• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar

information for practice

news, new scholarship & more from around the world


advanced search
  • gary.holden@nyu.edu
  • @ Info4Practice
  • Archive
  • About
  • Help
  • Browse Key Journals
  • RSS Feeds

Transforming Assessment: The Impacts and Implications of Large Language Models and Generative AI

Abstract

The remarkable strides in artificial intelligence (AI), exemplified by ChatGPT, have unveiled a wealth of opportunities and challenges in assessment. Applying cutting-edge large language models (LLMs) and generative AI to assessment holds great promise in boosting efficiency, mitigating bias, and facilitating customized evaluations. Conversely, these innovations raise significant concerns regarding validity, reliability, transparency, fairness, equity, and test security, necessitating careful thinking when applying them in assessments. In this article, we discuss the impacts and implications of LLMs and generative AI on critical dimensions of assessment with example use cases and call for a community effort to equip assessment professionals with the needed AI literacy to harness the potential effectively.

Read the full article ›

Posted in: Journal Article Abstracts on 05/10/2024 | Link to this post on IFP |
Share

Primary Sidebar

Categories

Category RSS Feeds

  • Calls & Consultations
  • Clinical Trials
  • Funding
  • Grey Literature
  • Guidelines Plus
  • History
  • Infographics
  • Journal Article Abstracts
  • Meta-analyses - Systematic Reviews
  • Monographs & Edited Collections
  • News
  • Open Access Journal Articles
  • Podcasts
  • Video

© 1993-2025 Dr. Gary Holden. All rights reserved.

gary.holden@nyu.edu
@Info4Practice