Beyond Personalization: Unlocking AI for Self-Learning

Valdir Souza's compelling composition (https://bit.ly/3UZXzzN) explores the widespread belief in AI's potential to revolutionize personalized education. He artfully weaves a narrative, much like a symphony, highlighting the key arguments and supporting his claims with insights from scientific literature.?

Applying critical thinking, I came to a different conclusion and wanted to share my thoughts.

The Limits of AI-Driven Personalization

Personalized lessons created by AI are not breakthroughs in Education; instead, they are attempts to integrate the old pedagogy into the new technology framework. AI algorithms analyze learners’ data to determine knowledge gaps and create personalized lessons that instruct users on filling these gaps using conscious learning/memorization. They also analyze learner data to tailor content, pace, and instructional strategies to individual learning preferences. However, a learning pathway based on past data and used to create learning instructions has little value since it is akin to the definition of insanity: repeating the same actions and expecting different results.

AI overlooks the importance of pedagogy.

Algorithm decisions are based on a myriad of data statistics, which unfortunately cannot determine the primary factor: which pedagogy was used and which new pedagogy should be applied to change the outcome. For example, traditional methods of learning a foreign language are based on conscious learning/memorization, which explains low English proficiency in many countries, even industrial ones, such as Japan, China, and Brazil. Moreover, English proficiency in these countries is gradually declining despite technological advancements, the proliferation of AI, and thousands of research studies on efficient language learning.

Remember the well-documented "replication crisis" – the widespread inability to reproduce countless scientific studies. This troubling phenomenon has many contributing factors, but the consequences are clear. This failure to replicate erodes public trust in science and fuels skepticism about research claims.

Consider the billions of dollars wasted each year on research that can't be reproduced—a shocking misuse of resources. Critically evaluating published scientific "proof " is crucial, as it often reflects the author's beliefs rather than independently verifiable truth.

I wrote a query for Gemini: What are your limitations in predicting the best pedagogy for future use?

Gemini’s response may surprise you:

“When it comes to predicting the "best" pedagogy or solution for the future, I face some limitations:

·??????? Inability to foresee novel breakthroughs:? New pedagogical approaches and solutions are constantly emerging. I might not know the latest research, trends, or technologies that could shape future best practices.

·??????? Limited understanding of evolving contexts: The effectiveness of a pedagogy or solution depends heavily on the specific context. Future contexts—social, cultural, technological—will inevitably change in ways I cannot fully anticipate.

·??????? Lack of real-world experience: While I can process and synthesize information, I lack the real-world experience of educators and practitioners who observe firsthand the successes and challenges of different approaches.”

Limitations of personalized lessons created by AI:

?????They focus exclusively on the traditional pedagogy of explicit learning (conscious learning/memorization).

??????They suffer from appalling forgetting curves and cross-translation problems hindering fluency and natural language processing.

??????The idea that tailoring instruction to specific learning styles significantly improves learning outcomes was debunked multiple times.

The Power of Self-Personalized Lessons

Learners create Self-Personalized Lessons by writing AI queries that reflect their current level in the target language, interests, and vocational needs. The objective is to create more engaging, effective, and efficient learning experiences that allow using a new pedagogy of implicit, subconscious training. The latter is instrumental in developing fluency in foreign languages since it eliminates forgetting and cross-translation problems typical for conscious learning. Learners are the creators of their learning journey and apply a new pedagogy to their created content. Thus, the impact of self-personalized lessons is dramatically different from the personalized lessons created by AI.

Deep Self-Learning transforms your creative thinking and problem-solving abilities. As Gandhi wisely said, "For things to change, I must change." You can shape your learning journey and make a real difference.

Advantages of Self-Personalized Lessons:?

????They combine the best of three revolutions: AI's power, subconscious training's benefits, and the autonomy of guided self-learning.

????Enhanced Retention and Fluency: By focusing on meaningful content and implicit, subconscious training, self-personalized lessons eliminate problems of conscious learning and encourage natural language acquisition.

?????Learner Autonomy: You are in control! You choose what you want to learn and how you want to learn it at your own pace. You're not just passively absorbing information but actively pursuing knowledge that matters to you. You are taking ownership of your education and becoming a lifelong learner.

Self-learners have a choice: Explicit or Implicit Memory and Conscious Learning or Subconscious Training.

Humans have two types of memory, Explicit and Implicit, and two systems of the mind: System One (conscious) and System Two (subconscious). AI cannot determine which type of memory and mind is used during data collection. This is the primary reason for personalized lessons' inability to maximize human efficiency in learning.

While knowledge acquisition often requires conscious effort, many skills, especially those related to complex problem-solving, language skills, and creativity, are developed through subconscious processes, practice, and immersion.

New Meaning of Self-Learning Concept

The self-learning concept has existed for centuries. Its meaning has transformed significantly due to the realization of a few facts:

·????Knowledge transfer from teachers to learners is obsolete and inefficient.

·????Knowledge requires conscious learning, whereas skills must be acquired subconsciously.

·???Knowledge is free and available to anybody. However, our technology requires ever-changing skills, so most companies, instead of diplomas, ask for skills certificates.

Modern neuroscience reveals how the brain learns and adapts, providing valuable insights for self-directed learning. Concepts like neuroplasticity emphasize the brain's capacity to rewire throughout life, highlighting the importance of continuous learning and challenging ourselves.

By understanding these principles and utilizing practical tools based on a combination of three revolutions, we can harness the power of self-learning to navigate an increasingly complex and interconnected world.

A prototype describing a paradigm shift in language learning is outlined in this post: https://www.dhirubhai.net/posts/aiwat_while-duolingo-has-revolutionized-language-activity-7245093919066062849-NJ-z?utm_source=share&utm_medium=member_desktop.

I offer free technical support to any company that turns this prototype into a commercial app and becomes the world's leading language company.