亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

"Don't Forget the Teachers": Towards an Educator-Centered Understanding of Harms from Large Language Models in Education

数学教育 教育学 社会学 心理学
作者
Emma Harvey,Allison Koenecke,René F. Kizilcec
出处
期刊:Cornell University - arXiv [Cornell University]
标识
DOI:10.48550/arxiv.2502.14592
摘要

Education technologies (edtech) are increasingly incorporating new features built on large language models (LLMs), with the goals of enriching the processes of teaching and learning and ultimately improving learning outcomes. However, the potential downstream impacts of LLM-based edtech remain understudied. Prior attempts to map the risks of LLMs have not been tailored to education specifically, even though it is a unique domain in many respects: from its population (students are often children, who can be especially impacted by technology) to its goals (providing the correct answer may be less important for learners than understanding how to arrive at an answer) to its implications for higher-order skills that generalize across contexts (e.g., critical thinking and collaboration). We conducted semi-structured interviews with six edtech providers representing leaders in the K-12 space, as well as a diverse group of 23 educators with varying levels of experience with LLM-based edtech. Through a thematic analysis, we explored how each group is anticipating, observing, and accounting for potential harms from LLMs in education. We find that, while edtech providers focus primarily on mitigating technical harms, i.e., those that can be measured based solely on LLM outputs themselves, educators are more concerned about harms that result from the broader impacts of LLMs, i.e., those that require observation of interactions between students, educators, school systems, and edtech to measure. Overall, we (1) develop an education-specific overview of potential harms from LLMs, (2) highlight gaps between conceptions of harm by edtech providers and those by educators, and (3) make recommendations to facilitate the centering of educators in the design and development of edtech tools.

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
搜集达人应助houyuhao123123采纳,获得10
3秒前
Arthur_x完成签到,获得积分10
3秒前
温不胜的破木吉他完成签到 ,获得积分10
5秒前
12秒前
16秒前
ding应助linjiadefeng采纳,获得10
18秒前
29秒前
30秒前
绘空事发布了新的文献求助10
35秒前
脑洞疼应助冰渊悬月采纳,获得10
40秒前
49秒前
甜甜诗筠完成签到,获得积分10
52秒前
婉莹完成签到 ,获得积分0
55秒前
甜甜诗筠发布了新的文献求助10
57秒前
朴素半烟完成签到 ,获得积分10
1分钟前
Sc完成签到,获得积分10
1分钟前
香蕉觅云应助甜甜诗筠采纳,获得10
1分钟前
思源应助科研通管家采纳,获得10
1分钟前
Kao应助科研通管家采纳,获得10
1分钟前
小蘑菇应助科研通管家采纳,获得10
1分钟前
1分钟前
1分钟前
绘空事发布了新的文献求助10
1分钟前
ZS完成签到,获得积分10
1分钟前
jxjsyf完成签到 ,获得积分10
2分钟前
2分钟前
小巧的傲晴完成签到,获得积分10
2分钟前
2分钟前
2分钟前
绘空事发布了新的文献求助10
2分钟前
大力的冬萱应助cyb采纳,获得20
2分钟前
如意盼夏完成签到 ,获得积分10
2分钟前
2分钟前
luo完成签到,获得积分10
2分钟前
2分钟前
大模型应助houyuhao123123采纳,获得10
2分钟前
3分钟前
3分钟前
3分钟前
3分钟前
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
Nondestructive Testing Handbook: Vol. 4, Thermal and Infrared Testing (IR), 4th ed 800
作者名:Kristopher P. Plain,悉尼大学的,目前只能查到其四篇论文,想找到其博士论文 590
Évora na Idade Média 555
Soil mites of the family Rhagidiidae (Actinedida: Eupodoidea). Morphology, Systematics, Ecology 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Radical Reactions 500
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 7370281
求助须知:如何正确求助?哪些是违规求助? 8977796
关于积分的说明 19087155
捐赠科研通 7012836
什么是DOI,文献DOI怎么找? 3224956
关于科研通互助平台的介绍 2388489
邀请新用户注册赠送积分活动 2205615