Developing an online educational curriculum to enhance parent-supervised driving

开发在线教育课程以加强家长监督驾驶

• 批准号: 8392844
• 负责人: Noelle LaVoie
• 金额: $ 11.69万
• 依托单位: PARALLEL CONSULTING, LLC
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-05 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8392844
• 关键词: Accounting; Address; Adult; Agreement; Algorithms; Automobile Driving; Behavioral; Cause of Death; Centers for Disease Control and Prevention (U.S.); Cessation of life; Collection; Decision Making; Development; Education; Educational Curriculum; Educational process of instructing; Effectiveness; Evaluation; Feedback; Focus Groups; Human; Injury; Interview; Knowledge; Laws; Lead; Learning; Licensing; Machine Learning; Mechanics; Mentors; Methods; Motor Vehicles; Online Systems; Parents; Performance; Phase; Preparation; Recommendation; Research; Risk; Role; Safety; Sampling; Semantics; Site; Source; Staging; Structure; Surveys; System; Teaching Method; Techniques; Technology; Teenagers; Time; Training; Vehicle crash; Work; aged; base; cost; design; evidence base; experience; improved; innovation; instrument; prospective; prototype; public health priorities; research and development; research study; response; success; teen driving; tool; trafficking; usability; web page

DESCRIPTION (provided by applicant): Motor vehicle crashes are the leading cause of death and injury for teens, accounting annually for over 3000 deaths, 100 times as many injuries, and over 14 billion dollars in associated costs. The CDC has identified traffic crashes and associated injuries as a top public health priority. Inexperience is the leading cause of crashes among novice teen drivers, but accumulating the necessary experiences to become a safe driver can take many years. Fortunately, evidence from driving and other domains suggests that it is possible to increase experiential knowledge through scenario-based training. Current methods for providing teens with practice focus on parent-supervised driving. However, parents are ill-prepared to handle this role, with many focusing only on the mechanics of driving, laws and general safety advice. Few parents discuss decision-making aspects of driving and may even pass on inaccurate information. Many parents limit the range of driving situations teens are exposed to mistakenly believing that this increases safety rather than dangerously limiting teens' ability to accumulate important driving experience. Our long-term objective is to design and validate an innovative tool that aims to accelerate the acquisition of critical safety knowledge for teen drivers. We propose to extend our team's past work by developing scenarios appropriate for parents to use to mentor their inexperienced teen drivers. The scenarios will be part of an online educational curriculum designed to help parents provide teens with guided practice as they learn how to drive. The online tool will combine scenario- based training with innovative applications of machine learning technology to evaluate scenario responses and provide tailored feedback containing practical, developmentally appropriate strategies for improving safety as well as recommendations for parent-supervised on-the-road practice. Phase I will address these specific aims: 1) Conduct foundational research to identify realistic scenarios commonly encountered by novice teen drivers through semi-structured interviews with teen drivers aged 15-18. 2) Collect representative responses to scenarios from teens with different levels of driving experience and adults to identify the progression of knowledge and identify developmentally appropriate strategies to use as feedback. 3) Create machine learning algorithms to provide tailored feedback and recommend on-the-road driving experiences based on responses to the scenarios. 4) Develop prototype online system. Phase II will focus on additional specific aims: 5) Develop the Phase I proof of concept into a complete online curriculum with refined algorithms. 6) Evaluate the online curriculum for usability, acceptance via focus groups, and effectiveness via a driving simulator experiment and limited field trial with novice teen drivers. The proposed product represents a significant shift in trainig approaches for teen drivers and through Phase III dissemination it will fill a critical need for evidence- based parent-taught driver's education. PUBLIC HEALTH RELEVANCE: Motor vehicle crashes are the leading cause of death and injury for teens, accounting annually for over 3000 deaths, 100 times as many injuries, and over 14 billion dollars in associated costs; despite this, many teens' primary source of driver's education is their parents. In Phase I we propose to extend our past work for teaching experiential knowledge and develop a prototype online educational curriculum that allows parents to provide teens with guided practice by utilizing innovative machine learning technologies, while Phase II will allow us to complete the prototype and evaluate its effectiveness. The proposed application represents a significant shift in training approaches that has the potential, through Phase III dissemination, to improve teen driving safety.

描述（由申请人提供）：机动车碰撞是青少年死亡和受伤的主要原因，每年造成3000多人死亡，100倍受伤，相关费用超过140亿美元。疾病预防控制中心已将交通事故和相关伤害确定为公共卫生的首要任务。缺乏经验是青少年新手司机撞车的主要原因，但积累必要的经验，成为一个安全的司机可能需要很多年。幸运的是，来自驾驶和其他领域的证据表明，通过基于驾驶的培训来增加经验知识是可能的。目前为青少年提供练习的方法集中在父母监督驾驶上。然而，家长们并没有做好充分的准备来处理这个角色，许多人只关注驾驶的机械，法律和一般的安全建议。很少有父母讨论驾驶的决策方面，甚至可能传递不准确的信息。许多父母限制了青少年接触到的驾驶情况的范围，错误地认为这增加了安全性，而不是危险地限制了青少年积累重要驾驶经验的能力。我们的长期目标是设计和验证一种创新工具，旨在加速青少年驾驶员获得关键安全知识。我们建议扩展我们的团队过去的工作，开发适合父母使用的场景来指导他们缺乏经验的青少年司机。这些场景将成为在线教育课程的一部分，旨在帮助家长在青少年学习如何驾驶时为他们提供指导练习。该在线工具将结合联合收割机基于场景的培训与机器学习技术的创新应用，以评估场景响应，并提供量身定制的反馈，其中包含实用的、适合发展的提高安全性的策略，以及家长监督的道路实践建议。第一阶段将针对这些具体目标：1）进行基础研究，通过与15-18岁的青少年司机进行半结构化访谈，确定新手青少年司机通常遇到的现实情况。2)收集具有不同驾驶经验水平的青少年和成年人对场景的代表性反应，以确定知识的进展，并确定适合发展的策略作为反馈。3)创建机器学习算法以提供量身定制的反馈，并根据对场景的响应推荐道路驾驶体验。4)开发原型在线系统。第二阶段将专注于其他具体目标：5）将第一阶段的概念验证开发成一个完整的在线课程，并提供完善的算法。6)评估在线课程的可用性，通过焦点小组接受，并通过驾驶模拟器实验和青少年新手驾驶员的有限现场试验的有效性。拟议的产品代表了一个显着的转变，在培训方法为青少年司机，并通过第三阶段的传播，它将填补一个关键的需要，以证据为基础的家长教司机的教育。 公共卫生关系：机动车碰撞是青少年死亡和受伤的主要原因，每年造成超过3000人死亡，100倍的伤害，以及超过140亿美元的相关费用;尽管如此，许多青少年的驾驶员教育的主要来源是他们的父母。在第一阶段，我们建议扩展我们过去的经验知识教学工作，并开发一个原型在线教育课程，允许家长利用创新的机器学习技术为青少年提供指导实践，而第二阶段将允许我们完成原型并评估其有效性。拟议的应用程序代表了培训方法的重大转变，通过第三阶段的传播，有可能提高青少年驾驶安全。