An Achievement Prediction Model of Meaningful Learning, Motivation, and Cognitive on SPANI: Partial Least Square Analysis

摘要

This paper employed an SPANI (Shooting Pose Adjustment with Nature Interactions) learning system with achievement prediction model of meaningful learning. Motivation, cognitive, and PLS (Partial Least Square) method was used to analyze the results. Proposed model is focused on information and communication technology teaching mode, meaningful learning, learning motivation, cognitive load, and learning achievement. Theories of SPANI achievement prediction model investigated the learner’s degree of meaningful learning, learning motivation, cognitive loading, and learning achievement (Huang et al. 2012, Credé and Phillips 2011, Deleeuw and Mayer 2008, and Peterson et al. 2010). Questionnaire and systems tests were used with 107 valid samples in the samples’ record to conduct narrative statistics, inspection of reliability and validity, and PLS of Structural Equation Modeling (SEM). The results show that the developing system is very helpful to learner’s learning motivation and learning achievement. And learner’s learning motivation, which influences the degree of the cognitive load and learning achievement, has a high relationship. It means, the designers of teaching materials can start with digital content to improve learning motivation and also handle the two important parts which are learning strategy and learning motivation. It can be very helpful in improving teaching quality.