Language & Literacy

reading

This is Part IV in a series digging into two articles from Keith Stanovich that provides useful ways for educators to understand the science in the science of reading.

In Part I, we examined a 2003 article that proposed 5 different “styles” that can influence how science is conducted and perceived.

Since Part II, we’ve been unpacking a long and stellar 2003 piece by Paula and Keith Stanovich, Using Research and Reason in Education: How Teachers Can Use Scientifically Based Research To Make Curricular & Instructional Decisions.”

Today in Part IV, we continue onward deeper into the article to examine the oh-so very science-y aspects of experimental design.

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The “science of reading” has become a loaded term — partly due to how “science” itself is conceived.

In Part I, we examined a 2003 article by Keith Stanovich that proposed 5 different “styles” that can influence how science is conducted and perceived. In that article, we learned that in education there may be a tendency to lean towards “coherence” in narratives or the “uniqueness” of silver bullet fads. These tendencies can subvert science-based reading practice.

In Part II, we will look at yet another stellar 2003 piece by Paula and Keith Stanovich titled, “Using Research and Reason in Education: How Teachers Can Use Scientifically Based Research To Make Curricular & Instructional Decisions.”

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I’ve observed an interesting divide in how people react to and interpret the term “the science of reading” (or “SOR” for short).

For some, the term elicits eager head nodding — it’s even become incorporated into the sales pitch of many a vendor of education products. For others, the term elicits a gut reaction akin to disgust.

There’s a lot wrapped up in how someone may think of “science” at large that then influences their reactions to the term of the “science of reading.” But don’t just take my word for it. Keith and Paula Stanovich penned some really insightful pieces about this in the early 2000s, and outlined how educators can understand and leverage science to inform their own instructional practice.

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There was a relatively recent Hechinger Report article by Jill Barshay, PROOF POINTS: Researchers blast data analysis for teachers to help students that seemed to indict any and all assessments and data use in schools as a royal waste of time. It bothered me because the only source cited explicitly in the article was a 2020 opinion piece by a professor who similarly vaguely discusses “interim assessment” and doesn’t provide explicit citations of her sources.

I tweeted out my annoyance to this effect.

To Ms. Barshay’s great credit, she responded with equanimity and generosity to my tweet with multiple citations.

Since she took that time for me, I wanted to reciprocate by taking the time to review her sources with an open mind, as well as reflect on where I might land after doing so.

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We recently examined Phillip Gough and Michael Hillinger’s 1980 paper, Learning to Read: An Unnatural Act, in which they made a neat analogy of learning to decode an alphabetic writing system to cryptanalysis. As a part of this cryptanalysis, children aren’t simply learning to decode, but more precisely, learning to decipher the written code. This distinction highlights that learning to read in English is not driven by paired-associative learning, but rather by internalizing an algorithm, a statistical, systematic, quasi-regular mapping.

This point is a sharp one because what they were saying is that we can’t teach such a cipher directly. We can’t just hand a kid the codebook.

So when I saw a reference recently to another Gough paper called Reading, spelling, and the orthographic cipher, co-written in 1992 with Connie Juel and Priscilla Griffith, I knew I needed to read this one, too.

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I’ll never forget the moment when I realized that the students in a school I was supporting had not read anything more than a few pages of text for close to two months.

There were a myriad of potential excuses for it. They were ramping up for test prep season, there was a spring break and a snow day, they had cycles of interim assessments that broke into their instructional time, they rotated between reading and writing units during core ELA time, and had been in the middle of a writing cycle, etc.

It took me a while to see it clearly, as I came only once a week, at most, and couldn’t always see the full picture. But then it hit me like a ton of bricks once I did. How could students improve their literacy when they weren’t expected to read for sustained and structured periods of time daily?

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The first thing that happened to reading is writing. For most of our history, humans have been able to speak but not read. Writing is a human creation, the first information technology, as much an invention as the telephone or computer.

—Mark Seidenberg, Language at the Speed of Sight

What is (un)natural about learning to read and write? We began our quest with this question, prompted by two references in a line in a David Share paper.

Like learning to read (English) which Gough famously dubbed “unnatural” [43], see also [3], becoming aware of the constituent phonemes in spoken words does not come “naturally”.

—Share, D. L. (2021). Common Misconceptions about the Phonological Deficit Theory of Dyslexia. Brain Sciences, 11(11), 1510.

This led us to unpack three foundational papers from 1976 to 1992 that have provided us with some surprising twists and turns and even moments, dare I say, of clarity.

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OK, we’re here, at our third paper in our series examining the naturalness, or not, of gaining literacy.

  • Liberman, A. M. (1992). Chapter 9 The Relation of Speech to Reading and Writing. In R. Frost & L. Katz (Eds.), Advances in Psychology (Vol. 94, pp. 167–178). North-Holland. https://doi.org/10.1016/S0166-4115(08)62794-6 Liberman comes strong out the gate with seven claims on why speech* is “more natural” than written language:
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In our last post in a series exploring the question, “What is (un)natural about learning to read and write?,” we looked at a paper from 1980 by Phillip Gough and Michael Hillinger, Learning to Read: An Unnatural Act, that provided a counter to Ken and Yetta Goodman’s argument that learning to read is natural, and provided us with a useful analogy: learning to read an alphabetic writing system is a form of cryptanalysis. Using this analogy, Gough and Hillinger drew out a fine-grained distinction between a code and a cipher that allowed them to make some precise observations about the difficulty of breaking the alphabetic cipher that have held up quite well over the years.

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Learning to Read: An Unnatural Act

In our last post in this series exploring the question, “What is (un)natural about learning to read and write?,” we looked at a paper from 1976 by Ken and Yetta Goodman that argued that written language is a form of oral language and thus, learned naturally in a literate society through exposure and use in the environment.

In this post, we’ll explore a direct counter to that argument made by Phillip Gough and Michael Hillinger in 1980.

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