nominal group recall, and these benefits continued in subsequent individual recall. Our findings demonstrate that pre-collaborative factors—specifically shared encoding—have flow-on benefits for group and individual recall amount, but not recall accuracy. We discuss these findings in terms of self- and cross-cuing in collaborative recall. (shrink)

The contents of our conscious mind can seem unpredictable, whimsical, and free from external control. When instructed to attend to a stimulus in a work setting, for example, one might find oneself thinking about household chores. Conscious content thus appears different in nature from reflex action. Under the appropriate conditions, reflexes occur predictably, reliably, and via external control. Despite these intuitions, theorists have proposed that, under certain conditions, conscious content resembles reflexes and arises reliably via external control. We introduce the (...) Reflexive Imagery Task, a paradigm in which, as a function of external control, conscious content is triggered reliably and unintentionally: When instructed to not subvocalize the name of a stimulus object, participants reliably failed to suppress the set-related imagery. This stimulus-elicited content is considered ‘high-level’ content and, in terms of stages of processing, occurs late in the processing stream. We discuss the implications of this paradigm for consciousness research. (shrink)

This research is motivated by the need to unravel the progression of learning models, which have been adapting to meet the demands of society in its constant dynamics of fluctuation and transformation. The aim of this work is to systematically examine the evolution of learning models, highlighting the paradigmatic changes that have favored the transition from traditional learning approaches to more innovative and transdisciplinary proposals. To achieve this, a bibliographic analysis is carried out, supported by the hermeneutic (...) method for the contextual interpretation of literature and discourses, in order to unravel the complexities inherent in the evolution of learning models. The results highlight the limiting influence of the simplicity paradigm in traditional educational formation and the need for a shift towards dialogicity and disciplinary collaboration and integration to advance towards complexity. It concludes by arguing in favor of adopting the complexity paradigm, advocating for a transdisciplinary epistemology and an interstructuring approach to learning, which allow for integral human development. Recognizing human complexity in teaching and learning demands a radical transformation of education towards more holistic and transformative practices, essential for building an equitable and just society. (shrink)

This paper reports the first study in the literature that adopts a bibliometric approach to systematically explore the scholarship in the young and fast‐growing research field of experimental philosophy. Based on a corpus of 1,248 publications in experimental philosophy from the past two decades retrieved from the PhilPapers website, the study examined the publication trend, the influential experimental philosophers, the impactful works, the popular publication venues, and the major research themes in this subarea of philosophy. It found, (...) first, an overall growing trend in publications in experimental philosophy, encompassing four developmental stages. Second, it found that significant changes in topics of interest have taken place, with some gaining increasing attention, others seemingly going out of fashion, and still others remaining popular constantly. Third, the study identified lists of leading philosophers, frequently cited publications, and popular journals helpful for researchers and newcomers to get a quick start in learning about the field. (shrink)

Dr. Strange sees Dr. Stephen Strange abandon his once-promising medical career to become a superhero with the ability to warp time and space, and to travel through various dimensions. In order to make this transition, he is required to abandon many of his previous assumptions about the way the world works and learn to see things in a new way. Importantly, this is not merely a matter of learning a few facts, or of mastering new techniques. Instead, Dr. Strange (...) is required to alter his conception of the basic nature of the world and of how he relates to it. In time, this change extends to his values as well, as Strange comes to embrace his role in safeguarding the human world from interdimensional threats. -/- It is tempting to interpret Dr. Strange’s experience as one that shows the limits of rational, scientific inquiry, or even of human knowledge more generally. However, in this essay, I’d like to explore a different interpretation: that Strange’s experience can most fruitfully be thought of as a scientific revolution, in which Strange moves from one way of carrying out scientific inquiry to a different, incompatible way of doing it. In order to do this, I’ll be exploring the work of philosopher and historian of science Thomas Kuhn, who wrote a book—The Structure of Scientific Revolutions--about just this topic. Among other things, Kuhn’s work introduced the highly useful (though commonly misunderstood) notion of a paradigm shift. -/- We’ll begin by exploring what Kuhn describes as normal science, which consists of applying a set of well-understood concepts and methods to problems of interest. This “puzzle-solving” aspect of science is exemplified by Strange’s early successes in medicine. During this stage, scientists have good reasons to avoid questioning the basic validity of their paradigm, and to instead blame any problems that arise on other factors, such as human error. (As fans will know, Strange is quite good at assigning blame in just this way.) A crisis only occurs when significant, serious anomalies have accrued, such as those that Strange encounters in the aftermath of his accident. Even then, however, the old paradigm will only be abandoned only if a new paradigm can be found. Again, Strange’s experience bears this out, as he is able to move on only when the Sorcerer Supreme introduces him to the Mystic Arts. -/- Along the way, we’ll consider what it means for a practice to count as a scientific paradigm, and why it’s not just “anything goes.” Among other things, a paradigm requires that practitioners agree on which problems are most important, which techniques are appropriate to which problems, and what exemplary models of successful work look like. The Mystic Arts of Strange’s world, unlike the pseudoscientific theories of our own, plausibly do quite well on these sorts of criteria. (shrink)

Low physics learning in the Philippines is a prevailing concern the education sector must resolve, so initiating technological interventions in teaching the subject, including flipped classrooms, and introducing a chatbot such as ManyChat Delivering Online-Offline learning could be helpful to improve scientific literacy in learning Electromagnetic (EM) waves. This study aimed to determine the significant learning differences between conventional teaching (CT), Flipped Classroom (FC), and ManyChat Delivering Online-Offline (MCDOO) Learning in teaching EM waves. Previous research (...) showed that flipped classrooms are effective in Physics lessons. At the same time, only a few studies have been found using MCDOO learning effectively in other subjects, yet to be in Physics lessons. The researcher used the randomized posttest-only control group experimental research design with four groups; Conventional Teaching (CT) as the control group while the experimental groups are: Flipped Classroom (FC), ManyChat Delivering Online-Offline (MCDOO) Learning, and lastly, the combined FC+MCDOO learning who underwent different learning sessions (traditional teaching, FC session via google classroom, MCDOO session and FC+ MCDOO via Messenger App respectively). One-Way ANOVA was performed to determine whether there were any significant learning differences. The results showed in the first and second competencies; the null hypotheses are accepted, so all the differences in all four groups are not significant there is not much of a difference between the scores of CT and FC, CT and MCDOO, and FC and MCDOO learning; however, in the third learning competency, the null hypothesis is rejected so then the Tukey Post Hoc test was conducted to point out where is/are the significant difference/s. The Tukey Post Hoc test revealed that CT and FC+MCDOO learning differs significantly. It means that FC+MCDOO learning boosts higher learning achievement than conventional teaching, FC alone, or MCDOO alone. This study concludes that using just one technological intervention in Physics teaching simply cannot produce a significant impact on the physics literacy of the students in EM learning. Utilizing a combination of technological approaches can make a meaningful difference to the literacy rate in Physics lessons, specifically electromagnetic waves. (shrink)

It has been argued that some recent experimental findings about the mere exposure effect can be used to argue for aesthetic antirealism: the view that there is no fact of the matter about aesthetic value. The aim of this paper is to assess this argument and point out that this strategy, as it stands, does not work. But we may still be able to use experimental findings about the mere exposure effect in order to engage with the aesthetic (...) realism/antirealism debate. However, this argument would need to proceed very differently and would only support a much more modest version of aesthetic antirealism. (shrink)

A theory of learning for the future advocates the teaching of a preparedness to respond in a creative way to difference and otherness. This includes an ability to act imaginatively in situations of uncertainties. John Dewey’s pragmatism holds the key to such a learning theory his view of the continuous meetings of individuals and environments as experimental and playful. That pragmatism has not yet been acknowledged as a relevant learning theory for the future may be due (...) to the immediate connotation and the many interpretations associated with the term ‘experience’, which is at the heart of Dewey’s educational thinking. Dewey defi ned experience in a way that is not well understood within educational research, and in a way that is easily confused with the term ‘experiential learning’. The latter refers to the importance of participants’ ‘experiences’ derived from bodily actions and stored in memory as more or less tacit knowledge. (shrink)

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

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

Evolutionary economics often focuses on the comparison between economic competition and the process of natural selection to select the fitter members of a given population. But that neglects the other "half" of an evolutionary process, the mechanism for the generation of new possibilities that is key to dynamic efficiency. My topic is the process of parallel experimentation which I take to be a process of multiple experiments running concurrently with some form of common goal, with some semi-isolation between the experiments, (...) with benchmarking comparisons made between the experiments, and with the "migration" of discoveries between experiments wherever possible to ratchet up the performance of the group. The thesis is that parallel experimentation is a fundamental dynamic efficiency scheme to enhance and accelerate variation, innovation, and learning in contexts of genuine uncertainty or known ignorance. Within evolutionary biology, this type of parallel experimentation scheme was developed in Sewall Wright's shifting balance theory of evolution. It addressed the rather neglected topic of how a population on a low fitness peak might eventually be able to go "downhill" against selective pressures, traverse a valley of low fitness, and then ascend a higher fitness peak. The theme of parallel experimentation is used to recast and pull together dynamic and pluralistic theories in economics, political theory, philosophy of science, and social learning. (shrink)

Analytical categories of scientific cultures have typically been used both exclusively and universally. For instance, when styles of scientific research are employed in attempts to understand and narrate science, styles alone are usually employed. This article is a thought experiment in interweaving categories. What would happen if rather than employ a single category, we instead investigated several categories simultaneously? What would we learn about the practices and theories, the agents and materials, and the political-technological impact of science if we analyzed (...) and applied styles, paradigms, and models simultaneously? I address these questions in general and for a specific case study: a brief history of systematics. (shrink)

With the current improvement of development towards pharmaceutical, distinctive ultrasound methodologies are open to find the fetal prosperity. It is analyzed with diverse clinical parameters with 2-D imaging and other test. In any case, prosperity desire of fetal heart still remains an open issue due to unconstrained works out of the hatchling, the minor heart appraise and inadequate of data in fetal echocardiography. The machine learning strategies can find out the classes of fetal heart rate which can beutilized for (...) earlier evaluating. With this background, we have utilized Cardiotocographic Fetal heart rate dataset removed from UCI Machine Learning Store for predicting the fetal heart rate health classes. The Prediction of fetal health rate are achieved in six ways. Firstly, the data set is preprocessed with Feature Scaling and missing values. Secondly, exploratory data investigation is done and the dispersion of target feature is visualized. Thirdly, the raw data set is fitted to all the classifiers and the performance is analysed before and after feature scaling. Fourth, the raw data set is subjected to undersampling methods like ClusterCentroids, RepeatedENN, AllKNN, CondensedNearestNeighbour, EditedNearestNeighbours, InstanceHardnessThreshold and NearMiss. Fifth, the undersampled dataset by above mentioned methods are fitted to all the classifiers and the performance is analyzed before and after feature scaling. Sixth, performance analysis is done using metrics like Precision, Recall, F-score, Accuracy and running time. The execution is done using python language under Spyder platform with Anaconda Navigator. Experimental results shows that the Decision Tree classifier tends to retain 98% before and after feature scaling for the underrsampling with EditedNearestNeighbours, RepeatedENN and AllKNN methods. (shrink)

The concept of 'authenticity' is highly valued on social media sites (SMSes), despite its ambiguous nature and definition. One interpretation of 'authenticity' by media scholars is a human's congruence with online portrayals of themselves (e.g. posting spontaneous photographs from their lives, or using real biodata online). For marketers and 'influencers', these patterns of behaviour can achieve certain gains: sales for a business, or success of a campaign. For existentialist philosophers, using 'authenticity' as a means to an end is against its (...) very definition. In this paper, I investigate what SMS users are looking for by their supposed 'authentic' portrayal online. My experimental approach draws upon empirical data from the Instagram social media site. Using machine learning techniques, descriptions and features of posts - including subjects, captions, and contexts - will be categorised and aggregated. I will then interpret these findings, drawing upon work by Taylor, Golomb, and Guignon, whose works on authenticity are based on mid-20th century existentalists. I argue that the existentialist ideals on authenticity are not necessarily present in contemporary SMS use. I will also argue that the popular interpretation of authenticity on SMSes can be self-defeating, when it seeks to turn the 'for-itself' into an 'in-itself'. (shrink)

This study primarily assessed students' achievement in mathematics using a mobile educational application to help them learn and adapt to changes in education. The study involved selected Grade 9 students at a public high school in Nueva Vizcaya, Philippines. This study used a quasi-experimental method, particularly a post-test control group design. Descriptive statistics such as frequencies, percent, mean, and standard deviation were used to describe the achievement of the students in mathematics. A t-test for independent samples was also computed (...) to determine if there is a significant difference between the students’ achievement in mathematics after using the mobile educational application by the control and experimental groups. Results revealed that students' achievement in mathematics was very proficient after using the application. Moreover, the usage of educational mobile applications has a better impact on students' achievement in mathematics than the traditional approach to teaching. Teachers are encouraged to place priority on solving problems. Overall, the use of the mobile educational application can enhance learning in mathematics, thus the continued use of the said application is advised. (shrink)

The high number of Dengue Hemorrhagic Fever (DHF) cases from year to year and the endemic status of DHF in Kutaraja District, Banda Aceh City encourages us to always make efforts to reduce the morbidity rate of DHF. The involvement of elementary school teachers is very important to participate in DHF control which will teach their students. This study was conducted to assess the effect of before and after administration of the DHF learning module on the average knowledge score (...) of 90 grade IV and V elementary school students in the Kutaraja District, Banda Aceh City. The quasi-experimental method and Focus Group Discussions involving schools and Puskesmas when designing DHF learning modules were conducted. One-group pretest-posttest design, consisting of 25 questions that were analyzed using the Wilcoxon Signed Ranks Test. The study results obtained an average pre-test score of 76.6% and a post-test average value of 90.6%. The DHF learning module was able to increase elementary school students' knowledge. The provision of DHF material by elementary school teachers through modules can be done to students to increase students' knowledge so that they can participate in reducing the incidence of dengue hemorrhagic fever. (shrink)

The proliferation of the Internet of Things (IoT) has transformed various industries by enabling smart environments and improving operational efficiencies. However, this expansion has introduced numerous security vulnerabilities, making IoT systems prime targets for cyberattacks. This paper proposes a machine learning-based intrusion detection framework tailored to the unique characteristics of IoT environments. The framework leverages feature engineering, advanced machine learning algorithms, and real-time anomaly detection to identify and mitigate security threats effectively. Experimental results demonstrate the efficacy of (...) the proposed approach in detecting diverse IoT-specific attacks, including denial-of-service (DoS), man-in-the-middle (MITM), and malware-based attacks. The Internet of Things (IoT) has revolutionized modern living by interconnecting devices and enabling seamless communication. However, the increasing reliance on IoT systems has exposed significant vulnerabilities, making them a prime target for security attacks. This paper proposes a machine learning-based intrusion detection framework to detect and mitigate security attacks in IoT environments. The framework integrates diverse machine learning algorithms to identify abnormal behavior and potential threats. Through comprehensive experiments and evaluations, this research demonstrates the efficacy of the proposed framework in terms of accuracy, scalability, and robustness. (shrink)

Replicability is widely regarded as one of the defining features of science and its pursuit is one of the main postulates of meta-research, a discipline emerging in response to the replicability crisis. At the same time, replicability is typically treated with caution by philosophers of science. In this paper, we reassess the value of replicability from an epistemic perspective. We defend the orthodox view, according to which replications are always epistemically useful, against the more prudent view that claims that it (...) is useful in very limited circumstances. Additionally, we argue that we can learn more about the original experiment and the limits of the discovered effect from replications at different levels. We hold that replicability is a crucial feature of experimental results and scientists should continue to strive to secure it. (shrink)

The study sought to investigate the effects of using cooperative learning on female teacher trainees of the Colleges of Education in learning some selected topics in Integrated Science. The investigation also sought to determine whether the Cooperative Learning Approach enhances the attitude and motivation of the trainees towards learning of Integrated Science. The study was carried out at the St. Monica’s College of Education in the Mampong Municipality of the Ashanti Region. In all, 80 teacher trainees (...) consisting of 40 each from control and experimental groups were purposively sampled to participate in the study. The teacher trainees in the experimental group were exposed to the Cooperative Learning Approach and the trainees in the control group were lectured during the period of the study. The results of the study showed that the cooperative learning strategy was very relevant and beneficial in helping the teacher trainees of the St. Monica’s College of Education to improve on their performance in, and attitudes towards, the teaching and learning of Integrated Science. It was therefore recommended among other things that the science teachers should endeavour to integrate cooperative learning into their routine methods of instruction in the teaching and learning of Integrated Science. (shrink)

The Pomodoro technique is a timed-based strategy used in fighting procrastination and found to increase academic performance. However, its effect on academic learning in a synchronous remote learning modality has yet to be investigated. The study used a mixed triangulation semiexperimental design using a whole sample (N=46), following all ethical equivalence procedures. The genetics concept mastery of the students was tested using a researcher-made test. ANCOVA results revealed that students taught using Pomodoro yielded significantly better concept mastery in (...) genetics than the lecture method. This study contributes to the evaluation of one science teaching strategy compatible with remote learning modality. (shrink)

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

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

The study aimed to determine if differentiated instruction effectively addresses learning gaps in mathematics. In particular, it explored how it can improve the student’s learning gaps concerning mathematical performance and confidence. The study employed a quasi-experimental design with 30 purposively-selected Grade 10 participants divided into differentiated (n = 15) and control groups (n = 15), ensuring the utmost ethical measures. The mean and standard deviation were used to describe the participants’ performance and confidence. Independent samples t-tests were (...) used to determine the significant differences in the performance and confidence between the two groups. In contrast, dependent samples t-tests were used to determine the significant differences in each group’s pre and posttest performance and confidence. Findings bared that the differentiated instruction successfully addressed students’ performance in mathematics even in a short period. It also increased the participants’ confidence when answering fundamental problems. Continuing differentiated instruction activities are recommended since it benefits students who struggle in mathematics, particularly in answering fundamental operations. Differentiated teaching activities in mathematics can boost academic achievement and engagement and prepare students for future success while fostering a positive and inclusive classroom culture that values individual learning needs and preferences. (shrink)

The present quasi-experimental study was undertaken to study students’ perceptions of the advantages and disadvantages of the LMS and the ‘real’ classroom. The data was collected using the online survey method (Google Form), which included questions related to students' perceptions of the effectiveness of both modes in enhancing knowledge, critical skills, and social competence. The study found that although the ratio of students who preferred ‘real’ classroom learning to learning through the LMS was higher, many students were (...) also comfortable with online learning. The present study concludes that a blended mode of learning, i.e., using digital learning tools with a more traditional classroom, can be a better option to meet the needs of both kinds of learners. (shrink)

Contemporary philosophers nearly unanimously endorse knowledge reliabilism, the view that knowledge must be reliably produced. Leading reliabilists have suggested that reliabilism draws support from patterns in ordinary judgments and intuitions about knowledge, luck, reliability, and counterfactuals. That is, they have suggested a proto-reliabilist hypothesis about “commonsense” or “folk” epistemology. This paper reports nine experimental studies (N = 1262) that test the proto-reliabilist hypothesis by testing four of its principal implications. The main findings are that (a) commonsense fully embraces the (...) possibility of unreliable knowledge, (b) knowledge judgments are surprisingly insensitive to information about reliability, (c) “anti-luck” intuitions about knowledge have nothing to do with reliability specifically, and (d) reliabilists have mischaracterized the intuitive counterfactual properties of knowledge and their relation to reliability. When combined with the weakness of existing arguments for reliabilism and the recent emergence of well supported alternative views that predict the widespread existence of unreliable knowledge, the present findings are the final exhibit in a conclusive case for abandoning reliabilism in epistemology. I introduce an alternative theory of knowledge, abilism, which out-performs reliabilism and well explains all the available evidence. (shrink)

From the mid-1960s until the late 1980s, the well-known general philosophies of science of the time were applied to economics. The result was disappointing: none seemed to fit. This paper argues that this is due to a special feature of economics: it possesses ‘orientational paradigms’ in high number. Orientational paradigms are similar to Kuhn’s paradigms in that they are shared across scientific communities, but dissimilar to Kuhn’s paradigms in that they are not generally accepted as valid guidelines for further research. (...) As will be shown by several examples, orientational paradigms provide economics with common points of reference that support its epistemic coherence and make scientific discourse more easily possible across school boundaries. With the help of systematicity theory, a newer general philosophy of science, one can further elucidate the role of orientational paradigms with regard to scientific progress. (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)

By leveraging convolutional neural networks (CNNs), the model identifies various plant diseases with high accuracy. The experimental setup includes a dataset consisting of healthy and diseased leaf images of different plant species. The dataset is preprocessed to remove noise and augmented to address the issue of class imbalance. The CNN model is then trained, validated, and tested on this dataset. The results indicate that the deep learning model achieves a classification accuracy of over 95% for most plant diseases. (...) Additionally, the system is designed to provide real-time feedback to farmers, helping them take immediate corrective action. This automated approach eliminates the need for expert human intervention and can be deployed on mobile devices for ease of use in rural areas. The potential future applications of this system include integration with precision agriculture techniques and expansion to a wider range of crops. (shrink)

It appears that consciousness science is progressing soundly, in particular in its search for the neural correlates of consciousness. There are two main approaches to this search, one is content-based (focusing on the contrast between conscious perception of, e.g., faces vs. houses), the other is state-based (focusing on overall conscious states, e.g., the contrast between dreamless sleep vs. the awake state). Methodological and conceptual considerations of a number of concrete studies show that both approaches are problematic: the content-based approach seems (...) to set aside crucial aspects of consciousness; and the state-based approach seems over-inclusive in a way that is hard to rectify without losing sight of the crucial conscious-unconscious contrast. Consequently, the search for the neural correlates of consciousness is in need of new experimental paradigms. (shrink)

This article provides the foundation for a new predictive theory of animal learning that is based upon a simple logical model. The knowledge of experimental subjects at a given time is described using logical equations. These logical equations are then used to predict a subject’s response when presented with a known or a previously unknown situation. This new theory suc- cessfully anticipates phenomena that existing theories predict, as well as phenomena that they cannot. It provides a theoretical account (...) for phenomena that are beyond the domain of existing models, such as extinction and the detection of novelty, from which “external inhibition” can be explained. Examples of the methods applied to make predictions are given using previously published results. The present theory proposes a new way to envision the minimal functions of the nervous system, and provides possible new insights into the way that brains ultimately create and use knowledge about the world. (shrink)

Abstract: Lotteries have long been a source of fascination and intrigue, offering the tantalizing prospect of unexpected fortunes. In this research paper, we delve into the world of lottery predictions, employing cutting-edge AI techniques to unlock the secrets of lottery outcomes. Our dataset, obtained from Kaggle, comprises historical lottery draws, and our goal is to develop predictive models that can anticipate future winning numbers. This study explores the use of deep learning and time series analysis to achieve this elusive (...) feat. Through rigorous experimentation and data-driven approaches, we seek to determine the viability of AI in the realm of lottery predictions. Our findings reveal both the promise and limitations of AI in this context, shedding light on the complexities of lottery data and the potential need for quantum computing as a last resort. (shrink)

The researcher was prompted to conduct this study to give intervention of the alarming situation which there is a low performance in solving problems related to geometry in Grade IV Mathematics. This study was about on how to enhance the mathematical competencies of the grade IV pupils using a downloaded worksheets as a learning activity. This study focused in giving remediation applying the intervention materials. These resources give several approaches to attain mastery using distinct drill cards. The investigation was (...) carried out utilizing quasi-experimental design. During administering the pre-test and post-test, the researcher used the weighted mean and t-test to determine the mean percentage scores of the respondents. The respondents were 56 fourth grade learners enrolled in Marangog Elementary School and Tagnate Elementary School in Hilongos East District for the school year 2019 – 2020. At the end of the study, it was found out the use of downloaded math worksheets were found effective means of improving the mastery level. In addition, based on the results gathered, the downloaded math worksheets which were used in the drills or practice greatly contributed to the elimination of non-numerates, and give significantly increasing the number of pupils who mastered the competencies related to geometry. As a result, a proposed innovative teaching strategy is recommended. -/- . (shrink)

Several important philosophical problems (including the problems of perception, free will, and scepticism) arise from antinomies that are developed through philosophical paradoxes. The critical strand of ordinary language philosophy (OLP), as practiced by J.L. Austin, provides an approach to such ‘antinomic problems’ that proceeds from an examination of ‘ordinary language’ (how people ordinarily talk about the phenomenon of interest) and ‘common sense’ (what they commonly think about it), and deploys findings to show that the problems at issue are artefacts of (...) fallacious reasoning. The approach is capable, and in need of, empirical development. Proceeding from a case-study on Austin’s paradigmatic treatment of the problem of perception, this paper identifies the key empirical assumptions informing the approach, assesses them in the light of empirical findings about default inferences, contextualisation failures, and belief fragmentation, and explores how these findings can be deployed to address the problem of perception. This facilitates a novel resolution of the problem of perception. Proceeding from this paradigm, the paper proposes ‘experimental critical OLP’ as a new research program in experimental philosophy that avoids apparent non-sequiturs of OLP, extends and transforms experimental philosophy’s ‘sources program’, and provides a promising new strategy for deploying empirical findings about how people ordinarily talk and think about phenomena, to address longstanding philosophical problems. (shrink)

Due to the emergence of ICT in ELT sector, seasoned English teachers find it resistant to such a shift despite having a positive attitude towards its use. This quasi-experimental study aimed to examine the extent to which seasoned English language teachers developed their ICT skills through a Service-Learning Activity (SLA). Using a one-group pre- and post-test design, this study collected the data through a modified Needs Assessment Survey (NAS) distributed to fourteen purposively selected participants. It was administered to (...) examine what professional ICT development would greatly benefit them. The data were analyzed using descriptive statistics and themes according to the Service-Learning Activity (SLA) topics. A Post Evaluation Survey (PES) was administered, and its result was compared to the initial test. The results showed that the seasoned teachers gained significant learning gains in terms of (1) sharing of knowledge from other teachers; (2) being encouraged to use ICT tools; (3) training opportunities; (4) working with other colleagues; and 5) attending professional workshops which include SLA. However, this study unveiled that the English teachers had no significant difference in perceptions regarding the roles of computers in teaching before and after the intervention. Limitations and recommendations for future studies were discussed. (shrink)

By leveraging convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers, this research presents an intelligent malware detection framework capable of identifying both known and zero-day threats. The methodology involves feature extraction from static, dynamic, and hybrid malware datasets, followed by training DL models to classify malicious and benign software with high precision. A robust experimental setup evaluates the framework using benchmark malware datasets, yielding a 96% detection accuracy and demonstrating resilience against adversarial attacks. Real-time analysis capabilities further (...) improve response times, reducing the risk of potential damage. The study also incorporates visualization tools to provide interpretable insights into model decisions, enhancing transparency for cybersecurity practitioners. Concluding with a discussion on the challenges and future prospects, this research paves the way for scalable, AI-driven solutions to combat evolving cyber threats. (shrink)

Introduction: Traditionally, empathy has been studied from two main perspectives: the theory-theory approach and the simulation theory approach. These theories claim that social emotions are fundamentally constituted by mind states in the brain. In contrast, classical phenomenology and recent research based on enactive theories consider empathy as the basic process of contacting others’ emotional experiences through direct bodily perception and sensation. Objective: This study aims to enrich knowledge of the empathic experience of pain by using an experimental phenomenological method. (...) Method: Implementing an experimental paradigm used in affective neuroscience, we exposed 28 healthy adults to a video of sportspersons suffering physical accidents while practicing extreme sports. Immediately after watching the video, each participant underwent a phenomenological interview to gather data on embodied, multi-layered dimensions (bodily sensations, emotions, and motivations) and temporal aspects of empathic experience. We also performed quantitative analyses of the phenomenological categories. Results: Experiential access to the other person’s painful experience involves four main-themes. Bodily resonance: participants felt a multiplicity of bodily, affective, and kinesthetic sensations. Attentional focus: some participants centered their attention more on their own personal discomfort and sensations of rejection, while others on the pain and suffering experienced by the sportspersons. Kinesthetic motivation: some participants experienced the feeling in their bodies to avoid or escape from watching the video, while others experienced the need to help the sportspersons avoid suffering any injury while practicing extreme sports. Temporality of experience: participants witnessed temporal fluctuations in their experiences, bringing intensity changes in their bodily resonance, attentional focus, and kinesthetic motivation. Finally, two experiential structures were found: one structure is self-centered empathic experience, characterized by bodily resonance, attentional focus centered on the participant’s own experience of seeing the sportsperson suffering, and self-protective kinesthetic motivation; the other structure is other-centered empathic experience, characterized by bodily resonance, attentional focus centered on the sportsperson, and prosocial kinesthetic motivation to help them. Discussion: We show how phenomenological data may contribute to comprehending empathy for pain in social neuroscience. In addition, we address the phenomenological aspect of the enactive approach to the three dimensions of embodiment of human consciousness, especially the intersubjective dimension. Also, based on our results, we suggest an extension of the enactive theory for non-interactive social experience. (shrink)

Collaborative learning emphasizes student-to-student interaction and the instructor’s role as a facilitator. Collaborative Online International Learning (COIL) was founded in 2005 by the State University of New York (SUNY) to help schools adapt their single classroom courses to an online, collaborative format and establish strong collaborations with professors with whom they would join classes and co-teach using SUNY COIL conferences and website, as well as pre-established partnerships between the institutions. However, as the globe becomes increasingly interconnected, educational challenges (...) aimed at cultivating intercultural competency become more important (Ceo-DiFrancesco & Bender-Slack, 2016). That is why this study aimed to (1) understand the lived experience of students who went under the COIL program in relation to SDG 12, (2) review the new knowledge students obtained when they took part in the COIL program in relation to SDG 12, and (3) discover the challenges students encountered while participating in the COIL program in relation to SDG 12. The researcher surveyed Filipino and Japanese students who participated in the COIL program concerning SDG12 from St. Patrick School of Quezon City, Kwansei Gakuin University, and Meiwa Senior High School. The study employed qualitative phenomenological research, and pertinent data were obtained through an open-ended survey questionnaire. The study was analyzed using Colaizzi’s descriptive phenomenological method. The results showed that the lived experiences of students who went under the COIL program in relation to SD12 have something to do with all their learnings and enjoyable experiences, intercultural and global interactions, and environmental discussions and action plans related to SDG 12. Moreover, students learned and understood better the negative impact of waste on the environment, environmental awareness and practices, the culture and norms in the Philippines and Japan, and the importance and benefits of collaboration. Lastly, the study also revealed the different challenges students encounter while participating in the COIL program in relation to SDG 12, such as cultural differences, language barriers, technical difficulties, and difficulties in experimentation. Thus, it was recommended to learn to adapt to everyone and adjust according to countries’ different cultures, practice and be proficient with the English language, have backup devices and platforms to use to ease technological problems, and improve implementations of experiments. (shrink)

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