The most useful textbook & academic posts of the week: February 9, 2018
This week’s article roundup includes a mix of foundational advice and reinvention of ideas. In the academic world, there are posts discussing ways to establish a track record of grant writing, visualization techniques, and ways to survive a PhD mixed with new scholarly search tools, publisher roles, and disruptions in scholarly communications.
From the textbook perspective, the benefits of print over digital, the intellectual properties of learning, and opinions on professors teaching from their own textbooks are mixed with open-access publishing, OER disruption, and new platforms for self-publishing textbooks.
As Debasish Mridha tells us, “Writing is a process of creating yourself again and again for an ever-searching mind.” As you write this week, keep searching as well.
As the year begins, many of you will be planning your research for the coming year and identifying funding schemes to target. Some will have received the outcomes of last year’s grant applications and will either be breathing a sigh of relief or girding their loins for the next attempt. Here are five tips for you to help build your track record.
John Willinsky’s new book is a history of thought and learning — combined with analysis of the development of intellectual property concepts and a case for open-access publishing. Willinsky looks to intellectual history to illustrate his points about open access today. The result is The Intellectual Properties of Learning: A Prehistory from Saint Jerome to John Locke (University of Chicago Press).
As many professors assign texts they have authored themselves, some professionals argue professors must be careful and confident with the practice.
The newest twist in educational publishing—Open Educational Resources or OER—is dramatically disrupting textbook publishing, and conventional wisdom holds that these resources may even replace traditional textbooks all together. Case in point: in just four years, Eureka Math, an OER K-12 curriculum developed by the nonprofit GreatMinds.org, and funded by a federal grant to the New York State Education Department, has become the most widely used math curriculum in the United States according to a 2016 report by the Rand Corporation. Out of the 1168 elementary school teachers Rand surveyed, 52% said they used Eureka. In comparison, the most popular math textbook was used by only 32% of teachers.
The Top Hat technology platform now supports in-class interactivity, lecture slides, homework, online test-taking and a content marketplace of digital teaching materials. It’s the latter feature that could set Top Hat apart in the crowded ed-tech space: “Everyone’s doing classroom response systems,” says Fiona Hollands, professor of education at Columbia University’s Teachers College, “but not everybody’s providing a platform for [professors’] self-publishing” of textbooks.
In addition to using printed books as a safe haven from technology, research has shown that readers connect with a printed novel better than a digital one. Readers engage in a practice called “linear reading” when they read a printed book, a method that allows readers to immerse themselves in the world of a novel. Sometimes referred to as “deep reading,” linear reading requires the human brain to analyze and make inferences based on the text, in addition to processing the content of the words. In contrast, research suggests that people who read e-books engage in “nonlinear reading,” which involves simply skimming a text, rather than processing or thinking through its deeper meaning.
In short, reading printed books literally uses a different part of the brain than reading e-books.
Big data has become an increasingly common topic of discussion. While the amount of available data and its role in the economy will continue to grow, we worry that the big data revolution will not live up to its promise if it is guided by the principle that bigger is always better. Data quality will limit the usefulness of big data.
If you’re doing academic research, theory can be very useful. Some, like @leenie48, may argue that it is essential. It is certainly a powerful counter when you’re playing the academic game. Yet theory is, like everything, value-laden. At present, in the UK, the French social theorist Bourdieu is so fashionable that the British Sociological Association is often spoken of, tongue in cheek, as the Bourdieu Sociological Association. At the other extreme, social theories from the Southern hemisphere are often ignored or unknown. So I would argue that if we are to include theory, we need to engage with the attributes of the theory or theories on which we wish to draw, and give a rationale for our choice. I find it frustrating that so much of academia seems to regard any use of theory as acceptable as long as there is use of theory, rather than questioning why a particular theory is being used.
Data in a table or spreadsheet is valuable, but as human beings, seeing patterns or being able to summarize tabular data can be challenging. Visualizations allow us to do exactly that – create a visual representation of the data, giving us a chance to see it and interpret complex data efficiently at a glance.
Unpaywall is a service that indexes open access repositories, university, government and scholarly society archives, and other sources that make articles available with authorization from the rightsholders and journals — about 47% of the articles that its users seek.
Academic writing is a complex business. And it’s that complexity that makes it tricky.
A friend of mine asked me for some advice about what to do in the lead up to the PhD submission. While I’m sure every experience is different, I think it’s reasonably safe to say that the following points would be useful for a majority of PhD candidates.
This update is a reframing and expansion of the list. I’ve changed the motif from the cost perspective (expense, level of difficulty, and duration) to the value perspective (uniqueness, value, importance). The list has always been implicitly a list of things journal publishers do, so this year I’ve made that explicit in the headline. The list now consists of 102 items, up from 96 two years ago.
So if Stage Two disruption is largely based on funder regulations (more open access, increased use of publisher-hostile Creative Commons licenses) falling on a mature market, we should look for survival — and growth — to come in a different direction. In fact, growth always seems to come where you least expect it. The devaluation of content by funding agencies and libraries gives rise to new commercial developments in computational publishing and workflow tools.