Increasing Academic Compliance with Mathematics Tasks Using the High-Preference Strategy with a Student with Autism
Increasing Academic Compliance with Mathematics Tasks Using the High-Preference Strategy with a Student with Autism
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DOI：
10.1080/10459880903217564
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发表时间：
2009-01-01
影响因子：
0.9
通讯作者：
Kubina, Richard M., Jr.
中科院分区：
文献类型：
--
作者：
Banda, Devender R.;Kubina, Richard M., Jr.
作者调查了一名13岁的自闭症中学生使用高偏好（高p）数学任务来增加低偏好（低p）数学任务启动的有效性。他们使用ABAB设计来确定高p任务与低p任务的有效性。结果表明，学生花更少的时间来启动低p数学问题之前，高p数学问题。本研究扩展了高p技术的文献，以提高自闭症学生的学业遵从行为。作者讨论了结果和未来的影响。
The authors investigated the effectiveness of using high-preference (high-p) mathematics tasks for increasing task initiation of low-preference (low-p) mathematics tasks with a 13-year-old middle school student with autism. They used an ABAB design to determine the effectiveness of high-p tasks with to comply with low-p tasks. Results indicated that the student took less time to initiate low-p mathematics problems that were preceded by high-p mathematics problems. This study extends the literature on high-p techniques to enhance academic compliance behaviors for students with autism. The authors discuss the results and future implications.