Designing and evaluating the acceptability of Conversational Recommender Systems for E-Learning
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School of Science |
Master's thesis
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en
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67
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Abstract
To assist educators in creating courses, this thesis studies the incorporation of a conversational agent into the WhoTeach® e-learning platform. The thesis highlights the e-learning industry’s rapid adaptation to online environments and the resulting obstacles by examining the industry’s situation before and during the COVID-19 epidemic. The report highlights how artificial intelligence (AI), and chatbots in particular, are becoming increasingly important in improving learning opportunities. But it also highlights the lack of assistance to teachers in course management. The main goal is to create a conversational agent that assists teachers by suggesting teaching materials such as videos, quizzes, documents and exercises. The design and implementation of the system is based on the principles of Human-Computer Interaction (HCI). In terms of methodology, focus groups, prototyping and the Unified Theory of Acceptance and Use of Technology (UTAUT) paradigm are used to evaluate the acceptability and usefulness of the system. The results show that the conversational agent has the potential to be an important tool in e-learning environments, showing significant improvement in the effectiveness and efficiency of course construction. By addressing both the technical elements and the user experience, this thesis advances the field by offering insights for the development and implementation of artificial intelligence-driven instructional assistance systems.Description
Supervisor
Nieminen, MarkoThesis advisor
Epifania, FrancescoMatamoros, Ricardo