Welcome!

Language is central to educational interactions; analyzing it can serve as a way to discover, measure, and facilitate the use of high-leverage teaching practices. Automating linguistic analysis via natural language processing (NLP) can enable tools that support educators. Such tools can provide educators with feedback on their classroom instruction, help them craft lesson plans, facilitate formative assessment, scale their support for students, among many other applications. This course offers the opportunity to understand the possibilities and the limitations of using NLP to support instruction. The course will cover topics including principles of computational social science research, ethics, bias and fairness in using NLP for education, translating expert measurement into automated scoring, large language models for education, among others. The course is centered on engaging with relevant papers and working towards a final project. The final project will allow you to dive deeper into a research question in this area, approach it from a critical social scientific lens and learn and apply NLP methods to address the question. You will be working with a teacher buddy throughout the course to develop your final project.

CS293 classes will be a mix of lectures followed by discussion sessions led by students during our class meetings.

Schedule

Note: tentative schedule is subject to change.
๐Ÿ”Ž Means that the paper will be a core part of the lecture.
๐ŸŒŸ Means that the paper will be the focus of the reading discussion.

Week Date Lecture Reading Assignment
1 Jan 6
Tuesday
Class Introduction
[slides]
Required Readings: Optional Readings: A0 out
Form teams, find a teacher buddy!

Sign up for a reading discussion by Friday, Jan 9.
1 Jan 8
Thursday
Discovery & Exploration in Educational Language Data
[slides]
Required Reading: Optional Reading: A1 out
2 Jan 13
Tuesday
Discovery & Exploration in Educational Language Data
Parsing, Lexical Analyses
[slides]
Required Reading: Optional Reading: -
2 Jan 15
Thursday
Centering Teachers in the Design & Development of Tools

Guest Visit by Dan Meyer
ASU GSV-keynote: The Difference Between Great AI and Great Teaching
Required Reading: Optional Reading:
-
3 Jan 20
Tuesday
Discovery & Exploration in Educational Language Data
Topic Modeling, Clustering, Grounded Exploration
[slides]
Required Reading: Optional Reading: A0 due Monday at 5pm
3 Jan 22
Thursday
Designing NLP Tools for Empowering Teachers in the Real World

Q&A with Rakiya Brown from TeachFX
Required Reading: Optional Reading: A2 out
4 Jan 27
Tuesday
Guest visit by Brian Veprek and Theofilos Strinopoulos, Google LearnLM team Required Reading: Optional Reading: A1 due Monday at 5pm
4 Jan 29
Thursday
Using NLP/Multimodal data for Educational Measurement
Data Annotation

Guest lecture by Mei Tan
Required Reading: Optional Reading: -
5 Feb 3
Tuesday
Using NLP/Multimodal data for Educational Measurement
[slides]
Required Reading (discussants can pick any):
Optional readings:
-
5 Feb 5
Thursday
Using Generative AI to Support Teachers
AI Feedback

Guest visit by Jennifer Meyer, University of Vienna
Required Reading: Optional Reading: A3 out
6 Feb 10
Tuesday
Using Generative AI to Support Tutors

Guest talk by Rene Kizilcec, Cornell
Required Readings: Optional Readings: --
6 Feb 12
Thursday
In-Class Project Work Session No readings -
7 Feb 17
Tuesday
Modeling Approaches & Synthetic Students (aka Simulation) Required Reading (discussants can choose any): Optional Reading: A2 due Monday at 5pm
7 Feb 19
Thursday
Practitioner-Centered Design of Teacher Support Tools [slides] Required Reading: Optional Reading: -
8 Feb 24
Tuesday
In Class Project Work Session - --
8 Feb 26
Thursday
Generative Language Models for Pre-service Teacher Training
Student Simulations

Guest talk by Julie Cohen, University of Virginia
Required Reading: Optional Readings: -
9 Mar 3
Tuesday
Deploying NLP Tools to Empower Teachers
Lesson Planning

Guest visit by Riz Malik, Coteach.ai
Required Reading: A3 due Monday at 5pm
9 Mar 5
Thursday
Frontiers and Open Questions TBA -
10 Mar 10
Tuesday
Final Presentations No reading -
10 Mar 12
Thursday
Final Presentations No reading Final paper due Monday, Mar 16 at 5pm

Overview

Course Info

Office Hours

Prerequisites

Academic Accommodations

Well-Being, Stress Management, & Mental Health