The term “direct and explicit instruction” is often used to sell products or to persuade state legislators to make bad decisions. But everybody already uses direct instruction in some form. It's not the 'what' of direct instruction that is in question; it's the 'how' and 'how much' of direct instruction. T

Our big human brains have evolved to become very efficient predicting machines (Hawkins, 2004). They are constantly accessing multiple data sources in order to give us a sense of what will happen next. Most of this is done at levels below our conscious awareness. For example, baseball players are able to run to the right spot to catch balls in the outfield because they can predict where it’s going to come down. Their big human brains instantly process a variety of information related to the sound of the bat hitting the ball as well as the height, speed, and angle of trajectory.

The same prediction process is used in language comprehension and reading (Gavard & Ziegler, 2022; Lupyan & Clark). Here, our prediction machine uses semantic, syntactic, and phonological information to make micro-predictions about words and meaning during the process of reading (Goodman, 1967; Laroche & Decon, 2019). Very much like baseball players catching pop flies, this enables us to efficiently and effectively create meaning with the print before us.

The problem with Orton-Gillingham and similar for-profit products (Lindamood, Wilson Language Training, Barton System, etc.) is that they try to reduce teaching to an algorithm. An algorithm is a formula for solving problems in which you follow a step-by-step set of procedures (with fidelity) to achieve a specific outcome. In other words, by correctly following a prescribed set of steps in the specified order, you will be led to a predefined solution. Algorithms are useful in mathematics and computer science for calculation, data processing, and automatic reasoning. For teaching of any kind? Not so much.

However, Orton-Gillingham would have you believe that if the teaching algorithm is followed explicitly, the teacher can be assured that students will learn to read. And if the algorithm does not work, you run them through the algorithm again … and again … and again. What these algorithmic programs offer is a false sense of certainty. Despite all the certainty thrown about, research to support the long-term effectiveness of these “direct, explicit, multi-sensory, structured, sequential, diagnostic, and prescriptive” instruction, it is simply not evident (Compton, et. al., 2014).

When somebody askes you, “What’s the Science of Reading?” what do you say? Is it a process? Is it a set of strategies? An approach or method? A reading program? A group or organization? In this chapter, I will attempt to define the Science of Reading. And notice that I’m using capital letters. This enables us to differentiate between a science of reading as one of several sciences of reading and the Science of Reading as a proper noun or title,

The Science of Reading seems to refer to a general consensus related to the strategies and practices that lead to improved reading outcomes. These strategies and practices have been determined to be effective using experimental or quasi-experimental research and conducted in authentic learning environments. Also, this research has established a causal link between strategies or practices and student outcomes (reading achievement). Thus, the Science of Reading can be thought of as a process that uses the standards in Figure 16.2 when making decisions related to reading instruction and policy. However, the SoR might best be described today as a self-defined movement that advocates these standards be used for making decisions related to reading policy and instruction.

The really big point is this: It’s the semantic connections that are most important, not orthographic, graphemic, or phonemic connections. When you encounter the words ‘elephant’ you don’t connect with short /e/ words. You don’t activate words containing the /ant/ letter pattern or words with silent ‘ph’ blends. You connect with elephant things, regardless of the letter sounds or patterns.

Just hearing the word ‘elephant’ brought some of the elephant things in your elephant schemata to consciousness. Meaning that, if elephant were followed by the words sock, trunk, swallow, you’d be able to identify the word ‘trunk’ microseconds faster than the other non-related words (Higgins, Rholes, & Jones,1977). This is called priming. Priming looks at how something that comes before primes or impacts what follows. The very word ‘elephant’ primed the pump so that I would be able to identify elephant words quicker and more efficiently. We’ll be looking at some of these research studies below.

1. It’s not a strategy to teach students.

2. It’s not a pedagogical strategy that teachers use.

3. It doesn’t exclude phonics instruction.

4. It doesn’t encourage children to use picture clues to figure out words.

5. It’s not an approach to teaching reading.

6. It’s not a method of “decoding” printed text.

7. It’s not a “staple of early reading instruction”.

8. It’s not whole language

9. It doesn’t exclude explicit and systematic instruction.

In his book, Global Mind Change (1989), Willis Harman describes three views of reality which he calls metaphysical perspectives. Metaphysical here refers to ontology or the question of the origins of the universe and the nature of reality. These perspectives are materialistic monism, dualism, and transcendental monism.

Why do we sometimes believe the unbelievable? Why is it our views are sometimes data-resistant? We like to think that reality determines our beliefs; however, at higher levels of belief systems, our beliefs determine reality. It's just the way of things.