Often these solutions are announced in a rush, leaving no time for a proper writeup, the isolation of new methods and ideas, and citing relevant previous work of others.
【局限】作者指出AI解决方案常常仓促公布，缺乏适当的文档编写、新方法与思想的提炼以及对他人相关工作的引用。这一局限揭示了当前AI生成数学内容的质量控制和学术规范缺失问题。
research often misidentifies pain points
Depuis longtemps, je suis d’avis que la rigueur d’un cours ne se mesure pas à la quantité de connaissances dont l’enseignant fait étalage, mais aux apprentissages que les étudiants font.
Which can lead to an assessment of pedagogical efficacy. It's funny, to me, that those who complain about "grade inflation" (typically admins) rarely entertain the notion that grades could be higher than usual if the course went well. The situation is quite different in "L&D" (Learning and Development, typically for training and professional development in an organizational context). "Oh, great! We were able to get everyone to reach the standard for this competency! Must mean that we've done something right in our Instructional Design!"
baisser les attentes
Reminds me of: http://itre.cis.upenn.edu/~myl/languagelog/archives/001961.html
We commonly look at Ivy League institutions as the standard of higher education in America, but the truth is that the majority of the nation's workforce, innovation identity and manufacturing futures are tied to those institutions which graduate outside of the realm of high achievers from wealthy families.