activity
20242026
most citedImplementation Considerations for Automated AI Grading of Student Work

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CY2026

Creating and Evaluating K-12 GenAI Assessment Graders Through Context Engineering

Zewei Tian, Alex Liu, Lief Esbenshade +6

The integration of large language models (LLMs) into educational assessment represents a transformative shift in classroom grading practices. While automated scoring systems and ma…

cs.CY2026

Generative AI in K-12 Classrooms: A Midyear Implementation Report

Lief Esbenshade, Alex Liu, Michael Xiao +6

This mid-year report summarizes teacher use of Colleague AI across 12 Washington State school districts from September 1 to December 31, 2025. Produced jointly by Colleague AI and…

cs.HC2025

AI as a Teaching Partner: Early Lessons from Classroom Codesign with Secondary Teachers

Alex Liu, Lief Esbenshade, Shawon Sarkar +6

This report presents a comprehensive account of the Colleague AI Classroom pilot, a collaborative design (co-design) study that brought generative AI technology directly into real…

cs.HC2025

Emerging Patterns of GenAI Use in K-12 Science and Mathematics Education

Lief Esbenshade, Shawon Sarkar, Drew Nucci +10

In this report, we share findings from a nationally representative survey of US public school math and science teachers, examining current generative AI (GenAI) use, perceptions, c…

cs.HC2025★ 1 cited

Implementation Considerations for Automated AI Grading of Student Work

Zewei Tian, Alex Liu, Lief Esbenshade +4

This study explores the classroom implementation of an AI-powered grading platform in K-12 settings through a co-design pilot with 19 teachers. We combine platform usage logs, surv…

cs.CY2025

Connecting Feedback to Choice: Understanding Educator Preferences in GenAI vs. Human-Created Lesson Plans in K-12 Education -- A Comparative Analysis

Shawon Sarkar, Min Sun, Alex Liu +4

As generative AI (GenAI) models are increasingly explored for educational applications, understanding educator preferences for AI-generated lesson plans is critical for their effec…

cs.AI2024★ 1 cited

Enhancing Instructional Quality: Leveraging Computer-Assisted Textual Analysis to Generate In-Depth Insights from Educational Artifacts

Zewei Tian, Min Sun, Alex Liu +2

This paper explores the transformative potential of computer-assisted textual analysis in enhancing instructional quality through in-depth insights from educational artifacts. We i…