The Big Picture
102 Papers, Four Dimensions
We reviewed the abstract of every proposal accepted by the AI SIG in the SITE 2026 conference, classifying each along four dimensions: what topic it addresses, what context it studies, what role AI plays in the research, and whether specific subject-matter content is involved. Here's what the landscape looks like.
The Topics
What Are We Talking About?
Seven topic areas emerged from the analysis. The conversation is dominated by two concerns: how ready educators are for AI (Competencies, Perceptions, and Adoption) and what the ethical guardrails should be (AI Ethics and Policy). Together these account for more than half of all papers. Hover over any card to see its papers.
Topic Distribution
Number of papers per topic area
The largest cluster — Competencies, Perceptions, and Adoption (34 papers) — is asking a fundamentally pre-adoption question: are we ready? The second-largest — AI Ethics and Policy (22 papers) — is asking a governance question: how do we keep this safe? Meanwhile, only 7 papers focus primarily on how AI shapes student learning itself.
The Role of AI
How Is AI Positioned?
Beyond topic, each paper positions AI differently. Is AI the tool being used? The subject being studied? A collaborator in the research process? The answer reveals how the field conceptualizes the relationship between educators and AI.
Roles at a Glance
Each square is one paper, colored by the role AI plays
Half of all papers (51) position AI as a Tool or Assistant — something to be used. A third (33) treat AI as a Subject of Inquiry — something to be studied and understood. Only 10 position AI as a Partner or Collaborator, and just 4 as a Tutor, Coach, or Generator. The field is still in an early phase: figuring out what AI is before figuring out what to do with it.
Role of AI by Topic Area
How each topic positions AI
The Context
Where Is This Research Happening?
As a teacher education conference, it's no surprise that Teacher Education is the most common research context. But note that nearly a quarter of papers don't specify a context at all — they discuss AI in education generically.
Research Context
Where the research takes place
Content Areas
Does Subject Matter Matter?
We also asked: does each paper engage with a specific subject-matter content area — math, science, literacy, the arts — or does it treat AI as content-agnostic? The vast majority discuss AI without reference to any specific discipline.
Content Area Breakdown
Each square is one paper
Only 27 of 102 papers (26%) name a specific content area. Of those, Literacy & Languages leads with 13, followed by STEM with 9. The remaining 75% discuss AI as if the subject being taught doesn't matter — a notable gap for a field that knows pedagogy is always shaped by content.
Methods
How We Did This
Data Collection & Classification
We collected all 102 unique propsals accepted to by the AI SIG for SITE 2026, extracting titles, abstracts, and keywords. Each paper was classified along four dimensions: Topic Area (the primary research focus), Context (the educational setting studied), Role of AI (how AI is positioned in the paper), and Content Area (whether specific subject matter is involved).
Visualization
The topic landscape uses TF-IDF vectorization of paper text, reduced to two dimensions via t-SNE. The keyword network shows co-occurrence relationships among the most frequent terms. All interactive visualizations are built with D3.js.
A Note on AI-Assisted Analysis
This analysis was conducted with the assistance of Claude (Anthropic). Metadata extraction, thematic clustering, and visualization generation were AI-assisted. Classifications were reviewed and corrected by the researcher, but some inaccuracies may still exist.