Birdbuddy in the classroom: leveraging AI-powered bird feeders for undergraduate biology education.

IF 1.5 Q2 EDUCATION, SCIENTIFIC DISCIPLINES
Journal of Microbiology & Biology Education Pub Date : 2026-04-30 Epub Date: 2026-03-04 DOI:10.1128/jmbe.00223-25
Manuela Tripepi, Jason Yang, Daud Tariq
{"title":"Birdbuddy in the classroom: leveraging AI-powered bird feeders for undergraduate biology education.","authors":"Manuela Tripepi, Jason Yang, Daud Tariq","doi":"10.1128/jmbe.00223-25","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) rapidly transforms biological research and STEM education by enabling automated data collection and analysis. In order to teach students about biodiversity monitoring, data validation, and the importance of human oversight in machine learning, we created an activity utilizing Birdbuddy, a commercially available AI-enabled bird feeder. Students set up feeders in their local surroundings, gather automatically produced photos and species identifications, and verify the data collected to assess the accuracy of AI outputs. The activities promote conversation on AI bias and inaccuracy while highlighting transferable skills like ecological analysis, spreadsheet management, and experimental design. Birdbuddy encourages use in undergraduate classes, K-12 partnerships, and community science projects due to its low cost, portability, and ease of maintenance. In addition to promoting inclusive, experiential learning and developing an appreciation for biodiversity and the scientific method, this technology offers a scalable, affordable way to connect ecological research with AI literacy.</p>","PeriodicalId":46416,"journal":{"name":"Journal of Microbiology & Biology Education","volume":" ","pages":"e0022325"},"PeriodicalIF":1.5000,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13130983/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Microbiology & Biology Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1128/jmbe.00223-25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/3/4 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 0

Abstract

Artificial intelligence (AI) rapidly transforms biological research and STEM education by enabling automated data collection and analysis. In order to teach students about biodiversity monitoring, data validation, and the importance of human oversight in machine learning, we created an activity utilizing Birdbuddy, a commercially available AI-enabled bird feeder. Students set up feeders in their local surroundings, gather automatically produced photos and species identifications, and verify the data collected to assess the accuracy of AI outputs. The activities promote conversation on AI bias and inaccuracy while highlighting transferable skills like ecological analysis, spreadsheet management, and experimental design. Birdbuddy encourages use in undergraduate classes, K-12 partnerships, and community science projects due to its low cost, portability, and ease of maintenance. In addition to promoting inclusive, experiential learning and developing an appreciation for biodiversity and the scientific method, this technology offers a scalable, affordable way to connect ecological research with AI literacy.

课堂上的鸟友:利用人工智能喂鸟器进行本科生物教育。
人工智能(AI)通过实现自动化数据收集和分析,迅速改变了生物学研究和STEM教育。为了让学生了解生物多样性监测、数据验证以及人类监督在机器学习中的重要性,我们利用Birdbuddy(一种商用的人工智能喂鸟器)创建了一个活动。学生们在当地环境中设置喂食器,收集自动生成的照片和物种识别,并验证收集到的数据,以评估人工智能输出的准确性。这些活动促进了对人工智能偏见和不准确性的讨论,同时强调了生态分析、电子表格管理和实验设计等可转移技能。Birdbuddy鼓励在本科课程、K-12伙伴关系和社区科学项目中使用,因为它的低成本、便携性和易于维护。除了促进包容性的体验式学习,培养对生物多样性和科学方法的欣赏,这项技术还提供了一种可扩展的、负担得起的方式,将生态研究与人工智能素养联系起来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of Microbiology & Biology Education
Journal of Microbiology & Biology Education EDUCATION, SCIENTIFIC DISCIPLINES-
CiteScore
3.00
自引率
26.30%
发文量
95
审稿时长
22 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书