Innovatiivisuus ja yhteistoiminnallinen oppiminen liike-elämässä ja opetuksessa

Innovativity and cooperative learning in business life and teaching The study comprises four articles and a summary, which analyse the concepts of innovation and innovativity and the cooperative learning connected to the innovation processes of companies. Th e study comments on what is innovativity. Another point of inspection is how the cooperative learning theory constructed on the basis of educational science lends it self to inspecting business innovations. At the end, we ponder upon how the concepts of innovativity can be used to inspect teachers’ activities. The studied business innovations were chosen on after considering expert statements. The key personnel in the innovation process were interviewed. The concept of innovation is inspected especially with the aid of concept analysis. The pedagogical innovativity study based on the view of education specialists in quantitative and the data was collected with a questionnaire created on the basis of previous research and literature. Different research methods were used in the studies, thus mixed methods were used for the whole of the doctoral thesis. The starting point for the whole, grounded theory, has to be understood here as a research strategy as well as a research method and data analysis method. The results show that innovativity is creativity that demands versatile learning and has positive eff ects on the process or event in practice. The results also show that in successful innovation businesses cooperative learning is something that has been found instead of searched. Cooperative learning can be seen as characteristic for innovation businesses. The five stage division of cooperative learning creates a useful method of analysing learning in innovation businesses. Innovativity connected to cooperative learning seems to make the creation of innovations possible. In addition to this, the results also show that a teacher’s innovativity is connected to reforms and an attitude that embraces them. Versatile learning in the individual and community is a prerequisite for innovativity. It is important that the teacher has a continuous will to renew teaching methods and combine work and teaching methods. The basic requirements are pedagogical vocational profi ciency and resourcefulness in everyday work.

Resa i röstens landskap : en narrativ studie av hur lärare blir professionella röstanvändare

The theme of this thesis is the learning process that occurs when teachers become professional voice users. The aim is to explore what it (really) means to become a professional voice user in a teaching profession; thereby developing an understanding of how future education in this field can be arranged so as to both effectively prevent vocal problems and to develop oral didactical competence among teachers. The ambition is to describe, interpret, and understand the learning process through a combination of emic and ethic research perspectives. The theoretical frame of reference reflects the cross disciplinary character of the thesis. Voice problems are common among both student teachers and inservice teachers and adversely affect professional competence, identity and quality of life. Additionally, vocal problems are proven to have a negative impact on pupils´ learning. The individual elements of learning are explored in the light of experiential learning theory and transformative learning theory. The social elements of learning are explored in relation to the theory of situated learning. In addition, theories of teacher professionalisation in terms of competence and identity are outlined. The empirical study has a longitudinal and multi method character. It is anchored in a phenomenological hermeneutical tradition, more specifically in narrative inquiry. The point of departure is the learning experiences of ten student teachers, who attended a ten week long course on voice production as part of their teacher training at Åbo Akademi University, in the autumn of 2002 and the spring of 2003. Four interviews in the form of conversations were conducted with each participant. These were crystallised with a process diary, a Swedish Voice Handicap Index, a voice observation, and a video observation. A fifth interview was conducted with each participant five years post teacher training, in the spring of 2008. Participant observation was also conducted throughout the course. The research materials have been analysed and interpreted narratively using a phenomenological hermeneutical method. The results are presented descriptively as individual narratives, which are reflected in logopedic research materials. Learning is here understood as emergent awareness. This is followed by a meta narrative concerning learning as experiences in the four dimensions body, thought, feeling, and relation. Finally, interpretation is expressed with respect to the theory of relational education. Learning is here understood as a movement in the field between the actual and the possible voice. It is also viewed as fundamentally rooted in inter-human relationships, in moments of presence and coexistence. As a tentative answer to the call for an existential space for learning in order to be a professional voice user, I suggest the concept of a learning refuge as a locus for a learning process built on trust, mutuality and openness.

Perspektivmöten i skola och handledning : lärares tankar om specialpedagogisk handledning

To create a more inclusive school, an increase in multidisciplinary cooperation is needed. One possible form of collaboration could encompass the special education teacher taking on the role of a consultant for other teachers in need of support in working with heterogeneous groups of pupils. Previous research shows that special education teachers see the role as consultant as diffuse and complex. The overarching aim of the present study involves deepening the knowledge on how consultation in a special educational context can be understood and developed based on teachers’ descriptions on this particular form of activity interpreted against various perspectives on consultation. The study is qualitative in nature and rests on a hermeneutic interpretive research tradition in combination with an abductive approach. The theoretical framework consists of two different approaches to consultation: the directive and the non-directive approach. The approaches differ regarding particular emphasis on advice and reflection during the consultation and with respect to who or what should be the focus of the consultation. The two approaches are here studied through various theories such as social learning theory, Bruner's theory of scaffolding, Roger’s humanist psychology, and constructivism. Semi-structured interviews were held with eighteen special education teachers (n=9) and class teachers (n=9) working in the compulsory school. The overall interpretation of the results shows that special education consultation can be understood as three different types of consultation. Consultation as counseling which harmonizes with the directive perspective on consultation is the most prominent type. In the consultation as counseling conversation, the special educational knowledge transfer is central and the focus is placed on the pupil. Although special education knowledge transfer emerges as a unique aspect of special education consultation, there are several inherent challenges in this type of consultation that can be addressed in that teachers also describe two other types of consultation. In the reflective consultation, there is a move away from the pupil focus and toward a focus on the class teacher and the use of reflection. The reflective consultation harmonizes with the non-directive approach to consultation. This type of consultation does not as of yet have a prominent place in the Finland-Swedish school context and at this stage it is not seen as a legitimate type of consultation according to the teachers’ descriptions. Despite this, certain aspects of the reflective conversation could be given more space in the development of consultation within special educational contexts. The co-operative consultation is characterized by the teachers acting as teammates and using professional exchange as a strategy for consultation. Both teachers' knowledge is seen as central, and rather than the special education teacher acting as the expert and moderator, the teachers control the consultation together and jointly move the work along. The co-operative consultation enables the focus to move from the pupil toward the context, which can lead to the development of inclusive practices. The results indicate that this type of consultation holds potential in the development of special educational consultation that takes place between equal colleagues. The co-operative consultation opens up for a third collaborative approach to consultation, where aspects of the directive and non-directive perspective can merge and develop. The thesis concludes with the proposal that special pedagogical consultation can be understood from an integrated perspective. The characteristics of the consultation can vary depending on the type of problem or situation, while co-operative consultation can be seen as the ideal as equal colleagues meet in consultation conversations. In order to develop the co-operative consultation, both teachers are required to have knowledge of consultation as a practice, to be part of a collaborative school climate, and that teachers are provided with enough time to take part in consultations.

Defending behavior in bullying situations

In order to encourage children and adolescents to defend and support their victimized peers, it is important to identify factors that either maximize or minimize the probability that students will engage in such behaviors. This thesis is composed of four studies designed to elucidate how a variety of factors work in conjunction to explain why some children defend their victimized classmates, whereas others remain passive or reinforce the bully. The conceptual framework of this thesis is drawn from several theoretical considerations, including social cognitive learning theory, the expectancy-value framework as well as the literature emphasizing the importance of empathy in motivating behaviors. Also the child-by-environment perspective and the socialecological perspective influenced this research. Accordingly, several intra- and interpersonal characteristics (e.g., social cognitions, empathy, and social status) as well as group-level factors (e.g., norms) that may either enhance or reduce the probability that students defend their victimized peers are investigated. In Studies I and II, the focus is on social cognitions, and special attention is paid to take into account the domain-specificity of cognition-behavior processes. Self-efficacy for defending is still an interest of study III, but the role of affective empathy on defending is also investigated. Also social status variables (preference and perceived popularity) are evaluated as possible moderators of links between intrapersonal factors and defending. In Study IV, the focus is expanded further by concentrating on characteristics of children’s proximal environments (i.e., classroom). Bullying norms and collective perceptions (i.e., connectedness among the students and the teachers’ ability to deal with bullying situations) are examined. Data are drawn from two research projects: the Kaarina Cohort Study (consisting of fourth and eighth graders) and the randomized controlled trial (RCT) evaluating the effects of the KiVa antibullying program (consisting of third to fifth graders). The results of the thesis suggest that defending the victims of bullying is influenced by a variety of individual level motivational characteristics, such as social cognitions and affective empathy. Also, both perceived popularity and social preference play a role in defending, and the findings support the conceptualization that behavior results from the interplay between the characteristics of an individual child and their social-relational environment. Classroom context further influences students’ defending behavior. Thus, antibullying efforts targeting peer bystanders should aim to influence intra- and interpersonal characteristics of children and adolescents as well as their social environment.

Extracurricular language activities in higher education: Perspectives of teachers and students

This Master’s thesis researches the topic “Extracurricular language activities in higher education: Perspectives of teachers and students”. In the light of several learning theories, namely, Self-Determination Theory, Social Learning Theory and Incidental Learning Theory, extracurricular participation in language related activities is studied. The main aims of the research are as follows: to study how extracurricular language activities can be organized and supported by the education institution; to investigate how such activities can promote the participants’ learning; and, to research how these activities can be developed and improved in the future. Due to the qualitative character of this research, the empirical data collected through interviews and their thematic analysis allow to study the participants’ perceptions on the above-mentioned issues. Among other results of the research, it can be noted that the organizers of extracurricular language activities and the participants of the activities may have different perspectives on the aims of the activities, as well as their advantages. Additionally, it has been found that the participants of activities would often speak on certain categories that imply the connection to some learning theories, which allows to hypothesize that some learning could be observed in those participants, following participation in extracurricular activities. This is an implication for further research in the area, which can focus on correlations between participation in extracurricular language activities and learning outcomes of the participants.

Information System ProcessInnovation Adoption, Adaptation, Learning, and Unlearning: A Longitudinal Case Study

This thesis examines the history and evolution of information system process innovation (ISPI) processes (adoption, adaptation, and unlearning) within the information system development (ISD) work in an internal information system (IS) department and in two IS software house organisations in Finland over a 43-year time-period. The study offers insights into influential actors and their dependencies in deciding over ISPIs. The research usesa qualitative research approach, and the research methodology involves the description of the ISPI processes, how the actors searched for ISPIs, and how the relationships between the actors changed over time. The existing theories were evaluated using the conceptual models of the ISPI processes based on the innovationliterature in the IS area. The main focus of the study was to observe changes in the main ISPI processes over time. The main contribution of the thesis is a new theory. The term theory should be understood as 1) a new conceptual framework of the ISPI processes, 2) new ISPI concepts and categories, and the relationships between the ISPI concepts inside the ISPI processes. The study gives a comprehensive and systematic study on the history and evolution of the ISPI processes; reveals the factors that affected ISPI adoption; studies ISPI knowledge acquisition, information transfer, and adaptation mechanisms; and reveals the mechanismsaffecting ISPI unlearning; changes in the ISPI processes; and diverse actors involved in the processes. The results show that both the internal IS department and the two IS software houses sought opportunities to improve their technical skills and career paths and this created an innovative culture. When new technology generations come to the market the platform systems need to be renewed, and therefore the organisations invest in ISPIs in cycles. The extent of internal learning and experiments was higher than the external knowledge acquisition. Until the outsourcing event (1984) the decision-making was centralised and the internalIS department was very influential over ISPIs. After outsourcing, decision-making became distributed between the two IS software houses, the IS client, and itsinternal IT department. The IS client wanted to assure that information systemswould serve the business of the company and thus wanted to co-operate closely with the software organisations.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Knowledge Sharing in a Virtual Learning Community

The focus of this Master’s Thesis is on knowledge sharing in a virtual Learning community. The theoretical part of this study aims at presenting the theory of knowledge sharing, competence development and learning in virtual teams. The features of successful learning organizations as well as enablers of effective knowledge sharing in virtual communities are also introduced to the reader in the theoretical framework. The empirical research for this study was realized in a global ICT company, specifically in its Human Resources business unit. The research consisted of two rounds of online questionnaires, which were conducted among all the members of the virtual Learning community. The research aim was to find shared opinions concerning the features of a successful virtual Learning community. The analysis of the data in this study was conducted using a qualitative research methodology. The empirical research showed that the main important features of a successful virtual Learning community are members’ passion towards the community way of working as well as the relevance of the content in the virtual community. In general, it was found that knowledge sharing and competence development are important matters in dynamic organizations as well as virtual communities as method and tool for sharing knowledge and hence increasing both individual and organizational knowledge. This is proved by theoretical and by empirical research in this study.

Solving the puzzle of mobile learning adoption

The dissertation seeks to explore how to improve users‘ adoption of mobile learning in current education systems. Considering the difference between basic and tertiary education in China, the research consists of two separate but interrelated parts, which focus on the use of mobile learning in basic and tertiary education contexts, respectively. In the dissertation, two adoption frameworks are developed based on previous studies. The frameworks are then evaluated using different technologies. Concerning mobile learning use in basic education settings, case study methodology is utilized. A leading provider of mobile learning services and products in China, Noah Ltd., is investigated. Multiple sources of evidence are collected to test the framework. Regarding mobile learning adoption in tertiary education contexts, survey research methodology is utilized. Based on 209 useful responses, the framework is evaluated using structural equation modelling technology. Four proposed determinants of intention to use are evaluated, which are perceived ease of use, perceived near-term usefulness, perceived ong-term usefulness and personal innovativeness. The dissertation provides a number of new insights for both researchers and practitioners. In particular, the dissertation specifies a practical solution to deal with the disruptive effects of mobile learning in basic education, which keeps the use of mobile learning away from the schools across such as European countries. A list of new and innovative mobile learning technologies is systematically introduced as well. Further, the research identifies several key factors driving mobile learning adoption in tertiary education settings. In theory, the dissertation suggests that since the technology acceptance model is initiated in work-oriented innovations by testing employees, it is not necessarily the best model for studying educational innovations. The results also suggest that perceived longterm usefulness for educational systems should be as important as perceived usefulness for utilitarian systems, and perceived enjoyment for hedonic systems. A classification based on the nature of systems purpose (utilitarian, hedonic or educational) would contribute to a better understanding of the essence of IT innovation adoption.

Towards adoption of eLearning technologies at Lappeenranta University of Technology: Understanding Teachers‟ Adoption of Blackboard Learning System

The electronic learning has become crucial in higher education with increased usage of learning management systems as a key source of integration on distance learning. The objective of this study is to understand how university teachers are influenced to use and adopt web-based learning management systems. Blackboard, as one of the systems used internationally by various universities is applied as a case. Semi-structured interviews were made with professors and lecturers who are using Blackboard at Lappeenranta University of Technology. The data collected were categorized under constructs adapted from Unified Theory of Acceptance and Use of Technology (UTAUT) and interpretation and discussion were based on reviewed literature. The findings suggest that adoption of learning management systems by LUT teachers is highly influenced by perceived usefulness, facilitating conditions and gained experience. The findings also suggest that easiness of using the system and social influence appear as medium influence of adoption for teachers at LUT.

Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.

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.

Computational chemistry studies of wood-derived lignans

This thesis is based on computational chemistry studies on lignans, focusing on the naturally occurring lignan hydroxymatairesinol (HMR) (Papers I II) and on TADDOL-like conidendrin-based chiral 1,4-diol ligands (LIGNOLs) (Papers III V). A complete quantum chemical conformational analysis on HMR was previously conducted by Dr. Antti Taskinen. In the works reported in this thesis, HMR was further studied by classical molecular dynamics (MD) simulations in aqueous solution including torsional angle analysis, quantum chemical solvation e ect study by the COnductorlike Screening MOdel (COSMO), and hydrogen bond analysis (Paper I), as well as from a catalytic point of view including protonation and deprotonation studies at di erent levels of theory (Paper II). The computational LIGNOL studies in this thesis constitute a multi-level deterministic structural optimization of the following molecules: 1,1-diphenyl (2Ph), two diastereomers of 1,1,4-triphenyl (3PhR, 3PhS), 1,1,4,4-tetraphenyl (4Ph) and 1,1,4,4-tetramethyl (4Met) 1,4-diol (Paper IV) and a conformational solvation study applying MD and COSMO (Paper V). Furthermore, a computational study on hemiketals in connection with problems in the experimental work by Docent Patrik Eklund's group synthesizing the LIGNOLs based on natural products starting from HMR, is shortly described (Paper III).

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.