The rise of Artificial Intelligence (AI) and Generative Artificial
Intelligence (GenAI) in higher education necessitates assessment reform. This
study addresses a critical gap by exploring student and academic staff
experiences with AI and GenAI tools, focusing on their familiarity and comfort
with current and potential future applications in learning and assessment. An
online survey collected data from 35 academic staff and 282 students across two
universities in Vietnam and one in Singapore, examining GenAI familiarity,
perceptions of its use in assessment marking and feedback, knowledge checking
and participation, and experiences of GenAI text detection.
Descriptive statistics and reflexive thematic analysis revealed a generally
low familiarity with GenAI among both groups. GenAI feedback was viewed
negatively; however, it was viewed more positively when combined with
instructor feedback. Academic staff were more accepting of GenAI text detection
tools and grade adjustments based on detection results compared to students.
Qualitative analysis identified three themes: unclear understanding of text
detection tools, variability in experiences with GenAI detectors, and mixed
feelings about GenAI's future impact on educational assessment. These findings
have major implications regarding the development of policies and practices for
GenAI-enabled assessment and feedback in higher education.

应对人工智能和生成人工智能在高等教育中的崛起需要进行评估改革，本研究通过探讨学生和学术人员对人工智能和生成人工智能工具的熟悉程度和舒适度，着眼于当前和未来在学习和评估中的应用，填补了关键空白。在线调查收集到来自越南的两所大学和新加坡的一所大学的 35 名学术人员和 282 名学生的数据，调查了生成人工智能的熟悉程度、其在评估标记和反馈、知识检测和参与中的应用以及生成人工智能文本检测的经验。描述性统计和思考性主题分析揭示了两个群体对生成人工智能的熟悉程度普遍较低。生成人工智能反馈受到负面评价，然而当与教师反馈结合时，评价更为积极。学术人员对生成人工智能文本检测工具以及基于检测结果的成绩调整更加接受，相对于学生而言。定性分析确定了三个主题：对文本检测工具的理解不清晰，对生成人工智能检测器的经验存在差异，以及对生成人工智能对教育评估未来影响感受复杂。这些发现对高等教育中生成人工智能评估和反馈的政策和实践的发展具有重要意义。