CAREER: Building an Online Learning for Mastery System That Creates a Student-centered STEM Learning Environment
CAREER: Building an Online Learning for Mastery System That Creates a Student-centered STEM Learning Environment
批准号:
1845436
负责人:
Zhongzhou Chen
金额:
$75.64万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2019
资助国家:
美国
项目状态:
未结题
起止时间:
2019-04-15 至 2025-03-31
中文摘要
该项目解决了当今美国STEM高等教育面临的三大挑战:教育日益多样化和非传统的学生群体,培养至少100万名额外的STEM毕业生,以及降低高等教育成本。该项目的目标是创建一个以学生为中心的在线学习系统,该系统有可能允许每个学生选择和参与最适合自己背景和学习需求的学习资源。 通过这种方式,在线学习系统可以大规模提供个性化的学习体验。 此外,通过使教师能够协同设计,创建,共享和改进教学资源,该项目旨在开发个性化的在线学习系统,而不增加(并可能减少)学生的高等教育成本。这种在线学习系统可能对第一代大学生、来自农村社区的学生和来自大学代表性不足的群体的学生、成人学习者以及其他可能不太准备在大学取得成功并在追求高等教育时面临重大经济或其他困难的人最有利。该项目的核心是创建一个在线学习掌握(OLM)系统,该系统将通过将最新的在线学习技术与“掌握学习”设计的概念相结合来设计。掌握学习将一个主题分解为一系列学习模块,每个模块都包含形成性评估,指导和实践。 这种方法使学生能够按照自己的节奏浏览材料。 OLM系统将由多个学习模块组成,每个模块将教学资源与形成性评估相结合,让已经掌握内容的学生快速前进,同时为有困难的学生提供充足的支持和机会,让他们按照自己的节奏赶上。OLM系统有可能产生大量关于每个学生学习过程的数据。这些数据比从传统的在线学习平台收集的数据具有更好的可解释性。该项目旨在开发分析算法,从数据中提取有关学生学习行为和学习困难的丰富信息。 反过来,这些数据将指导教师和研究人员开发新的教学材料和平台功能,以帮助学生成为更好的自我调节和主动学习者。这一过程类似于土木工程师根据从GPS系统收集的交通数据分析设计公路系统和安全功能。OLM系统的数据收集能力为教师和学生提供了这样一个“学习GPS”。该项目的结果有可能为我们理解学生在自定进度的在线STEM学习环境中的学习行为提供重要的新知识,并为有效的教学设计提供信息,以促进学生的学习过程。该项目拟开设两门在线课程。第一门课程将是在线大学物理入门课程,作为佛罗里达中部大学多门混合格式课程的在线组成部分。这门课程可能会在多个机构之间共享,包括奥兰多地区的六所当地州立大学。第二门课程将是为教师设计的发展课程,向他们介绍最新的在线学习技术和与OLM和掌握学习相关的研究成果,同时试图建立一个教师社区,以创建,改进,共享和重用OLM模块。 该项目不仅可以提高对有效在线教育的认识,还可以通过降低教育成本、增加可及性、支持获得STEM学位的多种途径,扩大STEM领域的参与。该奖项反映了NSF的法定使命,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。
英文摘要
The project addresses three major challenges facing STEM higher education in the United States today: educating an increasingly diverse and non-traditional student population, producing at least 1 million additional STEM graduates, and reducing the cost of higher education. The goal of the project is to create a student-centered online learning system that has the the potential to allow every student to select and engage with learning resources that best suit their own backgrounds and learning needs. In this way, the online learning system could provide a personalized learning experience at a large scale. In addition, by enabling instructors to collaboratively design, create, share, and improve instructional resources, the project aims to develop the personalized online learning system without increasing (and possibly reducing) the cost of higher education for students. This online learning system may be most beneficial to first-generation college students, students from rural communities and from groups that are underrepresented in college, adult learners, and others who may be less prepared to succeed in college and who face significant financial or other difficulties in pursuit of higher education. At the core of the project is creation of an Online Learning for Mastery (OLM) system, which will be designed by combining the latest online learning technology with the concept of "mastery learning" design. Mastery Learning breaks down a topic into a sequence of learning modules that each contain formative assessment, instruction, and practice. This approach enables students to move through the material at their own pace. The OLM system will consist of multiple sequences of learning modules, with each module combining instructional resources with formative assessment, allowing students who have already mastered the content to quickly move ahead, while providing struggling students ample support and opportunities to catch up at their own pace. The OLM system has the potential to produce a large amount of data on each student's learning process. These data have better interpretability than what is collected from conventional online learning platforms. The project aims to develop analysis algorithms to extract rich information about student learning behavior and learning difficulties from the data. The data, in turn, will guide instructors and researchers in developing new instructional materials and platform features to help students become better self-regulated and motivated learners. The process is akin to civil engineers designing highway systems and safety features based on analysis of traffic data collected from GPS systems. The data collection capability of the OLM system serves as such a "learning GPS" for both instructors and students. Results from the project have the potential to contribute significant new knowledge to our understanding of student learning behavior in a self-paced online STEM learning environment, and to inform effective instructional designs to facilitate a student's learning process. The project proposes to create two online courses. The first course will be an online introductory college physics course serving as the online component of multiple blended format courses at the University of Central Florida. This course could potentially be shared between multiple institutions including six local state colleges in the Orlando area. The second course will be a development course designed for instructors, introducing them to the latest online learning technologies and research findings related to OLM and mastery learning, while attempting to build a community of instructors for creating, improving, sharing, and reusing OLM modules. This project has the potential not only to increase knowledge about effective online education but also to broaden participation in STEM fields by reducing education cost, increasing accessibility, and supporting multiple pathways to a STEM degree.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.
期刊论文(14)
专著(0)
科研奖励(0)
会议论文
登录
查看更多内容
DOI:
10.1145/3636555.3636897
发表时间:
2024
期刊:
LAK '24: Proceedings of the 14th Learning Analytics and Knowledge Conference
影响因子:
--
作者:
[Wang, Karen D., Chen, Zhongzhou, Wieman, Carl]
通讯作者:
Wieman, Carl
Comparing student behavior in mastery and conventional style online physics homework
比较学生在掌握和传统在线物理作业中的行为
DOI:
10.1119/perc.2019.pr.guthrie
发表时间:
2020
期刊:
Physics Education Research Conference 2019
影响因子:
--
作者:
[Guthrie, Matthew W., Chen, Zhongzhou]
通讯作者:
Chen, Zhongzhou
A Multi-Level Trace Clustering Analysis Scheme for Measuring Students’ Self-Regulated Learning Behavior in a Mastery-Based Online Learning Environment
用于测量学生在基于掌握的在线学习环境中自我调节学习行为的多级跟踪聚类分析方案
DOI:
10.1145/3506860.3506887
发表时间:
2022
期刊:
LAK22: 12th International Learning Analytics and Knowledge Conference
影响因子:
--
作者:
[Zhang, Tom, Taub, Michelle, Chen, Zhongzhou]
通讯作者:
Chen, Zhongzhou
Measuring the level of homework answer copying during COVID-19 induced remote instruction
测量 COVID-19 引发的远程教学期间作业答案抄写的水平
DOI:
10.1103/physrevphyseducres.18.010126
发表时间:
2022
期刊:
Physical Review Physics Education Research
影响因子:
3.1
作者:
[Chen, Zhongzhou]
通讯作者:
Chen, Zhongzhou
Improving accuracy in measuring the impact of online instruction on students’ ability to transfer physics problem-solving skills
提高衡量在线教学对学生物理问题解决技能迁移能力影响的准确性
DOI:
10.1103/physrevphyseducres.17.010112
发表时间:
2021
期刊:
Physical Review Physics Education Research
影响因子:
3.1
作者:
[Whitcomb, Kyle M., Guthrie, Matthew W., Singh, Chandralekha, Chen, Zhongzhou]
通讯作者:
Chen, Zhongzhou
共 10 条
国内基金
海外基金
基于支链淀粉building blocks构建优质BE突变酶定向修饰淀粉调控机制的研究
-
批准号:31771933
-
项目类别:面上项目
-
资助金额:60.0万元
-
批准年份:2017
-
负责人:郭丽
-
依托单位: