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Proposta de tesi |
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Grup de recerca |
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Conversational Agents and Learning Analytics for MOOCs Higher Education Massive Open Online Courses (MOOCs) introduce a way of transcending formal higher education by realizing technology-enhanced formats of learning and instruction and by granting access to an audience way beyond students enrolled in any one Higher Education Institution. However, although MOOCs have been reported as an efficient and important educational tool, there is a number of issues and problems related to the educational aspect. More specifically, there is an important number of drop outs during a course, little participation, and lack of students’ motivation and engagement overall. This may be due to one-size-fits-all instructional approaches and very limited commitment to student-student and teacher-student collaboration. This thesis aims to enhance the MOOCs experience by integrating: • Collaborative settings based on Conversational Agents (CA) both in synchronous and asynchronous collaboration conditions • Screening methods based on Learning Analytics (LA) to support both students and teachers during a MOOC course CA guide and support student dialogue using natural language both in individual and collaborative settings. Moreover, LA techniques can support teachers’ orchestration and students’ learning during MOOCs by evaluating students' interaction and participation. Integrating CA and LA into MOOCs can both trigger peer interaction in discussion groups and considerably increase the engagement and the commitment of online students (and, consequently, reduce MOOCs dropout rate). |
Mail: scaballe@uoc.edu Mail: jconesac@uoc.edu |
SMARTLEARN |
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Enhancing educational support through an adaptive virtual educational advisor Nowadays, many systems help students to learn. Some of them aid students in finding learning resources or recommending exercises. Others aim to help the student in the assessment phase by giving feedback. Furthermore, others monitor the student's progress during the instructional process to recommend the best learning path to succeed in the course. Depending on the objectives/competencies of the subject, some features are more suitable than others.
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Mail: dbaneres@uoc.edu Mail: mrodriguezgo@uoc.edu Mail: iguitarth@uoc.edu Mail: mserravi@uoc.edu |
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Interactive recommendation systems for higher education enrollment
Higher education students at open / distance universities enjoy from a high degree of flexibility during enrollment, which allows them to choose from a long list of subjects to complete their degree. Although this can be seen as a success of enrollment flexibility measures, it may be also the source of one of the most well-known problems in open / distance education: high dropout rates, partly caused by inadequate enrollment. In this research line we will analyze and adapt state-of-the-art recommendation systems to the particularities of the enrollment procedure, taking into account enrollment data and academic results from previous semesters but also students’ preferences and personal interests. Our goal is to design and evaluate interactive recommendation systems that provide students and their mentors with support during enrollment, following a user-centered design approach.
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Mail: jminguillona@uoc.edu
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LAIKA |
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Boardgames for education During the last years the board game field have experimented a great expansion in the means of the quantity of boardgames available, if the variety of them, of the broad coverage of topics they address and the variety of mechanics they provide. They have great potential to become a great tool for learning, as many research studies show.
In this research line, we would like to address the latest innovations of using boardgames for learning and to explore the potential of using boardgames in the eLearning context and the mechanisms that appear in them.
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Mail: jconesac@uoc.edu Mail: aperezn@uoc.edu |