A literature survey on student feedback assessment tools and their usage in sentiment analysis
Norwegian University of Science and Technology（挪威科技大学）；Department of Information Technology and Electrical Engineering（信息技术与电气工程系）；Gjøvik, Norway（挪威吉维克（此处按要求不提取地址，实际应为机构外信息，正确处理应为仅保留大学名称，即原回答中“挪威科技大学”））
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.
LLM-assisted sentiment analysis for integrated computational and qualitative mixed methods education research: A case study of students' written reflection assignments
Chandra Family Department of Electrical and Computer Engineering, University of Texas at Austin（德克萨斯大学奥斯汀分校电子与计算机工程系）；Department of Engineering Education, Virginia Polytechnic Institute and State University（弗吉尼亚理工大学工程教育系）；Gallogly College of Engineering, University of Oklahoma（俄克拉荷马大学加洛格利工程学院）；Department of Mechanical and Materials Engineering, University of Nebraska-Lincoln（内布拉斯加大学林肯分校机械与材料工程系）
Learning from students' perception on professors through opinion mining
Laboratorios de Investigación en Inteligencia Artificial y Computación de Alto Desempeño, Analista（Analista人工智能与高性能计算研究实验室）；Fundación Universitaria Konrad Lorenz（康拉德·洛伦兹大学基金会）
Machine Translation, Sentiment Analysis, Text Similarity, Topic Modelling, and Tweets: Understanding Social Media Usage Among Police and Gendarmerie Organizations
The theoretical and methodical foundations of usage of information and communication technologies in teaching higher mathematics engineering students in universities of the United States
Media Usage in Post-Secondary Education and Implications for Teaching and Learning
Web 2.0已经渗透到学术生活中。在线信息服务在中学后教育中的使用导致教师教学方法以及学生的学习和学习行为发生了巨大变化。与此同时，传统的信息媒体，如教科书和印刷品，仍然是教学和学习的基本支柱。本文报道了一项关于西方大学学生和教师在教学中使用媒体的调查结果，突出了教师和学生在高等教育中使用新媒体和传统媒体的趋势。此外，该调查是一项国际研究计划的一部分，目前有来自10个国家的20所大学参与。此外，这项研究将有望成为正在进行的关于旨在促进在教学和学习中有效使用媒体的做法和政策的讨论的一部分。
The Relationship between Deteriorating Mental Health Conditions and Longitudinal Behavioral Changes in Google and YouTube Usages among College Students in the United States during COVID-19: Observational Study
