Q: What challenges are organizations facing when they try to implement AI as part of their learning strategy?
A: There are several challenges related to implementing advanced learning systems, specifically focusing on the integration of artificial intelligence and instructional design.Acceleration of Bad Practices
One significant challenge is the tendency of advanced learning systems to accelerate existing bad practices in learning and instructional design. There is a need to redirect this trend and I advocate for a scientific and mathematical approach to make learning sciences more exact and formal, contrasting this with the empirical, data-driven approaches that are common in mainstream learning engineering.Gap in Technical Expertise
Another challenge is the gap in technical expertise among instructional designers, especially those working in for-profit organizations. Many of these professionals are familiar with basic educational theories and learning tools but lack the advanced technical knowledge required to effectively utilize more sophisticated systems. Intermediate steps are needed to bridge this gap and make advanced systems more accessible and less daunting for these professionals.Misuse of AI Tools and Market Dominance
There’s a challenge of the market being dominated by tools that are not necessarily the best for the industry or learners. I emphasize the importance of having tools that are scientifically sound and express concerns about the misuse of AI tools, such as relying on outdated or debunked theories (like learning styles) in AI-driven instructional design. This highlights the need for careful consideration in how AI models like GPT are prompted and used in educational contexts.While advanced learning systems offer significant potential, their effective implementation is hampered by a range of challenges, including the perpetuation of outdated practices, gaps in technical knowledge among practitioners, and the market-driven selection of tools that may not align with sound educational principles.Integrating ChatGPT into learning platforms
Integrating a tool like ChatGPT into learning platforms offers the potential to enhance the efficiency, effectiveness, and interpretability of learning processes.Addressing the Risk of Perpetuating Bad Practices
There’s a concern that the arrival of ChatGPT-powered tools like quiz and flash card generators, as well as content creation tools, might accelerate and increase established bad practices in teaching and learning, rather than improving them. While learners can use ChatGPT independently to learn by formulating questions and receiving responses, this method may not align with the natural human learning process, which typically involves creating mental models and learning through trial and error.Creating Infrastructure for Effective Use
The integration of ChatGPT into learning platforms includes creating infrastructure for users to generate appropriate prompts and validate GPT responses, automatically generate prompts for high-quality responses, and facilitate the entire interaction between GPT and users. This process involves a deep study of human learning theories, exploring interdisciplinary sciences, and developing a unified tutoring engine for intelligent instructional activities. The goal is to develop a comprehensive and exact framework for structuring complex instructional experiences.With all this in mind, there is a strong need for a thoughtful and scientifically grounded approach to leveraging this technology in educational contexts.Aligning our use of advanced learning systems with learning sciences
As exciting as the prospect of AI may seem to the world of learner, there are several potential challenges to bridging the gap between learning sciences and their practical implementation in the context of advanced learning systemsQ: How does AI present challenges to Instructional Design?
A: Many professionals involved in producing and delivering training in for-profit organizations have some background in educational theory and learning tools, but this knowledge is often limited by certain software like Articulate and Captivate. There is a gap in moving from understanding these content production tools to using more advanced systems. The current approach in instructional design tends to rely on heuristics (rules of thumb) and improvisation, as learning sciences do not provide an exact recipe for course development.This indicates a need for intermediate steps to bridge the gap between basic educational tools and more sophisticated systems.Lack of Access to Advanced AI and Learning Science Knowledge
There’s a recognition that not everyone in the field of instructional design has a deep background in AI, programming, or advanced learning science. There are good papers and materials available, but learning professionals need to be directed towards practical applications like generating effective prompts for AI systems. This highlights the necessity of resources that can help instructional designers without a deep scientific background to understand and apply AI in their work.Integration of AI in Learning Platforms
My approach is to integrate systemic frameworks, structure algebras, inferences, and generative engines into AI technologies like ChatGPT to improve their transparency, interpretability, responsibility, effectiveness, and efficiency. This approach aims to humanize AI by augmenting human intelligence with artificial intelligence, making the result more applicable in educational contexts. This indicates a move towards creating AI systems that are more aligned with the principles of human learning and are more accessible to educators and instructional designers.The future of AI in learning and instructional design, particularly focusing on the integration of ChatGPT and similar AI tools.Enhancing AI Capabilities for Education
The approach aims to contribute to the next generation of ChatGPT theory and technology by adding systemic frameworks, structure algebras, inferences, and generative engines. This is intended to improve aspects like transparency, interpretability, responsibility, effectiveness, and efficiency of AI.The goal is to humanize AI by augmenting human intelligence with artificial intelligence, which is increasingly relevant in connecting higher education with jobs and careers. There is a recognition of the potential of AI tools like ChatGPT to learn and respond to human queries in natural language, which can be harnessed for educational purposes.Need for Infrastructure to Support AI in Learning
It’s important to provide infrastructure to effectively integrate GPT in learning environments. This is essential for getting the most from the potential of AI in learning sciences, because the integration of computer science and learning sciences requires a robust infrastructure to be truly beneficial.Overall, the future of AI in learning and instructional design involves enhancing the capabilities of AI tools like ChatGPT for educational purposes, while being mindful of the risks of reinforcing ineffective teaching practices and the need for adequate infrastructure to support this integration.
