Research On The Effect Of Online Learning Feedback Methods On Attention

As an important learning method,online learning meets the needs of ubiquitous learning and personalized learning in the information age with its convenience and flexibility.Teachers cannot provide face-to-face guidance to students in the learning mode of separation of time and space,and it is difficult for younger students to maintain long-term concentration during video viewing,which has hindered the development of online education.Recognizing students’ learning status in real time and providing personalized feedback and intervention is an important means to ensure the efficiency of online learning.Therefore,combining the physiological information measured by wearable technology with the data of learning activities to analyze and infer the individual learning status,through timely personalized feedback can improve the learning efficiency of online learning and ensure the learning effect.In this study,wearable sensors are used to collect EEG information of students,and to infer the state of concentration,which realizes the explicit expression of the implicit state,provides students with personalized guidance and intervention of learning state,improves the online learning effect and experience,and provides strong support for the brain-computer interface design of online learning.This article specifically carried out the following research:Firstly,on the basis of literature research,the principles,processes and methods of attention recognition are summarized and summarized,the concepts,influencing factors,design principles and application effects of learning feedback are analyzed,and the significance and role of EEG biofeedback are discussed.Secondly,an attention feedback and intervention system based on EEG signals was established in the context of online learning.Taking the second graders as a research object,an experiment was designed to explore the influence of feedback intervention forms and standards on attention during the online learning process.Through experimental research and semi-structured interviews,the results of data analysis show that(1)negative feedback is helpful to maintain learning attention and has statistical significance;(2)voice feedback is better than visual feedback,but there is no significant difference;(3)students report that they prefer voice feedback.Therefore,a voice-based negative feedback method was determined in the context of online learning to remind students to stay focused.Thirdly,based on the aforementioned research results,the design experiment explored the effects of personalized EEG biofeedback(negative voice-based feedback)on learners’academic performance,self-efficacy,attention state,and learning behavior in an online learning environment.Through comparative experiments and questionnaire surveys,the data analysis results show that when the attention is less than 40 and more than 5 seconds,give voice feedback "please keep attention",(1)can improve the learner’s academic performance;(2)self-efficacy for the learner has no significant effect;(3)can improve the learner’s attention level;(4)can reduce the learner’s irrelevant learning behavior.Finally,a strategy for improving attention in online learning is proposed.In the feedback design of the brain-computer interface,it strives to achieve the instantaneous feedback time,the personalization of the feedback content,the motivation of the feedback standard,and the visualization of the feedback form.