动感反用于理解程序执行
Satinder Gill1, Bryson J Goolsby1, Dianne T V Pawluk1
1Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA 23219, USA.
Sensors (Basel, Switzerland)
|June 10, 2023
概括
将动感反添加到教育机器人中可以提高编程命令回忆和终端准确性. 这种多模式的方法增强了不同学生风格的学习,克服了编程教育的挑战.
科学领域:
- 教育中的机器人技术
- 人与计算机的交互
- 教育技术的教育技术
背景情况:
- 编程教育对于STEM至关重要,但对于学生和教育工作者来说往往是具有挑战性的.
- 教育机器人被用来吸引学生,但它们的有效性各不相同.
- 学生的学习风格不同,这表明多模式反可以提高编程理解.
研究的目的:
- 通过使用教育机器人,调查联合动感和视觉反对编程命令解释的影响.
- 将多模式反与仅视觉和叙事反方法的有效性进行比较.
- 评估动感反是否有助于或阻碍机器人程序命令的理解.
主要方法:
- 人类参与者 (n=10人) 执行了涉及确定机器人程序命令序列的任务.
- 评估命令回忆精度和终点位置确定.
- 进行比较的条件:动感+视觉反,仅视觉反和叙事描述.
主要成果:
- 参与者准确地确定了运动指令和大小,并结合了动感+视觉反.
- 动感+视觉反的指令回忆精度高于仅视觉反.
- 与仅视觉相比,动感+视觉反和叙事方法的终点位置准确性明显更好.
结论:
- 综合动感和视觉反增强,而不是阻碍,机器人程序命令的解释.
- 教育机器人中的多模式反方法可以满足不同的学习风格.
- 这项研究表明,通过增强的反机制,提高了编程教育的学习成果.
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