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However, effectively explaining complex or large amounts of information, such as that contained in a textbook or library, in an intuitive, user-centered way is still an open challenge. Indeed, different people may search for and request different types of information, even though texts typically have a predefined exposition and content. With this paper, we investigate how explanatory AI can better exploit the full potential of the vast and rich content library at our disposal. Based on a recent theory of explanations from Ordinary Language Philosophy, which frames the explanation process as illocutionary question-answering, we have developed a new type of interactive and adaptive textbook. Using the latest question-answering technology, our e-book software (YAI4Edu, for short) generates on-demand, expandable explanations that can help readers effectively explore teaching materials in a pedagogically productive way. It does this by extracting a specialized knowledge graph from a collection of books or other resources that helps identify the most relevant questions to be answered for a satisfactory explanation. We tested our technology with excerpts from a textbook that teaches how to write legal memoranda in the U.S. legal system. Then, to see whether YAI4Edu-enhanced textbooks are better than random and existing, general-purpose explanatory tools, we conducted a within-subjects user study with more than 100 English-speaking students. The students rated YAI4Edu\u2019s explanations the highest. According to the students, the explanatory content generated by YAI4Edu is, on average, statistically better than two baseline alternatives (\n                    <jats:italic>P<\/jats:italic>\n                    values below .005).\n                  <\/jats:p>","DOI":"10.1007\/s40593-024-00399-w","type":"journal-article","created":{"date-parts":[[2024,5,6]],"date-time":"2024-05-06T10:01:43Z","timestamp":1714989703000},"page":"987-1021","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["How to Improve the Explanatory Power of an Intelligent Textbook: a Case Study in Legal Writing"],"prefix":"10.1016","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6285-1041","authenticated-orcid":false,"given":"Francesco","family":"Sovrano","sequence":"first","affiliation":[]},{"given":"Kevin","family":"Ashley","sequence":"additional","affiliation":[]},{"given":"Peter Leonid","family":"Brusilovsky","sequence":"additional","affiliation":[]},{"given":"Fabio","family":"Vitali","sequence":"additional","affiliation":[]}],"member":"78","published-online":{"date-parts":[[2024,5,6]]},"reference":[{"key":"399_CR1","unstructured":"Achinstein, P. 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