flowchart LR
A["Socio-Cultural<br>Communication<br>Theory"] --> D["A Smarter,<br>More Human<br>Pedalogical"]
B["Oral<br>Assessment"] --> D
C["Prompt Engineering<br>Training"] --> D
AI Pedagogy @ SCRP Summer 2026
Extending Pedalogical with Voice, Communication Theory, and AI Literacy
February 6, 2026
Who I Am and What I Do
At Willamette University
Dr. Lucas Cordova
- CS Professor at SCIS
- Teach courses in CS and Data Science like software development, data structures, algorithms, data engineering, and more
- Lab focuses on human-centered learning tools and AI-powered learning
Working on Pedalogical?
An AI platform built for learning, not just answers
Pedalogical is an AI-infused platform developed by students in the Cordova Lab at Willamette University. It helps instructors quickly build high-quality assessments and learning experiences without needing to become experts in educational technology or AI tooling.
What it already does
Supports multiple assessment types for any discipline, including textual and chat-based assessments designed to strengthen understanding and explanation
Grounded in psychological learning theories:
- Feynman Technique: learn by explaining in your own words
- Zone of Proximal Development: meet learners where they are
- Cognitive Load Theory: keep feedback focused and manageable
Feynman Technique Chatbot Example
Pedalogical in Action
This Summer: Three Big Extensions
Summer 2026 roadmap
We are extending Pedalogical in three major directions this summer, each designed to make the platform more responsive, more human, and more useful across disciplines.
Direction 1: Communication Theory
Learning is communication, not just correctness
We are expanding our theoretical foundation to include socio-cultural communication theory, which treats learning and explanation as situated communication that depends on:
- Audience and context
- Social norms and expectations
- Purpose and intent
The goal is to make Pedalogical’s feedback more sensitive to how learners express knowledge in real settings, not just whether they have the correct information.
Direction 2: Oral Assessment
Say it out loud
We are integrating oral assessment into Pedalogical. Students will be able to practice explaining and expressing their understanding out loud and receive feedback that supports growth in:
- Conceptual understanding
- Communication skills
- Confidence
Beyond the classroom
The pedagogical intent supports oral exams, discussion-based learning, and reflective explanation, but it also connects directly to real-world scenarios:
- Interview preparation
- Presentation rehearsal
- Professional communication practice
Direction 3: Prompt Engineering Training
Teaching students to use AI well
We are building a prompt engineering training module to help learners use generative AI effectively as a learning tool. The focus is on moving beyond one-shot prompting toward iterative workflows:
- Planning and decomposition
- Adding constraints and context
- Verification and revision
The goal is to equip learners with durable AI literacy skills that transfer across disciplines and tasks.
Why This Matters
The big picture
flowchart TD
A["Students learn<br>to explain"] --> B["Students learn<br>to communicate"]
B --> C["Students learn<br>to use AI<br>effectively"]
C --> D["Students become<br>better thinkers"]
D --> A
Pedalogical is not just a learning tool. It is a platform for building the skills that matter most: articulation, reflection, communication, and critical use of AI. This summer’s work makes it more responsive to real human learning.
Thank You!
Dr. Lucas Cordova
Ford Hall, Room 210