In order to understand the learners' needs, concerns, and directions for improving web design and development courses, this study collected similar courses from six universities in China's MOOC (Massive Open Online Course) platform(https://www.icourse163.org/). A combination of quantitative and qualitative analysis methods was employed, utilizing Python for word frequency analysis and ROSTCM6 for sentiment analysis. In-depth analysis was conducted on highly praised and negative comments. The experimental results revealed that the evaluation of the courses mainly focused on course content and instructor performance, with significantly more positive feedback than negative feedback. Students expressed concerns regarding the lack of practical materials, variations in software versions, and excessive theoretical content during lectures. Based on the research findings, recommendations were proposed in five aspects, including course content organization and arrangement.

Yi Meilian. Research on learner feedback and text analysis of web design and development course—Based on Online Open Course Reviews from 6 Institutions. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 7: 145-151. https://doi.org/10.25236/AJCIS.2023.060719.

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