Enseñar a aprender a pensar en los centros educativos, incluso en las actividades de evaluación.= Teaching to learn how to think at schools, even within assessment activities

El auténtico protagonismo de los centros educativostiene que dirigirse a ayudar a pensar a sus alumnos y aenseñarlos a aprender, es decir, el docente tiene queenseñar estrategias de aprendizaje y debe promover elesfuerzo del estudiante para facilitar la construcción deesquemas y el aprendizaje permanente.El profesor debe utilizar cualquier situación deaprendizaje para enseñar dichas estrategias deaprendizaje, incluso en las situaciones de evaluación;por lo tanto, en este trabajo se sugiere que en lasevaluaciones de los alumnos y alumnas se tenga encuenta la metacognición como factor fundamental en elaprendizaje y la enseñanza

Blended learning and student time-use in engineering education

Aiheen laajempi artikkeli on julkaistu konferenssi-CD:llä.

Machine Learning and Clinical Text. Supporting Health Information Flow

Fluent health information flow is critical for clinical decision-making. However, a considerable part of this information is free-form text and inabilities to utilize it create risks to patient safety and cost-­effective hospital administration. Methods for automated processing of clinical text are emerging. The aim in this doctoral dissertation is to study machine learning and clinical text in order to support health information flow.First, by analyzing the content of authentic patient records, the aim is to specify clinical needs in order to guide the development of machine learning applications.The contributions are a model of the ideal information flow,a model of the problems and challenges in reality, and a road map for the technology development. Second, by developing applications for practical cases,the aim is to concretize ways to support health information flow. Altogether five machine learning applications for three practical cases are described: The first two applications are binary classification and regression related to the practical case of topic labeling and relevance ranking.The third and fourth application are supervised and unsupervised multi-class classification for the practical case of topic segmentation and labeling.These four applications are tested with Finnish intensive care patient records.The fifth application is multi-label classification for the practical task of diagnosis coding. It is tested with English radiology reports.The performance of all these applications is promising. Third, the aim is to study how the quality of machine learning applications can be reliably evaluated.The associations between performance evaluation measures and methods are addressed,and a new hold-out method is introduced.This method contributes not only to processing time but also to the evaluation diversity and quality. The main conclusion is that developing machine learning applications for text requires interdisciplinary, international collaboration. Practical cases are very different, and hence the development must begin from genuine user needs and domain expertise. The technological expertise must cover linguistics,machine learning, and information systems. Finally, the methods must be evaluated both statistically and through authentic user-feedback.

Verenpaineen mittaamisen opettaminen sairaanhoitaja- ja terveydenhoitajaopiskelijoille

Teaching the measurement of blood pressure for both nursing and public health nursing students The purpose of this two-phase study was to develop the teaching of blood pressure measurement within the nursing degree programmes of the Universities of Applied Sciences. The first survey phase described what and how blood pressure measurement was taught within nursing degree programmes. The second intervention phase (2004-2005) evaluated first academic year nursing and public health nursing students’ knowledge and skills results for blood pressure measurement. Additionally, the effect on the Taitoviikko experimental group students’ blood pressure measurement knowledge and skills level. A further objective was to construct models for an instrument (RRmittTest) to evaluate nursing students measurement of blood pressure (2003-2009). The research data for the survey phase were collected from teachers (total sampling, N=107, response rate 77%) using a specially developed RRmittopetus-questionnaire. Quasi-experimental study data on the RRmittTest-instrument was collected from students (purposive sampling, experimental group, n=29, control group, n=44). The RRmittTest consisted of a test of knowledge (Tietotesti) and simulation-based test (TaitoSimkäsi and Taitovideo) of skills. Measurements were made immediately after the teaching and in clinical practice. Statistical methods were used to analyse the results and responses to open-ended questions were organised and classified. Due to the small amount of materials involved and the results of distribution tests of the variables, non-parametric analytic methods were mainly used. Experimental group and control group similar knowledge and skills teaching was based on the results of the national survey phase (RRmittopetus) questionnaire results. Experimental group teaching includes the supervised Taitoviikko teaching method. During Taitoviikko students studied blood pressure measurement at the municipal hospital in a real nursing environment, guided by a teacher and a clinical nursing professional. In order to evaluate both learning and teaching the processes and components of blood pressure measurement were clearly defined as follows: the reliability of measurement instruments, activities preceding blood pressure measurement, technical execution of the measurement, recording, lifestyle guidance and measurement at home (self-monitoring). According to the survey study, blood pressure measurement is most often taught at Universities of Applied Sciences, separately, as knowledge (teaching of theory, 2 hours) and skills (classroom practice, 4 hours). The teaching was implemented largely in a classroom and was based mainly on a textbook. In the intervention phase the students had good knowledge of blood pressure measurement. However, their blood pressure measurement skills were deficient and the control group students, in particular, were highly deficient. Following in clinical practice the experimental group and control group students’ blood pressure measurement recording knowledge improve and experimental groups declined lifestyle guidance. Skills did not improve within any of the components analysed. The control groups` skills on the whole, declined statistically.There was a significant decline amongst the experimental group although only in one component measured. The results describe the learning results for first academic year students and no parallel conclusions should be drawn when considering any learning results for graduating students. The results support the use and further development of the Taitoviiko teaching method. The RRmittTest developed for the study should be assessed and the results seen from a negative perspective. This evaluation tool needs to be developed and retested.

Towards the Best A++ Rating Productivity of Research and Teaching in Finnish Universities

Tämän tutkimusraportin suomenkielinen versio on osoitteessa: http://urn.fi/URN:ISBN:978-951-29-4509-2

Organizational learning from customer interaction

In the fierce competition of today‟s business world an organization‟s capacity to learn maybe its only competitive advantage. This research aims at increasing the understanding on how organizational learning from the customer happens in technology companies. In doing so it provides a synthesized definition of organizational learning and investigates processes of organizational learning within technology companies. A qualitative research method and in-depth interviews with different sized high technology companies, as applied here, enables in-depth study of the learning processes. Research contributes to the understanding of what type of knowledge firms acquire, how new knowledge is transferred and used in a learning firm‟s routines and processes. Research findings show that SMEs and large size companies also, depending on their position in the software value chain, consider different knowledge types as most important and that they use different learning methods to acquire knowledge from their customers.

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.

Mobile learning and video experience in delivering digital content

In recent years, the worldwide distribution of smartphone devices has been growing rapidly. Mobile technologies are evolving fast, a situation which provides new possibilities for mobile learning applications. Along with new delivery methods, this development enables new concepts for learning. This study focuses on the effectiveness and experience of a mobile learning video promoting the key features of a specific device. Through relevant learning theories, mobile technologies and empirical findings, the thesis presents the key elements for a mobile learning video that are essential for effective learning. This study also explores how previous experience with mobile services and knowledge of a mobile handset relate to final learning results. Moreover, this study discusses the optimal delivery mechanisms for a mobile video. The target group for the study consists of twenty employees of a Sanoma Company. The main findings show that the individual experience of learning and the actual learning results may differ and that the design for certain video elements, such as sound and the presentation of technical features, can have an impact on the experience and effectiveness of a mobile learning video. Moreover, a video delivery method based on cloud technologies and HTML5 is suggested to be used in parallel with standalone applications.

Adult education policy in the European Union during the Lisbon decade : the shift to vocational adult learning and work skills matching

This doctoral dissertation investigates the adult education policy of the European Union (EU) in the framework of the Lisbon agenda 2000–2010, with a particular focus on the changes of policy orientation that occurred during this reference decade. The year 2006 can be considered, in fact, a turning point for the EU policy-making in the adult learning sector: a radical shift from a wide--ranging and comprehensive conception of educating adults towards a vocationally oriented understanding of this field and policy area has been observed, in particular in the second half of the so--called ‘Lisbon decade’. In this light, one of the principal objectives of the mainstream policy set by the Lisbon Strategy, that of fostering all forms of participation of adults in lifelong learning paths, appears to have muted its political background and vision in a very short period of time, reflecting an underlying polarisation and progressive transformation of European policy orientations. Hence, by means of content analysis and process tracing, it is shown that the new target of the EU adult education policy, in this framework, has shifted from citizens to workers, and the competence development model, borrowed from the corporate sector, has been established as the reference for the new policy road maps. This study draws on the theory of governance architectures and applies a post-ontological perspective to discuss whether the above trends are intrinsically due to the nature of the Lisbon Strategy, which encompasses education policies, and to what extent supranational actors and phenomena such as globalisation influence the European governance and decision--making. Moreover, it is shown that the way in which the EU is shaping the upgrading of skills and competences of adult learners is modeled around the needs of the ‘knowledge economy’, thus according a great deal of importance to the ‘new skills for new jobs’ and perhaps not enough to life skills in its broader sense which include, for example, social and civic competences: these are actually often promoted but rarely implemented in depth in the EU policy documents. In this framework, it is conveyed how different EU policy areas are intertwined and interrelated with global phenomena, and it is emphasised how far the building of the EU education systems should play a crucial role in the formation of critical thinking, civic competences and skills for a sustainable democratic citizenship, from which a truly cohesive and inclusive society fundamentally depend, and a model of environmental and cosmopolitan adult education is proposed in order to address the challenges of the new millennium. In conclusion, an appraisal of the EU’s public policy, along with some personal thoughts on how progress might be pursued and actualised, is outlined.

Employees’ continuous learning and job satisfaction - effects on productivity

In today’s knowledge intense economy the human capital is a source for competitive advantage for organizations. Continuous learning and sharing the knowledge within the organization are important to enhance and utilize this human capital in order to maximize the productivity. The new generation with different views and expectations of work is coming to work life giving its own characteristics on learning and sharing. Work should offer satisfaction so that the new generation employees would commit to organizations. At the same time organizations have to be able to focus on productivity to survive in the competitive market. The objective of this thesis is to construct a theory based framework of productivity, continuous learning and job satisfaction and further examine this framework and its applications in a global organization operating in process industry. Suggestions for future actions are presented for this case organization. The research is a qualitative case study and the empiric material was gathered by personal interviews concluding 15 employee and one supervisor interview. Results showed that more face to face interaction is needed between employees for learning because much of the knowledge of the process is tacit and so difficult to share in other ways. Offering these sharing possibilities can also impact positively to job satisfaction because they will increase the sense of community among employees which was found to be lacking. New employees demand more feedback to improve their learning and confidence. According to the literature continuous learning and job satisfaction have a relative strong relationship on productivity. The employee’s job description in the case organization has moved towards knowledge work due to continuous automation and expansion of the production process. This emphasizes the importance of continuous learning and means that productivity can be seen also from quality perspective. The normal productivity output in the case organization is stable and by focusing on the quality of work by improving continuous learning and job satisfaction the upsets in production can be handled and prevented more effectively. Continuous learning increases also the free human capital input and utilization of it and this can breed output increasing innovations that can increase productivity in long term. Also job satisfaction can increase productivity output in the end because employees will work more efficiently, not doing only the minimum tasks required. Satisfied employees are also found participating more in learning activities.

Effects of caffeine on learning and memory in rats tested in the Morris water maze

We studied some of the characteristics of the improving effect of the non-specific adenosine receptor antagonist, caffeine, using an animal model of learning and memory. Groups of 12 adult male Wistar rats receiving caffeine (0.3-30 mg/kg, ip, in 0.1 ml/100 g body weight) administered 30 min before training, immediately after training, or 30 min before the test session were tested in the spatial version of the Morris water maze task. Post-training administration of caffeine improved memory retention at the doses of 0.3-10 mg/kg (the rats swam up to 600 cm less to find the platform in the test session, P<=0.05) but not at the dose of 30 mg/kg. Pre-test caffeine administration also caused a small increase in memory retrieval (the escape path of the rats was up to 500 cm shorter, P<=0.05). In contrast, pre-training caffeine administration did not alter the performance of the animals either in the training or in the test session. These data provide evidence that caffeine improves memory retention but not memory acquisition, explaining some discrepancies among reports in the literature.

Informal learning and competence development during a management trainee program

The purpose of this research was to study how management trainee program participants experienced the program with respect to their learning and competence development. Additionally, the purpose was also to examine what the trainees learned and how the learning occurred. Furthermore, factors affecting learning in the workplace were examined. The theoretical framework of this research was formed utilizing individual competence and informal learning frameworks. Research was conducted as a single case study and data was gathered by thematic interviews. The results of this research indicate that the trainees experienced the program as a good method for learning the overall picture of the organization and its business. Regarding competence development, especially knowledge- and cognitive competence categories were developed during the program. The best learning outcomes were achieved through learning by doing, in co-operation with others, and learning from others. The results indicate that the planning of the program and its structure have a significant effect on learning. Furthermore, a sufficient level of challenge was experienced as being important for the quality of the learning as well.

Effects of isoflavone on the learning and memory of women in menopause: a double-blind placebo-controlled study

Hormone decline is common to all women during aging and, associated with other factors, leads to cognitive impairment. Its replacement enhances cognitive performance, but not all women present a clinical and family or personal history that justifies its use, mainly women with a history of cancer. The aim of this study was to determine whether a daily oral dose of 80 mg of isoflavone extract for 4 months can produce benefits in women with low hormone levels, contributing to improvement in cognitive aspects. The sample comprised 50- to 65-year-old women whose menstruation had ceased at least 1 year before and who had not undergone hormone replacement. The volunteers were allocated to two groups of 19 individuals each, i.e., isoflavone and placebo. There was a weak correlation between menopause duration and low performance in the capacity to manipulate information (central executive). We observed an increase in the capacity to integrate information in the group treated with isoflavone, but no improvement in the capacity to form new memories. We did not observe differences between groups in terms of signs and symptoms suggestive of depression according to the Geriatric Depression Scale. Our results point to a possible beneficial effect of isoflavone on some abilities of the central executive. These effects could also contribute to minimizing the impact of memory impairment. Further research based on controlled clinical trials is necessary to reach consistent conclusions.