Affiliation:
1. Educational Psychology Department University of Connecticut Storrs Connecticut USA
Abstract
AbstractCriteria identify and define the aspects on which what we evaluate is judged and play a central role in evaluation practice. While work on the use of AI in evaluation is burgeoning, at the time of writing, a set of criteria to consider in evaluating the use of AI in evaluation has not been proposed. As a first step in this direction, Teasdale's Criteria Domains Framework was used as the lens through which to critically read articles included in this special issue. This resulted in the identification of eight criteria domains for evaluating the use of AI in evaluation. Three of these criteria domains relate to the conceptualization and implementation of AI in evaluation practice. Five criteria domains are focused on outcomes, specifically those stemming from the use of AI in evaluation. More work is needed to further identify and deliberate possible criteria domains for AI use in evaluation.
Subject
Management Science and Operations Research,Strategy and Management,Education
Reference59 articles.
1. The evaluator's role in valuing: Who and with whom;Alkin M. C.;New Directions for Evaluation,2012
2. Attick R.(2016 December 11).Intelligent things: It's all about machine learning. Retrieved fromhttp://www.linkedin.com/pulse/intelligent‐things‐its‐all‐machine‐learning‐roger‐attick/
3. Artificial intelligence and validity;Azzam T.;New Directions for Evaluation,2023
4. A Systematic Approach for Evaluating Artificial Intelligence Models in Industrial Settings
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献