The nature of communication structures of university students in an international web-based computer-supported collaborative learning (CSCL) course

Communication, the flow of ideas and information between individuals in a social context, is the heart of educational experience. Constructivism and constructivist theories form the foundation for the collaborative learning processes of creating and sharing meaning in online educational contexts. The Learning and Collaboration in Technology-enhanced Contexts (LeCoTec) course comprised of 66 participants drawn from four European universities (Oulu, Turku, Ghent and Ramon Llull). These participants were split into 15 groups with the express aim of learning about computer-supported collaborative learning (CSCL). The Community of Inquiry model (social, cognitive and teaching presences) provided the content and tools for learning and researching the collaborative interactions in this environment. The sampled comments from the collaborative phase were collected and analyzed at chain-level and group-level, with the aim of identifying the various message types that sustained high learning outcomes. Furthermore, the Social Network Analysis helped to view the density of whole group interactions, as well as the popular and active members within the highly collaborating groups. It was observed that long chains occur in groups having high quality outcomes. These chains were also characterized by Social, Interactivity, Administrative and Content comment-types. In addition, high outcomes were realized from the high interactive cases and high-density groups. In low interactive groups, commenting patterned around the one or two central group members. In conclusion, future online environments should support high-order learning and develop greater metacognition and self-regulation. Moreover, such an environment, with a wide variety of problem solving tools, would enhance interactivity.

Emotions in a Web-based Learning Environment

The aim of this thesis was to examine emotions in a web-based learning environment (WBLE). Theoretically, the thesis was grounded on the dimensional model of emotions. Four empirical studies were conducted. Study I focused on students’ anxiety and their self-efficacy in computer-using situations. Studies II and III examined the influence of experienced emotions on students’ collaborative visible and non-collaborative invisible activities and lurking in a WBLE. Study II also focused on the antecedents of the emotions students experience in a web-based learning environment. Study IV concentrated on clarifying the differences between emotions experienced in face-to-face and web-based collaborative learning. The results of these studies are reported in four original research articles published in scientific journals. The present studies demonstrate that emotions are important determinants of student behaviour in a web-based learning, and justify the conclusion that interactions on the web can and do have an emotional content. Based on the results of these empirical studies, it can be concluded that the emotions students experience during the web-based learning result mostly from the social interactions rather than from the technological context. The studies indicate that the technology itself is not the only antecedent of students’ emotional reactions in the collaborative web-based learning situations. However, the technology itself also exerted an influence on students’ behaviour. It was found that students’ computer anxiety was associated with their negative expectations of the consequences of using technology-based learning environments in their studies. Moreover, the results also indicated that student behaviours in a WBLE can be divided into three partially overlapping classes: i) collaborative visible ii) non-collaborative invisible activities, and iii) lurking. What is more, students’ emotions experienced during the web-based learning affected how actively they participated in such activities in the environment. Especially lurkers, i.e. students who seldom participated in discussions but frequently visited the online environment, experienced more negatively valenced emotions during the courses than did the other students. This result indicates that such negatively toned emotional experiences can make the lurking individuals less eager to participate in other WBLE courses in the future. Therefore, future research should also focus more precisely on the reasons that cause individuals to lurk in online learning groups, and the development of learning tasks that do not encourage or permit lurking or inactivity. Finally, the results from the study comparing emotional reactions in web-based and face-to-face collaborative learning indicated that the learning by means of web-based communication resulted in more affective reactivity when compared to learning in a face-to-face situation. The results imply that the students in the web-based learning group experienced more intense emotions than the students in the face-to-face learning group.The interpretations of this result are that the lack of means for expressing emotional reactions and perceiving others’ emotions increased the affectivity in the web-based learning groups. Such increased affective reactivity could, for example, debilitate individual’s learning performance, especially in complex learning tasks. Therefore, it is recommended that in the future more studies should be focused on the possibilities to express emotions in a text-based web environment to ensure better means for communicating emotions, and subsequently, possibly decrease the high level of affectivity. However, we do not yet know whether the use of means for communicating emotional expressions via the web (for example, “smileys” or “emoticons”) would be beneficial or disadvantageous in formal learning situations. Therefore, future studies should also focus on assessing how the use of such symbols as a means for expressing emotions in a text-based web environment would affect students’ and teachers’ behaviour and emotional state in web-based learning environments.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

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

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

Playing to Learn: Business Simulation Games as Leadership Learning Environments

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

Learning Grasp Affordances from Vision

Monimutkaisissa ja muuttuvissa ympäristöissä työskentelevät robotit tarvitsevat kykyä manipuloida ja tarttua esineisiin. Tämä työ tutkii robottitarttumisen ja robottitartuntapis-teiden koneoppimisen aiempaa tutkimusta ja nykytilaa. Nykyaikaiset menetelmät käydään läpi, ja Le:n koneoppimiseen pohjautuva luokitin toteutetaan, koska se tarjoaa parhaan onnistumisprosentin tutkituista menetelmistä ja on muokattavissa sopivaksi käytettävissä olevalle robotille. Toteutettu menetelmä käyttää intensititeettikuvaan ja syvyyskuvaan po-hjautuvia ominaisuuksi luokitellakseen potentiaaliset tartuntapisteet. Tämän toteutuksen tulokset esitellään.

Socially shared metacognitive regulation during collaborative learning processes in student dyads and small groups

Traditionally metacognition has been theorised, methodologically studied and empirically tested from the standpoint mainly of individuals and their learning contexts. In this dissertation the emergence of metacognition is analysed more broadly. The aim of the dissertation was to explore socially shared metacognitive regulation (SSMR) as part of collaborative learning processes taking place in student dyads and small learning groups. The specific aims were to extend the concept of individual metacognition to SSMR, to develop methods to capture and analyse SSMR and to validate the usefulness of the concept of SSMR in two different learning contexts; in face-to-face student dyads solving mathematical word problems and also in small groups taking part in inquiry-based science learning in an asynchronous computer-supported collaborative learning (CSCL) environment. This dissertation is comprised of four studies. In Study I, the main aim was to explore if and how metacognition emerges during problem solving in student dyads and then to develop a method for analysing the social level of awareness, monitoring, and regulatory processes emerging during the problem solving. Two dyads comprised of 10-year-old students who were high-achieving especially in mathematical word problem solving and reading comprehension were involved in the study. An in-depth case analysis was conducted. Data consisted of over 16 (30–45 minutes) videotaped and transcribed face-to-face sessions. The dyads solved altogether 151 mathematical word problems of different difficulty levels in a game-format learning environment. The interaction flowchart was used in the analysis to uncover socially shared metacognition. Interviews (also stimulated recall interviews) were conducted in order to obtain further information about socially shared metacognition. The findings showed the emergence of metacognition in a collaborative learning context in a way that cannot solely be explained by individual conception. The concept of socially-shared metacognition (SSMR) was proposed. The results highlighted the emergence of socially shared metacognition specifically in problems where dyads encountered challenges. Small verbal and nonverbal signals between students also triggered the emergence of socially shared metacognition. Additionally, one dyad implemented a system whereby they shared metacognitive regulation based on their strengths in learning. Overall, the findings suggested that in order to discover patterns of socially shared metacognition, it is important to investigate metacognition over time. However, it was concluded that more research on socially shared metacognition, from larger data sets, is needed. These findings formed the basis of the second study. In Study II, the specific aim was to investigate whether socially shared metacognition can be reliably identified from a large dataset of collaborative face-to-face mathematical word problem solving sessions by student dyads. We specifically examined different difficulty levels of tasks as well as the function and focus of socially shared metacognition. Furthermore, the presence of observable metacognitive experiences at the beginning of socially shared metacognition was explored. Four dyads participated in the study. Each dyad was comprised of high-achieving 10-year-old students, ranked in the top 11% of their fourth grade peers (n=393). Dyads were from the same data set as in Study I. The dyads worked face-to-face in a computer-supported, game-format learning environment. Problem-solving processes for 251 tasks at three difficulty levels taking place during 56 (30–45 minutes) lessons were video-taped and analysed. Baseline data for this study were 14 675 turns of transcribed verbal and nonverbal behaviours observed in four study dyads. The micro-level analysis illustrated how participants moved between different channels of communication (individual and interpersonal). The unit of analysis was a set of turns, referred to as an ‘episode’. The results indicated that socially shared metacognition and its function and focus, as well as the appearance of metacognitive experiences can be defined in a reliable way from a larger data set by independent coders. A comparison of the different difficulty levels of the problems suggested that in order to trigger socially shared metacognition in small groups, the problems should be more difficult, as opposed to moderately difficult or easy. Although socially shared metacognition was found in collaborative face-to-face problem solving among high-achieving student dyads, more research is needed in different contexts. This consideration created the basis of the research on socially shared metacognition in Studies III and IV. In Study III, the aim was to expand the research on SSMR from face-to-face mathematical problem solving in student dyads to inquiry-based science learning among small groups in an asynchronous computer-supported collaborative learning (CSCL) environment. The specific aims were to investigate SSMR’s evolvement and functions in a CSCL environment and to explore how SSMR emerges at different phases of the inquiry process. Finally, individual student participation in SSMR during the process was studied. An in-depth explanatory case study of one small group of four girls aged 12 years was carried out. The girls attended a class that has an entrance examination and conducts a language-enriched curriculum. The small group solved complex science problems in an asynchronous CSCL environment, participating in research-like processes of inquiry during 22 lessons (á 45–minute). Students’ network discussion were recorded in written notes (N=640) which were used as study data. A set of notes, referred to here as a ‘thread’, was used as the unit of analysis. The inter-coder agreement was regarded as substantial. The results indicated that SSMR emerges in a small group’s asynchronous CSCL inquiry process in the science domain. Hence, the results of Study III were in line with the previous Study I and Study II and revealed that metacognition cannot be reduced to the individual level alone. The findings also confirm that SSMR should be examined as a process, since SSMR can evolve during different phases and that different SSMR threads overlapped and intertwined. Although the classification of SSMR’s functions was applicable in the context of CSCL in a small group, the dominant function was different in the asynchronous CSCL inquiry in the small group in a science activity than in mathematical word problem solving among student dyads (Study II). Further, the use of different analytical methods provided complementary findings about students’ participation in SSMR. The findings suggest that it is not enough to code just a single written note or simply to examine who has the largest number of notes in the SSMR thread but also to examine the connections between the notes. As the findings of the present study are based on an in-depth analysis of a single small group, further cases were examined in Study IV, as well as looking at the SSMR’s focus, which was also studied in a face-to-face context. In Study IV, the general aim was to investigate the emergence of SSMR with a larger data set from an asynchronous CSCL inquiry process in small student groups carrying out science activities. The specific aims were to study the emergence of SSMR in the different phases of the process, students’ participation in SSMR, and the relation of SSMR’s focus to the quality of outcomes, which was not explored in previous studies. The participants were 12-year-old students from the same class as in Study III. Five small groups consisting of four students and one of five students (N=25) were involved in the study. The small groups solved ill-defined science problems in an asynchronous CSCL environment, participating in research-like processes of inquiry over a total period of 22 hours. Written notes (N=4088) detailed the network discussions of the small groups and these constituted the study data. With these notes, SSMR threads were explored. As in Study III, the thread was used as the unit of analysis. In total, 332 notes were classified as forming 41 SSMR threads. Inter-coder agreement was assessed by three coders in the different phases of the analysis and found to be reliable. Multiple methods of analysis were used. Results showed that SSMR emerged in all the asynchronous CSCL inquiry processes in the small groups. However, the findings did not reveal any significantly changing trend in the emergence of SSMR during the process. As a main trend, the number of notes included in SSMR threads differed significantly in different phases of the process and small groups differed from each other. Although student participation was seen as highly dispersed between the students, there were differences between students and small groups. Furthermore, the findings indicated that the amount of SSMR during the process or participation structure did not explain the differences in the quality of outcomes for the groups. Rather, when SSMRs were focused on understanding and procedural matters, it was associated with achieving high quality learning outcomes. In turn, when SSMRs were focused on incidental and procedural matters, it was associated with low level learning outcomes. Hence, the findings imply that the focus of any emerging SSMR is crucial to the quality of the learning outcomes. Moreover, the findings encourage the use of multiple research methods for studying SSMR. In total, the four studies convincingly indicate that a phenomenon of socially shared metacognitive regulation also exists. This means that it was possible to define the concept of SSMR theoretically, to investigate it methodologically and to validate it empirically in two different learning contexts across dyads and small groups. In-depth micro-level case analysis in Studies I and III showed the possibility to capture and analyse in detail SSMR during the collaborative process, while in Studies II and IV, the analysis validated the emergence of SSMR in larger data sets. Hence, validation was tested both between two environments and within the same environments with further cases. As a part of this dissertation, SSMR’s detailed functions and foci were revealed. Moreover, the findings showed the important role of observable metacognitive experiences as the starting point of SSMRs. It was apparent that problems dealt with by the groups should be rather difficult if SSMR is to be made clearly visible. Further, individual students’ participation was found to differ between students and groups. The multiple research methods employed revealed supplementary findings regarding SSMR. Finally, when SSMR was focused on understanding and procedural matters, this was seen to lead to higher quality learning outcomes. Socially shared metacognition regulation should therefore be taken into consideration in students’ collaborative learning at school similarly to how an individual’s metacognition is taken into account in individual learning.

Nursing Students’ Learning about an Empowering Discourse In Patient Education

The main purpose of this study was to describe and evaluate nursing students' learning about an empowering discourse in patient education. In Phase 1, the purpose was to describe an empowering discourse between a nurse and a patient. In Phase 2, the purpose was first to create a computer simulation program of an empowering discourse based on the description, and second, the purpose was to evaluate nursing students’ learning of how to conduct an empowering discourse using a computer simulation program. The ultimate goal was to strengthen the knowledge basis on empowering discourse and to develop nursing students’ knowledge about how to conduct an empowering discourse for the development of patient education. In Phase I, empowering discourse was described using a systematic literature review with a metasummary technique (n=15). Data were collected covering a period from January 1995 to October 2005. In Phase 2, the computer simulation program of empowering discourse was created based the description in 2006–2007. A descriptive comparative design was used to evaluate students’ (n=69) process of learning empowering discourse using the computer simulation program and a pretest–post-test design without a control group was used to evaluate students’ (n=43) outcomes of learning. Data were collected in 2007. Empowering discourse was a structured process and it was possible to simulate and learned with the computer simulation program. According to students’ knowledge, empowering discourse was an unstructured process. Process of learning empowering discourse using the computer simulation program was controlled by the students and it changed students’ knowledge. The outcomes of learning empowering discourse appeared as changes of students’ knowledge to more holistic and better-organized or only to more holistic or better-organized. The study strengthened knowledge base of empowering discourse and developed students to more knowledgeable in empowering discourse.

Designing gamification for collaborative learning in group work

Computer Supported Collaborative Learning (CSCL) is a teaching and learning approach which is widely adopted. However there are still some problems can be found when CSCL takes place. Studies show that using game-like mechanics can increase motivation, engagement, as well as modelling behaviors of players. Gamification is a rapid growing trend by applying the same mechanics. It refers to use game design elements in non-game contexts. This thesis is about combining gamification concept and computer supported collaborative learning together in software engineering education field. And finally a gamified prototype system is designed.