Reliability Issues in Current Approaches to Identify and Mitigate AI Bias

Research Overview

This research explores translanguaging in AI-assisted classrooms.

Objectives

  • Understand how students switch languages while learning.
  • Build AI tools that adapt to language diversity.
  • Enable equitable education through tech.

Image Example

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Dataset Sample

{
  "student_id": "abc123",
  "language": "Spanglish",
  "utterance": "Yo pienso que the Earth orbits el sol."
}

Inline code like const x = 5 is also supported.

Results Table

Metric Value
Accuracy 93.5%
Precision 91.2%
Recall 92.7%

External Resources

Future Work

  1. Expand model support for additional languages.
  2. Partner with more bilingual schools.
  3. Publish findings in academic venues.

Generated on: June 19, 2025

Publications

2017

Analyzing Learner Affect in a Scenario-Based Intelligent Tutoring System

Benjamin Nye, Shamya Karumbaiah, S Tugba Tokel, Mark G Core, Giota Stratou, Daniel Auerbach, Kallirroi Georgila

Proceedings of the 18th International Conference on Artificial Intelligence in Education (AIED)

View Paper

2016

Phishing training: A Preliminary Look at the Effects of Different Types of Training

Shamya Karumbaiah, Ryan T Wright, Alexandra Durcikova, Matthew L Jensen

Proceedings of the 11th Pre-ICIS Workshop on Information Security and Privacy (WISP)

View Paper

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