Whenever a student submits their final version of their thesis, a series of processes is triggered to finalize and archive the report. These processes are often handled in a less than efficient way which results in excessive manual labor and costs that can be prevent if automated. This report describes a solution that automates the series of processes that occur following a final thesis report submission. By utilizing the available information in a Canvas course and the content in the submitted thesis much of the manual cut-and-paste effort is avoided. Entering this data into DiVA is done by automated interaction via a browser, as DiVA does not have an application programming interface that could be used. The conclusion is that it is possible to automate this process through a headless browser. However, the automated parsing of the PDF version of the thesis proven to be inconsistent which results in the extracted data being inconsistent. With some improvements to the parsing module, the entire process could be fully automated. / Varje gång en student skickar in sin slutgiltiga version av sitt examensarbete, utlöses en serie av processer för att slutföra och arkivera examensarbetet. Dessa processer hanteras ofta på ett mindre än effektivt sätt vilket resulterar i extra mycket manuellt arbete och kostnader som kan förhindras ifall de automatiseras. Denna uppsats beskriver en lösning som automatiserar serien av processer som inträffar efter att ett slutgiltigt examensarbete har godkänts. Genom att använda tillgänglig information i en Canvas-kurs och innehållet i det inlämnade examensarbetet undviks mycket av den manuella ”klipp-och-klistra”-insatsen. Inmatning av den relevanta data från examensarbetet måste göras via automatiserad interaktion via en webbläsare i DiVA, eftersom DiVA inte hade ett API som kunde användas. Slutsatsen är att det är möjligt att automatisera detta genom en huvudlös webbläsare, även om modulen som behandlar PDF har visat sig vara inkonsekvent vilket i sin tur har resulterat i att den automatiska interaktionen är inkonsekvent. Med några optimeringar i analysmodulen kan hela processen automatiseras.

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The relevance of the research is due to the realization of new educational technologies in the system of general education, including programmed learning. The main drawback of the development of training programs is the imperfection in IT-technologies. The purpose of the master's thesis is to create a programmed learning system. The novelty of the thesis is obtaining a package of semi-formalized and mathematical models of an automated system of programmed learning. Training programs applied in the educational process and showed an increase in the level of student learning. / Актуальность темы обусловлена реализацией в системе общего образования новых педагогических технологий, одна из которых – программированное обучение. При этом основной недостаток разработки обучающих программ – несовершенство в поддержке ИКТ. Целью магистерской диссертации является создание системы программированного обучения. Научная новизна работы заключена в получении пакета полуформализованных и математической моделей автоматизированной системы программированного обучения. На основании этих моделей получены обучающие программы, примененные в учебном процессе и показавшие рост уровня обученности учащихся. Экономическая эффективность предлагаемого решения доказана методом NPV: прогнозируемое значение показателя NPV за 12 месяцев реализации проекта перешло нулевой порог.

Esta tese propõe conceitos, processos e uma arquitetura de sistemas para Monitoração e Acompanhamento da Aprendizagem Eletrônica (MAAE). A arquitetura é definida pelo seu modelo conceitual, pela interação com os serviços externos e pela representação XML dos conceitos e dos serviços. Ela independe de abordagem pedagógica específica. O Ponto de Observação é inserido em vários locais do Conteúdo da Aprendizagem Eletrônica. Um Elemento de Observação é associado ao Ponto de Observação, e é o responsável pela captura das interações do Processo de Aprendizagem Eletrônica. O Agenciador de Observação (Agenciador de Monitoração e Acompanhamento da Aprendizagem Eletrônica) recebe os eventos e solicitações dos Elementos de Observação e interage com os serviços externos. Os eventos são gravados no Repositório de Observação. A definição dos Processos de Aprendizagem Eletrônica é útil para a definição da estratégia de monitoração (Modelagem do Processo da Aprendizagem Eletrônica). Através da inserção dos mecanismos de observação nas Atividades de Aprendizagem (Processo da Produção do Conteúdo de Aprendizagem Eletrônica) é feita a monitoração do aprendiz (Processo da Aprendizagem Eletrônica) e se obtém as informações para análise (Avaliação e Análise da Aprendizagem Eletrônica). / This thesis proposes concepts, processes and a system architecture for Monitoring and Tracking E-Learning. The architecture is defined by a conceptual model, the interaction with external services and representation XML of the concepts and the services. It does not depend on any specific pedagogical boarding. The Monitoring Point is inserted in some places of the E-Learning Content. A Monitoring Element is associated to the Monitoring Point and it is for responsible of one of the interactions of the E-Learning Process. The Monitoring Service (E-Learning Monitoring and Following Service) receives the events and requests from the Monitoring Elements and it interacts with the external services. The events are recorded in the Monitoring Repository. The E-Learning Processes definition is useful to modeling the monitoring strategy (Learning Process Modeling), and insert to the monitoring mechanisms in the E-Learning Activities (Learning Content Production Process). The learner interaction monitoring occurs by getting the information according to the previous planning (Learning Process), and the generated information (Learning Analysis and Evaluation Process) is used in the analysis of learning tracking.

Esta tese propõe conceitos, processos e uma arquitetura de sistemas para Monitoração e Acompanhamento da Aprendizagem Eletrônica (MAAE). A arquitetura é definida pelo seu modelo conceitual, pela interação com os serviços externos e pela representação XML dos conceitos e dos serviços. Ela independe de abordagem pedagógica específica. O Ponto de Observação é inserido em vários locais do Conteúdo da Aprendizagem Eletrônica. Um Elemento de Observação é associado ao Ponto de Observação, e é o responsável pela captura das interações do Processo de Aprendizagem Eletrônica. O Agenciador de Observação (Agenciador de Monitoração e Acompanhamento da Aprendizagem Eletrônica) recebe os eventos e solicitações dos Elementos de Observação e interage com os serviços externos. Os eventos são gravados no Repositório de Observação. A definição dos Processos de Aprendizagem Eletrônica é útil para a definição da estratégia de monitoração (Modelagem do Processo da Aprendizagem Eletrônica). Através da inserção dos mecanismos de observação nas Atividades de Aprendizagem (Processo da Produção do Conteúdo de Aprendizagem Eletrônica) é feita a monitoração do aprendiz (Processo da Aprendizagem Eletrônica) e se obtém as informações para análise (Avaliação e Análise da Aprendizagem Eletrônica). / This thesis proposes concepts, processes and a system architecture for Monitoring and Tracking E-Learning. The architecture is defined by a conceptual model, the interaction with external services and representation XML of the concepts and the services. It does not depend on any specific pedagogical boarding. The Monitoring Point is inserted in some places of the E-Learning Content. A Monitoring Element is associated to the Monitoring Point and it is for responsible of one of the interactions of the E-Learning Process. The Monitoring Service (E-Learning Monitoring and Following Service) receives the events and requests from the Monitoring Elements and it interacts with the external services. The events are recorded in the Monitoring Repository. The E-Learning Processes definition is useful to modeling the monitoring strategy (Learning Process Modeling), and insert to the monitoring mechanisms in the E-Learning Activities (Learning Content Production Process). The learner interaction monitoring occurs by getting the information according to the previous planning (Learning Process), and the generated information (Learning Analysis and Evaluation Process) is used in the analysis of learning tracking.

The aims of this paper are to present some of the findings about the creation and utilization of online assignments and choice of support software for several calculus classes at Simon Fraser University (SFU) by considering the needs and perspectives of the instructors, students, and administrators. The term online assignment is used for a set of problems that are posted, submitted, graded, and recorded electronically through a course learning management system (LMS) of choice. The purpose of this note is to contribute to the discussion about a common question detected among research papers on the theme of online assignments; how can technology be used in teaching so that students benefit the most? Questions are provided to guide an instructor in choosing online assignment problems, and a list of necessary skills is supplied for an instructor to be able to deal effectively with this pedagogical tool.

The aims of this paper are to present some of the findings about the creation and utilization of online assignments and choice of support software for several calculus classes at Simon Fraser University (SFU) by considering the needs and perspectives of the instructors, students, and administrators. The term online assignment is used for a set of problems that are posted, submitted, graded, and recorded electronically through a course learning management system (LMS) of choice. The purpose of this note is to contribute to the discussion about a common question detected among research papers on the theme of online assignments; how can technology be used in teaching so that students benefit the most? Questions are provided to guide an instructor in choosing online assignment problems, and a list of necessary skills is supplied for an instructor to be able to deal effectively with this pedagogical tool.

This study investigated the effect of a blended-learning approach in the learning of problem-solving skills in a first-level distance education physics module. A problem-solving type of instruction with explicit teaching of a problem-solving strategy was implemented in the module, which was presented through correspondence, online using an in-house learning management system as well as two face-to- face discussion classes. The study used the ex post facto research design with stratified sampling to investigate the possible cause-effect relationship between the blended-learning approach and the problem-solving performance. The number of problems attempted, the mean frequency of using strategy in problem solving and the achievement marks of the three strata were compared using inferential statistics. The finding of the study indicated that the blended-learning approach had no statistically significant effect in the learning of problem-solving skills in a distance education module. / Educational Studies / M. Ed. (Open and Distance Learning)

In the world in which we live today, information and communication technology (ICT) has proliferated in all spheres of society, including in the corporate, social and academic arenas. Within these arenas ICT has made noteworthy contributions. In the academic space, which is the focus of this study, ICT has made a significant contribution to the communication and consultation between students and higher education institution staff. One such example has been the emergence of learning management systems (LMSs) in higher education institutions, both locally and globally, with LMSs providing higher education institutions with several possibilities as regards facilitating the online teaching and learning process. Nevertheless, research has shown that there is underutilisation of LMSs throughout the world. The purpose of this study, therefore, was to investigate the utilisation of LMSs in an open and distance learning (ODL) institution in South Africa to ascertain whether they are being used to their full potential. / Educational Studies / M. Ed. (Adult Education)

Feature extraction is an extremely important pre-processing step to pattern recognition, and machine learning problems. This thesis highlights how one can best extract features from the data in an exhaustively online and purely adaptive manner. The solution to this problem is given for both labeled and unlabeled datasets, by presenting a number of novel on-line learning approaches. Specifically, the differential equation method for solving the generalized eigenvalue problem is used to derive a number of novel machine learning and feature extraction algorithms. The incremental eigen-solution method is used to derive a novel incremental extension of linear discriminant analysis (LDA). Further the proposed incremental version is combined with extreme learning machine (ELM) in which the ELM is used as a preprocessor before learning. In this first key contribution, the dynamic random expansion characteristic of ELM is combined with the proposed incremental LDA technique, and shown to offer a significant improvement in maximizing the discrimination between points in two different classes, while minimizing the distance within each class, in comparison with other standard state-of-the-art incremental and batch techniques. In the second contribution, the differential equation method for solving the generalized eigenvalue problem is used to derive a novel state-of-the-art purely incremental version of slow feature analysis (SLA) algorithm, termed the generalized eigenvalue based slow feature analysis (GENEIGSFA) technique. Further the time series expansion of echo state network (ESN) and radial basis functions (EBF) are used as a pre-processor before learning. In addition, the higher order derivatives are used as a smoothing constraint in the output signal. Finally, an online extension of the generalized eigenvalue problem, derived from James Stone’s criterion, is tested, evaluated and compared with the standard batch version of the slow feature analysis technique, to demonstrate its comparative effectiveness. In the third contribution, light-weight extensions of the statistical technique known as canonical correlation analysis (CCA) for both twinned and multiple data streams, are derived by using the same existing method of solving the generalized eigenvalue problem. Further the proposed method is enhanced by maximizing the covariance between data streams while simultaneously maximizing the rate of change of variances within each data stream. A recurrent set of connections used by ESN are used as a pre-processor between the inputs and the canonical projections in order to capture shared temporal information in two or more data streams. A solution to the problem of identifying a low dimensional manifold on a high dimensional dataspace is then presented in an incremental and adaptive manner. Finally, an online locally optimized extension of Laplacian Eigenmaps is derived termed the generalized incremental laplacian eigenmaps technique (GENILE). Apart from exploiting the benefit of the incremental nature of the proposed manifold based dimensionality reduction technique, most of the time the projections produced by this method are shown to produce a better classification accuracy in comparison with standard batch versions of these techniques - on both artificial and real datasets.