College of Teacher Education, Ningbo University, Ningbo 315211, China.
Advanced Innovation Center for Future Education, Beijing Normal University, Beijing 100875, China.
Int J Environ Res Public Health. 2022 Jun 19;19(12):7505. doi: 10.3390/ijerph19127505.
Online courses are prevalent around the world, especially during the COVID-19 pandemic. Long hours of highly demanding online learning can lead to mental fatigue and cognitive depletion. According to Attention Restoration Theory, 'being away' or a mental shift could be an important strategy to allow a person to recover from the cognitive overload. The present study aimed to test the interleaving strategy as a mental shift method to help sustain students' online learning attention and to improve learning outcomes. A total of 81 seventh-grade Chinese students were randomly assigned to four learning conditions: blocked (by subject matter) micro-lectures with auditory textual information (B-A condition), blocked (by subject matter) micro-lectures with visual textual information (B-V condition), interleaved (by subject matter) micro-lectures with auditory textual information (I-A condition), and interleaved micro-lectures by both perceptual modality and subject matter (I-all condition). We collected self-reported data on subjective cognitive load (SCL) and attention level, EEG data during the 40 min of online learning, and test results to assess learning outcomes. The results showed that the I-all condition showed the best overall outcomes (best performance, low SCL, and high attention). This study suggests that interleaving by both subject matter and perceptual modality should be preferred in scheduling and planning online classes.
在线课程在全球范围内很流行,尤其是在 COVID-19 大流行期间。长时间高度要求的在线学习会导致精神疲劳和认知耗竭。根据注意力恢复理论,“离开”或思维转移可能是一个重要的策略,可以帮助人们从认知过载中恢复过来。本研究旨在测试交错策略作为一种思维转移方法,以帮助维持学生的在线学习注意力并提高学习成果。共有 81 名七年级的中国学生被随机分配到四种学习条件:(按主题)带有听觉文本信息的分组(B-A 条件)、(按主题)带有视觉文本信息的分组(B-V 条件)、(按主题)交错的带有听觉文本信息的分组(I-A 条件)和(按主题和感知模式)交错的带有听觉和视觉文本信息的分组(I-all 条件)。我们收集了关于主观认知负荷(SCL)和注意力水平的自我报告数据、在线学习 40 分钟期间的 EEG 数据以及评估学习成果的测试结果。结果表明,I-all 条件总体表现最佳(表现最好、SCL 最低、注意力最高)。本研究表明,在安排和规划在线课程时,应优先考虑同时按主题和感知模式进行交错。