Challenging Students Moral Laziness: Authentic Education Based on Existentialist Philosophy

This study examined the construct of relational repair in marriage in the context of accommodation theory and presented an instrument designed to measure relationship repair. The instrument provided the following four factors derived from a sample of 239 married people: assurances, openness, time, and punishments. Based on the connection between accommodation behavior and commitment, the study also assessed the relationship between the repair factors and Johnson, Caughlin, and Huston's (1999) tripartite marital commitment construct. Factor analysis provided support for the tripartite construct of commitment. Regression analysis revealed significant associations between personal and structural commitment and all four relational repair factors. Moral commitment was significantly associated with all of the repair factors except punishments.

In the modern world, coaching activities are gaining increasing popularity. Coaching, at its fundamental core, is based on the philosophy of existentialism and is aimed at changing (improving) society’s life. This article provides a philosophical justification for coaching. The phenomenon of coaching is considered through the prism of the fundamental concepts of existentialist philosophy, namely: existential authenticity, existential choice, and existential anxiety, from the perspective of existentialist philosophers such as J-P. Sartre, S. Kier-kegaard, M. Heidegger, and M. Merleau-Ponty. The authors demonstrate the interconnection of existential philosophy, emotional intelligence, and their role in modern coaching. However, there are several challenges, including ethical issues in coaching, finding a balance between existential exploration and emotional intelli-gence, as well as adapting the approach to different coaching contexts. Coaches need through training to inte-grate effectively existential principles with emotional intelligence. Beyond coaching, this integration has broader philosophical and psychological implications, encouraging self-discovery and emotional regulation in personal development, leadership, and individual and societal well-being. As a result, ethical questions arise, as existential coaching prompts clients to reflect on the ethical aspects of their choices, emphasizing empathy and ethical decision-making. The synthesis of existential foundations and emotional intelligence in coaching offers a transformative path to self-awareness, contributing to more effective performance for both clients and coaches.

„Paprastas“ Vakarų visuomenės žmogus nepripažįsta savo mirties kaip neišvengiamos ateities; jis stengiasi pamiršti savo mirtį ir gyvena taip, tarsi jo egzistencija būtų gyvenimas-be-mirties. Toks žmogus stengiasi vis labiau sustiprinti savąjį Aš, kad pabėgtų nuo nujaučiamos mirties keliamo egzistencinio nerimo. Egzistencijos filosofų manymu, savo mirties, kaip neatsiejamos gyvenimo dalies, pripažinimas lemia žmogaus tapimą autentišku, laisvu, sąmoningu. Savo mirtingumą įsisąmoninančiam žmogui iškyla dvi alternatyvos: pripažinti mirtį kaip gyvenimo esmę (mirtis-gyvenime) arba žvelgti į egzistenciją iš amžinybės perspektyvos (gyvenimas-mirtyje). Budizmas siūlo kitokią išeitį sulygindamas gyvenimą ir mirtį, parodydamas Aš (bandančio įsikabinti į vieną ar kitą) iliuziškumą. Pagrindinė sąvoka, išreiškianti budistinę egzistencijos sampratą, yra suunyataa – „tuštuma, niekas“. Ši sąvoka atliepia egzistencijos filosofų idėjas, tačiau su jomis nesutampa. Šiame straipsnyje lyginama M. Heideggerio, J. P. Sartre’o, Mokytojo Eckharto ir budizmo „nieko“ idėjos, atskleidžiami panašumai ir skirtumai.

In the context of the digital transformation of education, the development of digital literacy of future computer science teachers is becoming a priority, especially in terms of developing interactive educational content. This is necessary for effective learning of the material, stimulating the cognitive activity of students and developing their key competencies in the field of digital technologies. In the educational context, information interaction is organized through various modes, including intraactive (isolation), extraactive (passive transmission) and interactive. The interactive mode is characterized by two-way information flows involving an active dialogue between the student and the learning system. The organization of direct and reverse interactive interaction, when either the system or the student acts as the initiator of the exchange, plays a key role in shaping a dynamic educational trajectory. Mastering the methodology and principles of creating and using interactive resources is necessary to form the professional competence of a teacher who is able to effectively apply modern educational technologies. The article reveals the features of designing interactive educational content based on educational platforms (Digital educational content library, Yandex Uchebnik, 1C: Lesson, Udoba). The author's developments of interactive computer science tasks are presented: Drag and Drop Words, Find Words etc. Ready-made digital educational resources and platforms for developing your own interacttive educational material are presented. In the modern digital-oriented educational environment, the development of digital literacy of future computer science teachers, especially in terms of creating digital content, is a priority. This competence allows teachers to adapt existing resources, develop their own innovative materials, and actively involve students in the learning process, fostering professional autonomy and creativity.

In a large number of real world dilemmas and related applications the modeling of complex behavior is the central point. Over the past decades, new approaches based on Artificial Neural Networks (ANN) have been proposed to solve problems related to optimization, modeling, decision making, classification, data mining or nonlinear functions (behavior) approximation. Inspired from biological nervous systems and brain structure, Artificial Neural Networks could be seen as information processing systems, which allow elaboration of many original techniques covering a large field of applications. Among their most appealing properties, one can quote their learning and generalization capabilities. The main goal of this paper is to present, through some of main ANN models and based techniques, their real application capability in real world industrial dilemmas. Several examples through industrial and real world applications have been presented and discussed.

The use of digital technologies in modern educational environments is an urgent requirement. This article aims to study mobile technologies as an effective mechanism for supporting and developing inclusive learning in higher education institutions. To achieve this goal, the article employs methods of scientific content analysis of literature and comparison, which allow for identifying the positive aspects of integrating mobile technologies into inclusive education and the difficulties that exist on this path. The study results indicate a need to utilize both traditional and specialized technologies in the modern higher education landscape. The analysis reveals that traditional technologies supporting inclusion primarily include applications for organizing learning, mobile communication technologies, and applications for creating specialized learning content, including multimedia and virtual technologies for individuals with special educational needs. Among the specialized tools for supporting inclusive learning are apps that enhance vision and hearing. This category also includes mobile applications that support lectures through various subtitle options. The study found that such mobile technologies improve knowledge acquisition and enhance the efficiency of the learning process. It concludes that these applications contribute to greater student integration, reduce social isolation, develop social skills, and increase self-confidence.

The article analyses the correlation of professionalism and pedagogical mastery. In the modern educational environment, where the requirements for teachers are constantly growing, it is impossible to limit oneself only to ready-made knowledge and acquired experience. It is important to be able to apply your knowledge in teaching practice, to be flexible and adaptive. The authors of the study emphasise that for successful work in education requires building one’s pedagogical skills on the basis of cooperation and co-creation. This means that a teacher should be able to work not only independently, but also in a team, sharing experiences and ideas with colleagues and students. This approach contributes to the transformation of the role of teachers at creative universities. Instead of the traditional translation of knowledge, teachers become mentors, inspirers, and leaders of the learning process. They create conditions for the development of students’ creative abilities, stimulating their active participation in the educational process. Studying the dynamics, structure, and components of pedagogical mastery allows identifying key aspects essential for the development of a successful teacher.

This paper examines the concept of authenticity and its relevance in education, from a philosophical perspective. Under the heading of educational authenticity (EA), I critique Fred Newmann’s views on authentic pedagogy and intellectual work. I argue against the notion that authentic engagement is usefully analyzed in terms of a relationship between school work and: “real” work. I also seek to clarify the increasingly problematic concept of constructivism, arguing that there are two distinct constructivist theses, only one of which deserves serious attention. I explain that the correspondence view of authenticity pays insufficient attention to the reality that the presence of “real world” connections does not guarantee that teaching and learning will be truly authentic. As a bridge to a philosophically acceptable understanding of authenticity, I reflect on John Dewey, who famously strove to base his views on education on the experience of the child, while rejecting that such experience requires validation from the “real” world. And Jean Jacques Rousseau offers several clues as to how the search for an authentic self might proceed beyond the Romanticist vision of an inner essence. These include the idea of the self as constructed inter-subjectively, which I capture by the term “one among others” and which, in turn, reveals persons as dialogically engaged in working out who they are and what they stand for (an idea found in the work of Charles Taylor). There is a clear affinity here with the imperative proposed by Newmann. I embrace the idea that the cultivation of dialogue should be a key priority in classrooms, because dialogue drives each individual to seek meaning in the context of seeing her/himself as one among others. I highlight the role of the classroom community of inquiry as an environment which has the dual function of cultivating disciplined inquiry and facilitating the kind of personal development that can, most properly, be termed “authentic”.

Paper versus Screen: The Unresolved Conflict in Children's and Adolescents' Learning Processes.

The main issue to be addressed here is whether the ideas embodied in nonlinear dynamical systems and chaos are of any value in aiding our understanding of complicated physical phenomena. The views expressed will necessarily be selective and will reflect those features of modern thinking in dynamical systems theory which the author has found to be most useful in interpreting the outcome of experiments. The field may be viewed in the following way. On the one hand there are many splendid abstract mathematical ideas in discussions of dynamical systems and chaos, and on the other there are so-called ‘real world’ phenomena. As is usually the case in physics, the interpretation of experimental results in terms of a set of theoretical ideas is not always a straightforward matter and things are no different here. This is despite some claims in popular accounts that ‘chaos theory’ is the ‘answer’ to a wide variety of problems. An example of this oversimplification is to be found in the phenomenon of turbulence in fluid flows. Over the past decade the words ‘chaos’ and ‘turbulence’ have become synonymous in many popular accounts and yet the connection between the two is far from obvious even today. In the author’s opinion the ideas of chaos have thus far added very little to the understanding of the phenomenon of turbulence. Yet many research groups, including the author’s, continue to study this topic because a significant breakthrough in this very difficult subject seems tantalizingly close.

Cooperation Without Trust? By Karen S. Cook, Russell Hardin, and Margaret Levi. New York: Russell Sage Foundation, 2005. 256p. $32.50. Rationality and the Ideology of Disconnection. By Michael Taylor. Cambridge: Cambridge University Press, 2006. 238p. $75.00 cloth, $26.99 paper. The two books under review differ sharply on the fruitfulness of rational choice theory. Karen Cook, Russell Hardin, and Margaret Levi posit that even trust is best understood as a product of rational, materialist calculations. On their “encapsulated interest” view, trust “exists when one party to [a] relation believes the other party has incentive to act in his or her interest or to take his or her interests to heart” (p. 2). But can incentives truly whisper to the heart? Michael Taylor decries the baleful consequences, both intellectual and practical, that stem from assimilating all reasoned decision making to the numerical weighing of material incentives and ignoring the role of heartfelt personal and moral commitments.

The increasing demand for World Wide Web (Web) based courses has imposed some challenges in Information and Communications Technology (ICT) field, in particular when considering the education supported by the Web. One of the emerging needs of education supported by the Web is related to the Learning Objects (LO) usage inside Learning Management Systems (LMS). Besides production of "good quality" LO, it must be provided efficient methods concerning their storage and dissemination. However, some difficulties have been reported by teachers of Web based courses: "expensive costs" for LO authoring; lack of tools for sharing these materials; and negative practical experiences for reusing them in an LMS. Some proposals to mitigate these problems have been the development of Learning Object Repository (LOR) tools, mainly in order to facilitate the dissemination of LO. Despite the progress already achieved, there are still several barriers for their adoption by teachers such as lack of easy integration between LMS environment and LOR. In general, current integrations are not simple for typical users. In this context, the target of this project is to presents an innovative LOR, the Interactive Repository of Digital Contents -iRepository. Its model provides seamless integration with a particular LMS and offers several resources to help teaching and learning processes, such as registry of LO educational effectiveness. As a practical contribution, the fundamentals of iRepository model were implemented for an specific LMS, the Moodle system.

This article is about project-based learning is a learning model that is used to enable the students. Project-based learning is learning that engages students directly in the learning process by providing a task or project to be done in groups which will produce a real product. A learning process in which students actively construct knowledge by means of constantly acquiring new information. Project based learning is an innovative learning model and a greater emphasis on contextual learning through complex activities that provide opportunities for students, working individually or in groups, and in touch with the real world. Implementation of project-based learning that can either provide capabilities that are beneficial to the students. The success of project-based learning occurs when students get motivated, active students in learning, and produce high quality work. Keywords: Project Based Learning, Students Activities

Estamos en la era del aprendizaje automático y el descubrimiento automático de conocimientos a partir de datos se utiliza cada vez más para resolver problemas en nuestra vida diaria. Una clave para diseñar con éxito algoritmos inteligentes útiles es poder modelar la incertidumbre que está presente en el mundo real. Las redes bayesianas son una herramienta poderosa que modela la incertidumbre de acuerdo con la teoría de la probabilidad. Aunque la literatura contiene métodos que aprenden redes bayesianas a partir de conjuntos de datos con alta dimensionalidad, los métodos tradicionales no limitan la complejidad de inferencia de los modelos aprendidos, y a menudo producen modelos en los que la inferencia exacta es intratable. Esta tesis se centra en el aprendizaje de redes bayesianas tratables a partir de datos y contiene la siguientes cinco contribuciones: Primero, proponemos estrategias para aprender redes bayesianas en el espacio de órdenes de eliminación (i). De esta manera, podemos acotar de manera eficiente la complejidad de inferencia de las redes durante el proceso de aprendizaje. Esto es especialmente útil en problemas donde los datos están incompletos. En estos casos, el enfoque más común para aprender redes bayesianas es aplicar el algoritmo de esperanza-maximización estructural, que requiere realizar inferencia en cada iteración del proceso de aprendizaje. Aprovechando la reducida complejidad de inferencia de los modelos, proponemos un nuevo método con el propósito de garantizar la eficiencia del proceso de aprendizaje y a la vez mejorar el rendimiento del algoritmo original (ii). Además, estudiamos la complejidad de la clasificación multidimensional, una generalización de la clasificación multi-etiqueta, en redes bayesianas. Obtenemos cotas superiores para la complejidad del cómputo de las explicaciones más probables y de probabilidades marginales de las variables clase dado el valor de todas las variables predictoras (iii). Utilizamos estos límites para proponer estrategias eficientes para acotar la complejidad de los clasificadores multidimensionales basados en redes bayesianas durante el proceso de aprendizaje. Con el objetivo de mejorar el rendimiento de estos modelos, proponemos métodos para el aprendizaje discriminativo de clasificadores multidimensionales basados en redes bayesianas (iv). Finalmente, abordamos el problema de predecir la ausencia de ataques en pacientes con epilepsia en el lóbulo temporal tras someterse a cirugía (v). Para ello, utilizamos un clasificador multidimensional basados en redes bayesianas, que están especialmente diseñados para modelar las relaciones entre las variables clase, es decir, ausencia de ataques epilépticos uno, dos y cinco años después de la cirugía. ----------ABSTRACT---------- We are in the era of machine learning and the automatic discovery of knowledge from data is increasingly used to solve problems in our daily life. A key to successfully design useful intelligent algorithms is to be able to model the uncertainty that is present in the real world. Bayesian networks are a powerful tool that models uncertainty according to probability theory. Although the literature contains approaches that learn Bayesian networks from high dimensional datasets, traditional methods do not bound the inference complexity of the learned models, often producing models where exact inference is intractable. This thesis focuses on learning tractable Bayesian networks from data, and contains the following five contributions. First, we propose strategies for learning Bayesian networks in the space of elimination orders (i). In this manner, we can efficiently bound the inference complexity of the networks during the learning process. This is specially useful in problems where data is incomplete. In these cases, the most common approach to learn Bayesian networks is to apply the structural expectation-maximization algorithm, which requires performing inference at each iteration of the learning process. Taking advantage of the reduced inference complexity of the models, we propose a new method with the purpose of guaranteeing the efficiency of the learning process while improving the performance of the original algorithm (ii). Additionally, we study the complexity of multidimensional classification, a generalization of multilabel classification, in Bayesian networks. We provide upper bounds for the complexity of the most probable explanations and marginals of class variables conditioned to an instantiation of all predictor variables (iii). We use these bounds to propose efficient strategies for limiting the complexity of multidimensional Bayesian network classifiers during the learning process. With the objective of improving the performance of these models, we also propose methods for the discriminative learning of multidimensional Bayesian network classifiers (iv). Finally, we address the problem of predicting seizure freedom in patients that have undergone temporal lobe epilepsy surgery (v). For that, we use a multidimensional Bayesian network classifier, which is specially well fitted to model the relationships among the class variables, i.e., seizure freedom at one, two and five years after surgery.

At the time of teaching, the teacher has several methods used to support the learning program that has been made. One method used to train techniques is the method of distribution practice. The method of distribution practice is the principle of regulating the turnover of material in learning that is carried out through alternating arrangements of rest periods. Building knowledge has focused on distributed practices to make learning and remembering something new, easier for the brain. This paper aims to describe the steps for deciding to study time to improve the learning environment by learning distributed practice. From the discussion concluded: 1) Subjectively and comparatively there are types of distributed practice learning, namely distributed practice itself and mass practice. to show the two extremes of the break-to-work continuum, involving longer periods of rest and shorter periods of active practice (that is, work), and mass practices that involve less time in rest and longer in active practice (working) . Objectively to define both distribution schedules, especially when distributive effects on skills are continuously different from one training session. In this situation, the practice distributed can be defined as a training session in which the amount of rest time equals or greater than the amount of time in work, while a shared practice is then defined as a practice schedule where there is a greater amount of time in work than rest. 2) in general, most students learn a lot before and during the exam and ultimately are unable to remember most of the texts learned during the exam. 3) The act of learning in school is aimless, while activities that give rise to learning in the real world are goals. When the learning environment has an appropriate design, student attitudes and motivation increase. In addition to the academic success of students, he found that learning makes students happy during the learning process by giving them a rich learning experience, on the other hand psychological transformation is based on prerequisite skills, knowledge, and motives. When these prerequisites have not been developed in students, generic contradictions arise. The act of learning [not an activity] is a prerequisite for obtaining certain material, but they cannot be formed (obtained, learned) without being involved in the appropriate material. It is impossible to learn the appropriate learning actions first and then study the material. The actions, content, structure, and course are determined by the object; there is no formal action without content or aimlessly to be transferred to different materials. 4) Today The way to deliver academic information can only be understood by students when they join several new features of the academic learning environment that characterize the digital age. Without knowing how to take advantage of these new features, scholars and graduates will experience successful difficulties in the global economy characterized by three main features: competition and cost, globalization, and information intimacy.