Project details
Title: Empowering E-Learning Platforms with ChatGPT, Bard and Advanced
NLP: A New Era of AI-Driven Education.
Description: The e-learning landscape is rapidly evolving, with learners seeking
more interactive and personalized educational experiences. This research delves
into the integration of advanced NLP models, such as ChatGPT and Bard, into elearning platforms, aiming to create a more dynamic, responsive, and tailored
educational journey for users.
Objectives:
1. Literature Review: An extensive exploration of the current e-learning
ecosystem, highlighting the growing role of AI and NLP in shaping
educational experiences.
2. GPT in E-Learning: A thorough analysis of the potential of models like
ChatGPT and Bard in transforming e-learning platforms, from personalized
tutoring to dynamic content generation.
3. Design and User Experience: Key factors to consider when embedding
ChatGPT into e-learning environments. This includes understanding the
diverse needs of learners, curriculum constraints, and ensuring intuitive
user interactions.
4. Adaptive Learning Pathways: Investigating how ChatGPT and similar
models can be used to craft personalized learning trajectories, adapting
content and resources based on individual learner progress and feedback.
5. Ethical and Inclusivity Concerns: Addressing challenges related to ensuring
that AI- driven educational tools are unbiased, inclusive, and cater to a
diverse learner base.
6. Proof-of-Concept Development: Designing and building a prototype elearning platform that seamlessly integrates ChatGPT, showcasing its
potential in revolutionizing digital education.
7. User Evaluation: Conducting tests with learners from various backgrounds
and educational levels, collecting feedback on the platform’s adaptability,
engagement levels, and overall educational impact.
*** Bard is now Gemini
The specific issue concerns both education and artificial intelligence.
Therefore, due to my field of study, the approach to the subject must be made from the point of view of artificial intelligence.
In addition, I do not have that much technical knowledge on computer science since I am a mathematician, so the implementation part (points 6-7) should be more theoretical. (I also know this from the communication with the supervising professor so far)
Therefore, our particular emphasis should be on points 2-5
In general, the instructions I have from the supervising professor are not very directive since his approach is to go wherever the thesis is and it will be done roughly as I want.
Research will guide us….
What I know is that for elearning platforms, a general review should be made, but Moodle, which is a free opensource platform, should be mentioned.
In my opinion, it is crucial to make extensive reference to Large Language Models (LLMs) and to analyze their capabilities… References to training, fine-tuning, prompt tuning
methods tailored to the specific needs of platforms.
+ LLMs extensions/plugins
As I said before, creating a platform is not necessary, so points 6-7 are not mandatory (unless it changes them down the road, which I don’t think)
However, we should approach them a little theoretically, perhaps by
we present some suggestions (You with your experience will know better how we can approach this)