EVIDENCE · LEARNING · INTELLIGENCE
Understanding Human Learning in an Age of Artificial Intelligence
Exploring how evidence can inform the design, evaluation, and responsible use of artificial intelligence.
As intelligent technologies become increasingly capable, an essential question remains: How do we ensure that technological advancement also advances human understanding, learning, and capability?
At Aspen Grove Research, this question guides an emerging research agenda at the intersection of learning science, artificial intelligence, and human–AI collaboration.
THREE INTERCONNECTED AREAS OF INQUIRY
Understanding Learning. Evaluating Intelligence. Advancing Human Capability.
Learning Science & Human Intelligence
How people acquire knowledge, develop expertise, and build lasting understanding.
AI Evaluation & Alignment
How AI systems can be evaluated against established evidence and principles.
Human–AI Collaboration & Innovation
How interactions with AI shape thinking, decision-making, and human capability.
Our Areas of Inquiry
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Understanding how people learn is foundational to developing technologies that meaningfully support human growth.
This area explores how individuals acquire knowledge, develop expertise, and build the cognitive capabilities necessary for meaningful learning. Areas of interest include cognitive science, literacy development, instructional design, and the relationship between learning environments and human understanding.
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The capabilities of artificial intelligence must be considered alongside the quality, accuracy, and research alignment of what these systems produce.
This area examines approaches to evaluating AI-generated content and interactions against established research, with particular attention to instructional accuracy, alignment with learning science, and opportunities for systematic refinement.
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As artificial intelligence becomes increasingly integrated into learning and decision-making, understanding its relationship with human intelligence becomes essential.
This area explores how people interact with intelligent systems, how those interactions may influence reasoning and expertise, and how emerging technologies might strengthen rather than replace meaningful human engagement.
