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Student-Centered, AI-Enhanced Manifesto

I am working on an update to my post about how Our Education System is Broken. This is a second draft of a manifesto that outlines what we could do to fix it.

Update note: This document, titled 'Education Reimagined,' is intended to lay down the foundational principles that will frame a larger and evolving discussion about the future of education. While the term 'manifesto' has been used to describe it, reflecting its true dictionary definition as a declaration of intentions, it is recognized that this word may be seen as provocative to some readers. Please know that the intent here is not to provoke but to inspire and engage in meaningful dialogue. If the term 'manifesto' is a barrier, you may choose to view this as a 'statement of underlying principles' that seeks to bring together diverse perspectives in shaping an education system that respects and nurtures the individuality and potential of every learner.

Education Reimagined: A Student-Centered, AI-Enhanced Manifesto

  1. Inherent Worth and Dignity: Every student has inherent worth, and our reimagined education system will uphold this principle, embracing individuality and diversity (Rogers, 1980).
  2. AI-Driven Personalized Learning: Utilizing AI technology, students will receive individual one-on-one learning plans. These plans will be dynamic, adapting to students' unique strengths, needs, interests, and identities (Rose et al., 2019). The rigid "one-size-fits-all" approach is replaced with AI-guided customization, enabling all students to thrive at their own pace (Parsons, 2022).
  3. Empowered Students as Agents and Teachers: Students will be empowered as both learners and teachers, shaping their own educational journeys and contributing to the learning of their peers (Mitra, 2013). This collaborative environment fosters autonomy, creativity, and empathy, building a community of lifelong learners (Sawyer, 2008).
  4. Flexible, Multi-Age Learning Communities: Learning will occur in flexible, multi-age communities. AI's adaptability will support personalized skill grouping, mentorship, and collaboration (OECD, 2018), minimizing competition and arbitrary age-based segregation (Kohn, 1992).
  5. Holistic Development with AI Integration: Executive function, social-emotional learning, and identity development will be integrated with academics, nurtured through AI's continuous assessment and personalized support (D'Mello et al., 2021). This approach cultivates well-rounded human beings (Nagaoka et al., 2015).
  6. Community Integration and Real-World Engagement: Schools will be woven into community fabrics, connecting learning with lived experiences (OECD, 2020). Real-world internships, apprenticeships, and projects will be facilitated, with AI assisting in aligning opportunities to individual interests and strengths (Luckin et al., 2016).
  7. Strength-Based, Mastery-Oriented Assessment: AI-enhanced assessments will focus on students' strengths and mastery (Tomlinson, 2014). Advancement will be determined by skills demonstration, not age or time, supporting a more natural and personalized progression (Clarke et al., 2003).
  8. Normalization of Neurodiversity: Neurodiversity will be embraced, and universally designed AI-supported curriculum will cater to diverse learning styles (Meyer et al., 2014). Medical labels and deficits will be supplanted by recognition of each student's unique attributes (Armstrong, 2017).
  9. Educators as Facilitators in an AI-Assisted Environment: Educators will act as facilitators, fostering agency and intrinsic motivation (Pink, 2011). AI will augment their capabilities, allowing them to focus on personal connections and growth (Jiang et al., 2022). Coercion and control are replaced with autonomy and choice, enhanced by AI's precision and adaptability (Kohn, 1999).

References:

Armstrong, T. (2017). Neurodiversity in the classroom: Strength-based strategies to help students with special needs succeed in school and life. ASCD.

Clarke, S., Timperley, H., & Hattie, J. (2003). Assessing formative assessment. Hodder Moa Beckett Publishers.

D’Mello, S., Rosé, C. P., Taylor, L., & Graesser, A. (2021). Affect-aware learning technologies. Elsevier.

Jiang, S., Williams, A., Schenke, K., Warschauer, M., & O'Dowd, D. (2022). Predicting paper score performance using discourse analytics on student writing. Computers & Education, 104479.

Kohn, A. (1992). No contest: The case against competition. Houghton Mifflin.

Kohn, A. (1999). Punished by rewards: The trouble with gold stars, incentive plans, A's, praise, and other bribes. Houghton Mifflin Harcourt.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.

Meyer, A., Rose, D. H., & Gordon, D. (2014). Universal design for learning: Theory and practice. CAST Professional Publishing.

Mitra, S. (2013). Build a school in the cloud. TED Talk. https://www.ted.com/talks/sugata_mitra_build_a_school_in_the_cloud

Nagaoka, J., Farrington, C. A., Ehrlich, S. B., & Heath, R. D. (2015). Foundations for young adult success: A developmental framework. UChicago CCSR.

OECD. (2018). The future of education and skills: Education 2030. https://www.oecd.org/education/2030-project/contact/E2030_Position_Paper_(05.04.2018).pdf

OECD. (2020). The impact of COVID-19 on student equity and inclusion: Supporting vulnerable students during school closures and school re-openings. https://www.oecd.org/coronavirus/policy-responses/the-impact-of-covid-19-on-student-equity-and-inclusion-supporting-vulnerable-students-during-school-closures-and-school-re-openings-d593b5c8/

Parsons, S. (2022). Ethics, artificial intelligence, and education: An introduction. Learning, Media and Technology, 1-13.

Pink, D. H. (2011). Drive: The surprising truth about what motivates us. Penguin.

Rogers, C. R. (1980). A way of being. Houghton Mifflin.

Rose, D. H., Gravel, J. W., & Domings, Y. M. (2019). UDL Unplugged: The Role of Technology in UDL. http://udl-irn.org/udl-unplugged/

Sawyer, R. K. (2008). Optimising learning: Implications of learning sciences research. In OECD/CERI International Conference Learning in the 21st Century: Research, Innovation and Policy. https://www.oecd.org/site/educeri21st/40554299.pdf

Tomlinson, C. A. (2014). Differentiated classroom: Responding to the needs of all learners. ASCD.

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