As developed and advocated by Purkey and
Novak (2015), Invitational Education (IE) theory and practices, emphasize empowering
people to create places, policies, programs, and process that invite all
students to realize their potential. IE is grounded in five guiding principles:
intentionality, care, optimism, respect, and trust (I-CORT). IE’s core values can offer a
human-centered, ethical lens for integrating generative artificial intelligence (AI) into effective teaching and
learning.
Intentionality
should be the foundation of an I-CORT mindset (Purkey & Novak, 2015; Purkey, Novak, & Fretz, 2020; Anderson, 2024). Positive outcomes
come from intentional actions. This assumption empowers people to thoughtfully
integrate AI to support meaningful learning. When people intentionally and
strategically use AI implications include enhancing student engagement, agency,
and access rather than becoming a replacement for teaching. For example, when AI
is accessed in a Universal Design for Learning (UDL)-aligned platform, teachers can
more readily offer multiple means of representation and expression aligned to
their knowledge of the students’ diverse learning needs or preferences.
Perhaps a paradox, but stakeholders can
promote care by promoting human connection through AI-enhanced teaching. Advocates for IE theory
and practices believe caring relationships are at the heart of effective
education. Therefore, AI should augment
human interaction rather than reduce it. AI can efficiently design teaching and
learning tools that free teachers to focus more on relationships. When AI is
utilized to automate routine tasks such as basic grading, teachers can dedicate
more time to mentoring students through formative processes.
Surely optimism will be more evident
when teachers use AI to amplify students’ potential rather than their deficits.
Proponents of IE believe every student has untapped potential. A teacher’s
unconscious biases can be mitigated through AI utilization that avoids
deficit-based labels and instead, reveals strengths and growth areas. The
adaptive assessment tools available through AI can efficiently highlight
progress and recommended enrichment opportunities that the teacher effectively
identifies based on knowledge of the student.
IE theory believes that every person is
valuable and capable of learning. This
respect for the learner would be exhibited by the teacher designing or
identifying AI tools that honor student dignity and identity. Therefore, ensure AI tools respect diverse
identities by monitoring these tools for culturally responsive design and unbiased algorithms. For instance, only use AI-powered
writing tools that offer constructive, formative feedback without penalizing
dialects for multilingual learners.
Completing the I-CORT mnemonic, trust is
developed and sustained only by building or demanding transparent and ethical
AI systems. Every learning environment’s 5 Ps: its people, places, policies, programs, and processes, are essential elements that need to be
trustworthy to foster student growth. So, educational leaders and developers
must prioritize data privacy, transparency, and explainability in AI systems.
This is exemplified when using AI platforms that allow students and teachers to
understand how data is used and how recommendations such as personalized
learning paths are developed.
By aligning generative AI utilization with
the guiding principles of Invitational Education theory, educators can ensure
that technology serves as an invitation to learn and grow. Otherwise, we can
quickly become complicit in managing a surveillance mechanism or gatekeeping
instrument. Invitational Education theory, practices, and assumptions create
inclusive, empowering, and ethical learning environments whereby empowered teachers help students feel valued, supported,
and challenged.
To
cite:
Anderson, C.J. (June 30, 2025) Invitational Education theory and
assumptions can guide AI utilization for effective teaching and learning.
[Web log post] Retrieved from http://www.ucan-cja.blogspot.com/
References:
Anderson, C. J.
(2021). Developing your students' emotional intelligence and philosophical
perspective begins with I-CORT. Journal of Invitational Theory and
Practice, 27, 36-50.
Black,
P., & Wiliam, D. (2006). Developing a theory of formative assessment. In J.
Gardner (Ed.), Assessment and learning (pp. 81–100). Sage.
Calisici Celik N., Kiral B. (2022). Teacher empowerment
strategies: Reasons for non fulfilment and solution suggestions. Journal
of Qualitative Research in Education, 29, 179–202. https://doi.org/10.14689/enad.29.7
CAST (2024). Universal Design for Learning Guidelines version 3.0.
Retrieved from https://udlguidelines.cast.org
International Society for Technology in Education. (2025.). AI
in education and accessibility. ISTE. https://www.iste.org
Limon I.
(2022). Relationship between empowering leadership and teachers’ job
performance: Organizational commitment as mediator. Journal of Theoretical
Educational Science, 15(1), 16–41. https://doi.org/10.30831/akukeg.945201
Purkey, W. W.,
& Novak, J. M. (2015). Fundamentals of invitational education. (2nd Ed)
International Alliance for Invitational Education. Retrieved from: Fundamental of Invitational Education |
IAIE
Purkey, W.W.,
Novak, J.M., & Fretz, J.R. (2020). Developing inviting schools: A
beneficial framework for teaching. Teachers College Press.
U.S. Department of Education, Office of Educational Technology.
(2023). Artificial intelligence and the future of teaching and learning:
Insights and recommendations. https://files.eric.ed.gov/fulltext/
