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<p>The lockdown was announced on 24 March 2020 due to the ongoing pandemic COVID-19. Universities and colleges were in a panic about the learning of students as traditional classroom sessions were not possible. Human–Computer Interaction (HCI) was the only solution as students had to interact using computers for learning and sharing resources. In this paper, the effectiveness of E-learning and HCI is compared to offline learning. We have collected responses from students of various universities. Furthermore, the LearningSent score is proposed for various questions based on relevance in teaching–learning, assessment, and recruitment. Experiment analysis reveal a lot of interesting insights. Experiment analysis revealed that 71% of respondents are in favor of E-learning, 43% of students are in favor of E-assessment and 30.60% are of the opinion that E-learning is effective for recruitment. Furthermore, 29.50% of students have given a rating of 4 and 6.90% of users have given a rating of 5 to an overall methodology which indicates that improvements. 83% accuracy is achieved using training and testing on responses. Correlation analysis on numerical ratings and calculated regression score is 0.79 which proves that regression score calculated from textual responses using Logistic Regression and numerical ratings are in synchronization.</p>

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Performance comparison between E-learning during COVID-19 pandemic versus traditional classes utilizing sentiment analysis

  • 期刊论文

  • 发表日期：

    2025年1月17日

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  • Rahul Kumar Singh,
  • Gourav Bathla,
  • Pardeep Singh,
  • Tanupriya Choudhury,
  • Jung-Sup Um

摘要

The lockdown was announced on 24 March 2020 due to the ongoing pandemic COVID-19. Universities and colleges were in a panic about the learning of students as traditional classroom sessions were not possible. Human–Computer Interaction (HCI) was the only solution as students had to interact using computers for learning and sharing resources. In this paper, the effectiveness of E-learning and HCI is compared to offline learning. We have collected responses from students of various universities. Furthermore, the LearningSent score is proposed for various questions based on relevance in teaching–learning, assessment, and recruitment. Experiment analysis reveal a lot of interesting insights. Experiment analysis revealed that 71% of respondents are in favor of E-learning, 43% of students are in favor of E-assessment and 30.60% are of the opinion that E-learning is effective for recruitment. Furthermore, 29.50% of students have given a rating of 4 and 6.90% of users have given a rating of 5 to an overall methodology which indicates that improvements. 83% accuracy is achieved using training and testing on responses. Correlation analysis on numerical ratings and calculated regression score is 0.79 which proves that regression score calculated from textual responses using Logistic Regression and numerical ratings are in synchronization.