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Listen to the models: Sonified learning models for people who are blind

机译:听模式:针对盲人的声音学习模式

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Students who are blind need access to learning materials. This study looks at the learning of science by people who are blind using a curriculum-based textbook compared to their learning using an identical curriculum integrated with the Listening-to-Complexity (L2C), an agent-based model created on NetLogo. The L2C system employs sonified feedback that provides auditory streams synchronically. This study examines acquisition of scientific conceptual knowledge and systems reasoning for the Kinetic Molecular Theory (KMT) of gas and Gas Laws in chemistry. Twenty persons who are blind participated in this research; they were divided into two experimental groups: those using an accessible curriculum-based textbook and those using the same curriculum integrated with L2C agent-based models. Results showed that all research participants gained scientific knowledge; statistically significant differences were found for both experimental research groups between pre- and posttest. Those who learned through the L2C models performed with higher accuracy in the posttest; furthermore, learning using the NetLogo L2C models predicted their success at the posttest. A comparison of learning task accuracy between the two experimental groups showed that the participants who studied using the NetLogo L2C models performed with statistically significant differences in the five learning activities with integrated L2C models, but no differences were found for the learning activities without integrated L2C models. These research results are likely to have a beneficial impact on integrating sonified models in science education as a compensatory aid, allowing hands-on learning experience for students who are blind. Integrating sonified models will support their inclusion in the K-12 academic curriculum on an equal basis.
机译:失明的学生需要学习材料。这项研究着眼于盲人使用基于课程的教科书进行的科学学习,而不是盲人使用相同的课程与基于NetLogo创建的基于代理的模型(L2C)集成的学习所进行的学习。 L2C系统采用声音反馈,可同步提供听觉流。本研究探讨了化学概念知识的获取以及气体和气体定律的动力学分子理论(KMT)的系统推理。二十位盲人参加了这项研究;他们分为两个实验组:使用基于可访问课程的教科书的实验组,以及使用基于L2C Agent的模型集成的相同课程的实验组。结果表明,所有研究参与者都获得了科学知识。在实验前和实验后,两个实验研究组均发现统计学上的显着差异。那些通过L2C模型学习的人在后期测试中的准确性更高;此外,使用NetLogo L2C模型进行学习可以预测它们在后期测试中的成功。两个实验组之间学习任务准确性的比较表明,使用NetLogo L2C模型进行研究的参与者在使用集成L2C模型的五项学习活动中具有统计学上的显着差异,但是在没有使用集成L2C模型的学习活动中没有发现差异。这些研究结果可能会对将声纳模型整合到科学教育中作为补偿性援助产生有益的影响,从而为盲人学生提供动手学习的经验。整合语音模型将支持它们在平等的基础上纳入K-12学术课程。

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