This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…

Automated assessment using Natural Language Processing (NLP) has the potential to make English speaking assessments more reliable, authentic, and accessible. Yet without careful examination, NLP may exacerbate social prejudices based on gender or native language (L1). Current NLP-based assessments are prone to such biases, yet research and…

The digital transformation in educational assessment has led to the proliferation of large-scale data, offering unprecedented opportunities to enhance language learning, and testing through machine learning (ML) techniques. Drawing on the extensive data generated by online English language assessments, this dissertation investigates the efficacy…