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.

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.

Enhancing web-based learning resources with quizzes through an Authoring Tool and an Audience Response System

Quizzes are among the most widely used resources in web-based education due to their many benefits. However, educators need suitable authoring tools that can be used to create reusable quizzes and to enhance existing materials with them. On the other hand, if teachers use Audience Response Systems (ARSs) they can get instant feedback from their students and thereby enhance their instruction. This paper presents an online authoring tool for creating reusable quizzes and enhancing existing learning resources with them, and a web-based ARS that enables teachers to launch the created quizzes and get instant feedback from the class. Both the authoring tool and the ARS were evaluated. The evaluation of the authoring tool showed that educators can effectively enhance existing learning resources in an easy way by creating and adding quizzes using that tool. Besides, the different factors that assure the reusability of the created quizzes are also exposed. Finally, the evaluation of the developed ARS showed an excellent acceptance of the system by teachers and students, and also it indicated that teachers found the system easy to set up and use in their classrooms.

The development of selective copying: children’s learning from an expert versus their mother

This study tested the prediction that, with age, children should rely less on familiarity and more on expertise in their selective social learning. Experiment 1 (N=50) found that 5- to 6-year-olds copied the technique their mother used to extract a prize from a novel puzzle box, in preference to both a stranger and an established expert. This bias occurred despite children acknowledging the expert model’s superior capability. Experiment 2 (N=50) demonstrated a shift in 7-to 8-year-olds towards copying the expert. Children aged 9- to 10-years did not copy according to a model bias. The findings of a follow-up study (N=30) confirmed that, instead, they prioritized their own – partially flawed – causal understanding of the puzzle box.

Triple objective team mentoring: achieving learning objectives with chemical engineering students

A sophisticated style of mentoring has been found to be essential to support engineering student teams undertaking technically demanding, real-world problems as part of a Project-Centred Curriculum (PCC) at The University of Queensland. The term ‘triple-objective’ mentoring was coined to define mentoring that addresses not only the student’s technical goal achievement but also their time and team management. This is achieved through a number of formal mentor meetings that are informed by a confidential instrument which requires students to individually reflect on team processes prior to the meeting, and a checklist of technical requirements against which the interim student team progress and achievements are assessed. Triple-objective mentoring requires significant time input and coordination by the academic but has been shown to ensure effective student team work and learning undiminished by team dysfunction. Student feedback shows they value the process and agree that the tools developed to support the process are effective in developing and assessing team work and skills with average scores mostly above 3 on a four point scale.

Modellus: Learning Physics with Mathematical Modelling

Tese de doutoramento em Ciências da Educação, área de Teoria Curricular e Ensino das Ciências

Blended Learning project with Applied Optics. Case study

To show with the case of Applied Optics (AO), the adequacy of blended learning to the teaching/learning process in experimental Science and technology (S&T).

Integration of e-learning systems with repositories of learning objects

This paper describes a communication model to integrate repositories of programming problems with other e-Learning software components. The motivation for this work comes from the EduJudge project that aims to connect an existing repository of programming problems to learning management systems. When trying to use the existing repositories of learning objects we realized that they are mainly specialized search engines and lack features for integration with other e-Learning systems. With this model we intend to clarify the main features of a programming problem repository, in order to enable the design and development of software components that use it. The two main points of this model are the definition of programming problems as learning objects and the definition of the core functions exposed by the repository. In both cases, this model follows the existing specifications of the IMS standard and proposes extensions to deal with the special requirements of automatic evaluation and grading of programming exercises. In the definition of programming problems as learning objects we introduced a new schema for meta-data. This schema is used to represent meta-data related to automatic evaluation that cannot be conveniently represented using the standard: the type of automatic evaluation; the requirements of the evaluation engine; or the roles of different assets - tests cases, program solutions, etc. In the definition of the core functions we used two different web services flavours - SOAP and REST - and described each function as an operation for each type of interface. We describe also the data types of the arguments of each operation. These data types consist mainly on learning objects and their identifications, but include also usage reports and queries using XQuery.

Learning Activities with Semantic. Hypermedia in Higher Education

The increasing use of information and communication technologies (ICT) in diverse professional and personal contexts calls for new knowledge, and a set of abilities, competences and attitudes, for an active and participative citizenship. In this context it is acknowledged that universities have an important role innovating in the educational use of digital media to promote an inclusive digital literacy. The educational potential of digital technologies and resources has been recognized by both researchers and practitioners. Multiple pedagogical models and research approaches have already contributed to put in evidence the importance of adapting instructional and learning practices and processes to concrete contexts and educational goals. Still, academic and scientific communities believe further investments in ICT research is needed in higher education. This study focuses on educational models that may contribute to support digital technology uses, where these can have cognitive and educational relevance when compared to analogical technologies. A teaching and learning model, centered in the active role of the students in the exploration, production, presentation and discussion of interactive multimedia materials, was developed and applied using the internet and exploring emergent semantic hypermedia formats. The research approach focused on the definition of design principles for developing class activities that were applied in three different iterations in undergraduate courses from two institutions, namely the University of Texas at Austin, USA and the University of Lisbon, Portugal. The analysis of this study made possible to evaluate the potential and efficacy of the model proposed and the authoring tool chosen in the support of metacognitive skills and attitudes related to information structuring and management, storytelling and communication, using computers and the internet.

Explorations of the Practical Issues of Learning Prediction-Control Tasks Using Temporal Difference Learning Methods

There has been recent interest in using temporal difference learning methods to attack problems of prediction and control. While these algorithms have been brought to bear on many problems, they remain poorly understood. It is the purpose of this thesis to further explore these algorithms, presenting a framework for viewing them and raising a number of practical issues and exploring those issues in the context of several case studies. This includes applying the TD(lambda) algorithm to: 1) learning to play tic-tac-toe from the outcome of self-play and of play against a perfectly-playing opponent and 2) learning simple one-dimensional segmentation tasks.

Effective e-learning integration with traditional learning in a blended learning environment

E-Learning is an emerging tool that uses advanced technology to provide training and development in higher education and within industry. Its rapid growth has been facilitated by the Internet and the massive opportunities in global education. The aim of this study is to consider how effective and efficient e-learning is when integrated with traditional learning in a blended learning environment. The study will provide a comparison between purist ELearning and Blended learning environment. The paper will also provide directions for the blended learning environment which can be used by all the three main stakeholder student, tutors and institution to make strategic decision about the learning and teaching initiatives. The paper concludes that blended learning approaches offer the most flexible and scalable route to E-Learning.

Comparing the Teaching-Learning Process With and Without the Use of Computerized Technological Resources

Computerized technological resources have become essential in education, particularly for teaching topics that require the performance of specific tasks. These resources can effectively help the execution of such tasks and the teaching-learning process itself. After the development of a Web site on the topic of nursing staff scheduling, this study aimed at comparing the development of students involved in the teaching-learning process of the previously mentioned topic, with and without the use of computer technology. Two random groups of undergraduate nursing students from a public university in São Paulo state, Brazil, were organized: a case group (used the Web site) and a control group (did not use the Web site). Data were collected from 2003 to 2005 after approval by the Research Ethics Committee. Results showed no significant difference in motivation or knowledge acquisition. A similar performance for the two groups was also verified. Other aspects observed were difficulty in doing the nursing staff scheduling exercise and the students' acknowledgment of the topic's importance for their training and professional lives; easy access was considered to be a positive aspect for maintaining the Web site.

A Tamil hand-book : or Full introduction to the common dialect of that language on the plan of Ollenndorf and Arnold, for the use of foreigners learning Tamil, and of Tamilians learning English; with copious vocabularies (Tamil-English, and English-Tamil,) appendices containing reading lessons, analyses of letters, deeds, complaints, official documents.

7th ed. published under title: A handbook of the Tamil language.