History

TIMELINE AND VIRTUAL MUSEUM:

BRIEF INTRODUCTION:

In November 370 BC, Plato's classmates laughed as he wrote down Socrates' warnings about how writing would ruin education.
In November 2022, my students laughed when I warned them about AI, as they prompted its hallucination, it unnaturally putting a full white beard on an Indigenous grandmother, a character they had rightly pictured differently in the novel they were studying.

The technology changed. The responsive human learning didn't.

This timeline documents three years of student innovations with artificial intelligence across high school, undergraduate, and graduate classrooms. What emerges isn't a story of machines replacing human thinking, but of students discovering what technologies can and can't do—and what good human learning with AI looks like.

• Disciplinary supporting question
  
  Could it be that students learning with AI since November 2022 have merely created a monster for stupidity?
  
  Or are some enhancing their own much smarter intelligence repertoire?
  
  

• Interactive timeline showing student innovations from November 2022 to present.

KEY THEMES ACROSS THE TIMELINE:

• • Phase 1: Playful Experimentation (November 2022 - Spring 2023) Students initially used AI to complete assignments, then discovered its failures were more interesting than its successes. Laughter became the marker of learning—when students laughed at AI's mistakes, they were discovering their collaborative interpretive superiority.

  • Phase 2: Critical Appropriation (Fall 2023 - Spring 2024) Students began using AI as a "sparring partner" rather than a shortcut. They fed AI drafts into their analysis, tore up AI scripts to improvise authentic performances, and used AI tools to challenge famous literary critics.

  • Phase 3: Transformative Innovation (Fall 2024 - Fall 2025) Students moved beyond using AI to creating with it: building ethical guidelines, designing their own assessment rubrics and lesson plans and lessons, and developing AI tools for multilingual language bridges.

HISTORICAL PARALLELS:

This three-year evolution mirrors earlier educational technology adoptions:

• • Calculators (1970s): Initial fear of "students won't learn math" → Recognition that calculators freed students for higher-order problem solving

  • Word Processors (1980s): Initial fear of "students won't learn to write" → Recognition that revision became easier, writing improved

  • Search Engines (1990s): Initial fear of "students won't memorize anything" → Recognition that research skills became more sophisticated

  • AI Tools (2020s): Initial fear of "students will just let machines think" → Recognition that AI becomes raw material for collaborative interpretation

  • The pattern holds: Tools initially feared as replacements become catalysts for deeper human learning.
    
    

• Data sources used to address questions (e.g., bibliography, references, etc.)
  
  Student artifacts: Scripts, rubrics, AI-generated images, NotebookLM analyses, ElevenLabs voiceovers, D-ID animations (cited with permission)
  
  Personal observations: High school (R.L. Paschal High School), Undergraduate (Tarrant County College, College of Education at Texas Christian University [TCU]), Graduate (AddRan College of Liberal Arts at TCU),
  
  Professional Development Workshops:
  
  "E = MCP²: Experience Modern Classrooms Project², Amplified by AI, to Engage ALL Learners." Fort Worth Technology Conference, 19 Oct. 2024, Fort Worth, TX. Conference presentation.
  
  "Bard, Claude, ChatGPT, Students, and Me: In the Language Arts Classroom." e-Merge Digital Minds: Investigating What is Missing to Make Transformative Learning Happen, 20 Oct. 2023, Fort Worth, TX. Conference presentation.
  
  Publications:
  
  Coffey, Donavyn. "Indigenous Youth Are Using Coding and AI to Save Native Language." Teen Vogue, 24 Jan. 2024, www.teenvogue.com/story/these-coding-camps-are-teaching-indigenous-youth-to-save-native-language-through-ai.

Worcester, S.A. (2025). Good Human Learning with AI: Students Changing Education Since November 370 BC or 2022 AD. [Primary source - classroom observations and student work]

• Key concepts and skills necessary to address question
  
  

Historical Analysis:

• Chronological pattern recognition

• Comparative technology adoption studies

• Primary source analysis (teacher observations, student work)

• Historical continuity (Socrates with writing to 21st century students with AI)

Critical Thinking:

• Distinguishing between initial fears and actual outcomes both negative and positive

• Recognizing recurring patterns across different technologies

• Understanding how student agency shapes technology use

Research Skills:

• Working with primary sources (direct classroom observation)

• Synthesizing multiple data types (artifacts, reflections, published work)

• Documenting change over time

• Content description (e.g., evidence-backed claims)

CLAIM 1: Student innovations with AI followed predictable patterns of educational technology adoption: initial resistance → playful experimentation → critical appropriation → transformative use.

Evidence:

• November 2022: Students laughed at AI failures (bearded grandmother, missed humor in Anne Lamott).

• 2023: Students tore up AI scripts; they used multiple AIs to challenge literary critics.

• 2024: Students still found paper and electronic dictionaries useful, continued using Google Translate, but more and more employed AI for the art and science of translating a literary text from one human language to another.

• 2025: Students designed assessment rubrics, leaned into what Ethan Mollick calls the "jagged frontier," what one of the students renamed "janky creations."

CLAIM 2: Laughter and human enjoyment serve as the epistemological markers of learning—when students laughed at AI's mistakes, they were discovering their collective interpretive superiority—when students meta-cognitively re-cognize with smiles what they "love" about class and, more importantly, about their classmates (appreciating the fact that AI has no clue about when good human learning happens).

Evidence:

• "The whole class erupted in laughter" when AI put a beard on Minerva (Indigenous elder).

• Students "cracked up" when every AI missed every human-subtle joke in Anne Lamott's "Shitty First Drafts."

• Pattern 1: Laughter preceded insight in every documented innovation.

• Pattern 2: Involuntary smiles mark.

CLAIM 3: The three-year timeline mirrors earlier technology fears that proved unfounded—calculators, word processors, and search engines were all initially seen as threats that became tools for deeper learning.

Evidence:

• Calculators didn't end math education; they freed students for problem-solving. In 1994 the SAT began allowing calculators on some math sections; in 2023 the all digital SAT has built-in calculators on all the math sections.

• Word processors, grammar checkers, and spell checkers didn't end writing; they improved revision and editing practices. Electronic books, dictionaries, and encyclopedias have not eliminated paper book versions; they have enhanced ways of close reading and democratized knowledge making.

• Search engines didn't end research; they sophisticated information literacy.

• AI isn't ending thinking as of November 2022; it's becoming a means for collaborative interpretation and the necessity of critical, respectful, ethical thinking.
  
  

• Technology/media used to visually/conceptually represent student learning with AI
  
  AI Tools That Students Who Were In the Classroom With Me Have Used to Create With Since November 2022:

  • Chat for Schools, Skill Struck, skillstruck.com

  • ChatGPT. OpenAI, chat.openai.com.

  • Claude. Anthropic, claude.ai.

  • Curipod. Curipod AS, curipod.com

  • Gemini (formerly Bard). Google, ai.google.

  • DALL-E. OpenAI, openai.com/dall-e.

  • ElevenLabs. elevenlabs.io.

  • Free AI Literacy, Skill Struck, skillstruck.com

  • D-ID Studios. d-id.com. 

  • Magic School, magicschoolai

  • Palette, palette.fm.

  • GPT5. OpenAI, chat.chatbot.app

  • Notebook LM Google, notebooklm.google.com

  • Running Wolf, Michael. First Languages AI Reality (FLAIR), Mila–Quebec AI Institute, 2025. mila.quebec/en/ai4humanity/applied-projects/first-languages-ai-reality.