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E-EFL in the Saudi tertiary classroom
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThis study explores how digital technologies have been introduced and used in a Saudi e-EFL
Higher Education classroom and the degree to which this reflected self-efficacious and
heutagogical learning. Despite recent educational reforms in Saudi, the limitations of the
educational system make it ill-suited to the needs of the international job market, leaving Saudi
graduates under-equipped in an increasingly globalised workforce. Therefore, this quantitative
study collected from 41 teachers and 343 university students aims to identify the e-learning
experiences of Saudi e-EFL teachers and learners in order to gauge the influence of e-learning
integration on the desired progression to learner-centred learning. Additional qualitative data were
collected from teachers to be discussed within quantitative data. The data were interpreted and
factors influencing learning and teaching methods with digital technologies were analysed against
demographic data. The findings revealed that e-EFL teachers are unable to understand how they
use ICT technologies and the pedagogical approach they adopt to influence student learning and
their capacity to work in a self-directed manner. The present study makes an important
contribution to existing research as it provides vital insights for the Saudi educational community
to integrate pedagogical transformations into the equation of educational reforms and practices.
At a broader level, these insights provide an empirical basis for policymakers and researchers to
turn their attention to an issue with the potential to derail important educational reforms aligned
with the fulfilment of the Saudiâs 2030 Vision which aims to prepare a self-directed workforce for
effective participation in national socio-economic development and in the global knowledge
economy. Recommendations are made to integrate training in technology, pedagogy and content
knowledge for teachers as they would benefit from a better understanding of epistemological,
pedagogical and technical issues and skills to promote studentsâ heutagogical learning
Boundary breaking: how principals impact student engagement
The purpose of this study was to understand the impact site principles have on student engagement in the classroom through a sitewide art integration program with the outcome of increased knowledge in content areas. Researching the use of a sitewide art integration program at a Midwest high school, case study methodology was applied to administrator and teacher interviews using annual state test scores to triangulate for authenticity and impact. Six themes were identified from the interviews to have an impact on student engagement and increased content knowledge due to the art initiative. Those six themes were gathering teacher buy-in, the role of the administration, lack of enthusiasm, the impact of A Plus professional development, enhanced school climate and culture, the faculty demonstrated growth through A Plus, and student outcomes.
The results of the study indicated that principals do impact student engagement in the classroom with the outcome of deeper knowledge of content matter. Four areas for future research developed based on study findings. Because the faculty at the school of study was all white, a study with a diverse faculty and school would add to the literature of principal leadership affecting student engagement in the classroom. Future study is necessary to examine how an intentional leadership theory can have a greater or lesser impact on a sitewide art initiative with an outcome of increased student engagement and deeper learning of content matter. A disconnect was uncovered between the teachersâ perception of the climate of the school and the administratorsâ perception of the climate of the school related to the art initiative; therefore, further study could clarify this dissonance. Finally, students who had excellent ability on the end of year state tests had a lower performance outcome after the art initiative. This could be due to some teachersâ lack of enthusiasm for the art initiative. Thus, additional research is warranted.
Contributions of Human Prefrontal Cortex to the Recogitation of Thought
Human beings have a unique ability to not only verbally articulate past and present experiences, as well as potential future ones, but also evaluate the mental representations of such things. Some evaluations do little good, in that they poorly reflect facts, create needless emotional distress, and contribute to the obstruction of personal goals, whereas some evaluations are the converse: They are grounded in logic, empiricism, and pragmatism and, therefore, are functional rather than dysfunctional. The aim of non-pharmacological mental health interventions is to revise dysfunctional thoughts into more adaptive, healthier ones; however, the neurocognitive mechanisms driving cognitive change have hitherto remained unclear. Therefore, this thesis examines the role of the prefrontal cortex (PFC) in this aspect of human higher cognition using the relatively new method of functional near-infrared spectroscopy (fNIRS). Chapter 1 advances recogitation as the mental ability on which cognitive restructuring largely depends, concluding that, as a cognitive task, it is a form of open-ended human problem-solving that uses metacognitive and reasoning faculties. Because these faculties share similar executive resources, Chapter 2 discusses the systems in the brain involved in controlled information processing, specifically the nature of executive functions and their neural bases. Chapter 3 builds on these ideas to propose an information-processing model of recogitation, which predicts the roles of different subsystems localized within the PFC and elsewhere in the context of emotion regulation. This chapter also highlights several theoretical and empirical challenges to investigating this neurocognitive theory and proposes some solutions, such as to use experimental designs that are more ecologically valid. Chapter 4 focuses on a neuroimaging method that is best suited to investigating questions of spatial localization in ecological experiments, namely functional near-infrared spectroscopy (fNIRS). Chapter 5 then demonstrates a novel approach to investigating the neural bases of interpersonal interactions in clinical settings using fNIRS. Chapter 6 explores physical activity as a âbottom-upâ approach to upregulating the PFC, in that it might help clinical populations with executive deficits to regulate their mental health from the âtop-downâ. Chapter 7 addresses some of the methodological issues of investigating clinical interactions and physical activity in more naturalistic settings by assessing an approach to recovering functional events from observed brain data. Chapter 8 draws several conclusions about the role of the PFC in improving psychological as well as physiological well-being, particularly that rostral PFC is inextricably involved in the cognitive effort to modulate dysfunctional thoughts, and proposes some important future directions for ecological research in cognitive neuroscience; for example, psychotherapy is perhaps too physically stagnant, so integrating exercise into treatment environments might boost the effectiveness of intervention strategies
Neural foundations of cooperative social interactions
The embodied-embedded-enactive-extended (4E) approach to study cognition suggests that interaction with the world is a crucial component of our cognitive processes. Most of our time, we interact with other people. Therefore, studying cognition without interaction is incomplete. Until recently, social neuroscience has only focused on studying isolated human and animal brains, leaving interaction unexplored. To fill this gap, we studied interacting participants, focusing on both intra- and inter-brain (hyperscanning) neural activity. In the first study, we invited dyads to perform a visual task in both a cooperative and a competitive context while we measured EEG. We found that mid-frontal activity around 200-300 ms after receiving monetary rewards was sensitive to social context and differed between cooperative and competitive situations. In the second study, we asked participants to coordinate their movements with each other and with a robotic partner. We found significantly stronger EEG amplitudes at frontocentral electrodes when people interacted with a robotic partner. Lastly, we performed a comprehensive literature review and the first meta-analysis in the emerging field of hyperscanning that validated it as a method to study social interaction. Taken together, our results showed that adding a second participant (human or AI/robotic) fostered our understanding of human cognition. We learned that the activity at frontocentral electrodes is sensitive to social context and type of partner (human or robotic). In both studies, the participantsâ interaction was required to show these novel neural processes involved in action monitoring. Similarly, studying inter-brain neural activity allows for the exploration of new aspects of cognition. Many cognitive functions involved in successful social interactions are accompanied by neural synchrony between brains, suggesting the extended form of our cognition
Brain Computations and Connectivity [2nd edition]
This is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence. It is free to read on the Oxford Academic platform and offered as a free PDF download from OUP and selected open access locations.
Brain Computations and Connectivity is about how the brain works. In order to understand this, it is essential to know what is computed by different brain systems; and how the computations are performed.
The aim of this book is to elucidate what is computed in different brain systems; and to describe current biologically plausible computational approaches and models of how each of these brain systems computes.
Understanding the brain in this way has enormous potential for understanding ourselves better in health and in disease. Potential applications of this understanding are to the treatment of the brain in disease; and to artificial intelligence which will benefit from knowledge of how the brain performs many of its extraordinarily impressive functions.
This book is pioneering in taking this approach to brain function: to consider what is computed by many of our brain systems; and how it is computed, and updates by much new evidence including the connectivity of the human brain the earlier book: Rolls (2021) Brain Computations: What and How, Oxford University Press.
Brain Computations and Connectivity will be of interest to all scientists interested in brain function and how the brain works, whether they are from neuroscience, or from medical sciences including neurology and psychiatry, or from the area of computational science including machine learning and artificial intelligence, or from areas such as theoretical physics
Real-time generation and adaptation of social companion robot behaviors
Social robots will be part of our future homes.
They will assist us in everyday tasks, entertain us, and provide helpful advice.
However, the technology still faces challenges that must be overcome to equip the machine with social competencies and make it a socially intelligent and accepted housemate.
An essential skill of every social robot is verbal and non-verbal communication.
In contrast to voice assistants, smartphones, and smart home technology, which are already part of many people's lives today, social robots have an embodiment that raises expectations towards the machine.
Their anthropomorphic or zoomorphic appearance suggests they can communicate naturally with speech, gestures, or facial expressions and understand corresponding human behaviors.
In addition, robots also need to consider individual users' preferences: everybody is shaped by their culture, social norms, and life experiences, resulting in different expectations towards communication with a robot.
However, robots do not have human intuition - they must be equipped with the corresponding algorithmic solutions to these problems.
This thesis investigates the use of reinforcement learning to adapt the robot's verbal and non-verbal communication to the user's needs and preferences.
Such non-functional adaptation of the robot's behaviors primarily aims to improve the user experience and the robot's perceived social intelligence.
The literature has not yet provided a holistic view of the overall challenge: real-time adaptation requires control over the robot's multimodal behavior generation, an understanding of human feedback, and an algorithmic basis for machine learning.
Thus, this thesis develops a conceptual framework for designing real-time non-functional social robot behavior adaptation with reinforcement learning.
It provides a higher-level view from the system designer's perspective and guidance from the start to the end.
It illustrates the process of modeling, simulating, and evaluating such adaptation processes.
Specifically, it guides the integration of human feedback and social signals to equip the machine with social awareness.
The conceptual framework is put into practice for several use cases, resulting in technical proofs of concept and research prototypes.
They are evaluated in the lab and in in-situ studies.
These approaches address typical activities in domestic environments, focussing on the robot's expression of personality, persona, politeness, and humor.
Within this scope, the robot adapts its spoken utterances, prosody, and animations based on human explicit or implicit feedback.Soziale Roboter werden Teil unseres zukĂŒnftigen Zuhauses sein.
Sie werden uns bei alltĂ€glichen Aufgaben unterstĂŒtzen, uns unterhalten und uns mit hilfreichen RatschlĂ€gen versorgen.
Noch gibt es allerdings technische Herausforderungen, die zunĂ€chst ĂŒberwunden werden mĂŒssen, um die Maschine mit sozialen Kompetenzen auszustatten und zu einem sozial intelligenten und akzeptierten Mitbewohner zu machen.
Eine wesentliche FĂ€higkeit eines jeden sozialen Roboters ist die verbale und nonverbale Kommunikation.
Im Gegensatz zu Sprachassistenten, Smartphones und Smart-Home-Technologien, die bereits heute Teil des Lebens vieler Menschen sind, haben soziale Roboter eine Verkörperung, die Erwartungen an die Maschine weckt.
Ihr anthropomorphes oder zoomorphes Aussehen legt nahe, dass sie in der Lage sind, auf natĂŒrliche Weise mit Sprache, Gestik oder Mimik zu kommunizieren, aber auch entsprechende menschliche Kommunikation zu verstehen.
DarĂŒber hinaus mĂŒssen Roboter auch die individuellen Vorlieben der Benutzer berĂŒcksichtigen.
So ist jeder Mensch von seiner Kultur, sozialen Normen und eigenen Lebenserfahrungen geprĂ€gt, was zu unterschiedlichen Erwartungen an die Kommunikation mit einem Roboter fĂŒhrt.
Roboter haben jedoch keine menschliche Intuition - sie mĂŒssen mit entsprechenden Algorithmen fĂŒr diese Probleme ausgestattet werden.
In dieser Arbeit wird der Einsatz von bestĂ€rkendem Lernen untersucht, um die verbale und nonverbale Kommunikation des Roboters an die BedĂŒrfnisse und Vorlieben des Benutzers anzupassen.
Eine solche nicht-funktionale Anpassung des Roboterverhaltens zielt in erster Linie darauf ab, das Benutzererlebnis und die wahrgenommene soziale Intelligenz des Roboters zu verbessern.
Die Literatur bietet bisher keine ganzheitliche Sicht auf diese Herausforderung: Echtzeitanpassung erfordert die Kontrolle ĂŒber die multimodale Verhaltenserzeugung des Roboters, ein VerstĂ€ndnis des menschlichen Feedbacks und eine algorithmische Basis fĂŒr maschinelles Lernen.
Daher wird in dieser Arbeit ein konzeptioneller Rahmen fĂŒr die Gestaltung von nicht-funktionaler Anpassung der Kommunikation sozialer Roboter mit bestĂ€rkendem Lernen entwickelt.
Er bietet eine ĂŒbergeordnete Sichtweise aus der Perspektive des Systemdesigners und eine Anleitung vom Anfang bis zum Ende.
Er veranschaulicht den Prozess der Modellierung, Simulation und Evaluierung solcher Anpassungsprozesse.
Insbesondere wird auf die Integration von menschlichem Feedback und sozialen Signalen eingegangen, um die Maschine mit sozialem Bewusstsein auszustatten.
Der konzeptionelle Rahmen wird fĂŒr mehrere AnwendungsfĂ€lle in die Praxis umgesetzt, was zu technischen Konzeptnachweisen und Forschungsprototypen fĂŒhrt, die in Labor- und In-situ-Studien evaluiert werden.
Diese AnsÀtze befassen sich mit typischen AktivitÀten in hÀuslichen Umgebungen, wobei der Schwerpunkt auf dem Ausdruck der Persönlichkeit, dem Persona, der Höflichkeit und dem Humor des Roboters liegt.
In diesem Rahmen passt der Roboter seine Sprache, Prosodie, und Animationen auf Basis expliziten oder impliziten menschlichen Feedbacks an
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