On the Development of CAI Course Wares by Group Data

论基于群体数据的CAI课件开发

• 批准号: 60580244
• 负责人: MURAI Moriyasu
• 金额: $ 0.9万
• 依托单位: Faculty of Education, Oita University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for General Scientific Research (C)
• 财政年份: 1985
• 资助国家: 日本
• 起止时间: 1985 至 1986
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-60580244/
• 关键词: CAI; Course Ware; Factot Analysis; Interpretive Structural Modeling; 教材研究

The method of course decision, presently adopted at CAI for practical use, lacks flexibility regardless of either linear types (Skinner) or branching types (Crouder). Even in branching types, the learner simply follows several branchings decided and presented by the programmer. This means that in CAI with fixed branchings nothing more expected than the programmer'steaching ability of the material. What is worse, as long as the flexibility of course decision is limited, it is basically impossible to prepare a system coping with various individual differences because the size of softwares cannot be limitless. For these reasons, studies of intelligent CAI have been making great progress. These studies, however, are seen successful under the condition that the answers to sub-procedures are quite clear. But in reality, they are not clarified in many cases. Our study took a different approach. We assumed that a proper learning course for an individual is decided phenomenologically, by analysing the group dataand individual differences.We came to the conclusion that multivariate analyses were effective in many attempts to obtain significant information, by placing an individual's data in the group data. We found that in such affective domains as apprehending pictures and factor analyis, these were directly applicable. In the case of intellectual learning of new materials, the leaners' data itself has little deviation. Thus, learning courses should be decided in terms of interaction between the logical structures of the material assumed by the teacher, and the individual learner sassumption about the material placed in the group data. Finally, after much discussion, we obtained information for making algorisms of course decision for individual learners.

目前在CAI中采用的课程决策方法，无论是线性类型（斯金纳）还是分支类型（克劳德），都缺乏灵活性。即使在分支类型中，学习者也只是遵循程序员决定和提出的几个分支。这意味着在具有固定分支的CAI中，没有什么比程序员对材料的教学能力更受期待的了。更糟糕的是，只要课程决策的灵活性是有限的，它基本上是不可能准备一个系统，以应付各种个体差异，因为软件的大小不可能是无限的。因此，智能CAI的研究取得了很大的进展。然而，这些研究被认为是成功的条件下，子程序的答案是相当清楚的。但在现实中，它们在许多情况下并没有得到澄清。我们的研究采取了不同的方法。我们假设，一个适当的学习过程中，个人是决定现象，通过分析组数据和个体差异，我们得出的结论是，多元分析是有效的，在许多尝试获得显着的信息，通过放置在组数据的个人数据。我们发现，在这些情感领域，如理解图片和因素分析，这些是直接适用的。在新材料的智力学习中，学习者的数据本身几乎没有偏差。因此，学习课程应该根据教师所假设的材料的逻辑结构与个人学习者对放置在组数据中的材料的假设之间的相互作用来决定。最后，经过大量的讨论，我们得到的信息，制定算法的课程决策的个人学习者。

项目成果

富田礼志: 大分大学教育学部研究紀要. Vol.9,No1. 64-74 (1986)

富田灵史：大分大学教育学研究通报，第 9 卷，第 64-74 期（1986 年）。

榊原典子: 大分大学教育学部研究紀要. Vol.9,No1. 122-129 (1986)

榊原纪子：大分大学教育学部通报，第 9 卷，第 122-129 期（1986 年）。

Tadashi MATSUMOTO: "On the Development of CAI Course Wares Decided by Group Data --- Case of Music Reading in School Music Education ---" The Research Bulletin of the Faculty of Education, Oita University. Vol.9,No.1. 56-63 (1987)

松本正：《论群体数据决定的CAI课件开发——学校音乐教育中的音乐阅读案例——》大分大学教育学部研究通报。

村井護晏: 大分大学教育学部研究紀要. Vol.9,No1. 47-55 (1986)

村井盛明：大分大学教育学部通报，第 9 卷，第 47-55 期（1986 年）。

Noriko SAKAKIBARA: "On the Development of CAI Course Wares Decided by Group Data --- Case of Teaching Materials on Food of Homemaking Education ---" The Research Bulletin of the Faculty of Education, Oita University. Vol.9,No.1. 122-129 (1987)

榊原典子：“论由群体数据决定的CAI课件的开发——家政教育的食品教材案例——”大分大学教育学部研究报告。