A Phenomenological Study on Experience of Using Generative AI by University Students

生成语法 能力(人力资源) 生成模型 心理学 读写能力 现象学(哲学) 范围(计算机科学) 课程 数学教育 人工智能 理解力 教育学 本体论 计算机科学 公立大学
作者
YangJin Noh,Dongseong Park
出处
期刊:Korean Association For Learner-Centered Curriculum And Instruction [Korean Association For Learner-Centered Curriculum And Instruction]
卷期号:24 (20): 175-194
标识
DOI:10.22251/jlcci.2024.24.20.175
摘要

Objectives This study aims to explore the direction of Generative AI literacy education through the exploration of college students' experiences using Generative AI. Methods For this purpose, written and face-to-face in-depth interviews were conducted with 12 university stu-dents (5 male students and 7 female students) and analyzed by applying Colaizzi's phenomenological method, which consists of seven steps to explore the nature of common experiences rather than the individual participants. Results As a result of analyzing the interview data, 5 semantic themes and 14 sub-themes were derived under the essence of the experience called ‘co-evolution’. The five semantic themes consist of ‘getting to know new media’, ‘useful but dangerous existence’, ‘sharing roles with Generative AI’, ‘adapting to changes in the learning environment’, and ‘seeking a life that coexists with Generative AI’. The 14 semantic themes consisted of ‘matching up with Generative AI’, ‘creating my own method of using prompts’, ‘limitation of inanimate object’, ‘repeating unnecessary learning activities’, ‘incomplete learning assistant’, ‘my own tutor’, ‘reducing learning time’, ‘setting my own scope of use’, ‘another team member’, ‘passive new media user’, ‘recognition of reality and acceptance of new media’, ‘improving the competence to use Generative AI’, ‘selecting Generative AI according to the purpose of use’, and ‘competition with the human-specific domain’. Conclusions The discussion points on the direction of Generative AI literacy education for university students are as follows. First, it provides education in which prompts can be effectively input. Second, it provides guidelines so that the Generative AI can be used as an auxiliary tool rather than the main tool for learning. Third, it provides education on the characteristics of the Generative AI. Fourth, it enhances education on usage ethics.

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
JinHao的应助被科研通管家采纳,获得10
刚刚
刚刚
搜集达人的应助被科研通管家采纳,获得10
刚刚
华仔的应助被科研通管家采纳,获得10
1秒前
1秒前
SciGPT的应助被科研通管家采纳,获得10
1秒前
1秒前
1秒前
科目三的应助被科研通管家采纳,获得10
1秒前
Lucas的应助被科研通管家采纳,获得10
1秒前
完美世界的应助被科研通管家采纳,获得10
1秒前
哈哈哈发布了新的文献求助10
1秒前
cdercder的应助被科研通管家采纳,获得200
1秒前
2秒前
丘比特的应助被科研通管家采纳,获得10
2秒前
wanci的应助被科研通管家采纳,获得10
2秒前
JinHao的应助被科研通管家采纳,获得10
2秒前
赘婿的应助被科研通管家采纳,获得10
2秒前
完美世界的应助被科研通管家采纳,获得30
2秒前
2秒前
2秒前
小九九完成签到,获得积分10
3秒前
4秒前
追寻地坛发布了新的文献求助10
5秒前
XY完成签到 ,获得积分10
5秒前
微风发布了新的文献求助10
5秒前
三七四十三完成签到,获得积分10
5秒前
牛太虚完成签到,获得积分10
6秒前
6秒前
万能图书馆的应助被初景采纳,获得10
6秒前
7秒前
帽帽完成签到 ,获得积分10
8秒前
牧青发布了新的文献求助10
9秒前
刘同学发布了新的文献求助10
10秒前
10秒前
10秒前
11秒前
13秒前
鱼鱼鱼发布了新的文献求助30
14秒前
15秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
A Will for the Machine: Computerization, Automation, and the Arts in South Africa 400
Decentring Leadership 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7808433
求助须知:如何正确求助?哪些是违规求助? 9340928
关于积分的说明 20504324
捐赠科研通 7400692
什么是DOI,文献DOI怎么找? 3328820
关于科研通互助平台的介绍 2475533
邀请新用户注册赠送积分活动 2347140