基于刺激有机体反应理论的发现学习因素分析在学习成果转化中的应用

Suryadi, Ludfi Djajanto
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引用次数: 1

摘要

与刺激有机体反应模型(SOR)合作的发现学习方法可以解释学习模型,并解释刺激如何被五种感官捕获,然后被感知,从而引起对某事的反应。然而,由于发现方法中存在很多明显的缺陷,导致通常的回归模型分析存在差异,从而导致所得到的回归模型结构不太适合或精度不高。为了克服这种不精确或不足,因子回归分析可以用来克服多重共线性的情况。因子分析是因子分析技术和回归技术的结合。本研究的目的是从动机的表现变量出发,通过SOR的概念获得一种新的发现学习结构,以提高学习成果。调查对象为会计系2个学习项目中1班的市场营销学习,调查对象为114人。因子分析形成了一个名为new discoverymotivation & new discoveryteamwork的新变量结构,刺激后的最后一个因子回归结构为P2 (new Performance) = 3.443 + [(0.089 * (Newdiscoverymotivation) + 9.11 * (Newdiscoveryteamwork)]。研究结果证明,57.9%的个体关系水平和6.1%的集体关系水平足以实现维度影响,并且新构念明显提供了更高的成就。关键词:发现,动机,学习,刺激
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of Discovery Learning Factor Analysis in Transforming Learning Achievement Through Stimulus Organism Response Theory
The Discovery Learning method in collaboration with the Stimulus Organism Response Model (SOR) can explain the learning model and explain how the stimulus is captured by the five senses, then felt, causing a response to something. Whereas the discovery method with a lot of manifest causes discrepancies in the usual regression model analysis, so that the regression model constructs obtained are less suitable or less precise. To overcome this imprecision or deficiency, factor regression analysis can be used to overcome cases of multicollinearity. Factor analysis is a combination of factor analysis techniques and regression techniques. The purpose of this study was to obtain a new construct of discovery learning through the concept of SOR to improve learning achievement from the manifest variable of motivation. The object of research is marketing learning in class 1 in 2 study programs of the Department of Accounting with 114 respondents. The factor analysis formed is a new variable construct with the name New discovery motivation & New discovery teamwork, with the last Factor Regression construct after the stimulus is P2 (New Performance) = 3.443 + [(0.089 * (Newdiscoverymotivation) + 9.11 * (Newdiscoveryteamwork)]. The results of the study prove that the individual relationship level of 57.9% and collectively 6.1% is good enough to achieve dimensional influence and it is evident that new constructs provide increased achievement. Keywords—discovery, motivation, learning, stimulus
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