Can fictional literature help us lead better lives? This essay argues that some works of literature can help us both change our personal narratives and develop new narratives that will guide our actions, enabling us to better achieve our goals. Works of literature can lead us to consider the hypothesis that we might beneficially change our future-oriented, personal narratives. As a case study, this essay considers Ben Lerner’s novel, 10:04, which focuses on humans’ ability to develop new narratives, and which (...) articulates a narrative that takes into account both everyday life and large-scale issues like the global, environmental crisis. (shrink)

This article considers the theme of discernment in the tradition of Ignatian spirituality emanating from the Spiritual Exercises of St Ignatius of Loyola, the founder of the Society of Jesus. After a brief introduction which addresses the central problematic of bad influences that manifest themselves as good, the article turns to the life and work of two Jesuits, the 16th C English missionary to India, Thomas Stephens and the 20th C French historian and cultural critic, Michel de Certeau. Both kept (...) up a constant dialogue with local culture in which they sought authenticity in their response to ‘events’, whether a hideous massacre which shaped the pastoral commitment and writing of Stephens in the south of the Portuguese enclave of Goa or the 1968 student-led protests in Paris that so much affected the thinking of de Certeau. Very different in terms of personal background and contemporary experience, they both share in a tradition of discernment as a virtuous response to what both would understand as the ‘wisdom of the Spirit’ revealed in their personal interactions with ‘the other’. (shrink)

Personalized medicine recommendation systems are increasing in popularity to predict diseases and provide customized health advice on diet, workout plans and medication. The medical suggestion system can be valuable when pandemics, floods, or cyclones hit. In the age of Machine Learning (ML), recommender systems give more accurate, precise, and reliable clinical predictions while using less resources. Through the use of machine learning algorithms like Decision Tree, Random Forest, K-Means Clustering, and Hierarchical Clustering, these systems analyze patient inputs (...) such as lifestyle data, symptoms, and health metrics for accurate predictions of diseases and holistic recommendations on health. This inclusive process ensures each person receives tailored support to enhance the entire management of their health. The system's ability to suggest accurate diets, proper workouts, and appropriate drugs depending on the condition of the user significantly enhances its contribution toward more healthy lifestyles. The variety of algorithms increases accuracy and reliability as well because each model contributes uniquely in analyzing various aspects of patient data. This study presents a framework that demonstrates the system's efficacy in providing personalized disease predictions and health recommendations, which can benefit the development of preventive care and improve treatment outcomes. (shrink)

Persons with aphasia suffer from a loss of communication ability as a consequence of a brain injury. A small strand of research indicates effec- tiveness of dialogic interventions for communication development for persons with aphasia, but a vast amount of research studies shows its effectiveness for other target groups. In this paper, we describe the main parts of the hitherto technological development of an application named Dialogica that is (i) aimed at facilitating increased communicative participation in dialogic settings for persons (...) with aphasia and other communication disorders, (ii) based on comput- er game technology as well as on theory in dialogic education and argumenta- tion theory, and (iii) designed for mobile devices with larger screens. (shrink)

The purpose of this chapter is to outline some of the thinking behind new e-learning technology, including e-portfolios and personal learning environments. Part of this thinking is centered around the theory of connectivism, which asserts that knowledge - and therefore the learning of knowledge - is distributive, that is, not located in any given place (and therefore not 'transferred' or 'transacted' per se) but rather consists of the network of connections formed from experience and interactions with a (...) knowing community. And another part of this thinking is centered around the new, and the newly empowered, learner, the member of the net generation, who is thinking and interacting in new ways. These trends combine to form what is sometimes called 'e-learning 2.0' - an approach to learning that is based on conversation and interaction, on sharing, creation and participation, on learning not as a separate activity, but rather, as embedded in meaningful activities such as games or workflows. (shrink)

This paper explores the integration of multiple intelligences and artificial intelligence (AI) in language learning, focusing on its potential to enhance personalization and engagement. Drawing from existing research and studies conducted in various contexts, including the Philippines, this study aims to contribute to the understanding of the benefits, challenges, and effectiveness of this integration. The paper begins with an introduction that highlights the background and significance of integrating multiple intelligences and AI in language learning, identifying research gaps, objectives, (...) research questions, and the theoretical framework. A literature review provides an overview of multiple intelligences theory by Howard Gardner, the role of AI in language learning, and identifies gaps in the existing literature. The methodology section outlines the research design and approach, participant selection, data collection methods, validity and reliability measures, and ethical considerations. Findings and results are presented through the analysis of qualitative data, exploring emergent themes and patterns. The discussion section critically examines the identified research gaps, discusses the validity and reliability of the study, addresses the scope and limitations, and explores the implications of the findings for theory, practice, and future research. The conclusion summarizes the key findings and contributions of the study, reflects on the achievement of research objectives, offers recommendations for further research, and provides final remarks tying together the main points of the study. This paper contributes to the existing body of knowledge by providing insights into the integration of multiple intelligences and AI in language learning and its impact on personalization, engagement, and language learning outcomes. (shrink)

Underlying much current work in philosophy of imagination is the assumption that imagination is a skill. This assumption seems to entail not only that facility with imagining will vary from one person to another, but also that people can improve their own imaginative capacities and learn to be better imaginers. This paper takes up this issue. After showing why this is properly understood as a philosophical question, I discuss what it means to say that one imagining is better than another (...) and then discuss the kinds of imagination training and techniques that might be employed in an effort to get better at imagining. The discussion of these techniques draws insight from consideration of other skills-based activities, as well as from consideration of the creation of art and our engagement with literature and poetry. Over the course of this discussion, we also gain further insight into the nature of imagination. (shrink)

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

Recent psychological research shown that the places where we live are linked to our personality traits. Geographical aggregation of personalities has been observed in many individualistic nations; notably, the mountainousness is an essential component in understanding regional variances in personality. Could mountainousness therefore also explain the clustering of personality-types in collectivist countries like China? Using a nationwide survey (29,838 participants) in Mainland China, we investigated the relationship between the Big Five personality traits and mountainousness indicators at the provincial level. Multilevel (...) modelling showed significant negative associations between the elevation coefficient of variation (Elevation CV) and the Big Five personality traits, whereas mean elevation (Elevation Mean) and the standard deviation in elevation (Elevation STD) were positively associated with human personalities. Subsequent machine learning analyses showed that, for example, Elevation Mean outperformed other mountainousness indicators regarding correlations with neuroticism, while Elevation CV performed best relative to openness models. Our results mirror some previous findings, such as the positive association between openness and Elevation STD, while also revealing cultural differences, such as the social desirability of people living in China’s mountainous areas. (shrink)

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 (...) they are presumptuous. After elaborating this moral concern, I explore the possibility that carefully procuring the training data for image recognition systems could ensure that the systems avoid the problem. The lesson of this paper extends beyond just the particular case of image recognition systems and the challenge of responsibly identifying a person’s intentions. Reflection on this particular case demonstrates the importance (as well as the difficulty) of evaluating machine learning systems and their training data from the standpoint of moral considerations that are not encompassed by ordinary assessments of predictive accuracy. (shrink)

This study aimed to explore the teachers' experiences in addressing the learning gaps during the resumption of in-person classes post-pandemic. Specifically, it sought to determine the learning recovery strategies implemented and the challenges encountered by the teachers. Six (6) teachers from DepEd Zamboanga City Division were involved in this study employing a qualitative-phenomenological research design. The participants were purposively selected based on the criteria defined in this paper. The data were collected through in-depth interviews with semi-structured interview questions. (...) The findings revealed that the teachers employed a multifaceted approach to bridge the learning gaps. These include conducting remedial reading and pull-out sessions, integrating basic reading activities in all subject areas, and using differentiated instructions and materials. However, teachers also encountered challenges related to the limited availability of resources, the need for professional development to address pedagogical changes, the lack of parental support, and absenteeism among learners. The research finding suggests intervention at the individual and system levels to mitigate the learning gaps. Policy recommendations include upskilling and plans of teachers, particularly in teaching beginning reading, increasing funding allocation for basic education resources, reviewing implementation of the learning recovery plans, and improving collaboration with parents and community stakeholders to support learners’ education. (shrink)

Learning from Arguments advances accessible versions of key philosophical arguments, in a form that students can emulate in their own writing, and with the primary aim of cultivating an understanding of the dynamics of philosophical argumentation. -/- The book contains ten core chapters, covering the problem of evil, Pascal’s wager, personal identity, the irrationality of fearing death, free will and determinism, Cartesian skepticism, the problem of induction, the problem of political authority, the violinist argument, the future-like-ours argument, the ethics (...) of eating meat, utilitarianism (both act and rule), and the trolley problem. Additionally, there is an introductory chapter explaining what arguments are and surveying some common argumentative strategies, an appendix on logic explaining the mechanics and varieties of valid arguments, and an appendix providing detailed advice for writing philosophy papers. -/- Each of the ten core chapters offers a sustained argument for some controversial thesis, specifically written for an audience of beginners. The aim is to introduce newcomers to the dynamics of philosophical argumentation, using some of the arguments standardly covered in an introductory philosophy course, but without the additional hurdles one encounters when reading the primary sources of the arguments: challenging writing, specialized jargon, and references to unfamiliar books, philosophers, or schools of thought. (shrink)

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

Effective ethics teaching and training must cultivate both the critical thinking skills and the character traits needed to deliberate effectively about ethical issues in personal and professional life. After highlighting some cognitive and motivational obstacles that stand in the way of this task, the article draws on educational research and the author's experience to demonstrate how cooperative learning techniques can be used to overcome them.

The paper presents data collected using measures of personality, Islamic religiosity, psychological well-being, unethical behavior, and dark triad traits. The sample consists 277 Bruneian Malay Muslim university students. The participants were sampled at a public university in Brunei. Through cooperation with faculty members, a link to the online questionnaire was posted on the learning management system platform. The targeted population was informed they were invited to participate voluntarily, and all information would be confidential. Completed questionnaires were submitted by 171 (...) females and 106 males. The age ranged between 18 and 30 years old (M = 19.62, SD = 1.65). This data article presented the demographic characteristics of participants, followed by descriptive statistics of the measures concerning primarily personality and Islamic religiosity, followed by brief measures of psychological nature specifically psychological well-being, unethical behavior, and dark triad traits. Reliability and correlation details of measures were also provided. The comprehensive data, as detailed out in this paper, has various potential for further research and analyses by researchers who are interested in the measures and data presented. (shrink)

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

Emotion detection and management have emerged as pivotal areas in humancomputer interaction, offering potential applications in healthcare, entertainment, and customer service. This study explores the use of deep learning (DL) models to enhance emotion recognition accuracy and enable effective emotion regulation mechanisms. By leveraging large datasets of facial expressions, voice tones, and physiological signals, we train deep neural networks to recognize a wide array of emotions with high precision. The proposed system integrates emotion recognition with adaptive management strategies that (...) provide personalized feedback and interventions based on detected emotional states. Our approach surpasses traditional machine learning methods, demonstrating superior performance in real-time applications. (shrink)

Except in extraordinary circumstances, patients' clinical care should reflect their preferences. Incapacitated patients cannot report their preferences. This is a problem. Extant solutions to the problem are inadequate: surrogates are unreliable, and advance directives are uncommon. In response, some authors have suggested developing algorithmic "patient preference predictors" (PPPs) to inform care for incapacitated patients. In a recent paper, Earp et al. propose a new twist on PPPs. Earp et al. suggest we personalize PPPs using modern machine learning (ML) techniques. (...) In this paper, I argue that, contrary to Earp et al.'s claim, personalized patient preference predictors are neither technically feasible nor ethically desirable. (shrink)

There is a paucity of research on how psychopathy relates to decision-making. In this study, we assessed the relationship between affective decision-making and psychopathic personality. A sample of prisoners (n D 49) was characterized in terms of psychopathic traits using the Psychopathic Checklist: Screening Version (PCL:SV). Decision-making was assessed using the Iowa Gambling Task (IGT). Higher levels of psychopathy related to more advantageous choices (p D .003). Also counter-intuitively, higher levels of antisocial traits (facet 4) predicted advantageous choices during the (...) learning phase of the task (p D .004). Our findings suggest that some psychopathic facets may be more relevant to decisionmaking under risk, and highlight the importance of further investigations considering facet and trait-level relationships with decision-making. (shrink)

This article identifies and examines a tension in mental health researchers’ growing enthusiasm for the use of computational tools powered by advances in artificial intelligence and machine learning (AI/ML). Although there is increasing recognition of the value of participatory methods in science generally and in mental health research specifically, many AI/ML approaches, fueled by an ever-growing number of sensors collecting multimodal data, risk further distancing participants from research processes and rendering them as mere vectors or collections of data points. (...) The imperatives of the “participatory turn” in mental health research may be at odds with the (often unquestioned) assumptions and data collection methods of AI/ML approaches. This article aims to show why this is a problem and how it might be addressed. (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)

The development of conversational artificial intelligence (AI) has brought about new opportunities for improving the learning experience in education. ChatGPT, a large language model trained on a vast corpus of text, has the potential to revolutionize education by enhancing learning through personalized and interactive conversations. This paper explores the benefits of integrating ChatGPT in education in Thailand. The research strategy employed in this study was qualitative, utilizing in-depth interviews with eight key informants who were selected using purposive (...) sampling. The collected data was analyzed using content analysis and the software NVivo. The study's results indicated that ChatGPT can provide personalized learning experiences by adapting to individual student needs and preferences. Its ability to understand natural language and context can also facilitate more meaningful interactions between students and the system. Additionally, ChatGPT can assist with administrative tasks such as grading and feedback, allowing educators to focus on more personalized and meaningful interactions with students. Furthermore, ChatGPT can serve as a valuable tool for remote learning, providing students with the ability to access educational resources and support outside of traditional classroom settings. The paper also discusses potential ethical considerations in utilizing AI in education, such as data privacy and bias. Overall, this paper argues that the integration of ChatGPT in education has the potential to enhance the learning experience for students by providing personalized, interactive, and efficient support. (shrink)

This study aimed to unveil the lived experiences of teachers implementing personalized reading strategy. A qualitative design was utilized in this study to fourteen elementary teachers from Nuling Integrated School, Sultan Kudarat. These teachers were selected via purposive sampling who were subjected to Focus Group Discussion. A semi-structured questionnaire was validated and utilized in this study. The interview responses were audio-taped recorded with the consent from the participants. From the generated results, there were 6 emerging themes that described teachers’ (...) challenges in implementing personalized teaching strategy namely, patience in the development of activities, time constraint, alignment to learners’ needs, types of materials and activities, progress monitoring result, and parent-pupil convergence. Meanwhile, teachers coping mechanisms in handling struggling readers were focused on the provision of varied strategies, knowing students learning needs, utilization of Marungko approach, provision of instructional materials, and use ICT and videos. Furthermore, the insights acquired by teachers were diagnosing learners’ needs and interests, preparation consumes more time, and modification of learning activities. (shrink)

Autism is a psychopathological condition around which there is still much prejudice and stigma. The discrepancy between third-person and first-person accounts of autistic behavior creates a chasm between autistic and neurotypical (non-autistic) people. Epistemic injustice suffered by these individuals is great, and a fruitful strategy out of this predicament is much needed. I will propose that through the appropriation and implementation of methods and concepts from phenomenology and ecological-enactive cognitive science, we can acquire powerful tools to work towards greater epistemic (...) justice for autistic individuals. I will use the resources found in the skilled intentionality framework, integrated with various phenomenological theories. From these approaches, we can view autistic impairments and disability relationally and how epistemic enablement and disablement form. Phenomenology and its methods help us learn more about the perceptual and social experiences of autistic individuals. The voices of the autistics themselves will be of the greatest importance here. I will show that, through restructuring our landscape of affordances and with a greater phenomenological understanding of the autistic inner world, we can devise new strategies that afford greater epistemic enablement and epistemic justice. (shrink)

Information and communication technologies (ICTs) are building a new habitat (infosphere) in which future generations, living in advanced information societies, will spend an increasing amount of time. This paper introduces a series of articles that explore what constitutes a personal identity online (PIO) and how, as well as to what extent, individuals can learn to create, manage and perceive their PIOs in order to facilitate a healthy and rewarding online experience (onlife).

Advancements in machine learning have fuelled the popularity of using AI decision algorithms in procedures such as bail hearings, medical diagnoses and recruitment. Academic articles, policy texts, and popularizing books alike warn that such algorithms tend to be opaque: they do not provide explanations for their outcomes. Building on a causal account of transparency and opacity as well as recent work on the value of causal explanation, I formulate a moral concern for opaque algorithms that is yet to receive (...) a systematic treatment in the literature: when such algorithms are used in life-changing decisions, they can obstruct us from effectively shaping our lives according to our goals and preferences, thus undermining our autonomy. I argue that this concern deserves closer attention as it furnishes the call for transparency in algorithmic decision-making with both new tools and new challenges. (shrink)

Modular learning was used to assist elementary learners in continuing their education during the pandemic. This modular learning posed academic challenges. This phenomenological study delved into the academic challenges of modular learning of public-school elementary school learners. Validated In-depth interview protocol (IDI) was used to collect the data from ten (10) Grade six learners. Findings revealed that these academic challenges include unfavorable learning environments, reading comprehension issues, lack of motivation, and poor quality of printed learning (...) modules that affect the learners ability to comprehend and finish the module effectively. Consequently, modular learning allows learners to take responsibility for their learning by utilizing the available answers key, optimizing internet usage, scheduling time properly, and guessing answers. Considerably, the learners used face-to-face conversations, personal messages, and phone calls to communicate their educational queries. Moreover, the structure of self-learning modules facilitates independent study and complicates learners understanding. It is recommended that there is a need to enhance policies for improving module quality, allocate sufficient funds to improve the printed module quality, conduct relevant teacher training and workshops for developing quality printed modules, and sustain the home visitation program to monitor students modular learning progress. (shrink)

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

In this paper, we bring together research on complex problem solving with that on motivational psychology about goal setting. Complex problems require motivational effort because of their inherent difficulties. Goal Setting Theory has shown with simple tasks that high, specific performance goals lead to better performance outcome than do-your-best goals. However, in complex tasks, learning goals have proven more effective than performance goals. Based on the Zurich Resource Model, so-called motto-goals should activate a person’s resources through positive affect. It (...) was found that motto-goals are effective with unpleasant duties. Therefore, we tested the hypothesis that motto-goals outperform learning and performance goals in the case of complex problems. A total of N = 123 subject participated in the experiment. In dependence of their goal condition, subjects developed a personal motto, learning, or performance goal. This goal was adapted for the computer-simulated complex scenario Tailorshop, where subjects worked as managers in a small fictional company. Other than expected, there was no main effect of goal condition for the management performance. An unexpected gender effect revealed better performance for men than women, pointing to a potential stereotype threat. As hypothesized, motto goals led to higher positive and lower negative affect than the other two goal types. Even though positive affect decreased and negative affect increased in all three groups during Tailorshop completion, participants with motto goals reported the lowest rates of negative affect. Exploratory analyses investigated the role of affect in complex problem solving via mediational analyses and the influence of goal type on perceived goal attainment. (shrink)

The study focused on exploring and understanding the challenges junior high school teachers in the Division of Rizal faced during the full implementation of in-person classes and identifying the coping mechanisms they employed to adapt to this new educational landscape. Forty participants were purposefully selected from various public secondary school clusters in the division of Rizal. A qualitative phenomenological design was employed, and the information collected through Google Forms was imported into Microsoft Excel and Microsoft Word. After importing the data, (...) it was coded through and looked for patterns in the meaning of the data to find themes. It was analyzed using QDA Miner Lite to make a user-friendly, accessible, and simple-to-use software for qualitative data analysis. QDA Miner Lite allowed for a quicker and more accurate breakdown of documents, enabling organization, coding, annotation, retrieval, and analysis of document and image collections. The study revealed these categories and themes: Experiences in Teaching in In-Person Classes. Teachers' experiences during the full implementation of in-person classes were categorized into five themes: Comparison to distance learning modalities, Student- centered Focus, Positive emotional experiences, Challenging Emotional experiences, and Adaptations. Comparison of Teaching Experiences. The comparison and contrast of teaching experiences between distance learning and in-person learning revealed six themes: Assessment and Progress Monitoring, Stress and Fulfillment, Effectiveness and Limitations, Technology and Connectivity, preparation and Communication, and Learning Environment and Engagement. Identified Challenges in In- Person Classes. The study identified nine challenges faced by teachers and schools during the full implementation of in-person classes. These challenges encompassed issues related to Classroom Infrastructure and Facilities, Learning Gaps and Academic Challenges, Behavioral Issues and Student Discipline, Safety, and Security, Teacher Workload and Teaching Loads, Student Engagement and Parent Involvement, Gender-Responsive Policy and Early Pregnancy, Professional Development, and Learning Materials. Coping Mechanisms for Challenges. The coping mechanisms employed by teachers in response to the identified challenges included Collaborative Support and Professional Development, Resilience, and Positivity, Student-Centered Strategies Interventions, Adaptability, and Flexibility, Emphasizing Physical and Mental Health, Effective Communication Involvement of Stakeholders, Innovative Teaching Approaches, and Reminding Purpose and Passion. The study provides valuable insights into teachers' experiences and challenges in fully implementing in-person classes. The identified coping mechanisms offer potential strategies to support educators in navigating the complexities of teaching in this environment. Educational institutions and policymakers can use these insights to develop supportive and enriching learning environments for teachers and students. By implementing targeted interventions and policies, stakeholders can optimize the teaching and learning experiences in the in-person learning setting and foster a positive and conducive educational environment. (shrink)

The rapid adoption of telemedicine has transformed healthcare delivery, especially during the COVID-19 pandemic. This digital shift has enabled medical professionals to offer consultations and manage patients remotely, ensuring continuity of care while reducing exposure risks. However, the integration of telemedicine has presented both opportunities and challenges for doctors, particularly in terms of their work-life balance. This paper explores the digital adaptation of doctors in public and private hospitals concerning telemedicine practices and its impact on their work-life harmony. The study (...) highlights the advantages telemedicine offers, such as increased flexibility, reduced commuting time, and better time management. It also examines the challenges doctors face, including the demands of always being digitally accessible, the learning curve of new technologies, and the difficulty in maintaining boundaries between personal and professional life. Using both quantitative and qualitative data, this research compares the telemedicine adaptation experiences of doctors in public versus private hospitals, considering factors such as hospital infrastructure, support systems, and patient load. (shrink)

This chapter explores the personal and professional obstacles faced by Humanities and Social Science scholars contemplating pre-publication of their scholarly work in an on-line network. Borrowing a theoretical framework from the radical educational theorist Ivan Illich, it also develops the idea that pre-publication networks offer higher education a bottom-up, decentralized alternative to business-modeled e-learning. If learners would only embrace this more anarchical medium, appreciating writing for pre-publication as a process of open-ended discovery rather than product delivery, then the prospect (...) of deinstitutionalizing e-learning could become an exciting new reality. The chapter’s methodology is a combination of normative-theoretical analysis and small sample (n=2) case study based on the author’s personal and professional experiences. While the generalizability (or external validity) of the conclusions is limited, the author hopes to motivate further inquiry into the connection between on-line pre-publication and e-learning. (shrink)

In classroom sessions, various student-centered learning approaches, such as collaborative and problem-based learning, are used. Today, incorporating Information and Communication Technologies (ICT) into nursing education promotes self-directed and personalized learning among students.

Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with a (...) heart disease or not using the medical features of the person. We used many different algorithms of machine learning such as Gaussian Mixture, Nearest Centroid, MultinomialNB, Logistic RegressionCV, Linear SVC, Linear Discriminant Analysis, SGD Classifier, Extra Tree Classifier, Calibrated ClassifierCV, Quadratic Discriminant Analysis, GaussianNB, Random Forest Classifier, ComplementNB, MLP Classifier, BernoulliNB, Bagging Classifier, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Gradient Boosting Classifier, Decision Tree Classifier, and Deep Learning to predict and classify the patient with heart disease. A quite helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of heart diseases in any person. The strength of the proposed model was very satisfying and was able to predict evidence of having a heart disease in a particular person by using Deep Learning and Random Forest Classifier which showed a good accuracy in comparison to the other used classifiers. The proposed heart disease prediction model will enhances medical care and reduces the cost. This study gives us significant knowledge that can help us predict the person with heart disease. The dataset was collected from Kaggle depository and the model is implemented using python. (shrink)

Although current educational priorities tend to avoid strong moral positions, one of the world's most venerable yet persistently influential moral traditions not only lays out a number of major moral principles but also incorporates them into its pedagogy. Confucius teaches us about the importance of seeking knowledge, learning how to learn, applying ancient wisdom to contemporary situations, valuing virtue over material gain, following the Golden Rule, and living by our principles. He also has ways of assessing his own students' (...) progress in these matters. Confucius' pedagogy is an interesting model to consider and contrast with contemporary models. This chapter introduces these principles and assessments from the Analects and draws out some comparisons to and contrasts with two alternative theories in western moral thought, Augustine and John Dewey. -/- The accepted version of the paper is included here. Pagination does not match the published version. (shrink)

Due to the COVID-19 Pandemic, several changes have been forcibly made and observed in various fields and areas of society, one of which include the field of education; the foundation of the formation of intellect and knowledge. After two years of studying indoors and private educational institutions holding virtual classes, the time has finally come for students to be re- adjusted once more to the blended mode of learning; a combination of virtual and in-person classes. Thus, this study aimed (...) to investigate the development of students’ study habits and how these habits could potentially affect the students’ academic achievement or performance. The study utilized a descriptivecorrelational design to examine the impact of study habits to the academic performance of 137 senior high school students. The study made use of the Palsane and Sharma’s Study Habits Inventory, or also known as PSSHI, and using this instrument, the study has been able to procure sufficient results that will answer the present study’s problems. Using linear regression analysis, the present study found that there was a significance between the study habits and academic performance of the senior high school students, thus the study’s null hypothesis was eventually rejected. (shrink)

Personal recovery entails the idea of learning to live a good life in the face of mental illness. It takes place in a continuous dynamic between change and acceptance and involves the existential dimension in the broadest sense. With cognitive self-regulation and empowerment as central elements, however, current models of recovery mostly have an individual focus instead of a relational one. Furthermore, there seems to be an emphasis on the component of change. Little attention is payed to the role (...) and integration of dealing with loss in personal recovery. In this paper, the role of loss in mental illness will be elaborated from an existential perspective. This will be done by relating existential changes to possibly disruptive experiences of loss in wider experience. With the help of several perspectives on dealing with loss it will be argued this can be integrated in processes of recovery. Then, it will be elaborated how reexperiencing a state of being surrounded, or being included, being held is a necessary part of recovery. The result consists of a refinement of the view on personal recovery. The aim of this paper is therefore twofold: (1) to arrive at a better understanding of what existential loss and loss in wider experience in the context of psychopathology entails, and (2) to further develop perspectives on recovery in mental health care. (shrink)

The EdTech revolution in India has emerged as a transformative force, particularly during and after the COVID-19 pandemic, when traditional education systems faced unprecedented disruptions. While digital technologies have unlocked new opportunities for teaching and learning, they have also exposed systemic inequities and deepened the existing digital divide. This paper examines how EdTech is reshaping India's education landscape by addressing these challenges, with a focus on both the opportunities it presents and the barriers it creates. The shift to digital (...) learning platforms has empowered students with access to a broader array of learning resources, interactive content, and personalized learning paths. However, millions of students, particularly those from rural areas or lower-income families, struggle to access these resources due to a lack of digital infrastructure, reliable internet connectivity, and affordability of devices. Furthermore, the role of teachers has evolved, requiring new pedagogical approaches and technical skills to effectively harness these digital tools. (shrink)

Abstract: The incorporation of Artificial Intelligence (AI) into educational technology has dramatically transformed learning through Intelligent Tutoring Systems (ITS). These systems utilize AI to offer personalized, adaptive instruction tailored to each student's needs, thereby improving learning outcomes and engagement. This paper examines the development and impact of ITS, focusing on AI technologies such as machine learning, natural language processing, and adaptive algorithms that drive their functionality. Through various case studies and applications, it illustrates how ITS have (...) revolutionized traditional educational methods and addresses the challenges and limitations, including data privacy and system biases. The discussion also covers future directions in ITS development, highlighting emerging trends and potential advancements. The goal is to provide a thorough understanding of how ITS use AI to enhance educational experiences and suggest avenues for future research in this evolving field. (shrink)

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

Most of the existing studies on Bourdieu and the digital regards the social and class distinctions in the use of digital technologies, thus presupposing a certain transparency of technologies themselves. Our proposal is to refer to this attitude as “Bourdieu outside the digital.” Yet in this paper, another perspective called “Bourdieu inside the digital” is developed, which moves the focus on the effects of some emerging technologies on social distinctions and discrimination. The main hypothesis is that algorithms of machine (...) class='Hi'>learning are producers and reproducers of habitus. Although their results present a greater granularity with respect to the standard techniques of the past, these algorithms still reduce individuals to categories, general trends, classes, and behaviors. Such a reduction has flattening effects on the individuals’ self-understanding, especially in terms of identity and interaction with the social world. This is the phenomenon described in the article as the “personalization without personality,” whose consequences are both existential and social-political. This idea will be illustrated through qualitative and comparative analysis between the correspondence analysis and the multiple correspondence analysis used by Bourdieu in his works and some of those techniques that are performed today in big data analytics. (shrink)

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

The high prevalence of brain injury incidents in adolescence and adulthood demands effective models for re-learning lost cognitive abilities. Impairment in brain injury survivors’ higher-level cognitive functions is common and a negative predictor for long-term outcome. We conducted two small-scale interventions (N = 12; 33.33% female) with persons with acquired brain injuries in two municipalities in Sweden. Age ranged from 17 to 65 years (M = 51.17, SD = 14.53). The interventions were dialogic, inquiry-based, and inspired by the Philosophy (...) for Children Programme, a participatory thinking skills approach with documented higher-order cognitive outcomes, such as developed argumentation skills, in other target groups. Philosophical dialogues were conducted once a week in the two groups, totalling 12 dialogues per group. Group argumentation development was measured through compared scores from structured observations of filmed dialogues early and late in the intervention. Large positive changes in mean scores from early to late in the intervention, together with constantly high facilitator quality, suggest argumentation development in the sample due to the intervention. (shrink)

In this research, the author presents the lived experience of a graduate student and how she has overcome the feeling of isolation and challenges in distance learning. The participant of this qualitative phenomenological study is student from Visayas State University Open University (VSU-OU). This qualitative phenomenological study (Chambers, 2013) seeks to measure the in-depth experience of a distance learner from the southern Philippines and systematically analyze the culture of distance learning in order to understand the phenomenon of isolation (...) and be able to share in future studies. With in-depth personal interview, this study also allows readers to witness his personal stories which may validate others’ experiences who may not have an avenue to research about – hence phenomenological. It used the thematic qualitative approach in organizing the data presented in the study which involves analyzing themes and patterns she experienced in the phenomenon. It also mentions the respondent’s steps of overcoming isolation in distance education and avoiding quitting the study. And to do so, a network of connection among learners and university shall be present in order for a distance learner to succeed in the mode. (shrink)

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

Carl R. Rogers, the founder of client-centered therapy, contributed to the development of self-reliant learning in education. He applied such concepts of client-centered therapy as realness, prizing, acceptance, trust, and empathy to educational area, and called attention the importance of the authentic relationship between teacher and student with such books as Freedom to Learn, Becoming A Person, and A Way of Being. Besides, he also focused on teachers‟ attitudes in classrooms in his works. His views still continue to influence (...) the practices in both contemporary psychotherapy and education. The current study aims to introduce Rogers‟ views on teachers‟ attitudes facilitating students‟ learning, to discuss the views in the light of existentialist approaches and thus to make contributions to the development of educational environments. (shrink)

Healthcare professionals decide wisely about personalized medicine, treatment plans, and resource allocation by utilizing big data analytics and machine learning. To guarantee that algorithmic recommendations are impartial and fair, however, ethical issues relating to prejudice and data privacy must be taken into account. Big data analytics and machine learning have a great potential to disrupt healthcare, and as these technologies continue to evolve, new opportunities to reform healthcare and enhance patient outcomes may arise. In order to investigate (...) the patient’s outcomes with empirical evidence, this research was conducted using an online survey to incorporate healthcare professionals, patient’s reviews, and clinical staff. The data were analyzed using SmartPLS 4.0 to predict the structural model. The findings revealed a direct impact as positive influence of using machine learning on healthcare performance and patient outcomes through big data analytics. Moreover, it is evident that this can lead to personalized treatment plans, early interventions, and improved patient outcomes. Additionally, big data analytics can help healthcare providers optimize resource allocation, improve operational efficiency, and reduce costs. The impact of big data analytics on patient outcome and healthcare performance is expected to continue to grow, making it an important area for investment and research. (shrink)

Every person has his/her own unique signature that is used mainly for the purposes of personal identification and verification of important documents or legal transactions. There are two kinds of signature verification: static and dynamic. Static(off-line) verification is the process of verifying an electronic or document signature after it has been made, while dynamic(on-line) verification takes place as a person creates his/her signature on a digital tablet or a similar device. Offline signature verification is not efficient and slow for a (...) large number of documents. To overcome the drawbacks of offline signature verification, we have seen a growth in online biometric personal verification such as fingerprints, eye scan etc. In this paper we created CNN model using python for offline signature and after training and validating, the accuracy of testing was 99.70%. (shrink)