The successes of using artificial intelligence (AI) in analysing large-scale data at a low cost make it an attractive tool for analysing student data to discover models that can inform decision makers in education. This article looks at the case of decision making from models of student satisfaction, using research on ten years (2008–17) of National Student Survey (NSS) results in UK higher education institutions. It reviews the issues involved in measuring student satisfaction, shows that useful patterns exist in the data and presents issues involved in the value within the data when they are examined without deeper understanding, contrasting the outputs of analysing the data manually, and with AI. The article discusses risks of using AI and shows why, when applied in areas of education that are not clear, understood and widely agreed, AI not only carries risks to a point that can eliminate cost savings but, irrespective of legal requirement, it cannot provide algorithmic accountability.

中文翻译：

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人工智能可以帮助预测学习者的需求吗？预测学生满意度的经验教训

使用人工智能 (AI) 以低成本分析大规模数据的成功使其成为分析学生数据以发现可为教育决策者提供信息的模型的有吸引力的工具。本文利用对英国高等教育机构十年（2008-17 年）全国学生调查 (NSS) 结果的研究，研究根据学生满意度模型做出决策的案例。它回顾了衡量学生满意度所涉及的问题，表明数据中存在有用的模式，并在没有更深入理解的情况下检查数据时提出了与数据价值相关的问题，对比了手动分析数据和人工智能的输出。这篇文章讨论了使用人工智能的风险，并说明了为什么当应用于尚不明确、理解和广泛认同的教育领域时，