Recent developments in Generative Artificial Intelligence (GenAI) have created significant uncertainty in education, particularly in terms of assessment practices. Against this backdrop, we present an updated version of the AI Assessment Scale (AIAS), a framework with two fundamental purposes: to facilitate open dialogue between educators and students about appropriate GenAI use and to support educators in redesigning assessments in an era of expanding AI capabilities. Grounded in social constructivist principles and designed with assessment validity in mind, the AIAS provides a structured yet flexible approach that can be adapted across different educational contexts. Building on implementation feedback from global adoption across both the K-12 and higher education contexts, this revision represents a significant change from the original AIAS. Among these changes is a new visual guide that moves beyond the original traffic light system and utilises a neutral colour palette that avoids implied hierarchies between the levels. The scale maintains five distinct levels of GenAI integration in assessment, from "No AI" to "AI Exploration", but has been refined to better reflect rapidly advancing technological capabilities and emerging pedagogical needs. This paper presents the theoretical foundations of the revised framework, provides detailed implementation guidance through practical vignettes, and discusses its limitations and future directions. As GenAI capabilities continue to expand, particularly in multimodal content generation, the AIAS offers a starting point for reimagining assessment design in an era of disruptive technologies.

翻译：生成式人工智能（GenAI）的最新发展给教育领域带来了显著的不确定性，尤其在评估实践方面。在此背景下，我们提出了人工智能评估量表（AIAS）的更新版本，该框架具有两个基本目的：促进教育者与学生之间就如何合理使用GenAI展开公开对话，以及支持教育者在人工智能能力不断扩展的时代重新设计评估方案。AIAS以社会建构主义原则为基础，以评估效度为设计考量，提供了一种结构化且灵活的方法，可适应不同的教育情境。基于从K-12到高等教育全球范围内采纳该量表所获得的实施反馈，本次修订相较于原始AIAS作出了重大调整。其中一项变化是引入了新的视觉指南，它超越了原有的红绿灯系统，采用中性色调，避免了各层级间隐含的等级关系。该量表保留了评估中GenAI整合的五个不同级别（从“无AI”到“AI探索”），但进行了细化以更好地反映快速发展的技术能力和新兴的教学需求。本文阐述了修订后框架的理论基础，通过实际案例提供了详细的实施指导，并讨论了其局限性与未来方向。随着GenAI能力（特别是在多模态内容生成方面）的持续扩展，AIAS为在颠覆性技术时代重新构想评估设计提供了一个起点。