Online learning is becoming increasingly popular, whether for convenience, to accommodate work hours, or simply to have the freedom to study from anywhere. Especially, during the Covid-19 pandemic, it has become the only viable option for learning. The effectiveness of teaching various hard-core programming courses with a mix of theoretical content is determined by the student interaction and responses. In contrast to a digital lecture through Zoom or Teams, a lecturer may rapidly acquire such responses from students' facial expressions, behavior, and attitude in a physical session, even if the listener is largely idle and non-interactive. However, student assessment in virtual learning is a challenging task. Despite the challenges, different technologies are progressively being integrated into teaching environments to boost student engagement and motivation. In this paper, we evaluate the effectiveness of various in-class feedback assessment methods such as Kahoot!, Mentimeter, Padlet, and polling to assist a lecturer in obtaining real-time feedback from students throughout a session and adapting the teaching style accordingly. Furthermore, some of the topics covered by student suggestions include tutor suggestions, enhancing teaching style, course content, and other subjects. Any input gives the instructor valuable insight into how to improve the student's learning experience, however, manually going through all of the qualitative comments and extracting the ideas is tedious. Thus, in this paper, we propose a sentiment analysis model for extracting the explicit suggestions from the students' qualitative feedback comments.
翻译:在线学习越来越受欢迎,无论是为了方便,为了方便,是为了兼顾工作时间,还是只是为了让学生在任何地方自由学习。特别是,在Covid-19大流行期间,它已成为唯一的可行的学习选择。教授各种具有理论内容组合的各种核心编程课程的实效由学生互动和反应决定。与通过Zoom或小组进行的数字讲座相比,讲师可以在体育课中迅速从学生的面部表达、行为和态度中获得这种反应,即使听众基本上闲置和不互动。然而,虚拟学习的学生评估是一项艰巨的任务。尽管存在挑战,但不同的技术正在逐渐融入教学环境,以促进学生的参与和积极性。在本论文中,我们评估各种课堂反馈评估方法的有效性,如Kahooot! Mentiter,Padlet和投票,以帮助讲师在整个课期间从学生的面部得到实时反馈,并相应调整教学风格。此外,学生建议的一些专题包括辅导建议、加强教学风格、课程内容和其他主题。任何建议都对教师如何通过手动式分析来改进学生的学习过程的定性分析提出了宝贵的见解。