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We have an open PhD position as part of a large interdisciplinary research project. Collaborating research groups include the Leuven Engineering and Science Education Center (supervisor Tinne De Laet) and the Linguistics Research Unit (supervisor Tim Van de Cruys).
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The objective of this interdisciplinary project is to advance the field of generative Artificial Intelligence (genAI) and explainable AI (XAI) within the Learning Analytics (LA) domain. The goal is to facilitate the adoption of AI in higher education by generating and designing explanations of AI outputs for students and teachers using a combination of open-source Large Language Models (LLMs), interactive visual analytics, and machine learning (ML). As the future of AI should be perceived from a “hybrid intelligence” perspective, where AI is seen as a participant in conversations for learning, the project aims to gain better insight into these conversations to improve the quality of learning and education.
The project will specifically focus on strengthening the AI algorithms, particularly LLMs, to support students and teachers as collaborators with genAI and XAI. Explanations play a key role in approaches to strengthen LLMs, as research has shown hybrid explanations, either originating from humans or AI algorithms, have the potential to improve open-source LLMs. In the project, explanations serve a dual role:
The PhD position will focus on the following research question: How can hybrid explanations provided by humans (domain/educational experts including teachers) and AI algorithms improve the performance of open-source genAI algorithms and LLMs?
Currently, research on open-source LLMs is a high priority, aiming to provide an alternative to commercially available LLMs, which have raised questions concerning their transparency, ethical values, sustainability, dependency on big tech, and climate impact. Open-source LLMs have the potential to be custom-trained transparently and targeted, giving control back to developers and owners. The conceptual innovation of this project is the improvement of open-source LLMs' performance and behavior using hybrid explanations, combining AI-generated and human-generated (domain-expert) explanations. This will connect genAI, currently considered a black box, to theory-driven LA, which builds on educational theories and models. It will also offer customization of LLMs that higher education institutions seek, allowing for more transparent and ethical use of generative AI. Additionally, using AI explanations to improve the LLM itself is innovative, opening routes for peer-improvement and self-improvement of AI models.
We expect the following from applicants:
The position comes with full funding for four years, available from October 1, 2024. The actual starting date is negotiable.
The research will be conducted at the Faculty of Engineering Science of KU Leuven, campus Heverlee, and the Faculty of Arts of KU Leuven, Linguistics Research Unit, campus Leuven.
For more information, please contact Prof. dr. ir. Tinne De Laet, tel.: +32 16 32 70 75, email: tinne.delaet@kuleuven.be, or Prof. dr. Tim Van de Cruys, tel.: +32 16 32 35 19, email: tim.vandecruys@kuleuven.be.
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