基于Android的仿真模型通过多媒体开发:科学有意义的学习

IF 1.2 4区 教育学 Q3 EDUCATION, SPECIAL Journal of Special Education Technology Pub Date : 2023-04-18 DOI:10.23887/jet.v7i1.51890
F. Kumala, Jurina Ibrahim, Hefsi Anggi Ambarwati, Siti Mafulah, Sri Rahayu
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引用次数: 0

摘要

2019冠状病毒病导致学习损失,学生的学习动机下降,因此需要学习,以增加学习的动机和意义。本研究的目的是利用多媒体开发生命周期(MDLC)步骤开发一个基于android的模拟模型,以发展小学有意义的科学学习。本研究是一项发展研究,使用MDLC阶段,然后对材料,语言,媒体和用户专家进行试验。本研究的研究对象为专家、教师和五年级学生。技术分析采用描述性定量技术。数据收集方法包括问卷调查、访谈和测试。采用专家验证表、测试、访谈和师生回答问卷等形式的工具。研究结果表明,已开发的媒体材料专家的可行性为68%(适当),媒体专家的可行性为91%(非常可行),语言专家的可行性为94%(不错)。教师的实用性评估获得了87%的百分比(非常实用),学生获得了77%的比例(非常实用)。基于android的模拟是可行的。这也是基于前测平均分63.3分和后测平均分77.7分的提高。后测分数也显示高于最低完整性标准(KKM)的分数。基于android的Mock Up可以提高学生的学习效果,让学生的科学学习更有意义。
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Mock Up Based on Android Through Multimedia Development Live Cycle : Science Meaningfull Learning
Covid 19 has led to loss learning and decreased student motivation in learning so that learning is needed that can increase motivation and meaningfulness in learning. The purpose of this study was to develop an Android-based mock up using the Multimedia Development Live Cycle (MDLC) steps to develop meaningful science learning in elementary schools. This research is a development research using the MDLC stages followed by trials on material, language, media and user experts. The subjects of this study were experts, teachers and 5th grade students. Technical analysis used descriptive quantitative techniques. Data collection methods consist of questionnaires, interviews and tests. Instruments in the form of expert validation sheets, tests, interviews and teacher and student response questionnaires. The results of the study show that the media that has been developed has a material expert feasibility of 68% (appropriate), media expert 91% (very feasible), and language expert 94% (decent). The teacher's practicality assessment obtained a percentage of 87% (very practical) and students obtained a proportion of 77% with very practical criteria. Android-based mock up is feasible to use. This is also based on the results of an increase in the average pretest score of 63.3 and posttest of 77.7. Posttest scores also show scores above the Minimum Completeness Criteria (KKM). Android-based Mock Up can improve student learning outcomes and make science learning more meaningful for students.
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来源期刊
CiteScore
3.90
自引率
15.80%
发文量
31
期刊最新文献
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