Learning from worked-out examples: Fostering the integration of multiple representations

从已解决的示例中学习：促进多种表示的集成

• 批准号: 5414358
• 负责人: Professor Dr. Alexander Renkl
• 金额: --
• 依托单位: Leibniz-Institut für Wissensmedien (IWM)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2003
• 资助国家: 德国
• 起止时间: 2002-12-31 至 2005-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/5414358?language=en
• 关键词: Learning; worked; out; examples; Fostering

Learning from worked-out examples plays an important role in cognitive skill acquisition in well-structured domains such as mathematics. In addition, research has provided many guidelines how to structure example-based learning. However, there is hardly any research on worked-out examples in which multiple representations are employed with the instructional intention to foster deep understanding and flexible knowledge. Against this backgrond, worked-out examples with solutions in multiple representational formats (domain: stochastics/combinatorics) are employed in this project. The overall research question refers to the following issues: Can the understanding of solution procedures be fostered by the employment of multiple representations that are combined with instructional means that aim to foster the integration of different representations? Such instructional means are a) self-explanation prompts that direct the learners to identify the relations between different representations and b) corresponding instructional explanations. These issues are addressed by two experimental studies.

样例学习在结构良好的领域（如数学）的认知技能习得中起着重要作用。此外，研究提供了许多指导方针，如何构建基于示例的学习。然而，很少有研究工作的例子中，采用多种表征的教学意图，以促进深刻的理解和灵活的知识。针对这一背景，在这个项目中采用了多种代表性格式（域：随机/组合）的解决方案的工作了的例子。总体研究问题是指以下问题：可以理解的解决方案程序，促进就业的多个代表性相结合的教学手段，旨在促进不同的表征的整合？这种教学手段是a）引导学习者识别不同表征之间的关系的自我解释提示和B）相应的教学解释。这些问题通过两项实验研究来解决。