In the past year, significant strides have been made in the field of AI, particularly in generative models [1]. Despite this progress, much of the attention has been directed toward textual generative AI models, leaving other AI models for image, slides, and video generation in the shadows. This prompts a reflection on the predominant text-based nature of our education system. For individuals in STEM disciplines, it's common to encounter slides and textbooks that lean heavily towards textual content, often with minimal emphasis on visual elements. This observation raises questions about the balance between textual and visual components in educational materials.

If you're acquainted with my online ventures, you've likely noticed my inclination to explore both visual and textual realms, weaving together photography and occasional videos. The advent of generative AI models has undeniably transformed these creative pursuits. If you've engaged in generating texts, images, or videos using prompts, you've also likely witnessed the evolution in their generation over time. While the initial release of these models sparked considerable debates [2,3,4], especially within the education sector, I'll steer clear of looking into those discussions here. Instead, I'm reserving the space for a future exploration of the potential impact of generative AI on education—stay tuned for that intriguing conversation. For now, let's shift our focus to the imperative of exploring multimodal AI in the realm of education.

Two critical facets demand our attention: the learning profiles of students and their existing knowledge base. Traditional education often assumes a uniform baseline of knowledge among students, a notion that doesn't align with reality. Students harbor diverse interests and varying depths of knowledge acquired from external sources. This diversity places some students in a position of revisiting familiar terrain during class discussions, a scenario where the implementation of spaced repetition could be beneficial. However, this begs the question of whether their classroom time could be better spent exploring more advanced topics. Conversely, there are students who may lack essential skills for a new course, hindering their comprehension. This underscores the challenge of catering to diverse student needs within a singular educational framework.

Building on the aforementioned point, the diversity in students' learning preferences is a significant factor often overlooked in our predominantly textual education system. Addressing this, there arises a need to align educational content with students' preferred media. The challenge of creating content in multiple formats may seem daunting for educators, yet leveraging the versatility of prompts in generating diverse media can be a potent solution [5,6]. This opens up exciting possibilities for tailoring educational materials to suit individual learning styles, fostering a more inclusive and engaging learning experience.

We stand at the threshold of a potential revolution in the education sector, one driven by the integration of AI tools that could pave the way for personalized courses [7,8,9] tailored to individual students. Picture a classroom where teachers seamlessly address questions they might not have immediate answers to by directing students to pertinent sources, leveraging the vast informational landscape. Envision students adorned with headphones, each navigating their educational journey at a personalized pace. This prompts us to ponder the evolving role of teachers in this transformed educational landscape. Will they transition into facilitators, guiding students [10] through a customized learning experience? The prospect of reimagining traditional classroom dynamics sparks curiosity about the unfolding narrative of education in this AI-driven era.

References

  1. Incredibly smart or incredibly stupid? What we learned from using ChatGPT for a year
  2. Bender, Emily M., et al. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜” Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, Association for Computing Machinery, 2021, pp. 610–23. (PDF)
  3. New York City schools ban access to ChatGPT over fears of cheating and misinformation
  4. Here are the schools and colleges that have banned the use of ChatGPT over plagiarism and misinformation fears
  5. Introducing SeamlessM4T, a Multimodal AI Model for Speech and Text Translations
  6. What is Multimodal Search: "LLMs with vision" change businesses
  7. Education 2.0: How Technology is Changing the Way We Learn
  8. Generative Artificial Intelligence in education: What are the opportunities and challenges?
  9. ChatGPT is going to change education, not destroy it
  10. OpenAI wants teachers to use ChatGPT for education