A satisfação e a intenção de continuidade de uso em servços de e-learning:validação empírica de um modelo aplicado no serviço público

The present study aims to investigate the constructs of Technological Readiness Index (TRI) and the Expectancy Disconfirmation Theory (EDT) as determinants of satisfaction and continuance intention use in e-learning services. Is proposed a theoretical model that seeks to measure the phenomenon suited to the needs of public organizations that offer distance learning course with the use of virtual platforms for employees. The research was conducted from a quantitative analytical approach, via online survey in a sample of 343 employees of 2 public organizations in RN who have had e-learning experience. The strategy of data analysis used multivariate analysis techniques, including structural equation modeling (SEM), operationalized by AMOS© software. The results showed that quality, quality disconfirmation, value and value disconfirmation positively impact on satisfaction, as well as disconfirmation usability, innovativeness and optimism. Likewise, satisfaction proved to be decisive for the purpose of continuance intention use. In addition, technological readiness and performance are strongly related. Based on the structural model found by the study, public organizations can implement e-learning services for employees focusing on improving learning and improving skills practiced in the organizational environment

Empowering single mothers in Iran : Applying a problem-solving model in learning groups to develop participants' capacities to improve their lives

Since 2000, a problem-solving model has been taught to the Society for Protecting the Rights of the Child, and teachers and  students of social work in two universities in Iran. Since 2006, with the initiation of UNICEF, social workers, psychologists  and even some psychiatrists in Iran have been learning this model. In 2008, a group of researchers created an empowerment-oriented  psycho-social group and private intervention project to assess whether a group of Iranian single mothers could use this model, which was traditionally used by professionals only, to effectively and independently meet challenges in their own lives. Our results show that all women used the model effectively and, consequently, made more deliberate decisions to improve their life situations. Some of the women succeeded in finding a job and many improved their family relationships. This study suggests that empowerment-oriented social work can help many clients to achieve their goals, and that this psycho-social intervention project can be a useful model for social work in Iran and many other societies.

Consumer perceived risk, risk reduction strategies and transaction intentions in online marketplaces

Even though online commerce has garnered vast academic interest during the recent years, theoretical grounds for consumer behavior online still remains ambiguous. Despite the globally rapid growth of online commerce, only a fraction of Internet browsers end up purchasing goods online. This is argued to be caused by the intangible and distant nature of the Internet, causing overwhelming perceived risks for consumers and negatively affecting transaction intentions. To combat perceived risks, consumers may actively or passively seek to relieve those risks to tolerable level. These risk reduction strategies refer to both institutional mechanisms as well as consumer risk reduction strategies. The objective of this thesis is to provide further understanding upon the relationships between consumer perceived risk, risk reduction strategies and transaction intentions in online marketplaces. To serve the objectives of the present thesis, a quantitative approach was chosen as the method for conducting empirical research. The data was collected with an online survey through discussion board, using a random sample approach. The proposed research model was examined with a set of hierarchical regression analyses. Results revealed several direct relationships as well as moderating interaction effects. The key finding of this thesis is that institutional risk reduction mechanisms significantly contribute to consumer perceived risks. These mechanisms have the potential to reduce perceived risks, and therefore may stimulate transaction intentions. Additionally, it was observed that risk reduction strategies moderate the relationship between intermediary provided risk relievers, consumer perceived risks and transaction intentions. Retailer related risk reduction strategies were also shown to enforce the effectiveness of payment methods; however feedback and monitoring mechanism was shown to have a diminishing effect of perceived risk only when consumers did not rely on product related risk reduction strategies. The present thesis also illustrates the importance of effective information search, as those consumers are more willing to transact as the perceived risks become less significant. For managerial purposes, the importance of well-functioning institutional mechanisms cannot be emphasized enough.

Techniques for batch reinforcement learning in robotics

This thesis addresses the Batch Reinforcement Learning methods in Robotics. This sub-class of Reinforcement Learning has shown promising results and has been the focus of recent research. Three contributions are proposed that aim to extend the state-of-art methods allowing for a faster and more stable learning process, such as required for learning in Robotics. The Q-learning update-rule is widely applied, since it allows to learn without the presence of a model of the environment. However, this update-rule is transition-based and does not take advantage of the underlying episodic structure of collected batch of interactions. The Q-Batch update-rule is proposed in this thesis, to process experiencies along the trajectories collected in the interaction phase. This allows a faster propagation of obtained rewards and penalties, resulting in faster and more robust learning. Non-parametric function approximations are explored, such as Gaussian Processes. This type of approximators allows to encode prior knowledge about the latent function, in the form of kernels, providing a higher level of exibility and accuracy. The application of Gaussian Processes in Batch Reinforcement Learning presented a higher performance in learning tasks than other function approximations used in the literature. Lastly, in order to extract more information from the experiences collected by the agent, model-learning techniques are incorporated to learn the system dynamics. In this way, it is possible to augment the set of collected experiences with experiences generated through planning using the learned models. Experiments were carried out mainly in simulation, with some tests carried out in a physical robotic platform. The obtained results show that the proposed approaches are able to outperform the classical Fitted Q Iteration.

Eine Pädagogik von multinationalen Online Seminaren (Webinaren) in Echtzeit im Rahmen des Blended Learning-Konzepts

Online-Meetings in Echtzeit oder auch Webinare sind eine hervorragende Möglichkeit, mit den Gruppen auf virtuellem Wege kommunizieren zu können. Dieser Aspekt beinhaltet ein enormes Potential für die internationale und nationale Zusammenarbeit von unterschiedlichen Bildungsanbietern. Während Online-Konferenzen in der Geschäftswelt bereits zum Alltag gehören, ist man im Bildungsbereich noch weit davon entfernt Webinare als integrativen Bestandteil der Lehre anzusehen. Eingebunden in ein "Blended Learning"-Szenario erwiesen sich Webinare als ein effizientes Tool für die transnationale Kooperation von Gruppen. Sogar Großveranstaltungen können als Online-Event durchgeführt werden. Es bedarf jedoch einer sorgfältigen Planung und Inhaltserstellung, um aus einem Webinar eine attraktive Lehrveranstaltung für die Lernenden werden zu lassen. (DIPF/Orig.)

Automated Discovery of Social Networks in Online Learning Communities

As a way to gain greater insights into the operation of online communities, this dissertation applies automated text mining techniques to text-based communication to identify, describe and evaluate underlying social networks among online community members. The main thrust of the study is to automate the discovery of social ties that form between community members, using only the digital footprints left behind in their online forum postings. Currently, one of the most common but time consuming methods for discovering social ties between people is to ask questions about their perceived social ties. However, such a survey is difficult to collect due to the high investment in time associated with data collection and the sensitive nature of the types of questions that may be asked. To overcome these limitations, the dissertation presents a new, content-based method for automated discovery of social networks from threaded discussions, referred to as ‘name network’. As a case study, the proposed automated method is evaluated in the context of online learning communities. The results suggest that the proposed ‘name network’ method for collecting social network data is a viable alternative to costly and time-consuming collection of users’ data using surveys. The study also demonstrates how social networks produced by the ‘name network’ method can be used to study online classes and to look for evidence of collaborative learning in online learning communities. For example, educators can use name networks as a real time diagnostic tool to identify students who might need additional help or students who may provide such help to others. Future research will evaluate the usefulness of the ‘name network’ method in other types of online communities.

Scaling up online learning strategic and operational checklist

This checklist highlights key questions for institutions that are considering their online learning provision and relates to the Jisc Scaling up online learning (strategic and operational) guide.

Scaling up online learning Curriculum design and support for online learning checklist

This checklist highlights key questions for institutions that are considering their online learning provision and relates to the Jisc Scaling up online learning Curriculum design and support for online learning guide.

Scaling up online learning technology and tools for online learning checklist

This checklist highlights key questions for institutions that are considering their online learning provision and relates to the Jisc Scaling up online learning technology and tools for online learning guide.

Finnish Preclinical and Clinical Medical Students as Strategic L2 English Learners: Language Learning Strategies and Communicating with Patients

This thesis focused on medical students’ language learning strategies for patient encounters. The research questions concerned the types of learning strategies that medical students use and the differences between the preclinical students and the clinical students, two groups who have had varying amounts of experience with patients. Additionally, strategy use was examined through activity systems to gain information on the context of language learning strategy use in order to learn language for patient encounters. In total, 130 first-year medical students (preclinical) and 39 fifth-year medical students (clinical) participated in the study by filling in a questionnaire on language learning strategies. In addition, two students were interviewed in order to create activity systems for the medical students at different stages of their studies. The study utilised both quantitative and qualitative research methods; the analysis of the results relies on Oxford’s Strategic Self-Regulation Model in the quantitative part and on activity theory in the qualitative part. The theoretical sections of the study introduced earlier research and theories regarding English for specific purposes, language learning strategies and activity theory. The results indicated that the medical students use affective, sociocultural-interactive and metasociocultural-interactive strategies often and avoid using negative strategies, which hinder language learning or cease communication altogether. Slight differences between the preclinical and clinical students were found, as clinical students appear to use affective and metasociocultural-interactive strategies more frequently compared to the preclinical students. The activity systems of the two students interviewed were rather similar. The students were at different stages of their studies, but their opinions were very similar. Both reported the object of learning to be mutual understanding between the patient and the doctor, which in part explains the preference for strategies that support communication and interaction. The results indicate that the nature of patient encounters affects the strategy use of the medical students at least to some extent.

South West College: A whole-college approach to online learning and assessment

In 2013, South West College created a virtual college running synchronously alongside the physical college. Three years later, significant progress has been made towards offering online learning and assessment to learners based at home and abroad.

Does a peer model’s task proficiency influence children’s solution choice and innovation?

The current study investigated whether 4- to 6-year-old children’s task solution choice was influenced by the past proficiency of familiar peer models and the children’s personal prior task experience. Peer past proficiency was established through behavioral assessments of interactions with novel tasks alongside peer and teacher predictions of each child’s proficiency. Based on these assessments, one peer model with high past proficiency and one age-, sex-, dominance-, and popularity-matched peer model with lower past proficiency were trained to remove a capsule using alternative solutions from a three-solution artificial fruit task. Video demonstrations of the models were shown to children after they had either a personal successful interaction or no interaction with the task. In general, there was not a strong bias toward the high past-proficiency model, perhaps due to a motivation to acquire multiple methods and the salience of other transmission biases. However, there was some evidence of a model-based past-proficiency bias; when the high past-proficiency peer matched the participants’ original solution, there was increased use of that solution, whereas if the high past-proficiency peer demonstrated an alternative solution, there was increased use of the alternative social solution and novel solutions. Thus, model proficiency influenced innovation.

A university e-learning system to enhance higher education teaching environments: a model-base innovative service-orientated clouds intensive evolution approach.

The International Conference on Advanced Materials, Structures and Mechanical Engineering 2015 (ICAMSME 2015) was held on May 29-31, Incheon, South-Korea. The conference was attended by scientists, scholars, engineers and students from universities, research institutes and industries all around the world to present on going research activities. This proceedings volume assembles papers from various professionals engaged in the fields of materials, structures and mechanical engineering.

Scaling up online learning checklist: master version

This checklist highlights key questions for institutions that are considering their online learning provision and relates to all three of the Jisc Scaling up online learning guides.

Online MBPeT dashboard : enabling performance testing as a service in the cloud

In this thesis, tool support is addressed for the combined disciplines of Model-based testing and performance testing. Model-based testing (MBT) utilizes abstract behavioral models to automate test generation, thus decreasing time and cost of test creation. MBT is a functional testing technique, thereby focusing on output, behavior, and functionality. Performance testing, however, is non-functional and is concerned with responsiveness and stability under various load conditions. MBPeT (Model-Based Performance evaluation Tool) is one such tool which utilizes probabilistic models, representing dynamic real-world user behavior patterns, to generate synthetic workload against a System Under Test and in turn carry out performance analysis based on key performance indicators (KPI). Developed at Åbo Akademi University, the MBPeT tool is currently comprised of a downloadable command-line based tool as well as a graphical user interface. The goal of this thesis project is two-fold: 1) to extend the existing MBPeT tool by deploying it as a web-based application, thereby removing the requirement of local installation, and 2) to design a user interface for this web application which will add new user interaction paradigms to the existing feature set of the tool. All phases of the MBPeT process will be realized via this single web deployment location including probabilistic model creation, test configurations, test session execution against a SUT with real-time monitoring of user configurable metric, and final test report generation and display. This web application (MBPeT Dashboard) is implemented with the Java programming language on top of the Vaadin framework for rich internet application development. The Vaadin framework handles the complicated web communications processes and front-end technologies, freeing developers to implement the business logic as well as the user interface in pure Java. A number of experiments are run in a case study environment to validate the functionality of the newly developed Dashboard application as well as the scalability of the solution implemented in handling multiple concurrent users. The results support a successful solution with regards to the functional and performance criteria defined, while improvements and optimizations are suggested to increase both of these factors.