基于Pedati模型的预包装产品培训混合式学习教学设计开发

Wicaksono Febriantoro
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引用次数: 3

摘要

2014年第5号《民用国家机器(ASN)法》规定,ASN有权获得能力发展。此外,在2017年第11号关于公务员管理的PP中确认,每个政府官员都有权在一年内获得至少20(20)学时的能力发展。有限的计量技术培训分配导致并非所有印尼的ASN都有机会发展他们的能力。因此,有必要在常规方法的基础上,开展多种形式的计量培训。另一种选择是基于电子学习的培训。其目标之一是减少面对面的课程时间,因此PPSDK可以在不影响培训质量的情况下进行更多的技术培训。本研究将运用PEDATI模型,分析针对政府机构中预包装产品参与者的培训需求与特点,量身打造混合式学习设计的发展。本研究采用描述性定性的研究开发方法。设计结果如下:PEDATI模型的所有阶段都可以用于开发基于主题专家验证的混合式学习教学设计。第4阶段的建议是,异步学习活动的设计应该包括每个学习活动的时间分配,以便估计所需的总时间。准确地将学习活动映射为同步学习和异步学习,可以确保达到能力标准,同时减少进行面对面学习所需的时间。设计将面对面的学习活动从总共50个学习小时(5天)减少到只有20个学习小时(2天),但作为交换,培训参与者必须在在线活动中花费更长的时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blended Learning Instructional Design Development On The Prepackaged Products Training Using Pedati Model
Civil State Apparatus (ASN) Act No. 5 2014 stated that ASN have the right to gain competence development. Further in PP No.11 2017 on Civil Servant Management confirmed that every government officer is entitled to competence development for at least 20 (twenty) lesson hours in 1 (one) year.Limited metrological technical training allocationcauses not all ASN in Indonesia have the opportunity to develop their competence. Therefore, it is necessary to develop varieties of metrological trainings in addition to conventional methods. The alternative is e-learning based training. One of its goal is to reduce face to face lesson hour, as a result more technical training can be conducted by PPSDK without compromising training quality. This study will analyzed the development of blended learning design that is tailored to the training needs and characteristics of participants in government institutions with prepackaged products training case study using PEDATI model. Research and development (R&D) methods with descriptive qualitative approach is used in this study. Design outcomes are as follows: all stages in PEDATI model can be used to develop blended learning instructional design based on validation by subject matter experts. A recommendation in the 4th stage the design of asynchronous learning activities should include time allocation for each learning activity in order to estimate the total time required. Accurate learning activity mapping into synchronous and asynchronous learning can ensure the achievement of competence standard and simultaneously reducing time needed to conduct face to face learning. The design prune face to face learning activity from total 50 Learning Hours (5 days) to only 20 Learning Hours (2 days), but as the trade off training participants have to occupy longer time in online activities.
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