Explicit Instruction: Opportunities to Respond

Posts in this series…

  1. What is Explicit Instruction?
  2. Explicit Instruction: Segmenting Complex Skills
  3. Explicit Instruction: Teacher Talk and Equity
  4. Explicit Instruction: Modeling
  5. Explicit Instruction: Concreteness Fading

At this point, we have already looked at each individual component of explicit instruction, what remains is effectively putting each component together. As we segment complex skills, we should provide instructional breaks where we “stop teaching” and have our students apply what they are learning. When we do this, we are providing them with opportunities to respond (OTR), a key part of learning. 

  1. Teacher Directed OTR (TD-OTR) improves academic performance (Blood, 2010; Haydon & Hunter, 2011)
  2. Increased TD-OTR increases academic engagement and decreases disruptive behavior (MacSuga-Gage & Gage, 2015)
  3. TD-OTR improves behavioral outcomes for students with emotional and behavioral disorder (Lewis et al., 2004)
  4. TD-OTR improves academic and behavioral outcomes for students with EBD, in addition it also results in increased efficacy in the use of class time (Sutherland & Wehby, 2001)
  5. Ensuring high success for students with academic deficits and behavioral issues requires implementing flexible, universal interventions that address varied student abilities. They must be easily implemented within any instructional content area (Sprick, & Borgmeier, 2010)

In one sense, this is a case where the research backs up common sense. Of course students need to respond to the material and use it to learn. But, if it truly were so simple, then one would expect our students to be learning more. One glance at test scores shows us that there is a significant disconnect between research and practice.

Ideal Rates and the Problem

The disconnect is that while OTR, and especially TD-OTR work, they need to be used more often and in a more structured way than we tend to be comfortable with. Researchers estimate that the ideal OTR rate is roughly 3-3.5 per minute for general education students (Stitcher et. al, 2006; Stitcher et al., 2009). For students with high incidence disabilities, the ideal rate is even higher, somewhere between 4-6 OTR per minute (Council for Exceptional Children, 1987). But unfortunately, these children only receive about one OTR every twenty minutes, or about two opportunities per class (Hirn & Scott, 2012; Van Acker, Grant, & Henry, 1996).

The problem is that while all teachers provide their students with some form of OTR, we tend to only give students an OTR when the opportunity arises naturally. What we ought to do is build TD-OTR into our lesson plans to reinforce key concepts and give students chances to apply what they are learning. 

Using Teacher Directed Opportunities to Respond

It can be helpful to think like a coach. A baseball coach who says, “Keep your eyes on the ball.” or “Swing!” will only be of limited help. A good coach anticipates problems and breaks down the mechanics by explicitly explaining and modeling each part of the swing and having the child apply it in actionable segments. As the child gains proficiency in his or her swing, the coach puts more segments together until the child is ready to hit a pitch in a game.

***Notice, this follows the key pillars of explicit instruction outlined by Charles Archer.  Pillars of explicit instruction

A good teacher will do likewise. Don’t just ask a question once you finish your explanation. Use what you already know about your students and ask questions as you go. Don’t just call on volunteers. Then you will only be requiring students who raise their hands to engage and think deeply. Use alternative strategies to engage more students. Think-Pair-Share, choral response, and no-stakes quizzes are great tools for teachers to have at the ready.

 

Simple and Flexible 

One reason TD-OTR works is that it is flexible. This allows it to be effectively used with students of differing abilities, across grades and subjects (Sprick, & Borgmeier, 2010). TD-OTR is flexible because it is simple. The teacher asks students to respond, and then the teacher gives feedback (Ferkis et al., 1997). Pretty simple.

However, the fact that the method is simple doesn’t make implementation simple. TD-OTR must be structured. In order to develop structure, teachers should explicitly define the routines and expectations, provide feedback on expectations and performance, actively supervise students, and provide a high rate of OTRs (Simonsen et al., 2008). Essentially, explicit instruction is helpful not just for teaching our content, explicit instruction is also helpful for teaching our students class routines and expectations.  

The Two OTRs

There are two typical ways teachers use OTR. The first is to elicit an individual response. This happens when a teacher cold calls or asks students to raise their hands and calls on a volunteer. As one student answers, the rest of the class is ideally listening and still thinking. But this is the weak point of individual responses. How do you ensure that all students are thinking about your lesson if you only see what one student is thinking?

The other type of OTR is a unison response, where the teacher requires a group of students, or the entire class to respond.

Verbal Examples: Choral response, Think-Pair-Share

Non-Verbal Examples: gesture responses, written responses, response cards

The key to making this effective is structure and expectations. The students must know how to respond. For choral response, give students clear cues for when to start speaking. I prefer to use a hand gesture coupled with slightly raising the pitch of my voice. When using Think-Pair-Share (TPS), be sure to model it for your students first and let them practice using it and then give your students feedback on how to use the method of TPS better. This is particularly important because you do not want the share portion of TPS to devolve into chatting. One type of unison written response that works particularly well is no-stakes quizzing. (See my article for CogSciSci on how to use the above methods effectively).  

Your OTR

I find that the largest obstacle to effectively using TD-OTRs is myself. Thinking of good questions takes time. Thinking about how to frame the question (individual or unison, written or verbal) takes time. Learning how to teach your students to use the method effectively takes time. Then, it takes a bit more time still for your students to get used to TD-OTR. But it is worth it. See the list of 5 items at the start of this article if you are unsure.

I am getting a new curriculum next fall, so I have an ideal time to rethink how I should go about my teaching. My basic plan involves coming up with a list of concept questions with different scenarios.

Ex: Many questions about animal adaptations in a desert, rainforest, tundra, etc

Then I will use a smattering of different TD-OTR strategies and have students answer the questions and apply their learning.

How will you intentionally use TD-OTR?

 

Sources:

Blood, E. (2010). Effects of student response systems on participation and learning of students with emotional and behavioral disorders. Behavioral Disorders, 35, 214–228.

Council for Exceptional Children (CEC) (1987). Academy for effective instruction:

Working with mildly handicapped students. Reston, VA.

Haydon, T., & Hunter, W. (2011). The effects of two types of teacher questioning on teacher behavior and student performance: A case study. Education & Treatment of Children, 34(2), 229–245. https://doi.org/10.1353/etc.2011.0010

Ferkis, M. A., Belfiore, P. J., & Skinner, C. H. (1997). The effects of response repetitions on sight word acquisition for students with mild disabilities. Journal of Behavioral Education, 7, 307–324.

Hirn, R., & Scott, T. M. (2012). Academic and behavior response to intervention project. Louisville, KY: University of Louisville.

Lewis, T. J., Hudson, S., Richter, M., & Johnson, N. (2004). Scientifically supported practices in emotional and behavioral disorders: A proposed approach and brief review of current practices. Behavioral Disorders, 29, 247–259.

MacSuga-Gage, A. S., & Gage, N. A. (2015). Student-level effects of increased teacher-directed opportunities to respond. Journal of Behavioral Education, 24(3), 273–288. https://doi.org/10.1007/s10864-015-9223-2

Simonsen, Brandi & Fairbanks, Sarah & Briesch, Amy & Myers, Diane & Sugai, George. (2008). Evidence-based Practices in Classroom Management: Considerations for Research to Practice. Education and Treatment of Children. 31. 351-380. 10.1353/etc.0.0007. 

Sprick, R., & Borgmeier, C. (2010). Behavior prevention and management in three tiers in secondary schools. In M. R. Shinn & H. M. Walker (Eds.), Interventions for achievement and behavior problems in a three-tier model including RTI (pp. 435–468).

Stichter, J. P., Lewis, T. J., Richter, M., Johnson, N. W., & Bradley, L. (2006). Assessing antecedent variables: The effects of instructional variables on student outcomes through in-service and peer coaching professional development models. Education and Treatment of Children, 29, 665–692

Stichter, J. P., Lewis, T. J., Whittaker, T. A., Richter, M., Johnson, N. W., & Trussell, R. P. (2009). Assessing teacher use of opportunities to respond and effective classroom management strategies: Comparisons among high- and low-risk elementary schools. Journal of Positive Behavior Interventions, 11, 68–81.

Sutherland, Kevin & Wehby, J.. (2001). The Effect of Self-Evaluation on Teaching Behavior in Classrooms for Students with Emotional and Behavioral Disorders. Journal of Special Education – J SPEC EDUC. 35. 161-171. 10.1177/002246690103500306. 

Van Acker, R., Grant, S. H., & Henry, D. (1996). Teacher and student behavior as a function of risk for aggression. Education and Treatment of Children, 19(3), 316–334.

Explicit Instruction: Concreteness Fading

Posts in this series…
1. What is Explicit Instruction?
2. Explicit Instruction: Segmenting Complex Skills
3. Explicit Instruction: Teacher Talk and Equity
4. Explicit Instruction: Modeling

Concreteness fading is exactly what the name suggests. You start with a concrete example, and once your students have grasped it, you fade it out for a more abstract representation. The purpose behind this strategy is that abstract representations are more generalizable than concrete ones.

When teaching a concept you should use an example with strategically extraneous details. It sounds strange, but it’s true. Concrete examples help students with initial learning because they have extraneous details (Glenberg et al., 2004). These details help “ground” the concept in the familiar, allowing students to grasp the example. 

However, the extraneous details making up a concrete example hinder generalization and transfer (Petersen & McNeil, 2013). Hence the need to fade from concrete representations to abstract ones.

Useful Definitions

We do run into a bit of an academic language problem when talking about concreteness fading. Technically, abstract representations do not exist because, whenever you describe something, or write, or draw it, parts of that idea become concrete.

In their 2018 paper, Fyfe and Nathan propose a simple linguistic work around. Instead of referring to examples as concrete (specific and non transferrable) or abstract (general and transferrable) we instead identify them as less idealized (concrete) or more idealized (abstract). 

Concrete Examples (Less Idealized)

Not all concrete examples are created equal. Concrete examples that are less idealized add seductive details that make it more difficult than necessary in order to learn and generalize the example (Sundararajan & Adesope, 2020). So when we are crafting our concrete examples, we should be careful with the type of extraneous information we include, that extra information might not help initial learning.

We ought to include the extraneous information that improves initial learning (It isn’t really extraneous then, is it?). There are two types of information to be wary of: perceptual and conceptual.

Perceptual information pertains to the physical properties of the example. This could include 2D or 3D representations, visual surface features such as patterns and how real an object looks. Researchers have found that 3-Dimensional representations are generally more effective than 2-Dimensional objects, at least in math (Carbonneau, Marley, & Selig, 2013). In addition, representations that are particularly rich in visual surface features have been found to inhibit learning compared with less perceptually rich objects (Kaminski, Sloutsky, & Heckler, 2013).

The solution to this isn’t to only use 3-D or less perceptually rich representations. It is simply to be smart about it. 

What are you teaching? What is the main idea of the concept? Does the picture/diagram allow students to make incorrect inferences? How much explanation will students need to understand your concrete example? Is the “extraneous” information in this representation directly relevant to the concept?

Conceptual information is trickier, because it is learner dependent. Conceptual information depends on the background knowledge your students bring to the table. If your students are very familiar with an object, it is often difficult for them to think about that object abstractly (Petersen & McNeil, 2013).

Abstract Examples (More Idealized)

A good abstract, or idealized representation allows students to make the intended generalization with the least effort. Essentially, in a more idealized representation, your students will be more likely to successfully transfer their learning to a new context. We should also expect for students who are more novice to struggle with transferring their learning, even if they are able to think about the underlying ideas of the representation (Koedinger & Nathan, 2004).

The purpose of an idealized representation is to encourage generalization and transfer. Idealized representations achieve this by moving the focus from the what representation is to what the representation does. Idealized representations are able to do this because they lack the extraneous details of less idealized representations.

old lady or hag

The extraneous details of a less idealized representation help to ground the example in the familiar and the relatable, thus, providing a fertile context for initial learning (Glenberg et al., 2004; Schliemann & Carraher, 2002). And it is this same grounding that reduces transfer of learning. Think about an optical illusion. If you see the young lady first, it can be hard to then see the old hag, and vice versa. When we use more abstract, more idealized representations, we make it easier for students to generalize and transfer their learning.

Three Concrete Goals

According to Fyfe and Nathan (2002) three goals of concreteness fading are to

  1. Promote initial learning with a meaningful, less idealized representation of the concept. (grounded context)
  2. Promote transfer of learning by ending a learning sequence with a generic, broadly applicable idealized representation.
  3. Draw connections between less idealized (concrete) and more idealized (abstract) representations to create a well developed schema.

Concreteness Fading (Less to More Ideal)

Concreteness fading aims to take advantage of both concrete and abstract representations. The extraneous details of a less idealized example help the student to learn the concept, but these same details prevent students from transferring that concept, it is inert, inflexible knowledge (Schliemann & Carraher, 2002). However, if after initial learning you begin to use more idealized examples by reducing the extraneous details, your students will be more able to generalize and transfer the concept, making their knowledge applicable and flexible (Kaminski, Sloutsky, & Heckler, 2008).

As we fade from the less ideal to the more ideal, we don’t simply want to focus on the idealized examples. Concreteness fading is not a checklist procedure to follow, the initial concrete examples are still true, they are still valuable. 

The concrete examples help provide a continued grounding for the abstract ones, so we should ensure our students know not only the concrete and abstract representations of the concept, but we should also ensure they understand the connections between concrete and abstract representations by making the connections explicit. 

Fyfe and Natan encourage teachers to use a 3-step progression starting with a grounded, less idealized representation before fading into an abstract, idealized one. In order to do this successfully, teachers must reduce the perceptual and conceptual information their examples contain. 

The classic example of this 3-step model is in math. You start with a 3-D manipulative and go to an image on the paper and you finally conclude with just numbers. concreteness fading

This 3-step strategy can be applied in many other classes and age groups as well. In science, you could start teaching about a food chain by showing a video of a gazelle grazing in the savanna being silently stalked by a cheetah. Next, you could show the classic image of a food chain and then, finally, have your students generalize the pattern of food chains to any environment (producers to primary consumers to secondary consumers, etc).
1. Springbok Antelopes vs Cheetahs (Antelopes are a type of gazelle)
2. gazelle food chain
3. Producer –> Primary Consumer –> Secondary Consumer

*Note: You should use the correct vocabulary throughout your examples, whether they are concrete or abstract. Ex: The bush is a producer, the gazelle is a primary consumer, the cheetah is a secondary consumer.

This will give your students more exposure to the vocabulary in context, which will also make transferring their knowledge easier.

Concreteness Fading, Research, and Teachers

Concreteness fading is not an end all be all for education, it alone is not a silver bullet. But, if we want all of our students to know our subjects deeply, it is vitally important. The methods proposed by Fyfe and Nathan will also give our students exposure to multiple models of a concept, this likely increases the flexibility of their learning (Jacobson et al., 2020).

By teaching with methods aligning to research, we make the curriculum more accessible for all students. When we deviate from research and go with mere instinct, we increase the likelihood of creating an inequitable learning environment. Research alone is not some paneca of perfection, but without it, what are you going on beyond experience?

We should understand the broad principles of research and apply them to our context with nuance.

Sources

  • Carbonneau, Kira, Scott Marley, and James Selig. 2013. “A Meta-Analysis of the Efficacy of Teaching Mathematics with Concrete Manipulatives.” Journal of Educational Psychology 105 (2): 380–400. doi:10.1037/a0031084.
  • Fyfe, E. R., & Nathan, M. J. (2018). Making “concreteness fading” more concrete as a theory of instruction for promoting transfer. Educational Review, 71(4), 403–422. doi: 10.1080/00131911.2018.1424116
  • Glenberg, Arthur, Tiana Gutierrez, Joel Levin, Sandra Japuntich, and Michael Kaschak. 2004. “Activity and Imagined Activity Can Enhance Young Children’s Reading Comprehension.” Journal of Educational Psychology 96 (3): 424–436. doi:10.1037/0022-0663.96.3.424.
  • Jacobson, M. J., Goldwater, M., Markauskaite, L., Lai, P. K., Kapur, M., Roberts, G., & Hilton, C. (2020). Schema abstraction with productive failure and analogical comparison: Learning designs for far across domain transfer. Learning and Instruction,65, 101222. doi:10.1016/j.learninstruc.2019.101222
  • Kaminski, Jennifer, Vladimir Sloutsky, and Andrew Heckler. 2013. “The Cost of Concreteness: The Effect of Nonessential Information on Analogical Transfer.” Journal of Experimental Psychology: Applied 19:14–29. doi:10.1037/a0031931.
  • Koedinger, Kenneth, and Mitchell Nathan. 2004. “The Real Story behind Story Problems: Effects of Representations on Quantitative Reasoning.” Journal of the Learning Sciences 13 (2): 129–164.
  • Petersen, Lori, and Nicole McNeil. 2013. “Effects of Perceptually Rich Manipulatives on Preschoolers’ Counting Performance: Established Knowledge Counts.” Child Development 84: 1020–1033. doi:10.1111/cdev.12028.
  • Schliemann, Analucia, and David Carraher. 2002. “The Evolution of Mathematical Reasoning: Everyday versus Idealized Understandings.” Developmental Review 22 (2): 242–266.
  • Sundararajan, N., Adesope, O. Keep it Coherent: A Meta-Analysis of the Seductive Details Effect. Educ Psychol Rev (2020). https://doi.org/10.1007/s10648-020-09522-4

Explicit Instruction: Modeling

In a systematic review of the literature, Hughes, Morris, Therrien, and Benson (2017) reviewed 86 studies and determined that explicit instruction has 5 Pillars. The first pillar is segmenting complex skills. The second pillar is large, so I divided it up into two posts, think-alouds (teacher talk) and modeling.

In order for modeling to be effective, a teacher must have their teacher-talk down pat. As we are communicating our model, our language must be concise, clear, and strategically repetitive. Being concise is essential because our students are novices and do not have a well-developed schema. Being concise saves their working memory for the content of our course and the repetition helps ensure the content is integrated into their schema. However, concise-ity alone is not all we need. 

We must pair our conciseness with clarity. To speak clearly you ought to plan ahead, avoid ambiguity, and use proper grammar. In addition, be careful with figurative language. If you must use it, and it’s quite likely that you must, explicitly explain the figurative phrases to your students. 

Modeling

Modeling is one of the most efficient ways to learn new skills or knowledge (Bandura, 1986). At its most basic, modeling helps students learn skills, procedures, or behaviors through observation rather than through direct experience (Salisu & Ransom, 2014).

Modeling is important because it increases access to the curriculum. When we leave modeling out of our instruction, less students will be able to acquire and apply complex comprehension strategies (Fielding & Pearson, 1994).

When to Model

Modeling has been found to be particularly useful for well-structured tasks. These are tasks that can easily be broken down into component steps. Math is the most obvious example, you have a standard algorithm to follow that can be broken down into smaller sub-steps.

Less-structured tasks are tasks that cannot be easily broken down into sub-steps. As a result, these tasks are seen as higher-leveled. Modeling with less structured tasks is likely to be more difficult and less effective because, in order to succeed, students will need to pull knowledge and skills from a variety of areas. 

How to Model

Before you start modeling a concept or skill, bring your students’ background knowledge to mind. This can be done through review, sharing an image or video, etc. I am partial to using a combination of choral response and think-pair-share as a way to bring background knowledge to mind. By having students think about what they already know, you are making it easier for them to integrate the new knowledge into their existing schema and allowing students to move forward with the least amount of confusion.

When we are modeling a concept or skill for our students, we should make it as short and simple as possible. Only include what is important, don’t go down the rabbit hole. Interesting asides can wait. In addition, check for understanding throughout the modeling process. Even if you have your teacher talk down pat and have a well planned model, don’t assume that you can just run through the model once and have your students understand. Even with the most precise, perfect model, you still need to break it down into small steps and check for understanding.

Steps to Modeling

  1. Bring background knowledge to mind
  2. Make each step of your modeling short and simple
  3. Check for understanding between the steps
  4. Give students guided practice with feedback

Modeling Behavior

Disposition Modeling: When done well, this helps convey personal values and thought processes. By modeling a disposition, we are often able to make abstract rules and expectations more concrete.

To model dispositions we can simply explain and act out what we feel or think when a student is misbehaving. It is very important to note that this is not done with a condescending tone. It is done to help students understand the expectations, not to shame or let off some frustrated steam.

Educational Modeling

As far as education goes, there are many different types of modeling.

Meta-Cognitive Modeling: This is the classic think-aloud. Teachers talk through their own thought process and intentionally make the implicit steps explicit. This is particularly useful for teaching students how to interpret information, analyze concepts, and draw conclusions.

Modeling as Scaffolding: This takes into account where individual students are in the learning process. This type of modeling is the most difficult, because different students have different levels of knowledge and differing knowledge gaps. So, in order to model as scaffolding, a teacher must not only know the curriculum inside and out, he or she must also know their students.

In order to scaffold effectively, it is useful to think about where you expect students to struggle. Ask yourself, “What makes this concept difficult? Will my students lack the necessary background knowledge?” 

This planning helps in at least four ways.
1. If your students lack the necessary background knowledge, give it to children so that they have a chance to understand the model and concept you are trying to teach.
2.  It reduces your stress levels. If you have additional explanations and models at the ready, you will not be racking your brain for an example to give a student in the middle of class.
3. By preplanning additional models or supplementary explanations, you will likely help your struggling students understand the materials better.
4. You may even find that all your students benefit from the additional models and explanations. When this is the case, everyone’s’ life is easier (teacher & students) because more students understand from your teaching (whole class scaffolding) and less students need customized help, improving class flow and learning.

Task and Performance Modeling: In this, the teacher demonstrates a task to students before they do it on their own. This is the type of modeling that teachers most often used in a preplanned manner.

For complex processes like the scientific method or writing, it will likely be best to break down your modeling rather significantly by teaching one step per lesson. 

For example, I have tried to teach students how to form a hypothesis in one day, and the results have never really been pretty. The reason for this is that making a hypothesis involves many sub-steps including: observations, inferences, background knowledge, and asking scientific questions. Each of these sub-steps is relatively complicated by itself, let alone when you combine them! When students new to the scientific method try to apply all those steps at once, they experience cognitive overload. And, even if they follow the steps correctly, they are unlikely to remember how to use the scientific method the next day.

When dealing with complex material, students need to be exposed to one idea at a time. They do not yet have a developed schema with which to hold all this information. We need to remember this, and to build their schemas over time, they need to know and understand each sub-step. And, as we teach, we build on the previously learned material.

So, after learning from my own teaching failures, I have changed how I teach complex skills. Now, when I teach the scientific method to 5th or 6th grade students, I will generally start by teaching observations and inferences. We spend nearly a full lesson on this. After my students understand both observations and inferences, I will then teach them how to transfer that knowledge into a hypothesis.

In strategically breaking down my model of the scientific method into multiple days by focusing on one sub-step at a time, I have initially made the choice to cover less content. I have found that this approach pays dividends quickly and repeatedly. Now, my students better understand the complex process that is the scientific method. In addition, their better understanding allows for us to move through the content more quickly, which also gives us more time to go deeper.

Sometimes less leads to more.

Other blogposts in this series.

  1. What is Explicit Instruction?
  2. Explicit Instruction: Segmenting Complex Skills
  3. Explicit Instruction: Teacher Talk and Equity
  4. Explicit Instruction: Modeling
  5. Explicit Instruction: Concreteness Fading

Sources

Bandura A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.

Fialding, L. G., & Pearson, P. D. (1994). Synthesis of research reading comprehension: What works. Educational leadership, 51, 62-62.

Hughes, C. A., Morris, J. R., Therrien, W. J., & Benson, S. K. (2017). Explicit Instruction: Historical and Contemporary Contexts. Learning Disabilities Research & Practice, 32(3), 140–148. doi: 10.1111/ldrp.12142

Rosenshine, B., Meister, C., & Chapman, S. (1996). Teaching Students to Generate Questions: A Review of the Intervention Studies. Review of Educational Research, 66(2), 181-221. Retrieved February 19, 2020, from http://www.jstor.org/stable/1170607

Salisu, A., & Ransom, E. N. (2014). The Role of Modeling towards Impacting Quality Education. International Letters of Social and Humanistic Sciences, 32, 54–61. doi: 10.18052/www.scipress.com/ilshs.32.54

Explicit Instruction: Teacher Talk and Equity

Posts in this series…
1. What is Explicit Instruction?
2. Explicit Instruction: Segmenting Complex Skills
3. Explicit Instruction: Teacher Talk and Equity
4. Explicit Instruction: Modeling
5. Explicit Instruction: Concreteness Fading
6. Explicit Instruction: Opportunities to Respond

Hughes, Morris, Therrien, and Benson describe Modeling and Think Alouds as a core component of explicit instruction. In a subset to this component, they include “clear and precise language” (2017).

As teacher talk is seen as important no matter where you fall on the education traditional-progressive divide (though neither side remotely agrees on the type/amount of talk) it is depressing that empirical evidence supporting precise guidelines for teacher talk is generally lacking (Hollo & Wehby, 2017).

However, while guidelines are lacking, research into teacher talk is not. We know that teachers talk more than students (Sinclair & Coulthard, 1975). If we do not talk enough, we fail to communicate the content. Conversely, if we talk too much, we will overwhelm our students’ working memory (Grunewald & Pollack, 1990). Either way, our students fail to learn. Getting teacher talk right is important.

Lack of Clarity is Problematic

Lack of clarity is another problem that increases instructional casualties. This happens when teachers use poorly organized speech, characterized by vague terminology and hemming and hawing (Brophy, 1988, p. 245). Lack of clarity hurts all students, but it doesn’t do so equally. Unclear teacher talk hits struggling students with low language proficiency particularly hard (Ernst-Slavit & Mason, 2011), decreasing educational equity. 

The first step towards changing this is to know what types of speech make learning more difficult for students. However, changing teacher speech patterns is notoriously difficult (Dickinson, 2011). So we shouldn’t expect our habits or others’ habits to change just because we now know better. But we can and should expect consistent effort.

Sloppy Language

Sloppy language includes ambiguity, mazes, and errors. In their 2017 article, Hollo and Wehby described ambiguity as 

“words or phrases that indicate the speaker lacks confidence or knowledge, as demonstrated by equivocating, approximating, hedging, or bluffing (pretty much, maybe, probably, I guess; Hiller et al., 1969); decreased specificity of content or context (the thing, some kind of, all that; Smith, 1980); ambiguous referents (e.g., a pronoun without its noun referent; Chilcoat, 1987; Masterson et al., 2006); or hesitations that indicate the speaker’s lack of confidence (Bugental et al., 1999). Ambiguity also includes cloze statements in which the teacher asks an open-ended or fill-in-the-blank type of question, expecting a specific answer when in fact a range of responses would be logical (squirrels do what?).” 

Verbal mazes can occur in simple sentences with concrete and familiar vocabulary when the delivery lacks smoothness and/or is disfluent. Disfluency includes silent pauses, word and non-word fillers (like, uh, um), repetitions of words (But, but what I meant was), and repetitions of phrases (What I want, what I want you to do next is) (ASHA, 2020). 

Both ambiguous and disfluent (maze) teacher talk decrease student attention and increase student errors (Bugental et al., 1999)

Teachers can also flat out error. We can use incorrect grammar such as subject-verb agreement, improper tenses, and misplaced clauses. Commonsensically, it has been found that elementary student performance is better when they are taught with proper grammar have increased performance when they are taught with proper grammar (Forney & Smith, 1979).

Neat Language

I think it is probably easiest to fix ambiguous language and mazes. The path to fixing both is good planning. Ask yourself, “How should I explain this concept?” How should I model this skill?” Then jot down some notes and see what you can cut out, see what you should re-word. When you have made your explanation or model as simple and straightforward as possible without making it simplistic, you have arrived.

I am of the opinion that fixing errors is the most difficult because I this is the most ingrained speech pattern. You have been speaking and writing since you were a small child, getting rid of habitual errors will take a lot of intentional effort to undo. For this, I’d recommend humbling yourself and picking up a grammar workbook.

Clear Figurative Language?

Figurative language is one area where clarity is lacking by definition. Figurative language is simply words or phrases that have nonliteral meanings and are quite common in daily speech (ex: Metaphors, Similes, and phrases like “America is a melting pot.” “Time is money.” etc). Use of figurative language reduces the comprehension of students with specific language impairment (Nippold, 1991) and emotional behavioral disturbance (Mack & Warr-Leeper, 1992). In addition, figurative language also reduces the comprehension of English language learners (Palmer, Shackelford, Miller, & Leclere, 2006).

One reason comprehension of figurative language is reduced for the above populations is that many of these students have limited vocabularies with a narrow range of representations (Beck & McKeown, 2007). Essentially, when we use idioms, irony, wordplay, or colloquialisms, the information just goes over many students’ heads. And that’s problematic, just ask Drax.

drax

We must be careful with our use of figurative language. If we do not think it through, many students will struggle to access our teaching. The solution isn’t to avoid all forms figurative language like they have the plague. Imagine an English class that avoids metaphors and similes, or a science or social studies class that avoids abstract concepts. Describing that approach as being crazy as a loon and dumb as a doorknob barely scratches the surface of it. Such approaches obviously don’t support language development (Dickinson, 2011).

Increase Clarity, Increase Learning

Instead, we should make things clear. We should be explicit. We can explicitly teach students about figurative language whether we teach English or not. We should recognize when we use phrases that cause confusion and use it as an extra teachable moment. “When I say _________, what it means is________.” Basically, this is a student friendly definition for a phrase.

In addition to being explicit about our course content and about the language we use, we can restate key information in multiple linguistic forms. This strategic redundancy improves comprehension for general education students (Brophy, 1988; Crossan & Olson, 1969). And it increases equity because special education students (Lapadat, 2002), and ELLs (Park, 2002) also benefit from being exposed to the same content in different forms. 

This does increase teacher talk, but it needn’t reduce student talk. The solution is to take shorter “turns.” Nobody likes a monologue and besides, they are hard to follow, “The longer the speaking turn, the denser the informational chunk, and the greater the oral literacy demand” (Roter, Erby, Larson, & Ellington, 2007, p. 1445). Free up your students’ working memory and talk in short chunks.

The second part of taking a shorter speaking turn involves allowing students to talk. I believe the form this takes is generally of secondary importance, while the way you model, structure, and enforce behavior when it is the students’ turn to talk is of paramount importance (Modeling will be the subject of my next post in this series). 

Your students must know exactly what to do and how to do it. The effectiveness of student talk depends on how you model it and provide structure. I have found success with Choral Response and Think-Pair-Share as described in my article for CogSciSci.

An added benefit of this approach is that you will be giving students additional chances to respond, which has been shown to increase student performance (Haydon, Macsuga-Gage, Simonsen, & Hawkins, 2012) while also decreasing problem behavior in children with emotional behavioral distance (Sutherland & Wehby, 2001). 

This approach is effective because each question forces students to engage in retrieval practice, a learning strategy that has been proven to work with a wide array of students and subjects (Dunlovsky, 2013), increasing equity.

Increase Equity with Slow Teaching

Another effective practice for increasing equity is to simply slow down. Children with specific language impairments have been shown to have increased comprehension when the teacher speaks at a rate of 4.4 syllables per second or less. This slowed rate did not affect comprehension in children with typically developing language abilities (Montgomery, 2004). 

Increasing your wait time has been found to result in both increased quality and quantity of student responses (Tobin, 1986). By waiting just a little bit longer than normal, you allow for more students to think through your question.

Sources

American Speech-Language-Hearing Association. (n.d.). Childhood Fluency Disorders. Retrieved from https://www.asha.org/PRPSpecificTopic.aspx?folderid=8589935336§ion

Beck, I. L., & McKeown, M. G. (2007). Increasing young low-income children’s oral vocabulary

repertoires through rich and focused instruction. Elementary School Journal, 107(3), 251–271.

doi:10.1086/511706

Brophy, J. (1988). Research linking teacher behavior to student achievement: Potential implications for instruction of Chapter 1 students. Educational Psychologist, 23(3), 235–286. doi:10.1207/s15326985ep2303_3

Bugental, D. B., Lyon, J. E., Lin, E. K., McGrath, E. P., & Bimbela, A. (1999). Children “tune out” in response to the ambiguous communication style of powerless adults. Child Development, 70(1), 214–230. doi:10.1111/1467-8624.00016

Crossan, D., & Olson, D. R. (1969). Encoding ability in teacher-student communication games. Retrieved from ERIC database. (ED028981)

Dickinson, D. K. (2011). Teachers’ language practices and academic outcomes of preschool children. Science, 333, 964–967. doi:10.1126/science.1204526

Dunlosky, J. (2013). Strengthening the student toolbox: Study strategies to boost learning. American Educator, 37(3), 12-21 [PDF]

Ernst-Slavit, G., & Mason, M. R. (2011). “Words that hold us up”: Teacher talk and academic language in five upper elementary classrooms. Linguistics and Education, 22, 430–440. doi:10.1016/j.linged.2011.04.004

Forney, M. A., & Smith, L. R. (1979). Teacher grammar and pupil achievement in mathematics. Paper presented at the annual meeting of the Northeastern Educational Research Association, Ellenville, NY. Retrieved from ERIC database. (ED179976)

Gruenewald, L. J., & Pollak, S. A. (1990). Language interaction in curriculum and instruction: What the classroom teacher needs to know (2nd ed.). Austin, TX: PRO-ED.

Haydon, T., Macsuga-Gage, A. S., Simonsen, B., & Hawkins, R. (2012). Opportunities to respond: A key component of effective instruction. Beyond Behavior, 22(1), 23–31. doi: 10.1177/107429561202200105

Hollo, A., & Wehby, J. H. (2017). Teacher Talk in General and Special Education Elementary Classrooms. The Elementary School Journal, 117(4), 616–641. doi: 10.1086/691605

Hughes, C. A., Morris, J. R., Therrien, W. J., & Benson, S. K. (2017). Explicit Instruction: Historical and Contemporary Contexts. Learning Disabilities Research & Practice, 32(3), 140–148. doi: 10.1111/ldrp.12142

Lapadat, J. C. (2002). Relationships between instructional language and primary students’ learning. Journal of Educational Psychology, 94(2), 278–290.

Mack, A. E., & Warr-Leeper, G. A. (1992). Language abilities in boys with chronic behavior disorders. Language, Speech, and Hearing Services in Schools, 23, 214–223.

Montgomery, J. W. (2004). Sentence comprehension in children with SLI: Effects of input rate and phonological working memory. International Journal of Communication Disorders, 39(1), 115–133. doi:10.1080/13682820310001616985

Nippold, M. A. (1991). Evaluating and enhancing idiom comprehension in language-disordered students. Language, Speech, and Hearing Services in Schools, 22, 100–106. doi:10.1044/0161-1461.2203.100

Palmer, B. C., Shackelford, V. S., Miller, S. C., & Leclere, J. T. (2006). Bridging Two Worlds: Reading Comprehension, Figurative Language Instruction, and the English-Language Learner. Journal of Adolescent & Adult Literacy, 50(4), 258–267. doi: 10.1598/jaal.50.4.2

Park, E. S. (2002). On three potential sources of comprehensible input for second language acquisition. Working Papers in TESOL and Applied Linguistics, 2(3), 1–21.

Roter, D. L., Erby, L. H., Larson, S., & Ellington, L. (2007). Assessing oral literacy demand in genetic counseling dialogue: Preliminary test of a conceptual framework. Social Science & Medicine, 65, 1442–1457. doi:10.1016/j.socscimed.2007.05.033

Sinclair J., & Coulthard, R. M. (1975). Towards analysis of discourse: The English used by teachers and pupils. London: Oxford University Press.

Sutherland, K. S., & Wehby, J. H. (2001). Exploring the relationship between increased opportunities to respond to academic requests and the academic and behavioral outcomes of students with EBD: A review. Remedial and Special Education, 22(2), 113–121. doi:10.1177/074193250102200205

Tobin, K. (1986). Effects of teacher wait time on discourse characteristics in mathematics and language arts classes. American Educational Research Journal, 23(2), 191–200.

Explicit Instruction: Segmenting Complex Skills

Posts in this series…

1. What is Explicit Instruction?
2. Explicit Instruction: Segmenting Complex Skills
3. Explicit Instruction: Teacher Talk and Equity
4. Explicit Instruction: Modeling
5. Explicit Instruction: Concreteness Fading
6. Explicit Instruction: Opportunities to Respond

In this post, most of the referenced studies are from multimedia learning (educational videos) and special education contexts. However, the findings from the studies should transfer over to general education. The multimedia studies should transfer because they were looking into how segmenting a video impacts learning, this is very similar to how segmenting instruction would impact learning. The special education studies looked at effective teaching methods for learning disabled students, which should have an obvious transfer to students in general education. That said, if you know of any research on segmenting content/skills in a classroom context, please send them my way!

The Segmenting Effect

The segmenting effect states that students “learn better when multimedia interactions are presented in meaningful and coherent learner-paced segments, rather than as continuous units” (Mayer & Pilegard, 2014). I should note that in this context, learner-paced means something significantly different than what we would typically think. Learner-paced is only talking about the multimedia interaction, the assignment. In practice, this would involve some sort of pause or rewind function, allowing the student to rewatch and stop the presentation as needed. So, learner-paced only applies to the pacing of the assignment, not to the pacing of the curriculum.

Explaining the Segmenting Effect

  1. Segmenting gives students more time to mentally organize the information they are taking in. Giving them a chance to integrate it with preexisting knowledge.
  2. Continuous presentations may cause cognitive overload
  3. Segmentation may be more beneficial for novices than experts. Novices need more breaks (segments) because they lack a developed schema. Segmentation may have negative effects for experts (Spanjers et al., 2011).
  4. Experts may benefit from self segmenting their studies (Spanjers et al., 2010).

A meta-analysis found that segmenting improved both retention (45 out of 67 studies, 67%) and transfer (34 out of 56 studies, 61%) performance. It also found that, commonsensically, segmenting takes more time. In addition, learners with high levels of prior knowledge experienced greater benefits from segmenting than learners with low levels of prior knowledge. The meta-analysis also found that transfer performance was not impacted by prior knowledge (Rey et al., 2019). A study by Agarwal also found that factual knowledge did not impact transfer (2019).

An additional interesting finding by Rey et al. was that system paced segmenting (no learner choice) improves retention and transfer in addition to reducing perceived cognitive load, whereas learner-paced segmenting only led to an increase in transfer. This finding is easy to apply to the classroom.

Segmenting Instruction

Teachers should segment their lessons and provide students with “breaks” instead of allowing students to work and self-learn. What I mean by this is that we should teach something, and then, shortly after, stop the “teaching” and give students a chance to think about what they just learned.

For example, let’s say you are teaching about the rock cycle, and your students just learned weathering and erosion.

Teacher: “Ok, weathering means breaking rocks. Erosion means moving rocks. Chalk is a rock”
*grabs a piece of chalk and snaps it in half
“Ok, using our vocabulary words, what happened to the rock?”
Students: “Weathering!”
Teacher: “How do you know?”
Students: “It broke.”
Then you can draw a line by moving the chalk back and forth, heavily across the blackboard.
Teacher: See the small pieces of chalk falling down? What is that?”
Students: “Erosion?” “Weathering?”

At this point, some students will likely focus on the wrong part of your demonstration or example (regardless of what content/skill you are teaching). So, here you get specific and correct misconceptions immediately.

Teacher: “Weathering and erosion are BOTH happening in this example. But remember our definitions. Check your notes. What is weathering?”
Students: “Breaking rocks.”
Teacher: “Good! And what is erosion?”
Students: “Moving rocks.”
Teacher: “Excellent!” *resumes heavily drawing the chalk line. “Now, see the small pieces of rock falling down? What is that?”
Students: “Erosion!”
Teacher: “Perfect! Now, what is happening to the chalk when I rub it across the blackboard?”

And on and on.

While this process looks rather long and drawn out on paper (or the web) it is actually a fast paced, snappy exercise that only takes a minute or two. Using choral response is a quick, efficient way to segment your teaching, allowing students to integrate their new learning with their prior knowledge.

Since we all want our students to be able to apply what they are learning to their lives, we should give our students many differing examples, and many opportunities to apply their learning to different contexts. Research has found that exposing students to differing examples of the same concept helps them transfer their learning (Jacobson et al., 2020).

More Examples, More Transfer

After my students have a basic understanding of the key terms and their applications, I branch into more examples to help them generalize (transfer) their learning, often using short videos. I would then end this segment of class with  a similar routine of choral response and think-pair-share.

Teacher: “The mud sliding down the mountain is an example of…”
Students: “Erosion!”
Teacher: “Good! And when that rock crashed into the other rock and exploded, it was an example of….”
Students: “Weathering!”

Immediately following the choral response, I would shift into a pair-share (the think part was ~completed in the choral response and all students will at least know the answer, if not the explanation). The purpose for the immediate shift is to keep momentum going and build anticipation. I would have students explain to each other why one part was weathering and why the other was erosion. Then I would conclude this segment of instruction by having several students share their answers, followed by me clearly and succinctly restating or correcting their answer to the class.

Digging Deeper and Building Up

As we dig deeper into the concept of the rock cycle, we will add complexity to weathering and erosion. For example, we may dig into how the material affects the rate of weathering and erosion. Or we may explore how the volume of the weathering/erosive agent affects the rate of weathering and erosion. And as we add complexity, we are always referring back to what was learned previously. This helps make learning cumulative, gives students practice with a diverse array of examples which helps them transfer their learning, and it cements previous learning (ideally to the point of automaticity).

As you can tell by the previous paragraph, segmenting isn’t just something that you should take into account within your lesson, it ought to be taken into account throughout your unit planning. And actually implementing segmenting into your instruction will take time, meaning you will likely cover less content. But, the research shows your students will likely learn and retain more of the content/skills than otherwise. In addition, you can use strategies like choral response and think-pair-share to make the segments an effective use of time.

Sources

Agarwal, P. K. (2019). Retrieval practice and Bloom’s taxonomy: Do students need fact
knowledge before higher order learning? Journal of Educational Psychology, 111, 189-209.

Jacobson, M. J., Goldwater, M., Markauskaite, L., Lai, P. K., Kapur, M., Roberts, G., & Hilton, (2020). Schema abstraction with productive failure and analogical comparison: Learning designs for far across domain transfer. Learning and Instruction,65, 101222. doi:10.1016/j.learninstruc.2019.101222

Mayer, R. E., & Pilegard, C. (2014). Principles for managing essential processing in multimedia learning:segmenting, pre-training, and modality principles. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (2nd ed., pp. 316–344). Cambridge: Cambridge University Press.

Rey, G. D., Beege, M., Nebel, S., Wirzberger, M., Schmitt, T. H., & Schneider, S. (2019). A Meta-analysis of the Segmenting Effect. Educational Psychology Review31(2), 389–419. doi: 10.1007/s10648-018-9456-4

Spanjers, I. A. E., Van Gog, T., & VanMerrienboer, J. J. G. (2010). A theoretical analysis of how segmentation of dynamic visualizations optimizes students’ learning. Educational Psychology Review, 22(4), 411–423.

Spanjers, I. A., Wouters, P., Gog, T. V., & Merriënboer, J. J. V. (2011). An expertise reversal effect of segmentation in learning from animated worked-out examples. Computers in Human Behavior27(1), 46–52. doi: 10.1016/j.chb.2010.05.011

What is Explicit Instruction?

Like many educational approaches, the outer edges of explicit instruction are vague. But thankfully scholars have put in the effort to define its core components. The term explicit instruction first gained traction in the early 1990s to refer to “unambiguous, structured, systematic, and scaffolded” instruction (Archer & Hughes, 2011). 

In order to determine what researchers meant when they referred to explicit instruction, Hughes, Morris, Therrien, and Benson reviewed 86 studies mentioning a variety of key phrases associated with explicit instruction and found that it has 5 key components (2017).

Pillars of explicit instruction

Hughes, C. A., Morris, J. R., Therrien, W. J., & Benson, S. K. (2017).

Pillar 1: Segment Complex Skills/Content

This strategy is rather straightforward. Instead of starting out with the whole kit and caboodle, break it up into smaller chunks. The chunks are not just pieces of information, but time as well. Complex skills and knowledge should be taught step-by-step over time. The time may be as small as a single lesson or as large as an entire unit. 

Ideally, students will be able to achieve consistent success in one chunk of the skills/content before moving on to the next. The chunks should be taught cumulatively, meaning that students will continue to practice the skills/content they have already mastered along with the new subset of skills/content.

Scientific Method Example: There are a variety of ways that I like to segment the various skills/content I teach my students. In science class, one complex skill all students must learn is how to apply the scientific method. Depending on where you look, there can be anywhere from 6-9 steps. So, I segment this by teaching one step at a time. However, even when breaking this down into single steps, the steps each have their own unique substeps students must master before they can successfully apply the scientific method. 

Step 1: Ask a question

Scientific Method Example: I first teach my students that an observation precedes a question and that we use knowledge gained from our senses to generate questions. Next, I define what a scientific question is (must be testable). Then we generate some examples and non-examples. 

Pillar 2: Draw Student Attention to Important Features of the Content through Modeling/Think-Alouds

Modeling and think-alouds are used extensively in this pillar. The goal is to both show and tell students how to solve a problem or complete a task. Both modeling and think-alouds should be kept brief and consistent language should be used. Consistent word choice acts as another que, helping students remember the next step in a procedure, subset of the skill, part of the content.

Scientific Method Example: As I model making observations and asking scientific questions, I am conscious to consistently use various keywords as I provide numerous examples. 

“I observed the lion roaring with my sense of hearing. I observed the lion chasing the zebra with my sense of sight.” 

This gives students more exposure with the vocabulary and provides a familiar format for them to later apply the skill themselves. I then tell my students that we need to link our observations to our questions.

“I am going to use my observation of the lion chasing the zebra to create a question. Why is the lion chasing the zebra?”

Pillar 3: Promote Successful Engagement by Using Systematically Faded Supports/Prompts

After the initial set of modeling and explaining, teachers should still provide students with a substantial amount of support. This helps to ensure a high rate of initial success. As students find success in applying the skill/content, teachers should gradually remove support and give students more independence. This process should repeat until students are able to successfully complete work with full independence.

Scientific Method Example: Students will start applying the skill of asking scientific questions using the exact same structure I used in my examples in scenarios that are, initially, similar as well. This initial similarity helps students to successfully apply the skill. Then I gradually withdraw the support by having students make observations and ask questions in scenarios that become significantly different from the examples I taught at the beginning of class.

Pillar 4: Provide Opportunities for Students to Respond and Receive Feedback

Frequent opportunities to respond gives students frequent practice, which ensures that the teacher is able to give frequent feedback. This is a flexible strategy and can easily be applied to group, pair, or individual work in a variety of forms including oral, written, and action. It can also be used to informally assess a variety of knowledge depths and types including factual, procedural, conceptual, and conditional. In addition, these opportunities can be scaffolded, allowing all students to access the opportunity to respond.

Scientific Method Example: As my students are practicing the skill of making observations and asking scientific questions I walk around the room and provide feedback to different groups of students. I also keep the work periods relatively short by bringing the class back together to do brief whole-class activities.

For example, I may write a question on the board and ask students to raise their hand if it is a scientific question. This gets all students participating. I then confirm the answer. “It is a scientific question.” or “It is not a scientific question.”

I quickly shift into a Pair and Share activity (Students already did the “Think” step by raising or not raising their hand). “Tell you neighbor why this is/isn’t a scientific question. Ready… GO!”

During the whole-class activities I am able to get a rough gauge on the class’s understanding and can adjust my teaching as I go. After a few brief whole-class activities I redirect my students to their individual/small group work.

Pillar 5: Create Purposeful Practice Opportunities

Practice after the initial lesson reinforces what was learned and is important for generalizing and transferring new knowledge and skills. What is important is that the teacher is intentional with the practice opportunities they craft for their students. Whatever form the practice takes should be accompanied with feedback.

Scientific Method Example: See the example for pillar 4.

As you read through this, hopefully it became clear that many of the pillars should be applied at the same time. For example, if you are providing students with purposeful practice in class (Pillar 5) you should also be providing live feedback (Pillar 4). In giving feedback, you will find that students benefit from additional modeling/thinking aloud (Pillar 2) because they need more support (Pillar 3) as they practice that particular segment of the content (Pillar 1).

Other blogposts in this series

  1. Explicit Instruction: Segmenting Complex Skills
  2. Explicit Instruction: Teacher Talk and Equity
  3. Explicit Instruction: Modeling
  4. Explicit Instruction: Concreteness Fading
  5. Explicit Instruction: Opportunities to Respond

 

 

 

Citation:

Archer, A. L., & Hughes, C. A. (2011). Explicit instruction: Effective and efficient teaching. New York: Guilford Press.

Hughes, C. A., Morris, J. R., Therrien, W. J., & Benson, S. K. (2017). Explicit Instruction: Historical and Contemporary Contexts. Learning Disabilities Research & Practice32(3), 140–148. doi: 10.1111/ldrp.12142