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CAREER: Multimedia Explanation Generation for Knowledge-Based Learning Environments

CAREER: Multimedia Explanation Generation for Knowledge-Based Learning Environments
职业:基于知识的学习环境的多媒体解释生成
批准号:
9701503
负责人:
James Lester
金额:
$37.33万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1997
资助国家:
美国
项目状态:
已结题
起止时间:
1997-06-01 至 2001-05-31

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中文摘要
翻译
知识型 学习环境 可以 提供 高度定制的解决问题的经验,是针对每个学生的个人需求。 本项目通过开发实时多媒体,为新一代基于知识的学习环境创造技术 解释生成器 与 动画教学代理人。 动画教学代理在学习环境中具有突出的特点,可以观察学生的进步,为他们提供视觉上的情境化问题解决建议, 强大的激励作用。 该项目有三个主要目标:(1)发展 一 实时计算模型 多媒体解说 规划 用于动态 创建 定制的多媒体解释;(2)开发动画的计算模型 教学代理人;(3)进行 对这些模式的教学效果进行实证评估。 此外,该项目还开发了一个多媒体技术教学实验室,并启动了一个新的多学科课程,以知识为基础的多媒体学习环境。 这项工作大大推进了基于知识的 学习环境和人机交互。 再加上价格合理的多媒体硬件的迅速发展,这些技术的成功部署将对各级学生产生深刻而持久的影响。 通过在学习效率方面取得重大进展,这些技术将在课堂和工作场所广泛地带来根本性的改善。
英文摘要
Knowledge-based learning environments can provide highly customized problem-solving experiences that are tailored to the individual needs of each student. This project creates the technology for a new generation of knowledge-based learning environments by developing real-time multimedia explanation generators with animated pedagogical agents. Prominently featured in learning environments, animated pedagogical agents can observe students' progress, provide them with visually contextualized problem-solving advice, and play a powerful motivational role. The project has three major thrusts: (1) developing a computational model of real-time multimedia explanation planning for dynamically creating customized multimedia explanations; (2) developing a computational model of animated pedagogical agents; and (3) conducting empirical evaluations of the pedagogical effectiveness of these models. In addition, the project also develops a teaching laboratory for multimedia technology and initiates a new multidisciplinary course on Knowledge-Based Multimedia Learning Environments. This work significantly advances the state-of-the-art in knowledge- based learning environments and human-computer interaction. Coupled with rapid advances in affordable multimedia hardware, the successful deployment of these technologies will have a deep and lasting impact on students at all levels. By achieving significant gains in learning effectiveness, these technologies will bring about fundamental improvements in both the classroom and the workplace on a broad scale.
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ExplainIt: Improving Student Learning with Explanation-based Classroom Response Systems
  • 批准号:
    2111473
  • 项目类别:
    Standard Grant
  • 资助金额:
    $145.65万
  • 财政年份:
    2021
  • 负责人:
    James Lester
  • 依托单位:
AI Institute for Engaged Learning
  • 批准号:
    2112635
  • 项目类别:
    Cooperative Agreement
  • 资助金额:
    $1999.63万
  • 财政年份:
    2021
  • 负责人:
    James Lester
  • 依托单位:
Collaborative Research: PrimaryAI: Integrating Artificial Intelligence into Upper Elementary Science with Immersive Problem-Based Learning
  • 批准号:
    1934153
  • 项目类别:
    Standard Grant
  • 资助金额:
    $98.56万
  • 财政年份:
    2019
  • 负责人:
    James Lester
  • 依托单位:
EAGER: Collaborative Research: Building Capacity for K-12 Artificial Intelligence Education Research
  • 批准号:
    1938778
  • 项目类别:
    Standard Grant
  • 资助金额:
    $10.0万
  • 财政年份:
    2019
  • 负责人:
    James Lester
  • 依托单位:
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