AI or human? A study of university students’ awareness of library reference service agents

计算机科学 错误 步伐 质量(理念) 身份(音乐) 知识管理 人类智力 人工智能 情感(语言学) 要素(刑法) 图灵 主题(文档) 智能代理 专家系统 服务(商务) 人工智能应用 知识库 软件代理 万维网 人机交互 表达式(计算机科学) 图灵试验
作者
Di Wang,Jianting Guo,Kaiyang Zheng,Xizhou Deng
出处
期刊:The Electronic Library [Emerald Publishing Limited]
卷期号:: 1-19
标识
DOI:10.1108/el-06-2025-0230
摘要

Purpose This study aims to examine university students’ awareness of artificial intelligence (AI) acting as the agent in university libraries’ reference services. It also aims to identify and discover factors that influence students’ judgement. Design/methodology/approach A within-participant design experiment was designed for this study. Five tasks covering five disciplines were developed. Two versions (ChatGPT versus subject librarian) of feedback were generated for each task. Participants were asked to judge the identity of the agent (a simplified Turing test) for each task. Think-aloud protocols were used to further analyse the factors affecting students’ judgements. Findings This study indicates students’ limited ability to distinguish AI and human agents. They are more likely to mistake librarians for AI agents with complicated tasks. The perceived knowledge, ability and comprehensibility of the AI system and the provided information quality and expression approach, together with AI usage experience, significantly affect students’ awareness of AI. Students associate objective, thorough and expert knowledge with AI, while detailed, vivid and colloquial explanations to librarians. Originality/value This study provides valuable insights into students’ awareness of AI versus human agents in reference services by synthesizing a theoretical model to explain students’ AI awareness, specifying components for each element and their relationships. It also benefits the effective integration of AI technology in libraries, especially in reference services, by emphasizing the importance of keeping pace with the development of AI and improving students’ AI literacy.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
great7701完成签到,获得积分10
刚刚
云栖发布了新的文献求助10
刚刚
1秒前
1秒前
1秒前
cxt发布了新的文献求助10
1秒前
活力亦瑶发布了新的文献求助10
2秒前
3秒前
SWZ发布了新的文献求助30
4秒前
传奇3应助欣观采纳,获得10
5秒前
dcy发布了新的文献求助30
5秒前
cdercder应助心随以动采纳,获得10
5秒前
6秒前
6秒前
优秀的雨筠完成签到 ,获得积分10
6秒前
仙林AK47发布了新的文献求助20
7秒前
mastwu发布了新的文献求助10
7秒前
852应助踏实小蘑菇采纳,获得10
8秒前
噎鸣发布了新的文献求助10
8秒前
shy完成签到,获得积分10
8秒前
上官若男应助lvyinbing采纳,获得10
9秒前
Akim应助LU采纳,获得10
9秒前
10秒前
英姑应助WXG采纳,获得10
10秒前
Marxxu举报英勇的冰之求助涉嫌违规
10秒前
陈住气发布了新的文献求助10
11秒前
在水一方应助ber采纳,获得10
11秒前
土土发布了新的文献求助20
12秒前
12秒前
12秒前
12秒前
13秒前
平淡奇迹完成签到,获得积分10
13秒前
大模型应助cxt采纳,获得10
14秒前
李耐寒完成签到,获得积分10
14秒前
小馨要变有钱完成签到,获得积分10
14秒前
含蓄饼干完成签到,获得积分20
15秒前
搜集达人应助云栖采纳,获得10
15秒前
Sunny发布了新的文献求助10
15秒前
风趣的觅山完成签到,获得积分10
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Geist der Kunst und Kultur 1000
Resistance Spot Welding Dataset for Automobile Body-in-White Quality Analysis 748
日本現代怪異事典 副読本 700
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 650
Machine Learning for Asset Management and Pricing 600
Numerical analysis of the coupled atmosphere-ocean models (CAO II). II 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7395467
求助须知:如何正确求助?哪些是违规求助? 9001543
关于积分的说明 19158966
捐赠科研通 7031339
什么是DOI,文献DOI怎么找? 3229875
关于科研通互助平台的介绍 2392315
邀请新用户注册赠送积分活动 2211471