1) While the author claimed many benefits and advantages of ML in education, the lack of solid evidence made these arguments less persuasive. The reviewer encourages the author to add more concrete examples and data points throughout to support key claims about ML benefits and applications. Specifically, some numeric results would enhance the chapter significantly for the case study, which is one of the most valuable parts of this chapter.
2) The technical details of ML algorithms and models are somewhat limited. More depth here could significantly enhance the chapter. The author is strongly encouraged to expand the technical sections with more details on specific ML algorithms and models used in educational applications instead of merely discussing ML in general.
3) Some of the items are not well-discussed. For instance, at the end of Section 1, it is unclear what information the author intends to deliver by just giving one sentence like “Teaching Quality Evaluation: The feedback obtained via analytics endorses the topicality and the subject’s impact.”
4) The writing style and formatting are inconsistent in some places, with some informal language used. Specifically, some references are not in a consistent academic format. Please conduct thorough proofreading for consistent academic tone,formatting, and citation style/format.
5) The conclusion is quite brief and could be expanded to tie together key points more comprehensively. Please consider expanding the conclusion to summarize key takeaways and implications more comprehensively. For instance, some discussions on future directions should be added to discuss emerging trends and research areas.
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