Category: book report

  • Book Report Summer 2025 | HESA

    Book Report Summer 2025 | HESA

    Morning everyone.  The days are getting long, so that means it’s getting close to the time when I need to wrap up this blog for the (northern hemisphere) summer.  And that, in turn, means book report time, where I round up everything I’ve read on higher education for the past six months.

    (If you’re looking for non-higher education recommendations: Terry David Martin’s The Affirmative Action Empire: Nations and Nationalism in the Soviet Union 1923-1939 will re-wire your thinking about what the early Stalinism actually looked like, and Ashoka Mody’s India is Broken will probably do the same for post-Independence India.  Can’t give you much on the fiction side because most of what I have read is pretty meh, but if you’re into the detective genre, I can recommend Inspector Imanishi Investigates by Seicho Matsumoto.  Not quite as good as his earlier Tokyo Express – which is the most brilliant novel-length thriller based on train timetables ever written – but still pretty good.)

    Let’s start with institutional histories, of which I read two: A European University: The University of Helsinki 1640-2010 and A History of Temple University Japan: An Experiment in International Education.  The first is an absolute doorstopper (over 800 pages – down from about 1500 in the original Finnish) but from a scholarly perspective it is genuinely top-notch.  Because fundamentally it is not just a history of the university, but an intellectual history of the country as a whole.  In that sense, it recalls my favourite book of last year Université de Montréal: une historie urbaine et internationale, but also to some extent Martin Friedland’s history of the University of Toronto.  The Temple Japan was also pretty interesting.  Branch campuses don’t often get their own histories, and this one is a doozy: a roller-coaster story which shows exactly how hard it is to lay down roots in a country where you don’t really speak the language, where government is mostly hostile, and your partners – even where they are legitimate (which not all of Temple’s were) – don’t always have similar goals in mind.  Great stuff.

    Searching for Utopia: Universities and Their Histories by Hanna Holborn Grey is a good short book with a misleading title.  It’s not actually about the histories of the American university, but a history of the ideas that animate them and how these ideas echo across a century or more, animated for the most part by the words of Robert Hutchins (U Chicago) and Clark Kerr (U California). 

    I was in Japan for a bit back in March, and so decided to pick up Shigeru Nakayama’s Science, Technology and Society in Postwar Japan. It’s at least 25 years out of date but it is a pretty interesting read as a kind of pre-history of the modern Japanese scientific enterprise and helpful to understand why university science is such a small part of the overall equation.  I also read Grant Black’s Education Reform Policy at a Japanese Super Global University, a book about Tsukubu U, from Routledge.  It reads like a Master’s thesis and is mostly pretty banal, but it does have just enough interesting nuggets about how top-tier institutions in Japan are re-imagining their offerings in the early twenty-first century to make it worth a skim at least.

    Two books I read focusing specifically on American university finances were Let Colleges Fail: The Power of Creative Destruction in Higher Education by Richard K. Vedder and Joshua Travis Brown’s Capitalizing on College: How Higher Education Went from Mission-Driven to Margin-Obsessed.  You can skip the Vedder book; over his career he has written a lot of useful stuff about college cost structures but now in his 80s this (apparently) farewell book contains far too much “colleges are woke so fuck ‘em” for my taste.  Capitalizing on College is a lot more interesting, containing as it does eight case studies of religious colleges and how the various financial strategies they have adopted to stave off financial decline have worked out.  The answer – mostly pretty badly except for the one who traded God for Mammon – might not sound riveting or surprising, but the routes that each institution takes towards the bottom of the canyon are varied and collectively tell a pretty interesting story, all of which come down to “nobody really wants to pay for higher education”.  Thought-provoking even if it is 50-100 pages longer than it needed to be and is too casual with use of the term “neoliberal”.

    Sticking with the theme of books with lots of institutional case studies, I also polished off two books that are heavy on case studies: Inside College Mergers: Stories From the Front Lines (Mark La Brance, editor) and Strategic Mergers in Higher Education by Ricardo Azziz, Guilbert Henschke, Lloyd Jacobs and Sonita Jacobs.  The former is seven first-person accounts of mergers, some of which worked and some of which didn’t (which is great because failure cases are always underexplored in the literature), while the latter is a more analytical look at university mergers over time.  The latter is arguably the more significant book both because of its attempts at theory-building (its typology of mergers is particularly helpful, I think) and because in many ways its checklists of how to run a merger right are actually applicable to all universities at all times!  Its inclusion of European and Canadian experiences are commendable, even if they get some of the details wrong and is awkwardly-placed in a book which is fundamentally America-focused.  Two thumbs up anyway.

    Tenure Tracks in European Universities, (free download at the link) is a collection of essays edited by Elias Pekkola and Taru Siekkinen.  Following the introduction of global rankings, there was a widespread desire to copy this North American invention partly in order to incentivize greater productivity, but also to make researcher careers more attractive to international scholars (broadly speaking, the old European systems were nicer to early career academics and much harder on mid-career academics than the North American system).    Generally speaking, tenure never replaced the old hierarchy but rather now sits uneasily beside it, but the specific manner in which reform was implemented differed from place to place, and this book is a very helpful overview.

    Two books on UK higher education to look out for.  The first was The Secret Lecturer by…well, it’s a secret (the idea is a play on a series of articles and books in the Guardian called The Secret Footballer, in which a professional talked a lot about what goes on behind the scenes on a professional soccer team…the footballer was never named but most people think it was Dave Kitson).  It was interesting in many ways, showing what day-to-day life in a UK university looks like, and it is in many ways very disappointing.  It’s a bit blighted by the lecturer’s insistence on centering his own views about the relationship between universities and the arms trade, but that’s a minor quibble: I sure would like a Canadian equivalent.  The second was Higher Imagination: A Future for Universities by British/Australian policy wonk Ant Bagshaw, which was…intriguing.  Some bits of it will probably enrage a lot of faculty – in particular the bits about being relentlessly focused on programs as “products”, but the bits stressing that one of the key outputs of universities should be “joy” are pretty original (and, IMHO, true, even if it would be madness for any institution to say stuff like this out loud).

    Education, Skills and Technical Change: Implications for Future US GDP Growth is a book I should have read when it came out a few years ago.  It’s a series of quite technical economic papers from some of the biggest names in US economics, not about higher education itself, for the most part, but mostly about returns to skills.  Of the two which are more specifically about institutional production functions, the one by Caroline Hoxby is interesting, the other one, about the rise in college costs, is garbage (as the article’s discussant in the book, Sandy Baum, ably points out).  It’s one of those books where you don’t necessarily need to buy all the results, or believe that the results hold outside the United States, but you do just sort of stand slack-jawed in wonder at how many different ways they have to analyze a problem thanks to a system of economic and institutional data collection which doesn’t suck the way Canada’s does.

    The Promise of Higher Education: Essays in Honour of 70 Years of the International Association of Universities(also availableas a free download here) is a boatload of short ideas on the idea of higher education written on the occasion of the International Association of Universities.  Most of the individual articles are forgettable – the way to best experience this book is as a kind of mood music in favour of higher education’s greatest kumbaya themes.  But a couple are superb: in particular Simon Marginson and Lili Yang’s dissection of Chinese versus Western conceptions of institutional autonomy, as well as Pedro Teixera and Manja Klemencic’s article on the Civic Role of universities (also of interest is Daniel Levy’s screed against management-led institutional activism, which might be the politest and most substantive critique of institutional DEI approaches ever written). 

    The Learning-Centered University, whose author Steven Mintz I interviewed back here, is a book that was somewhat let down by poor editing.  The subject is interesting and Mintz is well-informed on the subject, but while the material is good, it’s presented in a somewhat disorganized fashion, which undermines the point a bit.  Knowledge Towns: Colleges and Universities as Talent Magnets, by David Staley and Dominic Endicottis…almost interesting.  That is to say: it has an interesting thesis about how cities can use educational institutions to re-define themselves, especially in periods of demographic change, but it is marred by some wishful thinking about the flexibility of institutional forms and a bunch of wishful thinking about things like “micro-colleges”.  Finally, there was Polarized by Degrees: How the Diploma Divide and the Culture War Transformed American Politics by Matt Grossman and David Hopkins, which is probably of more interest to political scientists studying voting patterns than it is to educationists trying to work out how to de-polarize the sector in the current environment of wild right-wing vandalism.

    On the subject of science more generally, I read Science of Science by Alexander Krauss (open access version available here), which is an interesting approach to the subject without being anywhere near as revolutionary as the author claims.  His central insight, though – that the history of science is to a very large extent a history of methodologies and the measurement tools that permit new methodologies to sprout – is pretty interesting and I am looking forward to the companion volume coming out later this year called The Motor of Scientific Discovery.  In the history of science category, I also picked up Scientific Babel: the Language of Science from the Fall of Latin to the Rise of English  by Michael Gordin which is about how over the course of two centuries English won out over German, French, Russian and a plethora of constructed languages like Volapuk, Esperanto and Ido (many of which, to my surprise, were actually constructed with the specific intention of being languages for the transmission of sciences) to become the lingua franca of sciences.  It’s terrific and I heartily endorse it.

    I think that’s it.  Hope you get some good reading this summer and if you find anything you think I need to read, drop me a line!

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  • Helping students evaluate AI-generated content

    Helping students evaluate AI-generated content

    Key points:

    Finding accurate information has long been a cornerstone skill of librarianship and classroom research instruction. When cleaning up some materials on a backup drive, I came across an article I wrote for the September/October 1997 issue of Book Report, a journal directed to secondary school librarians. A generation ago, “asking the librarian” was a typical and often necessary part of a student’s research process. The digital tide has swept in new tools, habits, and expectations. Today’s students rarely line up at the reference desk. Instead, they consult their phones, generative AI bots, and smart search engines that promise answers in seconds. However, educators still need to teach students the ability to be critical consumers of information, whether produced by humans or generated by AI tools.

    Teachers haven’t stopped assigning projects on wolves, genetic engineering, drug abuse, or the Harlem Renaissance, but the way students approach those assignments has changed dramatically. They no longer just “surf the web.” Now, they engage with systems that summarize, synthesize, and even generate research responses in real time.

    In 1997, a keyword search might yield a quirky mix of werewolves, punk bands, and obscure town names alongside academic content. Today, a student may receive a paragraph-long summary, complete with citations, created by a generative AI tool trained on billions of documents. To an eighth grader, if the answer looks polished and is labeled “AI-generated,” it must be true. Students must be taught how AI can hallucinate or simply be wrong at times.

    This presents new challenges, and opportunities, for K-12 educators and librarians in helping students evaluate the validity, purpose, and ethics of the information they encounter. The stakes are higher. The tools are smarter. The educator’s role is more important than ever.

    Teaching the new core four

    To help students become critical consumers of information, educators must still emphasize four essential evaluative criteria, but these must now be framed in the context of AI-generated content and advanced search systems.

    1. The purpose of the information (and the algorithm behind it)

    Students must learn to question not just why a source was created, but why it was shown to them. Is the site, snippet, or AI summary trying to inform, sell, persuade, or entertain? Was it prioritized by an algorithm tuned for clicks or accuracy?

    A modern extension of this conversation includes:

    • Was the response written or summarized by a generative AI tool?
    • Was the site boosted due to paid promotion or engagement metrics?
    • Does the tool used (e.g., ChatGPT, Claude, Perplexity, or Google’s Gemini) cite sources, and can those be verified?

    Understanding both the purpose of the content and the function of the tool retrieving it is now a dual responsibility.

    2. The credibility of the author (and the credibility of the model)

    Students still need to ask: Who created this content? Are they an expert? Do they cite reliable sources? They must also ask:

    • Is this original content or AI-generated text?
    • If it’s from an AI, what sources was it trained on?
    • What biases may be embedded in the model itself?

    Today’s research often begins with a chatbot that cannot cite its sources or verify the truth of its outputs. That makes teaching students to trace information to original sources even more essential.

    3. The currency of the information (and its training data)

    Students still need to check when something was written or last updated. However, in the AI era, students must understand the cutoff dates of training datasets and whether search tools are connected to real-time information. For example:

    • ChatGPT’s free version (as of early 2025) may only contain information up to mid-2023.
    • A deep search tool might include academic preprints from 2024, but not peer-reviewed journal articles published yesterday.
    • Most tools do not include digitized historical data that is still in manuscript form. It is available in a digital format, but potentially not yet fully useful data.

    This time gap matters, especially for fast-changing topics like public health, technology, or current events.

    4. The wording and framing of results

    The title of a website or academic article still matters, but now we must attend to the framing of AI summaries and search result snippets. Are search terms being refined, biased, or manipulated by algorithms to match popular phrasing? Is an AI paraphrasing a source in a way that distorts its meaning? Students must be taught to:

    • Compare summaries to full texts
    • Use advanced search features to control for relevance
    • Recognize tone, bias, and framing in both AI-generated and human-authored materials

    Beyond the internet: Print, databases, and librarians still matter

    It is more tempting than ever to rely solely on the internet, or now, on an AI chatbot, for answers. Just as in 1997, the best sources are not always the fastest or easiest to use.

    Finding the capital of India on ChatGPT may feel efficient, but cross-checking it in an almanac or reliable encyclopedia reinforces source triangulation. Similarly, viewing a photo of the first atomic bomb on a curated database like the National Archives provides more reliable context than pulling it from a random search result. With deepfake photographs proliferating the internet, using a reputable image data base is essential, and students must be taught how and where to find such resources.

    Additionally, teachers can encourage students to seek balance by using:

    • Print sources
    • Subscription-based academic databases
    • Digital repositories curated by librarians
    • Expert-verified AI research assistants like Elicit or Consensus

    One effective strategy is the continued use of research pathfinders that list sources across multiple formats: books, journals, curated websites, and trusted AI tools. Encouraging assignments that require diverse sources and source types helps to build research resilience.

    Internet-only assignments: Still a trap

    Then as now, it’s unwise to require students to use only specific sources, or only generative AI, for research. A well-rounded approach promotes information gathering from all potentially useful and reliable sources, as well as information fluency.

    Students must be taught to move beyond the first AI response or web result, so they build the essential skills in:

    • Deep reading
    • Source evaluation
    • Contextual comparison
    • Critical synthesis

    Teachers should avoid giving assignments that limit students to a single source type, especially AI. Instead, they should prompt students to explain why they selected a particular source, how they verified its claims, and what alternative viewpoints they encountered.

    Ethical AI use and academic integrity

    Generative AI tools introduce powerful possibilities including significant reductions, as well as a new frontier of plagiarism and uncritical thinking. If a student submits a summary produced by ChatGPT without review or citation, have they truly learned anything? Do they even understand the content?

    To combat this, schools must:

    • Update academic integrity policies to address the use of generative AI including clear direction to students as to when and when not to use such tools.
    • Teach citation standards for AI-generated content
    • Encourage original analysis and synthesis, not just copying and pasting answers

    A responsible prompt might be: “Use a generative AI tool to locate sources, but summarize their arguments in your own words, and cite them directly.”

    In closing: The librarian’s role is more critical than ever

    Today’s information landscape is more complex and powerful than ever, but more prone to automation errors, biases, and superficiality. Students need more than access; they need guidance. That is where the school librarian, media specialist, and digitally literate teacher must collaborate to ensure students are fully prepared for our data-rich world.

    While the tools have evolved, from card catalogs to Google searches to AI copilots, the fundamental need remains to teach students to ask good questions, evaluate what they find, and think deeply about what they believe. Some things haven’t changed–just like in 1997, the best advice to conclude a lesson on research remains, “And if you need help, ask a librarian.”

    Steven M. Baule, Ed.D., Ph.D.
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