Fostering Collaborative Knowledge Building by the Effective Provision of Knowledge about the Discussion Process

Peer-reviewed

A conceptual model for grid learning services automatic composition

Peer-reviewed

What leads people to keep on e-learning? An empirical analysis of users' experiences and their effects on continuance intention

User retention is a major goal for higher education institutions running their teaching and learning programmes online. This is the first investigation into how the senses of presence and flow, together with perceptions about two central elements of the virtual education environment (didactic resource quality and instructor attitude), facilitate the user¿s intention to continue e-learning. We use data collected from a large sample survey of current users in a pure e-learning environment along with objective data about their performance. The results provide support to the theoretical model. The paper further offers practical suggestions for institutions and instructors who aim to provide effective e-learning experiences.

Inter organizational learning within and by innovation networks

The thesis deals with the phenomenon of learning between organizations in innovation networks that develop new products, services or processes. Inter organizational learning is studied especially at the level of the network. The role of the network can be seen as twofold: either the network is a context for inter organizational learning, if the learner is something else than the network (organization, group, individual), or the network itself is the learner. Innovations are regarded as a primary source of competitiveness and renewal in organizations. Networking has become increasingly common particularly because of the possibility to extend the resource base of the organization through partnerships and to concentrate on core competencies. Especially in innovation activities, networks provide the possibility to answer the complex needs of the customers faster and to share the costs and risks of the development work. Networked innovation activities are often organized in practice as distributed virtual teams, either within one organization or as cross organizational co operation. The role of technology is considered in the research mainly as an enabling tool for collaboration and learning. Learning has been recognized as one important collaborative process in networks or as a motivation for networking. It is even more important in the innovation context as an enabler of renewal, since the essence of the innovation process is creating new knowledge, processes, products and services. The thesis aims at providing enhanced understanding about the inter organizational learning phenomenon in and by innovation networks, especially concentrating on the network level. The perspectives used in the research are the theoretical viewpoints and concepts, challenges, and solutions for learning. The methods used in the study are literature reviews and empirical research carried out with semi structured interviews analyzed with qualitative content analysis. The empirical research concentrates on two different areas, firstly on the theoretical approaches to learning that are relevant to innovation networks, secondly on learning in virtual innovation teams. As a result, the research identifies insights and implications for learning in innovation networks from several viewpoints on organizational learning. Using multiple perspectives allows drawing a many sided picture of the learning phenomenon that is valuable because of the versatility and complexity of situations and challenges of learning in the context of innovation and networks. The research results also show some of the challenges of learning and possible solutions for supporting especially network level learning.

The Transformation of Practical Teaching Focusing on Dialogic Learning

This study investigates the transformation of practical teaching in a Catalan school, connected to the design, implementation and development of project-based learning, and focusing on dialogic learning to investigate its limits and possibilities. Qualitative and design-based research (DBR) methods are applied. These methods are based on empirical educational research with the theory-driven of learning environments. DBR is proposed and applied using practical guidance for the teachers of the school. It can be associated with the current proposals for Embedding Social Sciences and Humanities in the Horizon 2020 Societal Challenges. This position statement defends the social sciences and the humanities as the most fundamental and important ideas to face all societal challenges. The results of this study show that before the training process, teachers apply dialogic learning in specific moments (for example, when they speak about the weekend); however, during the process and after the process, they work systematically with dialogic learning through the PEPT: they start and finish every activity with a individual and group reflection about their own processes, favouring motivation, reasoning and the implication of all the participants. These results prove that progressive transformations of teaching practice benefit cooperative work in class

Student experiences in a course blended learning

Fascination is a project for design students, developed jointly by the Technical University of Catalonia (UPC) and the University of Technology Thonburi (KMUTT), which works with two groups of students, one group of participants in Spain and another group in Thailand where, hands-on activities, a range of technologies are used to prepare students for the lessons, through learning activities and content. This research paper presents the test of both a general model and a tool for measuring the participants’ experiences in a course that uses a blended learning methodology, with the aim of collecting empirical evidence to justify the effort of applying this methodology, based on the participants’ satisfaction. The procedure used in the conceptualization of the survey, the generation of topics, the collection of data, and the validation of the scale of various items are described here. The information, provided by the 26 people surveyed about the course and the virtual environment that was used, was analyzed to measure their perceptions and explore possible relations. Finally the conclusions of the research and the future work are presented.

Consideraciones metodológicas para la enseñanza y el aprendizaje del deporte escolar = Methodological considerations for the teaching and learning of school sport

Sport is a fundamental content in the teaching and learning of Physical Education independently of whether it is seen assuch by some authors. In whichever case according to the treatment that we give it, it will have sufficient educationalpotential without forgetting that it is the student who is the important figure in the process. To achieve the objectives wemust facilitate practices that are in agreement with the indispensable ethical principles to try to bring about a meaningfuland functional learning. The methodological criteria that we present in this article have this intention helped by examplesthat make it easier to understand the teaching learning process

Data Consistency by a Metadata Management Solution

This thesis consists of three main theoretical themes: quality of data, success of information systems, and metadata in data warehousing. Loosely defined, metadata is descriptive data about data, and, in this thesis, master data means reference data about customers, products etc. The objective of the thesis is to contribute to an implementation of a metadata management solution for an industrial enterprise. The metadata system incorporates a repository, integration, delivery and access tools, as well as semantic rules and procedures for master data maintenance. It targets to improve maintenance processes and quality of hierarchical master data in the case company’s informational systems. That should bring benefits to whole organization in improved information quality, especially in cross-system data consistency, and in more efficient and effective data management processes. As the result of this thesis, the requirements for the metadata management solution in case were compiled, and the success of the new information system and the implementation project was evaluated.

Promoting Programming Learning. Engagement, Automatic Assessment with Immediate Feedback in Visualizations

The skill of programming is a key asset for every computer science student. Many studies have shown that this is a hard skill to learn and the outcomes of programming courses have often been substandard. Thus, a range of methods and tools have been developed to assist students’ learning processes. One of the biggest fields in computer science education is the use of visualizations as a learning aid and many visualization based tools have been developed to aid the learning process during last few decades. Studies conducted in this thesis focus on two different visualizationbased tools TRAKLA2 and ViLLE. This thesis includes results from multiple empirical studies about what kind of effects the introduction and usage of these tools have on students’ opinions and performance, and what kind of implications there are from a teacher’s point of view. The results from studies in this thesis show that students preferred to do web-based exercises, and felt that those exercises contributed to their learning. The usage of the tool motivated students to work harder during their course, which was shown in overall course performance and drop-out statistics. We have also shown that visualization-based tools can be used to enhance the learning process, and one of the key factors is the higher and active level of engagement (see. Engagement Taxonomy by Naps et al., 2002). The automatic grading accompanied with immediate feedback helps students to overcome obstacles during the learning process, and to grasp the key element in the learning task. These kinds of tools can help us to cope with the fact that many programming courses are overcrowded with limited teaching resources. These tools allows us to tackle this problem by utilizing automatic assessment in exercises that are most suitable to be done in the web (like tracing and simulation) since its supports students’ independent learning regardless of time and place. In summary, we can use our course’s resources more efficiently to increase the quality of the learning experience of the students and the teaching experience of the teacher, and even increase performance of the students. There are also methodological results from this thesis which contribute to developing insight into the conduct of empirical evaluations of new tools or techniques. When we evaluate a new tool, especially one accompanied with visualization, we need to give a proper introduction to it and to the graphical notation used by tool. The standard procedure should also include capturing the screen with audio to confirm that the participants of the experiment are doing what they are supposed to do. By taken such measures in the study of the learning impact of visualization support for learning, we can avoid drawing false conclusion from our experiments. As computer science educators, we face two important challenges. Firstly, we need to start to deliver the message in our own institution and all over the world about the new – scientifically proven – innovations in teaching like TRAKLA2 and ViLLE. Secondly, we have the relevant experience of conducting teaching related experiment, and thus we can support our colleagues to learn essential know-how of the research based improvement of their teaching. This change can transform academic teaching into publications and by utilizing this approach we can significantly increase the adoption of the new tools and techniques, and overall increase the knowledge of best-practices. In future, we need to combine our forces and tackle these universal and common problems together by creating multi-national and multiinstitutional research projects. We need to create a community and a platform in which we can share these best practices and at the same time conduct multi-national research projects easily.

Verbal learning in mild cognitive impairment and alzheimer's disease : behavioural and neural approaches

The main focus of the present thesis was at verbal episodic memory processes that are particularly vulnerable to preclinical and clinical Alzheimer’s disease (AD). Here these processes were studied by a word learning paradigm, cutting across the domains of memory and language learning studies. Moreover, the differentiation between normal aging, mild cognitive impairment (MCI) and AD was studied by the cognitive screening test CERAD. In study I, the aim was to examine how patients with amnestic MCI differ from healthy controls in the different CERAD subtests. Also, the sensitivity and specificity of the CERAD screening test to MCI and AD was examined, as previous studies on the sensitivity and specificity of the CERAD have not included MCI patients. The results indicated that MCI is characterized by an encoding deficit, as shown by the overall worse performance on the CERAD Wordlist learning test compared with controls. As a screening test, CERAD was not very sensitive to MCI. In study II, verbal learning and forgetting in amnestic MCI, AD and healthy elderly controls was investigated with an experimental word learning paradigm, where names of 40 unfamiliar objects (mainly archaic tools) were trained with or without semantic support. The object names were trained during a 4-day long period and a follow-up was conducted one week, 4 weeks and 8 weeks after the training period. Manipulation of semantic support was included in the paradigm because it was hypothesized that semantic support might have some beneficial effects in the present learning task especially for the MCI group, as semantic memory is quite well preserved in MCI in contrast to episodic memory. We found that word learning was significantly impaired in MCI and AD patients, whereas forgetting patterns were similar across groups. Semantic support showed a beneficial effect on object name retrieval in the MCI group 8 weeks after training, indicating that the MCI patients’ preserved semantic memory abilities compensated for their impaired episodic memory. The MCI group performed equally well as the controls in the tasks tapping incidental learning and recognition memory, whereas the AD group showed impairment. Both the MCI and the AD group benefited less from phonological cueing than the controls. Our findings indicate that acquisition is compromised in both MCI and AD, whereas long13 term retention is not affected to the same extent. Incidental learning and recognition memory seem to be well preserved in MCI. In studies III and IV, the neural correlates of naming newly learned objects were examined in healthy elderly subjects and in amnestic MCI patients by means of positron emission tomography (PET) right after the training period. The naming of newly learned objects by healthy elderly subjects recruited a left-lateralized network, including frontotemporal regions and the cerebellum, which was more extensive than the one related to the naming of familiar objects (study III). Semantic support showed no effects on the PET results for the healthy subjects. The observed activation increases may reflect lexicalsemantic and lexical-phonological retrieval, as well as more general associative memory mechanisms. In study IV, compared to the controls, the MCI patients showed increased anterior cingulate activation when naming newly learned objects that had been learned without semantic support. This suggests a recruitment of additional executive and attentional resources in the MCI group.

Problems and potentialities of e-Learning for regular undergraduate courses in emergency medicine

BACKGROUND: E-learning techniques are spreading at great speed in medicine, raising concerns about the impact of adopting them. Websites especially designed to host courses are becoming more common. There is a lack of evidence that these systems could enhance student knowledge acquisition. GOAL: To evaluate the impact of using dedicated-website tools over cognition of medical students exposed to a first-aid course. METHODS: Prospective study of 184 medical students exposed to a twenty-hour first-aid course. We generated a dedicated-website with several sections (lectures, additional reading material, video and multiple choice exercises). We constructed variables expressing the student's access to each section. The evaluation was composed of fifty multiple-choice tests, based on clinical problems. We used multiple linear regression to adjust for potential confounders. RESULTS: There was no association of website intensity of exposure and the outcome - beta-coeficient 0.27 (95%CI - 0.454 - 1.004). These findings were not altered after adjustment for potential confounders - 0.165 (95%CI -0.628 - 0.960). CONCLUSION: A dedicated website with passive and active capabilities for aiding in person learning had not shown association with a better outcome.

Learning Robot Environment through Simulation

Traditionally simulators have been used extensively in robotics to develop robotic systems without the need to build expensive hardware. However, simulators can be also be used as a “memory”for a robot. This allows the robot to try out actions in simulation before executing them for real. The key obstacle to this approach is an uncertainty of knowledge about the environment. The goal of the Master’s Thesis work was to develop a method, which allows updating the simulation model based on actual measurements to achieve a success of the planned task. OpenRAVE was chosen as an experimental simulation environment on planning,trial and update stages. Steepest Descent algorithm in conjunction with Golden Section search procedure form the principle part of optimization process. During experiments, the properties of the proposed method, such as sensitivity to different parameters, including gradient and error function, were examined. The limitations of the approach were established, based on analyzing the regions of convergence.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Playing to Learn: Business Simulation Games as Leadership Learning Environments

The aim of this dissertation is to investigate if participation in business simulation gaming sessions can make different leadership styles visible and provide students with experiences beneficial for the development of leadership skills. Particularly, the focus is to describe the development of leadership styles when leading virtual teams in computer-­supported collaborative game settings and to identify the outcomes of using computer simulation games as leadership training tools. To answer to the objectives of the study, three empirical experiments were conducted to explore if participation in business simulation gaming sessions (Study I and II), which integrate face-­to-­face and virtual communication (Study III and IV), can make different leadership styles visible and provide students with experiences beneficial for the development of leadership skills. In the first experiment, a group of multicultural graduate business students (N=41) participated in gaming sessions with a computerized business simulation game (Study III). In the second experiment, a group of graduate students (N=9) participated in the training with a ‘real estate’ computer game (Study I and II). In the third experiment, a business simulation gaming session was organized for graduate students group (N=26) and the participants played the simulation game in virtual teams, which were organizationally and geographically dispersed but connected via technology (Study IV). Each team in all experiments had three to four students and students were between 22 and 25 years old. The business computer games used for the empirical experiments presented an enormous number of complex operations in which a team leader needed to make the final decisions involved in leading the team to win the game. These gaming environments were interactive;; participants interacted by solving the given tasks in the game. Thus, strategy and appropriate leadership were needed to be successful. The training was competition-­based and required implementation of leadership skills. The data of these studies consist of observations, participants’ reflective essays written after the gaming sessions, pre-­ and post-­tests questionnaires and participants’ answers to open-­ ended questions. Participants’ interactions and collaboration were observed when they played the computer games. The transcripts of notes from observations and students dialogs were coded in terms of transactional, transformational, heroic and post-­heroic leadership styles. For the data analysis of the transcribed notes from observations, content analysis and discourse analysis was implemented. The Multifactor Leadership Questionnaire (MLQ) was also utilized in the study to measure transformational and transactional leadership styles;; in addition, quantitative (one-­way repeated measures ANOVA) and qualitative data analyses have been performed. The results of this study indicate that in the business simulation gaming environment, certain leadership characteristics emerged spontaneously. Experiences about leadership varied between the teams and were dependent on the role individual students had in their team. These four studies showed that simulation gaming environment has the potential to be used in higher education to exercise the leadership styles relevant in real-­world work contexts. Further, the study indicated that given debriefing sessions, the simulation game context has much potential to benefit learning. The participants who showed interest in leadership roles were given the opportunity of developing leadership skills in practice. The study also provides evidence of unpredictable situations that participants can experience and learn from during the gaming sessions. The study illustrates the complex nature of experiences from the gaming environments and the need for the team leader and role divisions during the gaming sessions. It could be concluded that the experience of simulation game training illustrated the complexity of real life situations and provided participants with the challenges of virtual leadership experiences and the difficulties of using leadership styles in practice. As a result, the study offers playing computer simulation games in small teams as one way to exercise leadership styles in practice.

Organisational learning and knowledge acquisition. A case study of internationalising manufacturers of wood-based prefabricated buildings

The study investigates organisational learning and knowledge acquisition of wood-based prefabricated building manufacturers. This certain group of case companies was chosen, because their management and their employees generally have a strong manufacturing and engineering background, while the housing sector is characterised by national norms, regulations, as well as local building styles. Considering this setting, it was investigated, how the case companies develop organisational learning capabilities, acquire and transfer knowledge for their internationalisation. The theoretical framework of this study constitutes the knowledge-based conceptualisation of internationalisation, which combines the traditional internationalisation process, as well as the international new venture perspective based on their commonalities in the knowledge-based view of the firm. Different theories of internationalisation, including the network-perspective, were outlined and a framework on organisational learning and knowledge acquisition was established. The empirical research followed a qualitative approach, deploying a multiple-case study with five case companies from Austria, Finland and Germany. In the study, the development of the wood-based prefabricated building industry and of the case companies are described, and the motives, facilitators and challenges for foreign expansion, as well as the companies’ internationalisation approaches are compared. Different methods of how companies facilitate the knowledge-exchange or learn about new markets are also outlined. Experience, market knowledge and personal contacts are considered essential for the internationalisation process. The major finding of the study is that it is not necessary to acquire the market knowledge internally in a slow process as proposed by the Uppsala model. In four cases companies engaged knowledge in symbiotic relations with local business partners. Thereby, the building manufacturers contribute their design and production capabilities, and in return, their local partners provide them with knowledge about the market and local regulations; while they manage the sales and construction operations. Thus, the study provides strong evidence for the propositions of network perspective. One case company developed the knowledge internally in a gradual process: it entered the market sequentially with several business lines, showing an increasing level of complexity. In both of the observed strategies, single-loop and double-loop learning processes occurred.