| CODE | ARI2131 | ||||||||||||||||
| TITLE | Artificial Intelligence in Education (AIED) | ||||||||||||||||
| UM LEVEL | 02 - Years 2, 3 in Modular Undergraduate Course | ||||||||||||||||
| MQF LEVEL | 5 | ||||||||||||||||
| ECTS CREDITS | 5 | ||||||||||||||||
| DEPARTMENT | Artificial Intelligence | ||||||||||||||||
| DESCRIPTION | This study-unit covers a number of topical areas that combine the use of Artificial Intelligence, engaging teaching technologies, and education pedagogy. Some of these areas include: - learning analytics, - learner profiling, - knowledge representation and reasoning, - semantic web technologies, - pedagogic-agents, - tangible interfaces, - wearables, - virtual/augmented reality, - ontological modeling, - intelligent tutoring systems, - educational games, - social networks, - crowdsourcing, - ubiquitous learning environments, and - ambient intelligence. Study-Unit Aims: The main aim of this study-unit is to introduce and investigate the use of AI in Education bringing together several AI topics, technology-enhanced education, and engaging / innovative technologies. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Define through practical and real scenarios the use of AI within educational setting; - Recognize the benefits of employing technology-enhanced methodologies to plan and design pedagogical sound experiences; - Identify different web technologies (Web 2.0) that can be assist educators during a learning process; - Discuss and justify the use of modern engaging technologies like social media, virtual reality and games with a classroom to assist and facilitate the educators' task; - Outline and distinguish the different technologies employed within a technology-enhanced education process to show the benefits extracted. 2. Skills: By the end of the study-unit the student will be able to: - Apply Artificially Intelligent techniques to generate learner profiles during an educational process; - Examine and interpret learning analytics collected and apply them to other academic situations; - Represent different learner knowledge and reasoning employing established AI technique to other similar situations within a school context; - Employ software development skills to design and build a prototype artefact that employs AI in education; - Recommend the use of specific technology-enhanced techniques within a particular academic situation; - Interpret and evaluate related artificial intelligence in education literature to present and defend personal opinions and interpretations. Main Text/s and any supplementary readings: Montebello, M. (2018) AI Injected e-Learning: The Future of Online Education, Springer International Publishing, ISBN 978-3-319-67928-0. Luckin, R., & Holmes, W. (2016). Intelligence Unleashed: An argument for AI in Education. Pearson, Open Ideas Series. (available online at: https://www.pearson.com/content/dam/corporate/global/pearson-dot-com/files/innovation/Intelligence-Unleashed-Publication.pdf) |
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| STUDY-UNIT TYPE | Ind Study, Lecture, Project and Online Learning | ||||||||||||||||
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| LECTURER/S | Vanessa Camilleri |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2024/5. It may be subject to change in subsequent years. |
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