Debate & Autism
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Gabriel Esquivel

Special education researcher · Debate educator · Applied AI

I'm an education researcher focused on how AI tools can work alongside evidence-based practices to reduce educational disparities for students with disabilities. My research practice grew out of eight years of competitive debate, developed through six years at a debate education startup in Taiwan, and is now grounded in formal training at the University of Kansas. I prepare English-language learners in grades 2–12 to compete against native speakers at international debate tournaments — and I build the measurement tools my classroom needs and does not yet have.

Taipei, Taiwan · email in the footer

Classes I teach

Policy Debate

The deep end: a year-long topic, evidence-heavy research, and two-on-two rounds where students build and defend a plan against every angle of attack. The format behind the open-source briefs below.

Public Forum Debate

Monthly topics drawn from live public controversy, judged for persuasion of an intelligent non-specialist — the format that teaches students to be understood, not just correct.

Political Gamification

An experimental curriculum where students role-play political avatars through debates and strategy games. Pre/post surveys and a self-reflection rubric measure anxiety, evidence usage, rule adherence, and whether students can explain what bias is and why people write evidence.

Smart Debate

Public Forum cut in half for elementary-school students — shorter speeches, same structure, so the youngest debaters get the real format at a size they can carry.

Debate Social Skills

Debate as a social-skills intervention, connected to my research adapting the ASCS-2 Autism assessment for measuring social skills in a debate context.

Education

MS, Special Education — University of Kansas, expected Fall 2026
BA, Economics — University of Kansas, 2017–2020 (recruited to debate on scholarship)

Debate record

Students coached

A note on language

This site follows the KU Department of Special Education's person-first convention — “a student with autism,” not “an autistic student” — while respecting that many people in the Autism community prefer identity-first language (“autistic”) because they consider Autism integral to who they are, not a limitation. Where this site quotes or describes people who state that preference, their preference wins. “Neurotypical” is used instead of “normal,” because the opposite of normal is strange, and nobody here is strange.

McKeithan, G. K., & Mann, L. B. (2025). Module 0: Getting started — Language matters. Lecture presented in SPED 760. Lawrence, KS: University of Kansas, Special Education Department. · See also: Research and Training Center on Independent Living. Guidelines: How to write and report about people with disabilities (8th ed.). University of Kansas. · For the identity-first counterpoint: Sinclair, J. Why I dislike “person first” language.

Debate samples

Three affirmative cases from three topics, published as they were actually used. If you have never opened a debate file before, they look strange — dense, heavily marked up, formatted by conventions that make no sense from outside. How to read debate files explains the anatomy in about three minutes.

Fisheries — Arctic topic, 2025–26

Resolved: The United States federal government should significantly increase its exploration and/or development of the Arctic.

An experiment in using AI to write an affirmative for debate. The AI helped me organize the thread, source evidence, and consider rebuttals. The affirmative argues the United States should increase exploratory fishing in the Arctic. There's a lot of content here, including documentation and teaching materials at the top. Debaters need to be prepared for any argument from any political, economic, critical, social, and even spiritual angle, so this file contains it all. Many other researchers at ADL contributed to the counterplan and kritik work for this file, including Jimin Park, Jet Semrick, Anthony Trufanov, Lily Ottinger, and Henry Mitchell.

Fisheries · .docx, 614 KB

AI governance — NATO topic, 2022–23

Resolved: The United States federal government should substantially increase its security cooperation with the North Atlantic Treaty Organization in one or more of the following areas: artificial intelligence, biotechnology, cybersecurity.

An affirmative exploring the boundaries of the human/AI partnership. The key thesis is that humans and AI must build a relationship of trust to be effective. This is written in a military context, since the topic was about NATO — but the underlying theme of trust was the lesson I really cared about teaching. You'll find pre-written scripts I wrote as drafts for the students to model and improve on during the debates. There's a lot of talk about “human extinction” in these files because it's part of the debate game, but I do think it can be hyperbolic at times.

Cognitive Warfare Early Alert System · .docx, 2.5 MB

Space-based solar power — CEDA/NDT college topic, 2019–20

Resolved: The United States federal government should establish a national space policy substantially increasing its international space cooperation with the People's Republic of China and/or the Russian Federation in one or more of the following areas: arms control of space weapons; exchange and management of space situational awareness information; joint human spaceflight for deep space exploration; planetary defense; space traffic management; space-based solar power.

My capstone project for my economics degree, and my last year of college debate. The affirmative argued the USA and China should cooperate to put solar panels in space and share the energy with the rest of the world. It included one version defending the market as a means of distributing the energy, and another defending a techno-utopian worldview. You can watch me defend this case on video.

Space-Based Solar Power · .docx, 2.3 MB