Here’s why academics should write for the public
There’s been much discussion about the needless complexity of academic writing.
In a widely read article in The Chronicle of Higher Education last year, Steven Pinker, professor of psychology at Harvard and author of several acclaimed books including The Sense of Style, analyzed why academic writing is “turgid, soggy, wooden, bloated, clumsy, obscure, unpleasant to read, and impossible to understand.”
More recently, Jeff Camhi, professor emeritus of biology at the Hebrew University of Jerusalem, discovered how much academic authors struggle when trying to write for a lay audience. He suggested writing programs should “develop a night course in creative nonfiction writing, specifically for professors.”
We think learning to write creative nonfiction isn’t a bad idea. But we disagree with Camhi’s suggestion that academics need a night course for this. We propose something simpler: academics just need to start writing, getting edited and seeing if the public reads them. Through this process, academics will not only learn to express themselves clearly, but most likely become better scientists as well.
What are the benefits?
Although both of us currently write for the public, we come at this from different perspectives – one of us has written for a few years, and the other started writing only this year.
We don’t think we are amazing writers, but we do think writing for the public has helped us improve. The immediate feedback from editors and the public has helped make our writing clearer.
We’ve learned that if we’re not clear and engaging, then editors and the general public simply won’t read us. And that continues to teach us how to improve the next time we write.
Public writing has also improved both our academic writing skills and scientific thinking abilities.
That’s because the first step in improving academic writing is to learn to reduce the jargon academics use and express concepts clearly. And this has forced us to distill our thinking to its absolute core.
Consequently, not only did the process improve the quality of our writing, but it also brought more clarity to the way we were thinking about our scientific problems.
For example, when we recently started to write an academic review article together, we first considered how we could write a piece for the public later based on the review. This helped us reconfigure the way we synthesized the literature, forcing us to discuss it clearly and logically.
Additionally, because public writing engages both the public and our academic colleagues, we’ve found that public commentary can be a form of “public peer review.” Exciting research ideas for academic papers have developed from our public pieces thanks to crowdsourced feedback.
For example, a Psychology Today magazine article written by one of us (Wai) led to feedback from editors and others on the importance of studying highly educated influential people. This resulted in a series of research papers, discussed subsequently in The Washington Post.
Such public engagement can bring in other benefits for an academic career. For instance, one of us (Miller) traveled to Amsterdam last month to give a keynote address at a conference about gender and science.
The conference organizers found him because of the attention he received in popular press about an international study that he had led on gender stereotypes in science. That popular press attention was initiated by the author contacting his university’s press office and working closely with its writers to collaboratively draft a press release.
In both our cases, public engagement opened up opportunities to network with academics and others within and outside our fields. And this happened only because people read the public pieces we had written.
It’s that simple
Writing for the public requires improving one’s skills, just the way it does for writing an academic article or a grant proposal. Yes, there is a “start-up cost” as you learn the ropes. But it isn’t as time-consuming as many academics may think.
In fact, both of us were very cautious when we first started to write for the public. We were even skeptical of its benefits given the perceived time cost. But earlier this year, one of us (Miller) learned how easy this process is.
He learned about a controversial study that he wanted to place in a broader context for the public. So he submitted a 199-word pitch that night to The Conversation, which encourages academics to write for the public. An editor replied the next morning giving advice on how to structure and write the piece for clarity.
The 765-word article took just one day to draft and one day to refine with the editor – lightning fast compared to academic journals. The Atlantic’s Quartz republished the article, which has now reached over 25,000 readers. Consider how most academic articles are read by only a handful of people.
We now believe that public writing is part and parcel of our identities as scholars.
Engage with the public to have social impact
Now that we’ve discussed some of the benefits of public writing and why we think academics should do it, we conclude by addressing one important structural component to the solution.
But what she did not mention is that more scientists are needed in the public square to become clearer and better writers as well. As we said earlier, that clarity can bring other indirect and direct benefits for science and scientists’ careers.
So why aren’t more academics writing for the public?
Well, it’s really quite simple. There’s little incentive built into the reward and promotion system, something Steven Pinker noted as well. Perhaps administrators need to include public engagement on equal footing as teaching, advising, publishing, and grant-getting in the tenure review process.
Many academics, including us, now realize that if we want to reach people who might benefit from our research, we have to step out of the ivory tower. We academics need to enter the discussion that the rest of the world engages in every day.
“Personalized learning” is that one area of research and practice that brings to the forefront many of the debates and issues that the field is engaging with right now. If one wanted to walk people through the field, and wanted to do so through *one* specific topic, that topic would be personalized learning.
Personalized cans? (CC-licensed image from Flickr)
Here’s are some of the questions that personalized learning raises:
- We have a problem with labels and meaning in this field. Heck, we have a problem with what to call ourselves: Learning Technologies or Educational Technology? Or perhaps instructional design? Learning Design? Learning, Design, and Technology? Or is it Learning Science? Reiser asks: What field did you say you were in? The same is true for personalized learning. Audrey Watters and Mike Caulfield ask what does “personalized learning” mean and what is the term’s history? Does it mean different pathways for each learner, one pathway with varied pacing for each learner, or something else?
- The Chan-Zuckerberg initiative and the Bill and Melinda Gates Foundation endorse personalized learning. What is the role of philanthropy in education in general and educational technology in particular? Should educators and researchers “beware of big donors” or should they enthusiastically welcome the support in the current climate of declining public monies?
- Where is the locus of control? Is personalization controlled by the learner? Is the control left to the software? What of shared control? Obsolete views of personalization and adaptive learning focus on how the system can control both the content and the learning process ignoring, for the most part, the learner, even though learner control appears to be an important determinant of success in e-learning (see Singhanayok & Hooper, 1998). The important question in my mind is the following: How do we balance system and learner control? Such shared control should empower students and enable technology to support and enhance the process. Downes distinguishes between personalized learning and personal learning. I think that locus of control is the distinguishing aspect, and that the role of shared control remains an open conceptual and empirical question. Debates about xMOOCx vs cMOOCs fall in here as well as the debate regarding the value of guided vs discovery learning.
- How do big data and learning analytics improve learning and participation? What are the limitations of depending on trace data? Personalized learning often appears to depend on the creation of learner profiles. For example, if you fit a particular profile you might receive a particular worked-out example or semi-completed problem, and problems might vary as one progresses through a pathway. Or, you might get an email from Coursera about “recommended courses” (see my point above regarding definitions and meanings). Either way, the role that large datasets, analytics, and educational data science – as well as the limitations and assumptions of these approaches, as we show in our research – is central to personalization and new approaches to education.
- What assumptions do authors of personalized learning algorithms make? We can’t answer this question unless we look at the algorithms. Such algorithms are rarely transparent. They often come in “black box” form, which means that what we have no insight into the processes of how inputs are transformed to outputs. We don’t know the inner workings of the algorithms that Facebook, Twitter, and Google Scholar use, and we likely won’t know how the algorithms that EdTechCompany uses work to deliver particular content to particular groups of students. If independent researchers can’t evaluate the inner workings of personalized learning software, how can we be sure that such algorithms so what they are supposed to do without being prejudicial? Perhaps the authors of education technology algorithms need a code of conduct, and a course on social justice?
- Knewton touts its personalization engine. Does it actually work? Connecting this to broader conversations in the field: What evidence do we have about the claims made by the EdTech industry? Is there empirical evidence to support these claims? See for example, this analysis by Phil Hill on the relationship between LMS use and retention/performance and this paper by Royce Kimmons on the impact of LMS adoption on outcomes. If you’ve been in the position of making a technology purchasing in K-12/HigherEd, you have likely experienced the unending claims regarding the positive impact of technology on outcomes and retention.
- And speaking of data and outcomes, what of student privacy in this context? How long should software companies keep student data? Who has access to the data? Should the data follow students from one system (e.g., K-12) to another (e.g., Higher Ed)? Is there uniformity in place (e.g., consistent learner profiles) for this to happen? How does local legislation relate to educational technology companies’ use of student data? For example, see this analysis by BCCampus describing how British Columbia’s Freedom of Information and Protection of Privacy Act (FIPPA) impacts the use of US-based cloud services. The more one looks into personalization and its dependence on student data, the more one has to explore questions pertaining to privacy, surveillance and ethics.
- Finally, what is the role of openness is personalized learning? Advocates for open frequently argue that openness and open practices enable democratization, transparency, and empowerment. For instance, open textbooks allow instructors to revise them. But, what happens when the product that publishing companies sell isn’t content? What happens, when the product is personalized learning software that uses OER? Are the goals of the open movement met when publishers use OER bundles with personalized learning software that restricts the freedoms associated with OER? What becomes of the open agenda to empower instructors, students, and institutions?
There’s lots to contemplate here, but the point is this: Personalized learning is ground zero for the field and its debates.
The New York Times published an article on an edX course (Introduction to Mao Zedong Thought) offered by Tsinghua University. Inside Higher Ed (IHE) wrote about it, too. The following quote from IHE articles summarizes the articles:
“That course is raising eyebrows because, despite hours of video lectures and supplemental material in the course, students would still have to tab over to Wikipedia to learn about the millions who died as a result of Mao’s land reforms or that his economic initiatives led to what may have been the greatest famine in human history, which killed tens of millions. Introduction to Mao Zedong Thought references those events glancingly in passing as “mistakes,” and generally heaps praise on Mao and his philosophies.”
I was asked to provide commentary for the New York Times article, and since it wasn’t included in the writeup, I thought it would be a good idea to share it publicly rather than leave it hidden away in my email inbox. Here is what I said:
Open courses are transparent, and that’s one of their positive aspects. They allow anyone to examine the ways that course creators think about a topic. The instructional materials from the Mao course are available to anyone to examine and study. One can look at the materials and ask: How do these materials position Mao Zedong? What are the elements of Mao’s thought that the creators of this course want to highlight? What elements of Mao’s thoughts are left behind and what are the elements that are being highlighted? What is the story that is being told here, and who stands to benefit from this story?
Stephen Downes made a similar argument in the IHE article: ““courses that might have been offered behind closed doors are offered for everyone to see.”
Now, that’s parsimonious :)
The Chronicle of Higher Education published a commentary some time ago that argued that professors are “naive users of social media” and must exercise caution. It’s difficult to argue with the recommendation to exercise caution, when one looks at the list of scholars who found themselves in trouble in the last year: Salaita, Goldrick-Rab, Grundy, and so on.
But, the claim that professors are naive users of social media is unsubstantiated and reveals a limited understanding of the literature on how professors actually use social media and what they think about them. My colleagues and I have been conducting research on networked scholarship and scholars’ use of social media since 2009, and since that time, I can’t recall interviewing a faculty member or reading a study that revealed naiveté regarding social media and the challenges/tensions they introduce. If anything, most academics have an astute understanding of how social media intersect with their professional (and personal) lives and make informed (and tactical) decisions regarding their use of these technologies.
Granted, many find themselves in conundrums as a result of being in collapsed contexts and being exposed to unanticipated audiences, but to argue naiveté is misinformed.