ENGAGE: A Game-based Curricular Strategy for Infusing Computational Thinking into Middle School Science

ENGAGE:将计算思维融入中学科学的基于游戏的课程策略

基本信息

  • 批准号:
    1640141
  • 负责人:
  • 金额:
    $ 249.89万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-08-15 至 2020-10-31
  • 项目状态:
    已结题

项目摘要

The STEM+Computing Partnership (STEM+C) program seeks to advance multidisciplinary integration of computing in STEM teaching and learning through applied research and development across one or more domains. Building on a previously developed and tested prototype for computer science education in a middle school oceanography elective, the ENGAGE project's objective is to design and study a more comprehensive curricular strategy for middle school life science using a game-based learning environment that will deeply integrate computational thinking practices within the life science curriculum. Topics will include the study of interdependent relationships of species in ecosystems, matter and energy in organisms and ecosystems, and natural selection of species and their adaptations for survival. Along with a focus on student learning, the project will develop and study a teacher professional development model to support teachers in the integration of computational thinking in middle school life science. Principal Investigators will gather specific evidence about the ways in which game-based learning can effectively support computationally rich science practices aligned with the new Science Education Framework (National Research Council, 2012) and the Computer Science Teachers' Association, Computer Science Education Computational Thinking Framework (2016). Specifically, the effort will: (1) design an innovative curricular strategy and novel game-based learning environment to develop computationally rich science practices (developing and using models, and analyzing and interpreting data), for middle school students from North Carolina and Florida; (2) investigate how middle school students develop computational thinking practices (creating abstractions and models, analyzing problems and artifacts, and developing computational artifacts) in middle school science classrooms with the game-based learning environment; and (3) develop an evidence-based teacher professional development program that supports teachers in the deep integration of computational thinking into middle grades science. The overarching research question will be: How can deep, mastery-oriented gameplay develop core computational thinking practices in middle school life science? Related sub-questions will include: (a) How can game-based learning promote the development of students' science and engineering practices?; (b) How can game-based learning promote student mastery of computational thinking deeply infused science education?; and (c) How can game-based learning for computationally rich science improve students' attitudes in science with regard to short-term self-efficacy, outcome expectancy, and long-term STEM career interest? The project will undertake three types of activities carried out in parallel across each year of the project. First, it will develop and iteratively refine the curricular strategy and collaborative game-based learning environment, which will be implemented at partner middle schools in North Carolina and Florida, with increasing numbers of teachers and students participating in each succeeding year. Second, the study will develop, implement, and refine the corresponding professional development materials and associated online and face-to-face activities. The teacher professional development will be implemented throughout the school year, utilizing both a summer institute and ongoing school-based support. Third, classroom studies will be conducted to build the evidence base on how middle school students can most effectively develop computationally rich science practices. For the classroom studies, the project will compare three conditions: (1) the baseline condition (standard science classroom practice with no project implementation) will utilize teachers who have not previously participated in the project; (2) the project-without-game condition, where students will participate in an implementation of the curricular strategy that provides out-of-game computational problem solving on data-rich science problems outside of the game, but does not provide the game-based learning experiences; and (3) implementation of a full version of the ENGAGE curricular strategy that provides both game-based learning experiences, as well as outside-of-game computational problem solving. Data-gathering strategies throughout the three-year duration of the study will include: classroom observations, individual teacher interviews, student and teacher focus groups, project-developed assessments, embedded game-based learning assessments, student-created artifact assessments, pre- and posttest assessments, and assessments of science and STEM attitudes. Data interpretation strategies will include: comparative analysis of scores across years and across the three experimental conditions, observational and formative analyses to guide refinement of learning tasks, qualitative and quantitative analyses of student performance and growth, and formative analysis of changes in self-reported attitudes. The main outcome of the project will be a research-informed and field-tested prototype integrating computational thinking into science learning at the middle school level. An external organization will conduct the formative and summative evaluations.
STEM+Computing Partnership(STEM+C)计划旨在通过跨一个或多个领域的应用研究和开发,推动STEM教学和学习中的多学科计算整合。基于先前开发和测试的原型,在中学海洋学选修计算机科学教育,参与项目的目标是设计和研究一个更全面的课程策略,中学生命科学使用基于游戏的学习环境,将深入整合计算思维的做法在生命科学课程。主题将包括研究生态系统中物种的相互依存关系,生物体和生态系统中的物质和能量,以及物种的自然选择及其生存适应。沿着以学生学习为中心,本项目将开发和研究教师专业发展模式,以支持教师在中学生命科学中整合计算思维。主要研究人员将收集有关基于游戏的学习如何有效支持计算丰富的科学实践的具体证据,这些科学实践与新的科学教育框架(国家研究理事会,2012年)和计算机科学教师协会,计算机科学教育计算思维框架(2016年)保持一致。具体而言,这一努力将:(1)设计创新的课程策略和新颖的游戏学习环境,以发展计算丰富的科学实践(开发和使用模型,分析和解释数据),面向来自北卡罗来纳州和佛罗里达的中学生;(2)调查中学生如何发展计算思维实践(创建抽象和模型,分析问题和工件,并开发计算工件)在中学科学教室与游戏为基础的学习环境;以及(3)开发一个以证据为基础的教师专业发展计划,支持教师将计算思维深度融入中年级科学。首要的研究问题将是:如何才能深入,掌握为导向的游戏开发核心计算思维的做法,在中学生命科学?相关的子问题包括:(a)游戏学习如何促进学生科学和工程实践的发展?(b)游戏化学习如何促进学生掌握计算思维?以及(c)基于游戏的计算丰富的科学学习如何改善学生在短期自我效能,结果预期和长期STEM职业兴趣方面的科学态度?该项目将在项目的每一年同时开展三类活动。首先,它将开发和迭代完善课程战略和基于游戏的协作学习环境,这将在北卡罗来纳州和佛罗里达的合作伙伴中学实施,每年都有越来越多的教师和学生参与。其次,该研究将开发、实施和完善相应的专业发展材料以及相关的在线和面对面活动。教师专业发展将在整个学年实施,利用暑期研究所和持续的校本支持。第三,将进行课堂研究,以建立证据基础,中学生如何才能最有效地发展计算丰富的科学实践。对于课堂研究,本项目将比较三个条件:(1)基线条件(标准的科学课堂实践,没有项目实施)将利用以前没有参加过项目的教师;(2)无博弈项目条件,在那里,学生将参与课程策略的实施,该策略提供了基于数据的游戏外计算问题解决,丰富的科学问题以外的游戏,但不提供基于游戏的学习经验;和(3)实施一个完整版本的参与课程战略,既提供基于游戏的学习经验,以及游戏外的计算问题解决。在整个三年的研究期间,数据收集策略将包括:课堂观察,个别教师访谈,学生和教师焦点小组,项目开发的评估,嵌入式基于游戏的学习评估,学生创建的工件评估,测试前和测试后评估,以及科学和STEM态度的评估。数据解释策略将包括:跨年度和跨三个实验条件的分数比较分析,观察和形成性分析,以指导学习任务的完善,学生的表现和成长的定性和定量分析,以及自我报告的态度变化的形成性分析。该项目的主要成果将是一个研究知情和现场测试的原型整合计算思维到科学学习在中学一级。一个外部组织将进行形成性和总结性评价。

项目成果

期刊论文数量(22)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
CEO: A Triangulated Evaluation of a Modeling-Based CT-Infused CS Activity for Non-CS Middle Grade Students
CEO:针对非计算机科学中年级学生基于建模、注入 CT 的计算机科学活动的三角评估
Improving Stealth Assessment in Game-Based Learning with LSTM-Based Analytics
利用基于 LSTM 的分析改进基于游戏的学习中的隐形评估
Promoting Computer Science Learning with Block-Based Programming and Narrative-Centered Gameplay
通过基于块的编程和以叙事为中心的游戏来促进计算机科学学习
Development of a Lean Computational Thinking Abilities Assessment for Middle Grades Students
中年级学生精益计算思维能力评估的开发
DeepStealth: Game-Based Learning Stealth Assessment With Deep Neural Networks
  • DOI:
    10.1109/tlt.2019.2922356
  • 发表时间:
    2020-04
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Wookhee Min;M. Frankosky;Bradford W. Mott;Jonathan P. Rowe;A. Smith;E. Wiebe;K. Boyer;James C. Lester
  • 通讯作者:
    Wookhee Min;M. Frankosky;Bradford W. Mott;Jonathan P. Rowe;A. Smith;E. Wiebe;K. Boyer;James C. Lester
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James Lester其他文献

The Tactical Uses of Passion: An Essay on Power, Reason, and Reality. By Bailey F.G.. (Ithaca, N.Y.: Cornell University Press, 1983. Pp. 275. $29.50, cloth; $9.95, paper.)
激情的战术运用:关于权力、理性和现实的文章。
  • DOI:
  • 发表时间:
    1983
  • 期刊:
  • 影响因子:
    0
  • 作者:
    O. Kirchkamp;Rosemarie Nagel;R. Sarin;A. Montuori;J. Rowe;Bradford W. Mott;James Lester;J. Scott Armstrong;Michael J. Spector;G. Burns;F. Cindio;C. Peraboni;Stefano A. Cerri;Michele Bernasconi;M. M. Galizzi;Julien Courtin;C. Gonzalez;Cyril Herry;Joseph Psotka;Sung;Emily S. Cross;Richard Ramsey;Allison C. Waters;D. Tucker;D. Erik Everhart;J. Jozefowiez;R. Chandler;Klaus P. Ebmeier;Mary E. Stewart;Nathalie Bier;Stéphane Adam;T. Meulemans;Raymond Angelo Belliotti;C. Poon;S. Schmid;K. Illeris;Charles Kalish;M. Laakso;Teemu Rajala;E. Kaila;T. Salakoski;E. Brannon
  • 通讯作者:
    E. Brannon
AI and the Future of Learning: Expert Panel Report
人工智能与学习的未来:专家小组报告
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    J. Roschelle;James Lester;J. Fusco
  • 通讯作者:
    J. Fusco
A multi-level growth modeling approach to measuring learner attention with metacognitive pedagogical agents
使用元认知教学代理衡量学习者注意力的多层次增长建模方法
  • DOI:
    10.1007/s11409-023-09336-z
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    3.3
  • 作者:
    Megan D. Wiedbusch;James Lester;R. Azevedo
  • 通讯作者:
    R. Azevedo
Affective Dynamics and Cognition During Game-Based Learning
基于游戏的学习过程中的情感动态和认知
  • DOI:
    10.1109/taffc.2022.3210755
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    11.2
  • 作者:
    Elizabeth B. Cloude;Daryn A. Dever;Debbie L. Hahs;Andrew Emerson;R. Azevedo;James Lester
  • 通讯作者:
    James Lester
Qualitative aspects of breathlessness in health and disease
健康和疾病中呼吸困难的定性方面
  • DOI:
  • 发表时间:
    2009
  • 期刊:
  • 影响因子:
    10
  • 作者:
    Jaclyn A. Smith;Paul Albert;Enrica Bertella;James Lester;Sandy Jack;Peter M.A. Calverley
  • 通讯作者:
    Peter M.A. Calverley

James Lester的其他文献

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{{ truncateString('James Lester', 18)}}的其他基金

ExplainIt: Improving Student Learning with Explanation-based Classroom Response Systems
ExplainIt:通过基于解释的课堂响应系统改善学生的学习
  • 批准号:
    2111473
  • 财政年份:
    2021
  • 资助金额:
    $ 249.89万
  • 项目类别:
    Standard Grant
AI Institute for Engaged Learning
人工智能参与学习研究所
  • 批准号:
    2112635
  • 财政年份:
    2021
  • 资助金额:
    $ 249.89万
  • 项目类别:
    Cooperative Agreement
Collaborative Research: PrimaryAI: Integrating Artificial Intelligence into Upper Elementary Science with Immersive Problem-Based Learning
合作研究:PrimaryAI:通过基于问题的沉浸式学习将人工智能融入高年级基础科学
  • 批准号:
    1934153
  • 财政年份:
    2019
  • 资助金额:
    $ 249.89万
  • 项目类别:
    Standard Grant
EAGER: Collaborative Research: Building Capacity for K-12 Artificial Intelligence Education Research
EAGER:协作研究:K-12 人工智能教育研究能力建设
  • 批准号:
    1938778
  • 财政年份:
    2019
  • 资助金额:
    $ 249.89万
  • 项目类别:
    Standard Grant
Supporting Student Planning with Open Learner Models in Middle Grades Science
通过中年级科学的开放学习者模型支持学生规划
  • 批准号:
    1761178
  • 财政年份:
    2018
  • 资助金额:
    $ 249.89万
  • 项目类别:
    Standard Grant
Collaborative Research: FW-HTF: Augmented Cognition for Teaching: Transforming Teacher Work with Intelligent Cognitive Assistants
合作研究:FW-HTF:增强教学认知:利用智能认知助手改变教师工作
  • 批准号:
    1840120
  • 财政年份:
    2018
  • 资助金额:
    $ 249.89万
  • 项目类别:
    Standard Grant
Multimodal Visitor Analytics: Investigating Naturalistic Engagement with Interactive Tabletop Science Exhibits
多模式访客分析:研究交互式桌面科学展览的自然参与
  • 批准号:
    1713545
  • 财政年份:
    2018
  • 资助金额:
    $ 249.89万
  • 项目类别:
    Continuing Grant
Improving Science Problem Solving with Adaptive Game-Based Reflection Tools
使用基于游戏的自适应反思工具提高科学问题的解决能力
  • 批准号:
    1661202
  • 财政年份:
    2017
  • 资助金额:
    $ 249.89万
  • 项目类别:
    Continuing Grant
Collaborative Research: Big Data from Small Groups: Learning Analytics and Adaptive Support in Game-based Collaborative Learning
协作研究:来自小组的大数据:基于游戏的协作学习中的学习分析和自适应支持
  • 批准号:
    1561655
  • 财政年份:
    2016
  • 资助金额:
    $ 249.89万
  • 项目类别:
    Continuing Grant
Collaborative Research: PRIME: Engaging STEM Undergraduate Students in Computer Science with Intelligent Tutoring Systems
合作研究:PRIME:利用智能辅导系统让 STEM 本科生学习计算机科学
  • 批准号:
    1626235
  • 财政年份:
    2016
  • 资助金额:
    $ 249.89万
  • 项目类别:
    Standard Grant

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