课题基金 / 基金详情

Active Learning as a Basis for Reform of Undergraduate Life Science Education

Active Learning as a Basis for Reform of Undergraduate Life Science Education
主动学习作为本科生命科学教育改革的基础
批准号:
9909411
负责人:
Harold Modell
金额:
$45.84万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2000
资助国家:
美国
项目状态:
已结题
起止时间:
2000-02-01 至 2003-06-30

项目摘要

项目成果

Harold Modell的其他基金

相似基金

相关文献

中文摘要
翻译
科学教育的有意义的改革只有在我们成功地将教育研究中获得的知识转化为课堂上的实际应用时才是可能的。 在新兴理论的指导下,我们必须确定什么样的课堂教学方法最能帮助学生获得更有意义的学习。 正是通过这种应用研究,我们将达到一个了解科学的一般人群的目标。 在确定是否有更多的“有意义的学习”发生的第一步是衡量学生的知识和技能基础,因为他们进入我们的课程(输入状态),并定义,在明确的条款,可衡量的结果,反映了期望的学习(输出状态)。 本项目首先侧重于开发适当的工具,用于测量生理学中的概念变化和概念学习。 然后,该项目使用这些测量工具来检查主动学习技术(帮助学生建立和测试心理模型)在帮助学生纠正现有的误解和改善概念学习方面的有效性。 该项目包括三项研究。 研究1的目标是更好地了解进入生理学课程的本科生的实际知识和技能基础,并确定这些学生所持有的误解的患病率。 研究2探讨了在学生实验室环境中导致成功的概念转变(纠正现有误解)的教师-学生互动的类型。 研究3探讨了两种方法来帮助学生建立适当的心理模型的生理系统(即,概念学习)。其中一组实验旨在确定帮助学生建立和应用生理学中循环的一般模型(而不是根据情境特定模型来查看概念)是否会导致更好的概念学习。 第二组实验的重点是两个问题,使用问题解决作为促进概念学习的工具。 第一,问题解决练习是否提供了一个概念框架,以增强概念学习?第二,是使用问题的方式(即,在心理模型建立过程中提供一个语境框架,或作为一个需要应用心理发展的最终练习)是决定概念学习程度的一个重要因素? 该项目的成果与所有科学教育有关。 为了帮助学生获得对科学最广泛的理解,我们必须在实际的课堂环境中发现什么样的教学技术最能帮助他们建立和使用适当的心理模型。
英文摘要
Meaningful reform in science education is onlly possible if we sucessfully translate knowledge gained from educational research to practical applications in the classroom. Guided by emerging theory, we must determine what classroom approaches will best faculty to help students attain more meaningful learning. It is through this applied research that we will reach the goal of a general population that understands science. The first steps in detemining if more "meaningful learning" is occurring is to measure the knowledge and skills base of students as they enter our courses (the input state) and to define, in explicit terms, measurable outcomes that reflect the desired learning (the output state). This project focuses first on developing appropriate tools for measuring conceptual change and conceptual learning in physiology. The project then uses these measurement tools to examine the effectiveness of active learning techniques (helping students build and test mental models) in helping students remedy existing misconceptions and improve conceptual learning. The project consists of three studies. The goal of Study 1 is to gain a better understanding of the actual knowledge and skills base of undergraduate students entering physiology courses and to determine the prevalence of misconceptions held by these students. Study 2 examines the types of instructor-students interactions that lead to successful conceptual change (remedy of existing misconceptions) in the student laboratory environment. Study 3 examines two approaches to helpingstudents build appropriate mentals models of physiological systems (i.e., conceptual learning). One set of experiments is designed to determine if helping students build and apply general models of recurring in physiology (as opposed to viewing the concepts in terms of situationally specific models) leads to greater conceptual learning. A second set of experiments focuses on two questions related to the use of problem solving as a vehicle for promoting conceptual learning. First, do problem solving exercises provide a conceptual framework that enhances conceptual learning?Second, is the manner in which the problems are used (i.e., to provide a contexual framework during mental model building or as a culminating exercise requiring application of the mental developed) a significant factor in determining the degree of conceptual learning attained? The results of this project are relevant to all science education. To help students gain the broadest understanding of science, we must discover, in the context of the actual classroom, what instructional techniques best help them build and use appropriate mental models.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Validating A Pedagogy For Conceptual Learning: Application in Internet Delivered Physiology Experiments
Efficacy of Active Learning in Remediating Misconceptions in Undergraduate Physiology
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Understanding structural evolution of galaxies with machine learning
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2022
  • 负责人:
    Nicola Rosario Napolitano
  • 依托单位:
煤矿安全人机混合群智感知任务的约束动态多目标Q-learning进化分配
  • 批准号:
    --
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    30万元
  • 批准年份:
    2022
  • 负责人:
    吉建娇
  • 依托单位:
基于领弹失效考量的智能弹药编队短时在线Q-learning协同控制机理
  • 批准号:
    62003314
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    24.0万元
  • 批准年份:
    2020
  • 负责人:
    沈剑
  • 依托单位: