Unlocking Educational Equity: Exploring AI-Responsive Learning: Part 1
Educating AI for a More Equitable Future: Lessons in Adaptive Learning"
“Personalizing Pathways, Energizing Equity,” Image Generated by Midjourney.
What Types of Posts Do You Like Most?
Here at Educating AI we offers several distinctive types of posts:
Close examinations of the core principles of AI-Responsive Education
Deep dives into theoretical issues underpinning AI-Responsive Education
Lesson-plans and unit-studies for AI-Responsive Curriculum
Explorations of educational prompt-engineer and case-use
Literary engagements with AI-Responsive fiction, nonfiction, and memoir
As the audience of Educating AI grows, I am interested in what kinds of posts are most meaningful or useful to my readers. If you have a moment, please send me a note letting me know what kinds of content you would like to see more of in the future posts. Or drop a note in comments.
AI-Responsive Education: The Core Principle of Equity
In my guest post for AI Supremacy, I posited 4 core principles at the heart of AI-Responsive Education: (1) Connection, (2) Equity, (3) Purpose, and (4) Experience.
I think of these Principles as Design Features that educators can use when creating systems to respond to and engage with generative AI technologies inside and outside the classroom.
As guiding principles, they are broad and evocative; they are fields of inquiry that establish provisional boundaries even as they spur on ongoing processes of creation.
As any good designer will tell you, too firm or rigid of foundational principles will restrict a creative process before it has the chance to get started. In this spirit, I continue to offer up these Core Principles of AI-Responsive Education.
Equity, Adaptive Learning, Personalization
In this post, I will only be able to scratch the surface of the Principle of Equity. Here, I will focus primarily on Equity in relationship to Adaptive Learning and Personalization of Instruction, following in the footsteps of some very interesting Substack posts by Dan Meyer of Mathworlds and Bechem Ayuk of The Value Junction.
In my two-part post, I will fuse two of my post-types together: (1) a critical examination of a core principle with (2) some practical lesson planning for the practitioners in my audience. I hope you enjoy!
Equity: Helping All Students Reach Their Potential
In education, Equity refers to the principles and process of providing all students with resources, support, and opportunities they need to achieve the full academic potential, regardless of their individual characteristics, backgrounds, prior learning, or circumstance. Equity aims to ensure fairness and justice in the educational system, reducing disparities in educational outcomes and opportunities among different student groups.
“Equality and Equity as Political Principles,” International Women’s Day 2024.
Equity in education is often contrasted with equality, which assumes that all students receive the same resources or treatment. In contrast, equity recognizes that students have diverse needs and circumstances and strives to provide what is necessary for each student to succeed.
Equity and Adaptive Learning: The Connection
In school, equity and adaptive learning are interconnected. Adaptive learning refers to a personalized and data-driven approach to education that tailors instruction to individual students' needs, abilities, and learning styles. The promise of adaptive learning is its ability to offer a more equitable form of curriculum, instruction, and assessment.
Promoting Inclusivity: Adaptive learning actively strives to ensure that all students have access to the highest quality education. It caters to the specific learning requirements of each student, irrespective of their background or learning challenges. This approach fosters a more inclusive educational environment where every student feels supported and valued.
Cultivating Self-Efficacy: As adaptive learning empowers students to take control of their educational journey, it often leads to an increase in self-efficacy. Students become more confident in their abilities as they see their progress and growth in a personalized learning environment.
Reducing Opportunity Gaps: Adaptive learning has the potential to minimize opportunity gaps that may arise from differences in students' socioeconomic status or access to educational resources. By tailoring content and instruction to individual needs, it helps level the playing field and provides an equitable chance for all students to succeed.
Real-World Preparation: As adaptive learning adapts content and instruction to the demands of the contemporary world, it equips students with relevant skills and knowledge, preparing them for success in a rapidly changing job market. This empowerment can be particularly vital for underserved and under-resourced communities, as it opens doors to a wider range of opportunities.
Adaptive Learning through Personalization
At a recent Global Online Academy seminar on “Assessing Learning with AI,” Director of Professional Learning Deepjyot Sihdu presented personalization of instruction as the equity “superpower” behind most adaptive learning. In my lesson below, I will build on this key insight.
Sidhu and GOA understand personalization of learning as unfolding through 3 interconnected dynamics:
“Agency: How might I offer students more voice and choice in what and how they demonstrate their learning?”
“Depth: How might I offer students opportunities to dig deeper than before?”
“Relevance: How might I offer students chances to connect their learning to their own lives in more meaningful ways?”
Importantly for our venture here at Educating AI, generative AI offers the educator an amazing opportunity to adapt and personalize curriculum, instruction, and assessment in new and innovative ways, potentially creating more inclusive and equitable classroom spaces as a result.
It is not that AI allows us to personalize in a fundamentally new way. Rather, AI allows us to deepen existing practices and methods given an instructor’s willingness to engage with these new tools in a critical, ethical, and creative manner.
Lesson: Student-Choice Vocabulary Lists
For this lesson, students will need access to a LLM.
I realize that this is still a tricky question for many schools and educators.
Permissions are a tricky thing to navigate and negotiate. ChatGPT users can be 13 years of age. Claude users need to be 18 or over.
Should teachers send out an announcement through a LMS informing that students will sign-up?
Signing up usually entails entering both a school email and a phone number verification.
Should teachers send home permission slips?
Schools are still working out their protocols. I would love to hear from educators on how your school is working through these complexities.
This lesson is designed to be an ongoing process that students engage with as they read a longer text across a unit.
Upcoming Posts
In my next post, I will present a comprehensive lesson plan for a vocabulary unit where students can choose the words they want to learn.
In this unit, students will harness the power of artificial intelligence to enhance their core vocabulary skills based on a central text.
The lesson has three main stages:
In the first stage, students will identify vocabulary words that align with the unit's objectives, their reading level, and personal interests.
In the second stage, students will use AI to practice these vocabulary skills to prepare for a final assessment. During this practice phase, they will gather data and evidence, which their teacher will review. This feedback loop allows for adjustments to the instruction and practice methods to cater to individual and group needs.
In a third stage, students will utilize AI to create customized quizzes for the specific words they have chosen to learn. They will structure their responses in a way that instructors can easily input into a LLM for quick assessment.
Thanks for reading Educating AI.
Nick Potkalitsky, Ph.D.
Regarding my preferred post types: Yes! Send them all!