Integrating Natural Language Processing in Middle School Science Classrooms: An Experience Report

被引:5
作者
Katuka, Gloria Ashiya [1 ]
Chakraburty, Srijita [2 ]
Lee, Hyejeong [2 ]
Dhama, Sunny [1 ]
Earle-Randell, Toni [1 ]
Celepkolu, Mehmet [1 ]
Boyer, Kristy Elizabeth [1 ]
Glazewski, Krista [3 ]
Hmelo-Silver, Cindy [2 ]
McKlin, Tom [4 ]
机构
[1] Univ Florida, Gainesville, FL 32611 USA
[2] Indiana Univ, Bloomington, IN USA
[3] North Carolina State Univ, Raleigh, NC USA
[4] Findings Grp, Atlanta, GA USA
来源
PROCEEDINGS OF THE 55TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, SIGCSE 2024, VOL. 1 | 2024年
基金
美国国家科学基金会;
关键词
Natural language processing; NLP and AI learning; NLP plus Science; middle school science classrooms;
D O I
10.1145/3626252.3630881
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
With the increasing prevalence of large language models (LLMs) such as ChatGPT, there is a growing need to integrate natural language processing (NLP) into K-12 education to better prepare young learners for the future AI landscape. NLP, a sub-field of AI that serves as the foundation of LLMs and many advanced AI applications, holds the potential to enrich learning in core subjects in K-12 classrooms. In this experience report, we present our efforts to integrate NLP into science classrooms with 98 middle school students across two US states, aiming to increase students' experience and engagement with NLP models through textual data analyses and visualizations. We designed learning activities, developed an NLP-based interactive visualization platform, and facilitated classroom learning in close collaboration with middle school science teachers. This experience report aims to contribute to the growing body of work on integrating NLP into K-12 education by providing insights and practical guidelines for practitioners, researchers, and curriculum designers.
引用
收藏
页码:639 / 645
页数:7
相关论文
共 41 条
[1]  
2023, Arxiv, DOI [arXiv:2303.08774, DOI 10.48550/ARXIV.2303.08774, 10.48550/arXiv.2303.08774]
[2]  
Alm Cecilia O., 2021, P AAAI C INTELLIGENC
[3]  
[Anonymous], 2017, Teachable Machine
[4]  
[Anonymous], 2017, BASICS Study ECS Student Implementation and Contextual Factor Questionnaire Measures Measurement scales
[5]  
[Anonymous], 2017, Machine Learning for Kids
[6]  
Ayanwale MA, 2022, Computers and Education: Artificial Intelligence, V3, DOI [DOI 10.1016/J.CAEAI.2022.100099, 10.1016/j.caeai.2022.100099/]
[7]  
Brown TB, 2020, ADV NEUR IN, V33
[8]   Exploring Middle School Students' Reflections on the Infusion of CS into Science Classrooms [J].
Celepkolu, Mehmet ;
Fussell, David Austin ;
Galdo, Aisha Chung ;
Boyer, Kristy Elizabeth ;
Wiebe, Eric N. ;
Mott, Bradford W. ;
Lester, James C. .
SIGCSE 2020: PROCEEDINGS OF THE 51ST ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, 2020, :671-677
[9]   Sentiment Analysis: From Opinion Mining to Human-Agent Interaction [J].
Clavel, Chloe ;
Callejas, Zoraida .
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, 2016, 7 (01) :74-93
[10]   NLP4Science: Designing a Platform for Integrating Natural Language Processing in Middle School Science Classrooms [J].
Dhama, S. ;
Katuka, G. ;
Celepkolu, M. ;
Boyer, K. E. ;
Glazewski, K. ;
Hmelo-Silver, C. .
2023 IEEE SYMPOSIUM ON VISUAL LANGUAGES AND HUMAN-CENTRIC COMPUTING, VL/HCC, 2023, :269-273