Date
Publisher
arXiv
The rapid emergence of generative artificial intelligence (AI) and related
technologies has the potential to dramatically influence higher education,
raising questions about the roles of institutions, educators, and students in a
technology-rich future. While existing discourse often emphasizes either the
promise and peril of AI or its immediate implementation, this paper advances a
third path: a principled framework for guiding the use of AI in teaching and
learning. Drawing on decades of scholarship in the learning sciences and uses
of technology in education, I articulate a set of principles that connect broad
our educational goalsto actionable practices. These principles clarify the
respective roles of educators, learners, and technologies in shaping curricula,
designing instruction, assessing learning, and cultivating community. The piece
illustrates how a principled approach enables higher education to harness new
tools while preserving its fundamental mission: advancing meaningful learning,
supporting democratic societies, and preparing students for dynamic futures.
Ultimately, this framework seeks to ensure that AI augments rather than
displaces human capacities, aligning technology use with enduring educational
values and goals.
Study at a glance
- Question: What principles should guide educators and policymakers when integrating artificial intelligence into teaching and learning?
- Setting and data: Higher education focus, with broader relevance to pre- and post-college environments; no empirical dataset analyzed.
- Method: Conceptual and policy analysis based on learning sciences and technology literature
Why it matters
Discourse often focuses only on AI's promise and peril or its immediate implementation. A principled framework is needed to bridge this gap, ensuring AI augments rather than displaces human capacities while aligning with enduring educational values.
Key findings
- Educational practices with AI must center on three core human objectives: cultivating discernment, fostering empathy for collaboration, and building a learner's sense of self and agency.
- Instructional designs require determining which tasks must remain educator-led and student-led versus what responsibilities can safely and feasibly be outsourced to AI technologies.
- Without proactive guidance, ubiquitous AI access risks devolving educational goals into superficial performance and cheating, while widening learning gaps for lower-resourced learners.
Summary drafted with AI from the full paper and may contain errors. See the full paper for details.
What is the application?
Who is the user?
Who age?
Why use AI?
Study design
