supervisors: pantelis papadopoulos & ahsen cini
Artificial Intelligence refers to technologies that can be used in problems that normally require human intelligence, such as visual perception, speech recognition, and decision making. The recent leaps in AI, largely due to machine learning and deep learning, made technology more robust and accurate in dealing with such problems. As a result, AI found several applications in Education playing the role of adaptive infrastructure, a helpful companion, or a tutor.
Nevertheless, there are still great challenges ahead. First, there is a constant need for more effective and efficient technology, as errors are still common, often with devastating consequences. Second, as information on learning and academic achievement is private and well-protected, there is a lack of the large datasets required for training machine learning models, meaning that there is not enough information for the system to accurately identify a current or desirable state. Third, even in the case of effective tools, there is still the issue of acceptance by students and teachers. This is a general issue for AI, as the interpretability of used algorithms in human terms may be extremely low. In a field such as Education where the argument is the foundation of academic discourse, accepting a suggestion from an AI system without further elaboration can be problematic and diminish the potential of the technology, raising also ethical issues.
AI applications are already in our daily lives. Some are more obvious than others. From self-driving cars and cleaning robots, to predictive text on our phones and the exercises picked for us in a language learning app. While it is possible to create your own AI applications based on your skills in R or Python, this theme is primarily for people interested in examining already available AI technologies and their impact on different facets of Education.
EXAMPLE RESEARCH QUESTIONS WITHIN THIS THEME:
- How can AI technologies increase engagement and transactivity in collaborative settings?
- How can we identify and avoid bias in AI in Education?
- How to use educational data mining and learning analytics in pedagogical meaningful guidance?
- How can voice recognition and voice-to-text technologies be used for discourse analysis and feedback?
- What are the promises, shortcomings, and barriers to adopting AI technologies in schools?
- How can AI technologies assist the teacher in monitoring, orchestrating, or assessing student activity?
TOPICS RELATED TO THE THEME
(feel free to suggest your own!):
- Artificial Intelligence and ethics
- Conversational agents in education (linked to a running project)
- Learning analytics and pedagogy