In last decade or so, e-learning seems to be emerging as the dominant model of learning but questions are being raised about the trade-offs in switching from traditional classroom based learning to e-learning; for example, e-learning is cost effective, round the clock accessible and convenient but there are questions raised about its quality and effectiveness. In last decade Saudi government has undertaken several steps for reforming the education system in the Kingdom including provision of education for all. E-learning can play a vital role in helping Saudi government reach its ambitious targets but despite its obvious benefits the overall adoption of e-learning in the Kingdom has remained low. The key problem in this regard is lo perceived effectiveness of e-learning. E-learning is quite beneficial in that it can help individuals not only acquire knowledge but also skills which allows them to learn independently without constraints using the vast amount of education resources available online. However, the main focus of the e-learning community in the Kingdom has remained restricted to teaching specific subjects. This research argues that the true potential of e-learning is much broader and useful than currently perceived by the e-learning community in the Kingdom. E-learning has the potential of producing lifelong learners. Hence the focus of e-learning community should be on overall skills development. This research thus defines e-learning effectiveness in terms of both short term goals (that is, learning about the subject) and long term goals (improving skills and motivations for being lifelong and independent learner). This research investigates impact of four kinds of interactivity (Student-Student, Student-teacher, Student-content, Student-System) on effectiveness of e-learning. This is a mixed methods research. Data was collected using focus groups and questionnaire surveys. This research finds that all four kinds of interactivity play a role in improving effectiveness of e -learning All four kinds of interactivities were found significant for improving course learning. Student-teacher, Student-Student and Student-Content interactivities were found critical for improving independent learning skills. Student-Student an Student-Content interactivity was found critical for improving motivation for being lifelong e-learner.

Languages are culturally transmitted through a repeated cycle of learning and communicative interaction. These two aspects of cultural transmission impose (at least) three interacting pressures that can shape the evolution of linguistic structure: a pressure for learnability, a pressure for expressivity, and a pressure for coordination amongst users in a linguistic community. This thesis considers how these sometimes competing pressures impact linguistic complexity across cultural time. Using artificial language and iterated learning experimental paradigms, I investigate the conditions under which complexity in morphological and syntactic systems emerges, spreads, and reduces. These experiments illustrate the interaction of transmission, learning and use in hitherto understudied domains - morphosyntax and word order. In a first study (Chapter 2), I report the first iterated learning experiments to investigate the evolution of complexity in compositional structure at the word and sentence level. I demonstrate that a complex meaning space paired with pressures for learnability and communication can result in compositional hierarchical constituent structure, including fixed combinatorial rules of word formation and word order. This structure grants a productive and productively interpretable language and only requires learners to acquire a finite lexicon and a finite set of combinatorial rules (i.e., a grammar). In Chapter 3, I address the unique effect of communicative interaction on linguistic complexity, by removing language learning completely. Speakers use their native language to express novel meanings either in isolation or during communicative interaction. I demonstrate that even in this case, communicative interaction leads to more efficient and overall simpler linguistic systems. These first two studies provide support for the claim that morphological and syntactic complexity are shaped by an overarching drive towards simplicity (or learnability) in language learning and communication. Chapter 4 reports a series of experiments assessing the possibility that the simplicity bias found in the first two studies operates at a different strength depending on the linguistic level. Studies in natural language learning and in pidgin/creole genesis suggest that while morphological variation seems to be highly susceptible to regularisation, variation in other syntactic features, like word order, appears more likely to be reproduced. I test this experimentally by comparing regularisation of unconditioned variation across morphology and word order in the context of artificial language learning. I show that language users in fact regularise unconditioned variation in a similar way across linguistic levels, suggesting that the simplicity bias may be driven by a single, non-level-specific mechanism. Taken together, the experimental evidence presented in this thesis supports the hypothesis that the cultural and cognitive pressures acting on language users during learning and communicative interaction - for learnability, expressivity and coordination - are at least partially responsible for the evolution of linguistic complexity. Specifically, they are responsible for the emergence of linguistic complexity which maximises learnability and communicative efficiency, and for the reduction of complexity which does not. More generally, the approach taken in this thesis promotes a view of complexity in linguistic systems as an evolving variable determined by the biases of language learners and users as languages are culturally transmitted.

Current literature indicates a lack of exploration of factors relating to Taiwanese students’ critical thinking in the field of English as a Foreign Language (EFL). The research study was a case study based on the social constructivist framework. The aim of this study was to explore how teacher and students interactions online impacted critical thinking by addressing the social norm in Confucius Heritage Culture (CHC). The characteristics of the social norm of CHC do not readily support verbalizing thoughts and challenging others face-to-face in public, which are important to the practice of critical thinking. The research was conducted in an English-major reading class at a university in Taiwan. The data collection methods included focus groups, collaborative inquiry with the teacher, and the researcher’s participant observation in both face-to-face and online discussions. The findings suggested that students need teacher’s cognitive, affective, pedagogical and technical support and face-to-face small group support before engaging in online interactions. Modified debates in new face-to-face models of interaction helped maximise the social constructivist approach with the teacher’s shepherd facilitation. The online interaction patterns in a CHC context underwent a three-phase process, which described how CHC students externalised critical thinking within groups, inter-groups and inter-classes in online form. The study contributes to our understanding and the development of culturally suitable approaches to cognitive, affective, pedagogical and technical guidelines needed in facilitating EFL students’ critical thinking in face-to-face and online interactions in the context of Taiwan.

This study aimed at investigating university preparatory school students&rsquo / and teachers&rsquo / perceptions of computer-assisted language learning (CALL) environment. The sample consisted of 308 students and 50 teachers from Zonguldak Karaelmas University Preparatory School. Data was gathered from the participants via two Effective CALL Questionnaires (ECALLQ) developed by the researcher. Both inferential and descriptive statistics were used to analyze the data. Principal component analysis was used to find the dimensions of the student questionnaire. Repeated measures ANOVA and paired-samples t-test were employed to define the priorities of the students within the dimensions of each subscale. MANOVA was used to investigate whether there were significant differences among students&rsquo / CALL environment perceptions with respect to certain background variables.Descriptive statistics were used to analyze students&rsquo / and teachers&rsquo / perceptions of computer&rsquo / s role and teacher&rsquo / s role in CALL environment and to analyze all participants&rsquo / responses to the open-ended questions.The study indicated that students perceive the computer&rsquo / s role with respect to (1)language skills, (2) overall effect of computer and (3) motivation / teacher&rsquo / s role with respect to (1) teacher assistance, (2) teacher guidance and (3) teacher presence / students&rsquo / expectations from the teacher with respect to (1) laboratory activities guided by the teacher and (2) overall guidance. According to the students&rsquo / perceptions, language skills,teacher assistance and lab activities guided by the teacher were found to be the most effective dimensions.Descriptive statistics showed that both students and teachers are undecided about the effectiveness of CALL, and they believe that teachers are effective in CALL environment.

Ensemble learning is a promising direction of research in machine learning, in which an ensemble classifier gives better predictive and more robust performance for classification problems by combining other learners. Meanwhile agent-based systems provide frameworks to share knowledge from multiple agents in an open context. This thesis combines multi-agent knowledge sharing with ensemble methods to produce a new style of learning system for open environments. We now are surrounded by many smart objects such as wireless sensors, ambient communication devices, mobile medical devices and even information supplied via other humans. When we coordinate smart objects properly, we can produce a form of collective intelligence from their collaboration. Traditional ensemble methods and agent-based systems have complementary advantages and disadvantages in this context. Traditional ensemble methods show better classification performance, while agent-based systems might not guarantee their performance for classification. Traditional ensemble methods work as closed and centralised systems (so they cannot handle classifiers in an open context), while agent-based systems are natural vehicles for classifiers in an open context. We designed an open and social ensemble learning architecture, named J-model, to merge the conflicting benefits of the two research domains. The J-model architecture is based on a service choreography approach for coordinating classifiers. Coordination protocols are defined by interaction models that describe how classifiers will interact with one another in a peer-to-peer manner. The peer ranking algorithm recommends more appropriate classifiers to participate in an interaction model to boost the success rate of results of their interactions. Coordinated participant classifiers who are recommended by the peer ranking algorithm become an ensemble classifier within J-model. We evaluated J-model’s classification performance with 13 UCI machine learning benchmark data sets and a virtual screening problem as a realistic classification problem. J-model showed better performance of accuracy, for 9 benchmark sets out of 13 data sets, than 8 other representative traditional ensemble methods. J-model gave better results of specificity for 7 benchmark sets. In the virtual screening problem, J-model gave better results for 12 out of 16 bioassays than already published results. We defined different interaction models for each specific classification task and the peer ranking algorithm was used across all the interaction models. Our research contributions to knowledge are as follows. First, we showed that service choreography can be an effective ensemble coordination method for classifiers in an open context. Second, we used interaction models that implement task specific coordinations of classifiers to solve a variety of representative classification problems. Third, we designed the peer ranking algorithm which is generally and independently applicable to the task of recommending appropriate member classifiers from a classifier pool based on an open pool of interaction models and classifiers.

Thesis (M. Phil.)--University of Hong Kong, 1993.

The master's thesis is concerned with the progress of teaching staff in the context of intergenerational learning in nursery and primary schools. The thesis is divided into two parts. The theoretical part defines the concept of intergenerational learning and describes further connected terms. It is also dealt with the issue of the work environment and the specifics of the school organization, which distinguishes from the ordinary organization and points to the importance of the cooperation of the teaching staff. It defines the intergenerational teachings of teachers and further characterizes its forms, contents and types. The practical part consists of a research survey in the environment of schools, the respondents of which are teaching staff of nursery and elementary schools - teachers, educators, special educators, teachers' assistants and directors of these organizations. The aim of this work is to specify the conditions and critical spots in the pedagogical environment using structured questionnaires in the use of intergenerational learning in primary and nursery schools, to identify its most frequent forms and to define the contents in which it is used most often. The survey was carried out using a quantitative method in the form of a structured questionnaire on the basis of which research...

Education in knowledge society is challenged with a lot of problems in particular the interaction between the teacher and learner in social networking software as a key factor affects the learners’ learning and satisfaction (Prammanee, 2005) where “to teach is to communicate, to communicate is to interact, to interact is to learn” (Hefzallah, 2004, p. 48). Analyzing the relation between teacher-learner interaction from a side and learning outcome and learners’ satisfaction from the other side, some basic problems regarding a new learning culture using social networking software are discussed. Most of the educational institutions pay a lot of attentions to the equipments and emerging Information and Communication Technologies (ICTs) in learning situations. They try to incorporate ICT into their institutions as teaching and learning environments. They do this because they expect that by doing so they will improve the outcome of the learning process. Despite this, the learning outcome as reported in most studies is very limited, because the expectations of self-directed learning are much higher than the reality. Findings from an empirical study (investigating the role of teacher-learner interaction through new digital media wiki in higher education and learning outcome and learner’s satisfaction) are presented recommendations about the necessity of pedagogical interactions in support of teaching and learning activities in wiki courses in order to improve the learning outcome. Conclusions show the necessity for significant changes in the approach of vocational teacher training programs of online teachers in order to meet the requirements of new digital media in coherence with a new learning culture. These changes have to address collaborative instead of individual learning and ICT wiki as a tool for knowledge construction instead of a tool for gathering information. / Bildung in der Wissensgesellschaft ist mit einer Vielzahl von Herausforderungen verbunden. Insbesondere die Interaktion zwischen Lehrenden und Lernenden ist in sozialen Netzwerken durch Software bestimmt, die als ein wesentlicher Faktor den Lernerfolg der Lernenden und ihre Zufriedenheit bestimmt (Prammanee, 2005), da “to teach is to communicate, to communicate is to interact, to interact is to learn” (Hefzallah, 2004, S. 48). Die Analyse der Art der Lehrer-Schüler-Interaktion auf der einen Seite und das Lernergebnis und die Zufriedenheit der Lernenden auf der anderen Seite, sind einige grundlegende zu diskutierende Herausforderungen hinsichtlich einer neuen Lernkultur mit Social-Networking-Software. Eine Vielzahl der Bildungseinrichtungen achten daher auf die Ausstattung mit Ausrüstungen und zugehörigen Informations- und Kommunikationstechnologien (IKT) zur Gestaltung von Lernsituationen. Sie versuchen die IKT in ihren Institutionen als Lehr-und Lernumgebungen zu integrieren, da sie damit einen positiven Effekt auf den Ausgang des Lernprozesses verbinden. Trotzdem sind die Lernergebnisse, die in den meisten Studien untersucht wurden, sehr begrenzt. Es zeigt sich, dass die Erwartungen der Lehrkräfte an selbstgesteuertes Lernen viel höher sind, als die Ergebnisse der Studien repräsentieren. Auf Grundlage dieser Ausgangssituation wurde eine empirischen Studie (Untersuchung der Rolle der Lehrer-Schüler-Interaktion durch neue digitale Medien Wiki in der Hochschulbildung und des Lernerfolgs und der Zufriedenheit der Lernenden) durchgeführt. Aus den Ergebnissen wurden Empfehlungen über die Notwendigkeit der pädagogischen Interaktionen zur Unterstützung von Lehr-und Lernaktivitäten in Wiki Kursen abgeleitet, um den Lernerfolg zu verbessern. Die Schlussfolgerungen zeigen die Notwendigkeit für deutliche Änderungen in der Herangehensweise der beruflichen Bildung der Online-Lehrer, um die Anforderungen der neuen digitalen Medien im Einklang mit einer neuen Lernkultur zu erfüllen. Diese Veränderungen beeinhalten im Kern kooperatives statt individuelles Lernen und den Einsatz von IKT-Wiki als ein Werkzeug für die Wissenskonstruktion statt für das Sammeln von Informationen.

Interaction is a core element in the design of blended and distance learning environments. The importance of understanding these interactions and what might increase effectiveness of such interactions in education is paramount for meaningful learning. This dissertation consists of two qualitative case studies designed to provide a rich, descriptive look at interactions in a high school distance/blended-learning context in the home-study and technology-meditated seminary program of The Church of Jesus Christ of Latter-day Saints. In the study article, Moore's (1989) interaction framework was used as a lens for understanding the learner experience. Thematic narratives were used to highlight themes related to students' perceived learning gains from learner-content interaction and their hesitancy to engage in learner-learner and learner-instructor interactions if they had not met personally. In the second study, Garrison's (2007) Community of Inquiry framework was used to understand the impact that teacher decisions, other than the selection of content, had on the cognitive and social climate of the learning experience. This study describes how a teacher's facilitation of social interaction influences the course learning outcomes. The results highlight the teacher's role in providing the educational and social climate needed to foster learner interactions. This study noted that when the teachers gave learners the opportunity to interact in a live setting, it appeared to foster the relationships needed to interact online. The narratives also highlight how a teacher helped learners interact with one another around content online.

In der vorliegenden Dissertation wurde ein datengetriebenes Verfahren zum maschinellen Lernen von Mensch-Roboter Interaktionen auf Basis von Mensch-Mensch Demonstrationen entwickelt. Während einer Trainingsphase werden Bewegungen zweier Interakteure mittels Motion Capture erfasst und in einem Zwei-Personen Interaktionsmodell gelernt. Zur Laufzeit wird das Modell sowohl zur Erkennung von Bewegungen des menschlichen Interaktionspartners als auch zur Generierung angepasster Roboterbewegungen eingesetzt. Die Leistungsfähigkeit des Ansatzes wird in drei komplexen Anwendungen evaluiert, die jeweils kontinuierliche Bewegungskoordination zwischen Mensch und Roboter erfordern. Das Ergebnis der Dissertation ist ein Lernverfahren, das intuitive, zielgerichtete und sichere Kollaboration mit Robotern ermöglicht.