Humanities and Arts

An Evaluation of Khanmigo, a Generative AI Tool, as a Computer-Assisted Language Learning App


  Peer Reviewed

Abstract

The recent advancement in technology has attracted learners’ attention worldwide to Generative Artificial Intelligence (GenAI) for educational purposes. While GenAI has shown promising results for general language purposes (Godwin-Jones, 2023; Xiao & Zhi, 2023), the potential of GenAI for language learning has not been fully explored. This paper, therefore, endeavors to decipher the potential of a GenAI app, Khanmigo, as a language learning tool, specifically for learning French. The app was analyzed by the researcher through her interactions of about 17.5 hours using Chapelle’s (2001) Evaluation Framework for discerning the task appropriateness of a given Computer-Assisted Language Learning (CALL) tool. While the app does not show robust performance in all the six criteria suggested for evaluation, it still holds some promise.

Key Questions

What is Khanmigo?

Khanmigo is a Generative AI (GenAI) tool developed by Khan Academy, designed to assist learners across various subjects by providing interactive, AI-driven support.

How can Khanmigo be used for language learning?

While not specifically designed for language learning, Khanmigo offers activities that can aid in learning languages like French through interactive exercises and AI-generated feedback.

What is Chapelle’s Evaluation Framework?

Chapelle’s (2001) Evaluation Framework is a set of criteria used to assess the appropriateness of Computer-Assisted Language Learning (CALL) tools, focusing on aspects like language learning potential, learner fit, and authenticity.

How effective is Khanmigo for learning French?

According to the study, Khanmigo shows potential for aiding French language learners but does not perform robustly across all evaluation criteria, indicating room for improvement.

What are the limitations of using Khanmigo for language learning?

Limitations include a lack of tailored language learning features, potential issues with learner fit, and the need for more authentic language interaction capabilities.