Design and use of mobile technology in distance language education : Matching learning practices with technologies-in-practice

This thesis focuses on the adaptation of formal education to people’s technology- use patterns, theirtechnology-in-practice, where the ubiquitous use of mobile technologies is central. The research question is: How can language learning practices occuring in informal learning environments be effectively integrated with formal education through the use of mobile technology? The study investigates the technical, pedagogical, social and cultural challenges involved in a design science approach. The thesis consists of four studies. The first study systematises MALL (mobile-assisted language learning) research. The second investigates Swedish and Chinese students’ attitudes towards the use of mobile technology in education. The third examines students’ use of technology in an online language course, with a specific focus on their learning practices in informal learning contexts and their understanding of how this use guides their learning. Based on the findings, a specifically designed MALL application was built and used in two courses. Study four analyses the app use in terms of students’ perceived level of self-regulation and structuration. The studies show that technology itself plays a very important role in reshaping peoples’ attitudes and that new learning methods are coconstructed in a sociotechnical system. Technology’s influence on student practices is equally strong across borders. Students’ established technologies-in-practice guide the ways they approach learning. Hence, designing effective online distance education involves three interrelated elements: technology, information, and social arrangements. This thesis contributes to mobile learning research by offering empirically and theoretically grounded insights that shift the focus from technology design to design of information systems.

Machine Learning Algorithms in Heavy Process Manufacturing

In a global economy, manufacturers mainly compete with cost efficiency of production, as the price of raw materials are similar worldwide. Heavy industry has two big issues to deal with. On the one hand there is lots of data which needs to be analyzed in an effective manner, and on the other hand making big improvements via investments in cooperate structure or new machinery is neither economically nor physically viable. Machine learning offers a promising way for manufacturers to address both these problems as they are in an excellent position to employ learning techniques with their massive resource of historical production data. However, choosing modelling a strategy in this setting is far from trivial and this is the objective of this article. The article investigates characteristics of the most popular classifiers used in industry today. Support Vector Machines, Multilayer Perceptron, Decision Trees, Random Forests, and the meta-algorithms Bagging and Boosting are mainly investigated in this work. Lessons from real-world implementations of these learners are also provided together with future directions when different learners are expected to perform well. The importance of feature selection and relevant selection methods in an industrial setting are further investigated. Performance metrics have also been discussed for the sake of completion.

Simultaneous prediction of symptom severity and cause in data from a test battery for Parkinson patients, using machine learning methods

The main purpose of this thesis project is to prediction of symptom severity and cause in data from test battery of the Parkinson’s disease patient, which is based on data mining. The collection of the data is from test battery on a hand in computer. We use the Chi-Square method and check which variables are important and which are not important. Then we apply different data mining techniques on our normalize data and check which technique or method gives good results.The implementation of this thesis is in WEKA. We normalize our data and then apply different methods on this data. The methods which we used are Naïve Bayes, CART and KNN. We draw the Bland Altman and Spearman’s Correlation for checking the final results and prediction of data. The Bland Altman tells how the percentage of our confident level in this data is correct and Spearman’s Correlation tells us our relationship is strong. On the basis of results and analysis we see all three methods give nearly same results. But if we see our CART (J48 Decision Tree) it gives good result of under predicted and over predicted values that’s lies between -2 to +2. The correlation between the Actual and Predicted values is 0,794in CART. Cause gives the better percentage classification result then disability because it can use two classes.

Students’ Role in Distance Learning

1. IntroductionMuch of the support that students have in a traditional classroom is absent in a distance learning course. In the traditional classroom, the learner is together with his or her classmates and the teacher; learning is socially embedded. Students can talk to each other and may learn from each other as they go through the learning process together. They also witness the teacher’s expression of the knowledge firsthand. The class participants communicate to each other not only through their words, but also through their gestures, facial expressions and tone of voice, and the teacher can observe the students’ progress and provide guidance and feedback in an as-needed basis. Further, through the habit of meeting in a regular place at a regular time, the participants reinforce their own and each other’s commitment to the course. A distance course must somehow provide learners other kinds of supports so that the distance learner also has a sense of connection with a learning community; can benefit from interaction with peers who are going through a similar learning process; receives feedback that allows him or her to know how he or she is progressing; and is guided enough so that he or she continues to progress towards the learning objectives. This cannot be accomplished if the distance course does not simultaneously promote student autonomy, for the distance course format requires students to take greater responsibility for their own learning. This chapter presents one distance learning course that was able to address all of these goals. The English Department at Högskolan Dalarna, Sweden, participates in a distance learning program with Vietnam National University. Students enrolled in this program study half-time for two years to complete a Master’s degree in English Linguistics. The distance courses in this program all contain two types of regular class meetings: one type is student-only seminars conducted through text chat, during which students discuss and complete assignments that prepare them for the other type of class meeting, also conducted through text chat, where the teacher is present and is the one to lead the discussion of seminar issues and assignments. The inclusion of student-only seminars in the course design allows for student independence while at the same time it encourages co-operation and solidarity. The teacher-led seminars offer the advantages of a class led by an expert.In this chapter, we present chatlog data from Vietnamese students in one distance course in English linguistics, comparing the role of the student in both student-only and teacher-led seminars. We discuss how students navigate their participation roles, through computer-mediated communication (CMC), according to seminar type, and we consider the emerging role of the autonomous student in the foreign-language medium, distance learning environment. We close by considering aspects of effective design of distance learning courses from the perspective of a foreign language (FL) environment.

Language and interaction in online asynchronous communication in university level English courses

Interaction involves people communicating and reacting to each other. This process is key to the study of discourse, but it is not easy to study systematically how interaction takes place in a specific communicative event, or how it is typically performed over a series of repeated communicative events. However, with a written record of the interaction, it becomes possible to study the process in some detail. This thesis investigates interaction through asynchronous written discussion forums in a computer-mediated learning environment. In particular, this study investigates pragmatic aspects of the communicative event which the asynchronous online discussions comprise. The first case study examines response patterns to messages by looking at the content of initial messages and responses, in order to determine the extent to which characteristics of the messages themselves or other situational factors affect the interaction. The second study examines in what ways participants use a range of discourse devices, including formulaic politeness, humour and supportive feedback as community building strategies in the interaction. The third study investigates the role of the subject line of messages in the interaction, for example by examining how participants choose different types of subject lines for different types of messages. The fourth study examines to what extent features serving a deictic function are drawn on in the interaction and then compares the findings to both oral conversation and formal academic discourse. The overall findings show a complex communicative situation shaped by the medium itself, type of activity, the academic discipline and topic of discussion and by the social and cultural aspects of tertiary education in an online learning environment. In addition, the findings may also provide evidence of learning.  

E-learning opens the door to the global community. Novice users experiences of e-learning in a Somali University

E-learning has become one of the primary ways of delivering education around the globe. In Somalia, which is a country torn within and from the global community by a prolonged civil war, University of Hargeisa has in collaboration with Dalarna University in Sweden adopted, for the first time, e-learning. This study explores barriers and facilitators to e-learning usage, experienced by students in Somalia’s higher education, using the University of Hargeisa as case study. Interviews were conducted with students to explore how University of Hargeisa’s novice users perceived elearning, and what factors positively and negatively affected their e-learning experiences. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was used as a framework for interpreting the results. The findings show that, in general, the students have a very positive attitude towards e-learning, and they perceived that e-learning enhanced their educational experience. The communication aspect was found to be especially important for Somali students, as it facilitated a feeling of belonging to the global community of students and scholars and alleviated the war-torn country’s isolation. However, some socio-cultural aspects of students’ communities negatively affected their e-learning experience. This study ends with recommendations based on the empirical findings to promote the use and enhance the experience of e-learning in post conflict Somali educational institutions