Future revenue models: Transformation from textbooks to digital solutions in the educational publishing industry, Case Sanoma Learning

This study was conducted in order to learn how companies’ revenue models will be transformed due to the digitalisation of its products and processes. Because there is still only a limited number of researches focusing solely on revenue models, and particularly on the revenue model change caused by the changes at the business environment, the topic was initially approached through the business model concept, which organises the different value creating operations and resources at a company in order to create profitable revenue streams. This was used as the base for constructing the theoretical framework for this study, used to collect and analyse the information. The empirical section is based on a qualitative study approach and multiple-case analysis of companies operating in learning materials publishing industry. Their operations are compared with companies operating in other industries, which have undergone comparable transformation, in order to recognise either similarities or contrasts between the cases. The sources of evidence are a literature review to find the essential dimensions researched earlier, and interviews 29 of managers and executives at 17 organisations representing six industries. Based onto the earlier literature and the empirical findings of this study, the change of the revenue model is linked with the change of the other dimen-sions of the business model. When one dimension will be altered, as well the other should be adjusted accordingly. At the case companies the transformation is observed as the utilisation of several revenue models simultaneously and the revenue creation processes becoming more complex.

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.

Determination of slurry’s viscosity using case based reasoning approach

Case-based reasoning (CBR) is a recent approach to problem solving and learning that has got a lot of attention over the last years. In this work, the CBR methodology is used to reduce the time and amount of resources spent on carry out experiments to determine the viscosity of the new slurry. The aim of this work is: to develop a CBR system to support the decision making process about the type of slurries behavior, to collect a sufficient volume of qualitative data for case base, and to calculate the viscosity of the Newtonian slurries. Firstly in this paper, the literature review about the types of fluid flow, Newtonian and non-Newtonian slurries is presented. Some physical properties of the suspensions are also considered. The second part of the literature review provides an overview of the case-based reasoning field. Different models and stages of CBR cycles, benefits and disadvantages of this methodology are considered subsequently. Brief review of the CBS tools is also given in this work. Finally, some results of work and opportunities for system modernization are presented. To develop a decision support system for slurry viscosity determination, software application MS Office Excel was used. Designed system consists of three parts: workspace, the case base, and section for calculating the viscosity of Newtonian slurries. First and second sections are supposed to work with Newtonian and Bingham fluids. In the last section, apparent viscosity can be calculated for Newtonian slurries.

Emancipating and developing learning activity: Systemic intervention and re-instrumentation in higher education.

The central theme of this thesis is the emancipation and further development of learning activity in higher education in the context of the ongoing digital transformation of our societies. It was developed in response to the highly problematic mainstream approach to digital re-instrumentation of teaching and studying practises in contemporary higher education. The mainstream approach is largely based on centralisation, standardisation, commoditisation, and commercialisation, while re-producing the general patterns of control, responsibility, and dependence that are characteristic for activity systems of schooling. Whereas much of educational research and development focuses on the optimisation and fine-tuning of schooling, the overall inquiry that is underlying this thesis has been carried out from an explicitly critical position and within a framework of action science. It thus conceptualises learning activity in higher education not only as an object of inquiry but also as an object to engage with and to intervene into from a perspective of intentional change. The knowledge-constituting interest of this type of inquiry can be tentatively described as a combination of heuristic-instrumental (guidelines for contextualised action and intervention), practical-phronetic (deliberation of value-rational aspects of means and ends), and developmental-emancipatory (deliberation of issues of power, self-determination, and growth) aspects. Its goal is the production of orientation knowledge for educational practise. The thesis provides an analysis, argumentation, and normative claim on why the development of learning activity should be turned into an object of individual|collective inquiry and intentional change in higher education, and why the current state of affairs in higher education actually impedes such a development. It argues for a decisive shift of attention to the intentional emancipation and further development of learning activity as an important cultural instrument for human (self-)production within the digital transformation. The thesis also attempts an in-depth exploration of what type of methodological rationale can actually be applied to an object of inquiry (developing learning activity) that is at the same time conceptualised as an object of intentional change within the ongoing digital transformation. The result of this retrospective reflection is the formulation of “optimally incomplete” guidelines for educational R&D practise that shares the practicalphronetic (value related) and developmental-emancipatory (power related) orientations that had been driving the overall inquiry. In addition, the thesis formulates the instrumental-heuristic knowledge claim that the conceptual instruments that were adapted and validated in the context of a series of intervention studies provide means to effectively intervene into existing practise in higher education to support the necessary development of (increasingly emancipated) networked learning activity. It suggests that digital networked instruments (tools and services) generally should be considered and treated as transient elements within critical systemic intervention research in higher education. It further argues for the predominant use of loosely-coupled, digital networked instruments that allow for individual|collective ownership, control, (co-)production, and re-use in other contexts and for other purposes. Since the range of digital instrumentation options is continuously expanding and currently shows no signs of an imminent slow-down or consolidation, individual and collective exploration and experimentation of this realm needs to be systematically incorporated into higher education practise.

Skill Development in Music Reading. The Eye-Movement Approach

This dissertation examined skill development in music reading by focusing on the visual processing of music notation in different music-reading tasks. Each of the three experiments of this dissertation addressed one of the three types of music reading: (i) sight-reading, i.e. reading and performing completely unknown music, (ii) rehearsed reading, during which the performer is already familiar with the music being played, and (iii) silent reading with no performance requirements. The use of the eye-tracking methodology allowed the recording of the readers’ eye movements from the time of music reading with extreme precision. Due to the lack of coherence in the smallish amount of prior studies on eye movements in music reading, the dissertation also had a heavy methodological emphasis. The present dissertation thus aimed to promote two major issues: (1) it investigated the eye-movement indicators of skill and skill development in sight-reading, rehearsed reading and silent reading, and (2) developed and tested suitable methods that can be used by future studies on the topic. Experiment I focused on the eye-movement behaviour of adults during their first steps of learning to read music notation. The longitudinal experiment spanned a nine-month long music-training period, during which 49 participants (university students taking part in a compulsory music course) sight-read and performed a series of simple melodies in three measurement sessions. Participants with no musical background were entitled as “novices”, whereas “amateurs” had had musical training prior to the experiment. The main issue of interest was the changes in the novices’ eye movements and performances across the measurements while the amateurs offered a point of reference for the assessment of the novices’ development. The experiment showed that the novices tended to sight-read in a more stepwise fashion than the amateurs, the latter group manifesting more back-and-forth eye movements. The novices’ skill development was reflected by the faster identification of note symbols involved in larger melodic intervals. Across the measurements, the novices also began to show sensitivity to the melodies’ metrical structure, which the amateurs demonstrated from the very beginning. The stimulus melodies consisted of quarter notes, making the effects of meter and larger melodic intervals distinguishable from effects caused by, say, different rhythmic patterns. Experiment II explored the eye movements of 40 experienced musicians (music education students and music performance students) during temporally controlled rehearsed reading. This cross-sectional experiment focused on the eye-movement effects of one-bar-long melodic alterations placed within a familiar melody. The synchronizing of the performance and eye-movement recordings enabled the investigation of the eye-hand span, i.e., the temporal gap between a performed note and the point of gaze. The eye-hand span was typically found to remain around one second. Music performance students demonstrated increased professing efficiency by their shorter average fixation durations as well as in the two examined eye-hand span measures: these participants used larger eye-hand spans more frequently and inspected more of the musical score during the performance of one metrical beat than students of music education. Although all participants produced performances almost indistinguishable in terms of their auditory characteristics, the altered bars indeed affected the reading of the score: the general effects of expertise in terms of the two eye- hand span measures, demonstrated by the music performance students, disappeared in the face of the melodic alterations. Experiment III was a longitudinal experiment designed to examine the differences between adult novice and amateur musicians’ silent reading of music notation, as well as the changes the 49 participants manifested during a nine-month long music course. From a methodological perspective, an opening to research on eye movements in music reading was the inclusion of a verbal protocol in the research design: after viewing the musical image, the readers were asked to describe what they had seen. A two-way categorization for verbal descriptions was developed in order to assess the quality of extracted musical information. More extensive musical background was related to shorter average fixation duration, more linear scanning of the musical image, and more sophisticated verbal descriptions of the music in question. No apparent effects of skill development were observed for the novice music readers alone, but all participants improved their verbal descriptions towards the last measurement. Apart from the background-related differences between groups of participants, combining verbal and eye-movement data in a cluster analysis identified three styles of silent reading. The finding demonstrated individual differences in how the freely defined silent-reading task was approached. This dissertation is among the first presentations of a series of experiments systematically addressing the visual processing of music notation in various types of music-reading tasks and focusing especially on the eye-movement indicators of developing music-reading skill. Overall, the experiments demonstrate that the music-reading processes are affected not only by “top-down” factors, such as musical background, but also by the “bottom-up” effects of specific features of music notation, such as pitch heights, metrical division, rhythmic patterns and unexpected melodic events. From a methodological perspective, the experiments emphasize the importance of systematic stimulus design, temporal control during performance tasks, and the development of complementary methods, for easing the interpretation of the eye-movement data. To conclude, this dissertation suggests that advances in comprehending the cognitive aspects of music reading, the nature of expertise in this musical task, and the development of educational tools can be attained through the systematic application of the eye-tracking methodology also in this specific domain.

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.

Biomedical Event Extraction with Machine Learning

Biomedical natural language processing (BioNLP) is a subfield of natural language processing, an area of computational linguistics concerned with developing programs that work with natural language: written texts and speech. Biomedical relation extraction concerns the detection of semantic relations such as protein-protein interactions (PPI) from scientific texts. The aim is to enhance information retrieval by detecting relations between concepts, not just individual concepts as with a keyword search. In recent years, events have been proposed as a more detailed alternative for simple pairwise PPI relations. Events provide a systematic, structural representation for annotating the content of natural language texts. Events are characterized by annotated trigger words, directed and typed arguments and the ability to nest other events. For example, the sentence “Protein A causes protein B to bind protein C” can be annotated with the nested event structure CAUSE(A, BIND(B, C)). Converted to such formal representations, the information of natural language texts can be used by computational applications. Biomedical event annotations were introduced by the BioInfer and GENIA corpora, and event extraction was popularized by the BioNLP'09 Shared Task on Event Extraction. In this thesis we present a method for automated event extraction, implemented as the Turku Event Extraction System (TEES). A unified graph format is defined for representing event annotations and the problem of extracting complex event structures is decomposed into a number of independent classification tasks. These classification tasks are solved using SVM and RLS classifiers, utilizing rich feature representations built from full dependency parsing. Building on earlier work on pairwise relation extraction and using a generalized graph representation, the resulting TEES system is capable of detecting binary relations as well as complex event structures. We show that this event extraction system has good performance, reaching the first place in the BioNLP'09 Shared Task on Event Extraction. Subsequently, TEES has achieved several first ranks in the BioNLP'11 and BioNLP'13 Shared Tasks, as well as shown competitive performance in the binary relation Drug-Drug Interaction Extraction 2011 and 2013 shared tasks. The Turku Event Extraction System is published as a freely available open-source project, documenting the research in detail as well as making the method available for practical applications. In particular, in this thesis we describe the application of the event extraction method to PubMed-scale text mining, showing how the developed approach not only shows good performance, but is generalizable and applicable to large-scale real-world text mining projects. Finally, we discuss related literature, summarize the contributions of the work and present some thoughts on future directions for biomedical event extraction. This thesis includes and builds on six original research publications. The first of these introduces the analysis of dependency parses that leads to development of TEES. The entries in the three BioNLP Shared Tasks, as well as in the DDIExtraction 2011 task are covered in four publications, and the sixth one demonstrates the application of the system to PubMed-scale text mining.

International Partnering strategy for e-learning provider in emerging economies: Evidence from East Africa learning institutions

International partnership has received growing interest in the literature during the past decades due to globalization, increased technological approaches and rapid changes in competitive environments. The study specifically determines the support provided by international partners on promotion of e-learning in East Africa, assess the motives of partner selection criteria, the determinants of selecting partners, partner models and partner competence of e-learning provider. The study also evaluates obstacles of e-learning partnering strategy in East Africa learning institutions. The research adopts a descriptive survey design. Target population involved East Africa learning institutions with a list of potential institutions generated from the Ministry of Higher Education database. Through a targeted reduction of the initial database, consisting of all learning institutions, both public and private, the study created a target sample base of 200 learning institutions. Structured questionnaires scheduled were used to collect primary data. Study findings showed the approach way East African communities in selecting their e-learning partners depend on international reputation of partners, partner with ability to negotiate with foreign governments, partner with international and local experiences, nationality of foreign partner and partners with local market knowledge.

Co-creating value with customers as a new approach of entering new market

Global trends associated with development of information technology, globalization, industrial and economic changes are influencing on company and customer domains and thus transforming company-customer relationship. The company centric paradigm with a strong product focus shifts to a customer oriented one with a strong emphasis on customer collaboration. As a result, the customer role changes from a passive observer to an active player. Moreover, global trends contribute to transformation of competitive environment making it tougher and simplifying an access to resources previously considered as unique. All that factors push the companies towards cooperation with customers in order to identify unarticulated needs and finding the best possible solution to existing customer problems. The Master’s Thesis is done for Outotec (Lappeenranta) which considers extension of dewatering business in Russian coal market. Research aims to identify key features of coal preparation and dewatering of fine coal and tailings in Russian preparation plants; analyze the state of Russian coal market and evaluate market potential for Outotec dewatering solutions. The study has a qualitative nature and implements an action research methodology that involves both creation of knowledge and introduction of changes into the system. The base for taking actions is formed by theoretical framework that targets on describing company - customer interaction and has selected co-creation as the most appropriate method of customer involvement. The integration of co-creation approach into an action research cycle allows not only fulfilling the research objectives but also facilitates organizational learning and intraorganizational collaboration, assists in establishing customer contacts and making the first steps into the market, bringing new joint projects to the company and opening real business opportunities.

Learning information technology business in a changing industry landscape. Introducing Team Entrepreneurship in Renewing Bachelor Education in Renewing Bachelor Education in Information

Speed, uncertainty and complexity are increasing in the business world all the time. When knowledge and skills become quickly irrelevant, new challenges are set for information technology (IT) education. Meta-learning skills – learning how to learn rapidly - and innovation skills have become more essential than single technologies or other specific issues. The drastic changes in the information and communications technology (ICT) sector have caused a need to reconsider how IT Bachelor education in Universities of Applied Sciences should be organized and employed to cope with the change. The objective of the study was to evaluate how a new approach to IT Bachelor education, the ICT entrepreneurship study path (ICT-ESP) fits IT Bachelor education in a Finnish University of Applied Sciences. This kind of educational arrangement has not been employed elsewhere in the context of IT Bachelor education. The study presents the results of a four-year period during which IT Bachelor education was renewed in a Finnish University of Applied Sciences. The learning environment was organized into an ICT-ESP based on Nonaka’s knowledge theory and Kolb’s experiental learning. The IT students who studied in the ICT-ESP established a cooperative and learned ICT by running their cooperative at the University of Applied Sciences. The students (called team entrepreneurs) studied by reading theory in books and other sources of explicit information, doing projects for their customers, and reflecting in training sessions on what was learnt by doing and by studying the literature. Action research was used as the research strategy in this study. Empirical data was collected via theme-based interviews, direct observation, and participative observation. Grounded theory method was utilized in the data analysis and the theoretical sampling was used to guide the data collection. The context of the University of Applied Sciences provided a good basis for fostering team entrepreneurship. However, the results showed that the employment of the ICT-ESP did not fit into the IT Bachelor education well enough. The ICT-ESP was cognitively too tough for the team entrepreneurs because they had two different set of rules to follow in their studies. The conventional courses engaged lot of energy which should have been spent for professional development in the ICT-ESP. The amount of competencies needed in the ICT-ESP for professional development was greater than those needed for any other ways of studying. The team entrepreneurs needed to develop skills in ICT, leadership and self-leadership, team development and entrepreneurship skills. The entrepreneurship skills included skills on marketing and sales, brand development, productization, and business administration. Considering the three-year time the team entrepreneurs spent in the ICT-ESP, the challenges were remarkable. Changes to the organization of IT Bachelor education are also suggested in the study. At first, it should be admitted that the ICT-ESP produces IT Bachelors with a different set of competencies compared to the conventional way of educating IT Bachelors. Secondly, the number of courses on general topics in mathematics, physics, and languages for team entrepreneurs studying in the ICTESP should be reconsidered and the conventional course-based teaching of the topics should be reorganized to support the team coaching process of the team entrepreneurs with their practiceoriented projects. Third, the upcoming team entrepreneurs should be equipped with relevant information about the ICT-ESP and what it would require in practice to study as a team entrepreneur. Finally, the upcoming team entrepreneurs should be carefully selected before they start in the ICT-ESP to have a possibility to eliminate solo players and those who have a too romantic view of being a team entrepreneur. The results gained in the study provided answers to the original research questions and the objectives of the study were met. Even though the IT degree programme was terminated during the research process, the amount of qualitative data gathered made it possible to justify the interpretations done.

A Bayesian Approach for Forecasting Heat Load in a District Heating System

The growing population in cities increases the energy demand and affects the environment by increasing carbon emissions. Information and communications technology solutions which enable energy optimization are needed to address this growing energy demand in cities and to reduce carbon emissions. District heating systems optimize the energy production by reusing waste energy with combined heat and power plants. Forecasting the heat load demand in residential buildings assists in optimizing energy production and consumption in a district heating system. However, the presence of a large number of factors such as weather forecast, district heating operational parameters and user behavioural parameters, make heat load forecasting a challenging task. This thesis proposes a probabilistic machine learning model using a Naive Bayes classifier, to forecast the hourly heat load demand for three residential buildings in the city of Skellefteå, Sweden over a period of winter and spring seasons. The district heating data collected from the sensors equipped at the residential buildings in Skellefteå, is utilized to build the Bayesian network to forecast the heat load demand for horizons of 1, 2, 3, 6 and 24 hours. The proposed model is validated by using four cases to study the influence of various parameters on the heat load forecast by carrying out trace driven analysis in Weka and GeNIe. Results show that current heat load consumption and outdoor temperature forecast are the two parameters with most influence on the heat load forecast. The proposed model achieves average accuracies of 81.23 % and 76.74 % for a forecast horizon of 1 hour in the three buildings for winter and spring seasons respectively. The model also achieves an average accuracy of 77.97 % for three buildings across both seasons for the forecast horizon of 1 hour by utilizing only 10 % of the training data. The results indicate that even a simple model like Naive Bayes classifier can forecast the heat load demand by utilizing less training data.

Designing new learning experiences? : exploring corporate E-learners’ self-regulated learning

The context of this study is corporate e-learning, with an explicit focus on how digital learning design can facilitate self-regulated learning (SRL). The field of e-learning is growing rapidly. An increasing number of corporations use digital technology and elearning for training their work force and customers. E-learning may offer economic benefits, as well as opportunities for interaction and communication that traditional teaching cannot provide. However, the evolving variety of digital learning contexts makes new demands on learners, requiring them to develop strategies to adapt and cope with novel learning tools. This study derives from the need to learn more about learning experiences in digital contexts in order to be able to design these properly for learning. The research question targets how the design of an e-learning course influences participants’ self-regulated learning actions and intentions. SRL involves learners’ ability to exercise agency in their learning. Micro-level SRL processes were targeted by exploring behaviour, cognition, and affect/motivation in relation to the design of the digital context. Two iterations of an e-learning course were tested on two groups of participants (N=17). However, the exploration of SRL extends beyond the educational design research perspective of comparing the effects of the changes to the course designs. The study was conducted in a laboratory with each participant individually. Multiple types of data were collected. However, the results presented in this thesis are based on screen observations (including eye tracking) and video-stimulated recall interviews. These data were integrated in order to achieve a broad perspective on SRL. The most essential change evident in the second course iteration was the addition of feedback during practice and the final test. Without feedback on actions there was an observable difference between those who were instruction-directed and those who were self-directed in manipulating the context and, thus, persisted whenever faced with problems. In the second course iteration, including the feedback, this kind of difference was not found. Feedback provided the tipping point for participants to regulate their learning by identifying their knowledge gaps and to explore the learning context in a targeted manner. Furthermore, the course content was consistently seen from a pragmatic perspective, which influenced the participants’ choice of actions, showing that real life relevance is an important need of corporate learners. This also relates to assessment and the consideration of its purpose in relation to participants’ work situation. The rigidity of the multiple choice questions, focusing on the memorisation of details, influenced the participants to adapt to an approach for surface learning. It also caused frustration in cases where the participants’ epistemic beliefs were incompatible with this kind of assessment style. Triggers of positive and negative emotions could be categorized into four levels: personal factors, instructional design of content, interface design of context, and technical solution. In summary, the key design choices for creating a positive learning experience involve feedback, flexibility, functionality, fun, and freedom. The design of the context impacts regulation of behaviour, cognition, as well as affect and motivation. The learners’ awareness of these areas of regulation in relation to learning in a specific context is their ability for design-based epistemic metareflection. I describe this metareflection as knowing how to manipulate the context behaviourally for maximum learning, being metacognitively aware of one’s learning process, and being aware of how emotions can be regulated to maintain volitional control of the learning situation. Attention needs to be paid to how the design of a digital learning context supports learners’ metareflective development as digital learners. Every digital context has its own affordances and constraints, which influence the possibilities for micro-level SRL processes. Empowering learners in developing their ability for design-based epistemic metareflection is, therefore, essential for building their digital literacy in relation to these affordances and constraints. It was evident that the implementation of e-learning in the workplace is not unproblematic and needs new ways of thinking about learning and how we create learning spaces. Digital contexts bring a new culture of learning that demands attitude change in how we value knowledge, measure it, define who owns it, and who creates it. Based on the results, I argue that digital solutions for corporate learning ought to be built as an integrated system that facilitates socio-cultural connectivism within the corporation. The focus needs to shift from designing static e-learning material to managing networks of social meaning negotiation as part of a holistic corporate learning ecology.

On a practical realization of Kolb's experiential learning cycle

This study aims to extend prior knowledge on the learning and developmental outcomes of the experiential learning cycle of David Kolb by the analysis of its practical realization at Team Academy. The study is based on the constructivist approach to learning and considers, among others, the concepts of autonomy support, Nonaka and Takeuchi's knowledge creation model, Luft and Ingham's Johari Window and Deci and Ryan's Self-determination theory. For the investigation deep interviews were carried out with the participants of Team Academy, both learners and coaches. Taking the interview results and the above described theories into consideration this study concludes that experiential learning results not only in effective learning, but also in a remarkable soft skill acquisition, self-development and increase in motivation with an internal locus of causality. Real-life projects permit the learners to experience real challenges. By the practical activities and teamwork they also get the possibility to find out their personal strengths, weaknesses and unique capacities.

University students’ regulation of learning and text processing – examples from medical and teacher education

The general aim of the thesis was to study university students’ learning from the perspective of regulation of learning and text processing. The data were collected from the two academic disciplines of medical and teacher education, which share the features of highly scheduled study, a multidisciplinary character, a complex relationship between theory and practice and a professional nature. Contemporary information society poses new challenges for learning, as it is not possible to learn all the information needed in a profession during a study programme. Therefore, it is increasingly important to learn how to think and learn independently, how to recognise gaps in and update one’s knowledge and how to deal with the huge amount of constantly changing information. In other words, it is critical to regulate one’s learning and to process text effectively. The thesis comprises five sub-studies that employed cross-sectional, longitudinal and experimental designs and multiple methods, from surveys to eye tracking. Study I examined the connections between students’ study orientations and the ways they regulate their learning. In total, 410 second-, fourth- and sixth-year medical students from two Finnish medical schools participated in the study by completing a questionnaire measuring both general study orientations and regulation strategies. The students were generally deeply oriented towards their studies. However, they regulated their studying externally. Several interesting and theoretically reasonable connections between the variables were found. For instance, self-regulation was positively correlated with deep orientation and achievement orientation and was negatively correlated with non-commitment. However, external regulation was likewise positively correlated with deep orientation and achievement orientation but also with surface orientation and systematic orientation. It is argued that external regulation might function as an effective coping strategy in the cognitively loaded medical curriculum. Study II focused on medical students’ regulation of learning and their conceptions of the learning environment in an innovative medical course where traditional lectures were combined wth problem-based learning (PBL) group work. First-year medical and dental students (N = 153) completed a questionnaire assessing their regulation strategies of learning and views about the PBL group work. The results indicated that external regulation and self-regulation of the learning content were the most typical regulation strategies among the participants. In line with previous studies, self-regulation wasconnected with study success. Strictly organised PBL sessions were not considered as useful as lectures, although the students’ views of the teacher/tutor and the group were mainly positive. Therefore, developers of teaching methods are challenged to think of new solutions that facilitate reflection of one’s learning and that improve the development of self-regulation. In Study III, a person-centred approach to studying regulation strategies was employed, in contrast to the traditional variable-centred approach used in Study I and Study II. The aim of Study III was to identify different regulation strategy profiles among medical students (N = 162) across time and to examine to what extent these profiles predict study success in preclinical studies. Four regulation strategy profiles were identified, and connections with study success were found. Students with the lowest self-regulation and with an increasing lack of regulation performed worse than the other groups. As the person-centred approach enables us to individualise students with diverse regulation patterns, it could be used in supporting student learning and in facilitating the early diagnosis of learning difficulties. In Study IV, 91 student teachers participated in a pre-test/post-test design where they answered open-ended questions about a complex science concept both before and after reading either a traditional, expository science text or a refutational text that prompted the reader to change his/her beliefs according to scientific beliefs about the phenomenon. The student teachers completed a questionnaire concerning their regulation and processing strategies. The results showed that the students’ understanding improved after text reading intervention and that refutational text promoted understanding better than the traditional text. Additionally, regulation and processing strategies were found to be connected with understanding the science phenomenon. A weak trend showed that weaker learners would benefit more from the refutational text. It seems that learners with effective learning strategies are able to pick out the relevant content regardless of the text type, whereas weaker learners might benefit from refutational parts that contrast the most typical misconceptions with scientific views. The purpose of Study V was to use eye tracking to determine how third-year medical studets (n = 39) and internal medicine residents (n = 13) read and solve patient case texts. The results revealed differences between medical students and residents in processing patient case texts; compared to the students, the residents were more accurate in their diagnoses and processed the texts significantly faster and with a lower number of fixations. Different reading patterns were also found. The observed differences between medical students and residents in processing patient case texts could be used in medical education to model expert reasoning and to teach how a good medical text should be constructed. The main findings of the thesis indicate that even among very selected student populations, such as high-achieving medical students or student teachers, there seems to be a lot of variation in regulation strategies of learning and text processing. As these learning strategies are related to successful studying, students enter educational programmes with rather different chances of managing and achieving success. Further, the ways of engaging in learning seldom centre on a single strategy or approach; rather, students seem to combine several strategies to a certain degree. Sometimes, it can be a matter of perspective of which way of learning can be considered best; therefore, the reality of studying in higher education is often more complicated than the simplistic view of self-regulation as a good quality and external regulation as a harmful quality. The beginning of university studies may be stressful for many, as the gap between high school and university studies is huge and those strategies that were adequate during high school might not work as well in higher education. Therefore, it is important to map students’ learning strategies and to encourage them to engage in using high-quality learning strategies from the beginning. Instead of separate courses on learning skills, the integration of these skills into course contents should be considered. Furthermore, learning complex scientific phenomena could be facilitated by paying attention to high-quality learning materials and texts and other support from the learning environment also in the university. Eye tracking seems to have great potential in evaluating performance and growing diagnostic expertise in text processing, although more research using texts as stimulus is needed. Both medical and teacher education programmes and the professions themselves are challenging in terms of their multidisciplinary nature and increasing amounts of information and therefore require good lifelong learning skills during the study period and later in work life.