Applying the motivation-hygiene theory as a means of measuring learner satisfaction with blended learning courses in higher education

This study describes research on a postgraduate blended learning programme within the Department of Education at the University of Aveiro in Portugal. It is based on a multi-philosophical paradigm and examines students‟ satisfaction levels through the application of Herzberg‟s Motivation and Hygiene Theory. The main question being addressed in this research is: “Can the Motivation and Hygiene Theory be adopted as a means to measure student satisfaction with their blended learning environment?” Embedded within this research question are four fundamental questions which set the scene for the development of this research study and are explored in greater detail in Chapters 4 and 5 respectively: 1. What are the factors responsible for bringing about learning satisfaction with their b-Learning course? 2. What are the factors responsible for bringing about learning dissatisfaction with their b-Learning course? 3. Can these factors be represented as Motivation and Hygiene factors? 4. Will this method of measuring learning satisfaction lead to a set of guidelines that could be considered as a framework for the development of b-Learning courses? The results indicate that the Motivation and Hygiene Theory or an adapted version such as the Enricher and Enabler Theory proposed in this study could be considered as a plausible means of analysing an institution‟s b-Learning processes. The opportunity to carry out future research is evident and can be varied depending on the research objectives in mind. Examples where further exploration would be beneficial lay within the application of this theory to the wider sector; the use of larger samples, focusing on the teachers, as well as the learners and the application of Web 2.0 technologies as means of gathering information. The results of this research will be of great significance to those areas of education that are interested in locating quick and efficient means by which to evaluate their b-Learning and to no lesser extent e-Learning environments.

Avaliação em contextos de blended learning no ensino superior

The increasing complexity of the Information Society and the Bologna Declaration in the European context has led Higher Education (HE) institutions to revise their curricula courses, as far as the adoption of new strategies for teaching and learning as well as evaluation are concerned. It can also be emphasized that there has been a growing use of eLearning and of blended learning (bLearning) in HE, since these modes of training seem to be a very convenient option for lifelong learning. In this context, quality is taken as an essential goal in the development of the European Space for Education and Training, where HE institutions compete among themselves, and where evaluation is determinant as a promoter of this quality. Considering the problems summarized above, the research developed, based on four published scientific papers, intended to answer a set of research questions related to evaluation of bLearning contexts in HE. The study used diverse techniques and instruments (questionnaires, document analysis, and observation mediated technologies) spanning two methodological approaches: i) study of descriptive and exploratory nature and ii) case studies of bLearning modules. In the first approach an evaluation model for bLearning courses was developed, where we collected and analyzed, at a national level, the opinions of teachers with bLearning experience about the model dimensions. The case studies presented are post graduation curricular units, where bLearning teaching, learning and evaluation strategies were explored and evaluated, namely peer assessment. The main contributions of the first approach are: the process of questioning around the evaluation of bLearning courses, namely the quality assurance criteria for bLearning, as well as the model developed, providing a framework of theoretical, methodological and empirical elements that can be adapted in similar contexts. From the case studies emerged: the developed evaluation guidelines and the data collection instruments, in order to disseminate evaluation “best practices” that may be useful for other units in similar contexts. Regarding the recommendations about the evaluation of teaching of bLearning courses we emphasize: the use of versatile evaluation objects; the evaluation throughout the process and not just at the end; and the involvement of multiple evaluators, including students (whose feedback is essential to monitor the quality of teaching and learning). From the case studies we highlight: the need for discussion of evaluation frameworks to explore, and consequent increase in the transparency of the evaluation process; the increased interaction between groups; and the peer assessment as a strategy to promote active and autonomous learning. In addition to the contributions and recommendations for practice and research in the area of evaluation in bLearning contexts in HE, listed above, it also emerged from this study useful guidelines regarding educational evaluation in bLearning contexts, in order to improve the quality of teaching, learning and evaluation in such contexts.

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.

Master in Innovative Tourism Development: a blended learning experience in the Polytechnic Institute of Viana do Castelo

This chapter analyses a Portuguese HEI’s first experience with blended learning. Focusing on the Master in Innovative Tourism Development currently being held at the Superior School of Technology and Management of the Polytechnic Institute of Viana do Castelo, it presents the institutional background and rationale behind the course’s implementation, identifying its strengths and weaknesses, as well as areas of potential development. Based on an evaluation research carried out throughout the course’s first three editions and that involved students, faculty and institutional leaders, it summarizes the main results of a long term-study, putting forth a set of recommendations for improvements and defining potential areas of intervention in future editions of the course.