The Learning Analytics of Scientific Simulation Game

碩士 === 國立中央大學 === 網路學習科技研究所 === 105 === The modeling-based learning with simulation games help students build scientific models in a contextualized environment. However, it’s still difficult for the novice students to learn with the complex simulation games without expert guidance. This study design...

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Main Authors: Cai-Ting Wen, 温采婷
Other Authors: Chen-Chung Liu
Format: Others
Language:zh-TW
Published: 2017
Online Access:http://ndltd.ncl.edu.tw/handle/s2ftvp
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spelling ndltd-TW-105NCU057260092019-05-15T23:39:52Z http://ndltd.ncl.edu.tw/handle/s2ftvp The Learning Analytics of Scientific Simulation Game 科學模擬遊戲學習歷程之學習分析 Cai-Ting Wen 温采婷 碩士 國立中央大學 網路學習科技研究所 105 The modeling-based learning with simulation games help students build scientific models in a contextualized environment. However, it’s still difficult for the novice students to learn with the complex simulation games without expert guidance. This study designed a learning activity based on a simulation game to guide students to construct their science models in simulation game. Participants were 25 students who are 10-th grade in a physics class. To understand how they learned in the simulation game, the models the students constructed, their performance and learning activities, as well as their conceptions of learning science and approaches to learning were collected. Content analysis and lag sequential analysis were applied to analyze the data. The result showed that most students were able to build a sound scientific model to solve the problem. Such a result indicates that the simulation game enhanced the students’ understanding of the problem. However, significant number of the students encountered difficulty in such modeling activity. This study thus applied supervised analysis to understand the factors influencing the students’ problem solving outcomes. The result found that whether students were able to link the reference material with the simulation game is a key factor influencing problem solving outcomes. Furthermore, this study applied unsupervised analysis to discover the hidden pattern that can not be seen by supervised analysis. The results reflects that those students simply relied on reference material in modeling activities tended not be able to solve problem through modeling. Therefore, this study suggested that educators need to apply some pedagogical scaffolding, for instance meta-cognitive scaffolding, in future design to guide these students to effectively learn through simulation games. Chen-Chung Liu 劉晨鐘 2017 學位論文 ; thesis 98 zh-TW
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description 碩士 === 國立中央大學 === 網路學習科技研究所 === 105 === The modeling-based learning with simulation games help students build scientific models in a contextualized environment. However, it’s still difficult for the novice students to learn with the complex simulation games without expert guidance. This study designed a learning activity based on a simulation game to guide students to construct their science models in simulation game. Participants were 25 students who are 10-th grade in a physics class. To understand how they learned in the simulation game, the models the students constructed, their performance and learning activities, as well as their conceptions of learning science and approaches to learning were collected. Content analysis and lag sequential analysis were applied to analyze the data. The result showed that most students were able to build a sound scientific model to solve the problem. Such a result indicates that the simulation game enhanced the students’ understanding of the problem. However, significant number of the students encountered difficulty in such modeling activity. This study thus applied supervised analysis to understand the factors influencing the students’ problem solving outcomes. The result found that whether students were able to link the reference material with the simulation game is a key factor influencing problem solving outcomes. Furthermore, this study applied unsupervised analysis to discover the hidden pattern that can not be seen by supervised analysis. The results reflects that those students simply relied on reference material in modeling activities tended not be able to solve problem through modeling. Therefore, this study suggested that educators need to apply some pedagogical scaffolding, for instance meta-cognitive scaffolding, in future design to guide these students to effectively learn through simulation games.
author2 Chen-Chung Liu
author_facet Chen-Chung Liu
Cai-Ting Wen
温采婷
author Cai-Ting Wen
温采婷
spellingShingle Cai-Ting Wen
温采婷
The Learning Analytics of Scientific Simulation Game
author_sort Cai-Ting Wen
title The Learning Analytics of Scientific Simulation Game
title_short The Learning Analytics of Scientific Simulation Game
title_full The Learning Analytics of Scientific Simulation Game
title_fullStr The Learning Analytics of Scientific Simulation Game
title_full_unstemmed The Learning Analytics of Scientific Simulation Game
title_sort learning analytics of scientific simulation game
publishDate 2017
url http://ndltd.ncl.edu.tw/handle/s2ftvp
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