Analyzing and Supporting Students' Learning Behaviors in Computational STEM Learning Environments
分析和支持学生在计算 STEM 学习环境中的学习行为
基本信息
- 批准号:2017000
- 负责人:
- 金额:$ 74.92万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-10-01 至 2024-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Computational thinking (CT) is the foundation of modern competency in a multitude of STEM-related fields. Learning strategies influence the way a student processes information and learns, which in turn, requires the proper control and regulation of their cognitive processes. More specifically, an effective learning strategy requires students to have adequate descriptive, procedural, and conditional knowledge of the strategies they apply. This project will study the learning processes of middle school students when they are involved in learning science using a computational modeling approach. The research that will be performed will help us to better understand how to effectively integrate CT and computing into the K-12 science curricula. To examine how learning evolves, and the difficulties students face in developing and applying synergistic processes, a task-oriented framework will be developed to analyze student learning behaviors as they work on modeling and problem-solving tasks. This project will use adaptive scaffolding to synergistically teach scientific concepts with computational modeling to middle school students. Student learning behaviors will be analyzed using self-regulated learning theory. This project aims to make the following research contributions: (1) develop a framework for analyzing student learning behaviors and strategies as they are involved in their model building, model debugging, and problem solving tasks; (2) use a combination of students activity logs and eye tracking data to understand student cognitive and metacognitive processes as they work in the C2STEM environment; and (3) study the effectiveness of the adaptive scaffolding and feedback generation framework by analyzing how this helps students overcome their difficulties, and progress in their learning and problem solving tasks. An intelligent peer agent in an artificial intelligence system will be developed to achieve these goals.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
计算思维(CT)是众多STEM相关领域现代能力的基础。学习策略影响着学生处理信息和学习的方式,这反过来又要求对他们的认知过程进行适当的控制和调节。更具体地说,有效的学习策略要求学生对他们所应用的策略有足够的描述性、程序性和条件性知识。该项目将使用计算建模方法研究中学生参与科学学习时的学习过程。将进行的研究将帮助我们更好地了解如何有效地将CT和计算融入K-12科学课程。为了研究学习如何演变,以及学生在开发和应用协同过程中面临的困难,将开发一个以任务为导向的框架来分析学生在建模和解决问题任务时的学习行为。这个项目将使用自适应脚手架协同教中学生科学概念与计算建模。学生的学习行为将使用自我调节学习理论进行分析。本研究的主要目的是:(1)建立一个分析学生在模型建立、模型调试和问题解决过程中的学习行为和策略的框架;(2)结合学生的活动日志和眼动数据,了解学生在C2 STEM环境中的认知和元认知过程;及(3)研究自适应支架及反馈生成框架的有效性,分析它如何帮助学生克服困难,并在学习和解决问题的任务中取得进展。该奖项反映了NSF的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(14)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Using Collaborative Interactivity Metrics to analyze students’ Problem-Solving Behaviors during STEM+C Computational Modeling Tasks
使用协作交互指标分析学生在 STEM C 计算建模任务期间解决问题的行为
- DOI:
- 发表时间:2023
- 期刊:
- 影响因子:3.6
- 作者:Snyder Caitlin;Hutchins, Nicole;Cohn, Clayton;Fonteles, Joyce;Biswas, Gautam
- 通讯作者:Biswas, Gautam
Coherence across conceptual and computational representations of students’ scientific models
学生科学模型的概念和计算表示的一致性
- DOI:
- 发表时间:2021
- 期刊:
- 影响因子:0
- 作者:Hutchins, N.M.;Basu, S.;McElhaney, K.;Chiu, J.;Fick, S.;Zhang, N.;Biswas, G.
- 通讯作者:Biswas, G.
A Chain-of-Thought Prompting Approach with LLMs for Evaluating Students’ Formative Assessment Responses in Science
法学硕士评估学生的思想链提示方法——科学中的形成性评估反应
- DOI:
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Cohn, Clayton;Hutchins, Nicole;Biswas, Gautam
- 通讯作者:Biswas, Gautam
Instructor facilitation of STEM+CT discourse: engaging, prompting and guiding students’ computational modeling in physics
教师促进 STEM CT 讨论:吸引、提示和指导学生 — 物理计算建模
- DOI:
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Snyder, C.
- 通讯作者:Snyder, C.
Measuring and Analyzing Students’ Strategic Learning Behaviors in Open-Ended Learning Environments
测量和分析学生在开放式学习环境中的战略学习行为
- DOI:10.1007/s40593-021-00275-x
- 发表时间:2021
- 期刊:
- 影响因子:4.9
- 作者:Zhang, Ningyu;Biswas, Gautam;Hutchins, Nicole
- 通讯作者:Hutchins, Nicole
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Gautam Biswas其他文献
Surface instability of a thin electrolyte film undergoing coupled electroosmotic and electrophoretic flows in a microfluidic channel
微流体通道中经历电渗和电泳耦合流动的电解质薄膜的表面不稳定性
- DOI:
10.1002/elps.201100306 - 发表时间:
2011 - 期刊:
- 影响因子:2.9
- 作者:
Bahni Ray;P. D. S. Reddy;D. Bandyopadhyay;S. Joo;Ashutosh Sharma;Shizhi Qian;Gautam Biswas - 通讯作者:
Gautam Biswas
Cointegration Analysis and Forecasting of the Export Function of Bangladesh Using the Error Correction Model
利用误差修正模型对孟加拉国出口函数进行协整分析与预测
- DOI:
10.21203/rs.3.rs-70018/v1 - 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
K. Islam;Gautam Biswas - 通讯作者:
Gautam Biswas
Simulation-Based Game Learning Environments: Building and Sustaining a Fish Tank
基于模拟的游戏学习环境:建造和维护鱼缸
- DOI:
10.1109/digitel.2007.44 - 发表时间:
2007 - 期刊:
- 影响因子:0
- 作者:
Jason Tan;Gautam Biswas - 通讯作者:
Gautam Biswas
Investigating Self-Regulated Learning in Teachable Agent Environments
研究可教代理环境中的自我调节学习
- DOI:
- 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
J. Kinnebrew;Gautam Biswas;Brian Sulcer;Roger Taylor - 通讯作者:
Roger Taylor
Do Foreign Grants and Capital Formation Indeed Impact Economic Growth? An Empirical Evidence from Bangladesh
外国赠款和资本形成确实会影响经济增长吗?
- DOI:
10.24018/ejdevelop.2023.3.3.280 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
K. Islam;Gautam Biswas - 通讯作者:
Gautam Biswas
Gautam Biswas的其他文献
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{{ truncateString('Gautam Biswas', 18)}}的其他基金
EAGER: Co-Designing a Cognitive Teaching Assistant to Support Evidence-Based Instruction in Open-Ended Learning Environments
EAGER:共同设计认知助教,支持开放式学习环境中的循证教学
- 批准号:
2327708 - 财政年份:2023
- 资助金额:
$ 74.92万 - 项目类别:
Standard Grant
Collaborative Research: Computational Modeling for Integrating Science and Engineering Design: Model Construction, Manipulation, and Exploration
协作研究:科学与工程设计相结合的计算建模:模型构建、操作和探索
- 批准号:
2055597 - 财政年份:2021
- 资助金额:
$ 74.92万 - 项目类别:
Continuing Grant
Collaborative Research: An Interdisciplinary Approach to Prepare Undergraduates for Data Science Using Real-World Data from High Frequency Monitoring Systems
协作研究:利用高频监测系统的真实数据为本科生准备数据科学的跨学科方法
- 批准号:
1915487 - 财政年份:2019
- 资助金额:
$ 74.92万 - 项目类别:
Continuing Grant
I-Corps: Predicting and Preventing Mold Growth and Unforeseen HVAC Equipment Failures with an Intelligent Monitoring and Alerting System
I-Corps:通过智能监控和警报系统预测和预防霉菌生长和不可预见的 HVAC 设备故障
- 批准号:
1951810 - 财政年份:2019
- 资助金额:
$ 74.92万 - 项目类别:
Standard Grant
FW-HTF: Collaborative Research: Augmenting and Advancing Cognitive Performance of Control Room Operators for Power Grid Resiliency
FW-HTF:合作研究:增强和提高控制室操作员的认知表现以提高电网弹性
- 批准号:
1840052 - 财政年份:2018
- 资助金额:
$ 74.92万 - 项目类别:
Standard Grant
Convergence HTF: Collaborative: Workshop on Convergence Research about Multimodal Human Learning Data during Human Machine Interactions
融合 HTF:协作:人机交互过程中多模态人类学习数据的融合研究研讨会
- 批准号:
1744333 - 财政年份:2017
- 资助金额:
$ 74.92万 - 项目类别:
Standard Grant
Research and Assessment on Synergistic Learning of Physics and Programming through Computational Modeling and Problem Solving
通过计算建模和问题解决来研究和评估物理和编程的协同学习
- 批准号:
1640199 - 财政年份:2016
- 资助金额:
$ 74.92万 - 项目类别:
Standard Grant
Collaborative Research: Using Data Mining and Observation to derive an enhanced theory of SRL in Science learning environments
协作研究:利用数据挖掘和观察得出科学学习环境中 SRL 的增强理论
- 批准号:
1561676 - 财政年份:2016
- 资助金额:
$ 74.92万 - 项目类别:
Standard Grant
BIGDATA: EAGER: Infrastructure and Analytics for Data Intensive Research in Open-Ended Learning Environments
BIGDATA:EAGER:开放式学习环境中数据密集型研究的基础设施和分析
- 批准号:
1548499 - 财政年份:2015
- 资助金额:
$ 74.92万 - 项目类别:
Standard Grant
DIP: Extending CTSiM: An Adaptive Computational Thinking Environment for Learning Science through Modeling and Simulation in Middle School Classrooms
DIP:扩展 CTSiM:通过中学课堂建模和仿真学习科学的自适应计算思维环境
- 批准号:
1441542 - 财政年份:2014
- 资助金额:
$ 74.92万 - 项目类别:
Standard Grant
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