The Needs Analysis of Student Team Achievement Division Learning Model Development to Improve Science Learning Achievement of Children With Special Needs in Inclusive School

Serla Kusuma Arum, S. Sunardi, H. Widyastono
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Abstract

This study aims to analyze the need for developing a student team achievement division learning model to improve the science learning achievement of children with special needs in inclusive schools. Analysis of the needs of this learning model uses qualitative research. Data collection uses interviews. The data analysis technique used is descriptive analysis. The research respondents were special assistant teachers and 1 class teacher at 6 inclusive schools in the city of Surakarta. This research is limited to the analysis of learning needs in the science learning process conducted in inclusive schools. The results of this study indicate that 83% of teachers in inclusive schools still use conventional method that is lecture method in delivering science material to students but they use student activity in evaluating their classes. The teacher distinguishes children with special needs from other regular children in giving assignments. 58% of teachers do not understand the STAD cooperative learning model. It can be concluded that the current learning in inclusive classes has not been able to accommodate the needs of characteristics of children with special needs in inclusive classes. It is proved by the learning achievements, especially the science learning achievements of children with special needs, which are lower than other children in their class. Therefore, it is necessary to develop a STAD learning model.
全纳学校学生团队成就分工学习模式发展对特殊需要儿童科学学习成就的需求分析
本研究旨在分析在全纳学校中,为提高特殊需要儿童的科学学习成就,是否需要建立学生团队成就分工学习模式。对这种学习模式的需求分析采用了定性研究。数据收集使用访谈。使用的数据分析技术是描述性分析。调查对象是泗水市6所全纳学校的特别助理教师和1名班主任。本研究仅限于对全纳学校科学学习过程中学习需求的分析。本研究的结果表明,在全纳学校中,83%的教师仍然使用传统的方法,即讲课方法向学生传授科学材料,但他们使用学生活动来评估他们的课程。老师在布置作业时把有特殊需要的孩子和其他正常的孩子区别开来。58%的教师不理解STAD合作学习模式。可以得出结论,目前的全纳班学习还不能适应特殊需要儿童在全纳班的特点。特殊需要儿童的学习成绩,特别是科学学习成绩低于班级其他儿童,证明了这一点。因此,有必要开发一个STAD学习模型。
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