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| Design and Delivery Features of Direct Instruction That You Didn’t Know You Didn’t Know, and Didn’t Know You Needed |
| Sunday, May 24, 2020 |
| 5:00 PM–6:50 PM |
| Marriott Marquis, Level M4, Independence A-C |
| Area: EDC; Domain: Translational |
| Chair: Adam Hockman (The Mechner Foundation/ABA Technologies) |
| Discussant: Adam Hockman (The Mechner Foundation/ABA Technologies) |
| CE Instructor: Janet S. Twyman, Ph.D. |
| Abstract: If you design, select, modify, or deliver instruction, this session is for you! Direct Instruction (DI) programs are highly effective, with design and delivery based on the content’s “Big Idea” and application of three powerhouse components: content analysis, instructional sequencing, and clear communication. Content analysis is an active and creative part of instructional design that ensures concepts are learned and readied for teaching generalization. Thoughtful sequencing and example juxtaposition improve efficiency. Clear communication reduces ambiguity and errors—for both the teacher and the learner—and influences DI’s presentation features (e.g., scripting, active student responding, pacing, progress monitoring). The program elements of true DI move the instructional design process beyond simply selecting multiple exemplars, the prevailing method in much of behavior analytic teaching. This session will apply and extend these core features to real-world contexts for any and all teaching, content, and circumstances. Our goal? You’ll learn to infuse these critical components of DI into your own instructional design and delivery. |
| Instruction Level: Basic |
| Keyword(s): Concept Learning, Direct Instruction, Instructional Design |
| Target Audience: Behavior analysts (certified), educators, instructional designers |
| Learning Objectives: 1. Participants will describe the importance of content analysis for effective and efficient teaching. 2. Participants will give examples and non-examples of a concept. 3. Participants will describe five sequencing features of DI and how they support efficient learning. 4. Participants will explain how DI principles extend to a wide range of behavior analytic teaching, such as the promotion of complex verbal behavior. |
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| Features of Direct Instruction: Analysis of the Domain and Effective Interaction |
| (Theory) |
| TIMOTHY A. SLOCUM (Utah State University), Kristen Rolf (Utah State University) |
| Abstract: Direct Instruction (DI) includes numerous features that can be adopted by behavior analysts to improve teaching outcomes across many populations. This presentation will focus on two of those features: (1) analysis of the content domain, and (2) presentation and lesson delivery. Analysis of the content domain is one of the most underappreciated and powerful components of DI. It involves analyzing the content domain to be learned (e.g., beginning reading, basic language skills, narrative language, social skills, calculus) to identify broadly applicable generalizations (“Big Ideas”) that must be taught in order for students to later derive numerous untaught responses. This analysis is foundational to highly generative instruction, and is further enhanced through lesson presentation and delivery. In small group instruction, DI’s instructional formats, student grouping recommendations, scripted presentations, ongoing data-based decision-making rules, brisk pacing, component skill mastery criteria, and correction procedures make it possible to bring about interactive and effective instruction. |
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| Creating the Components for Teaching Concepts |
| (Theory) |
| KENT JOHNSON (Morningside Academy) |
| Abstract: An important dimension of Direct Instruction (DI) programs involves teaching conceptual behavior related to the broadly applicable generalizations of a content domain. In this presentation I will outline the necessary components for teaching a concept in any domain. The first step (1) is to conduct a concept analysis of the critical features that define the concept, and the features that vary from instance to instance of the concept. From this prescription we must (2) develop a range of typical and far-out examples of the concept that illustrate both the critical and variable features, (3) develop a minimum rational set of close-in non-examples of the concept, each of which is missing only one critical feature, and (4) develop additional examples and non-examples that may be needed to produce the desired discriminations. Multiple exemplar teaching is not enough. Teaching a concept this way produces generative responding to examples as well as non-examples not presented during instruction. To assess learners’ generative responding, we must (5) create another set of far-out examples and close-in non-examples from the concept-analysis prescription. Finally, after initially acquiring conceptual behavior, learners must (6) practice with additional far-out examples and close-in non-examples. Once these components are created, a teacher is ready to develop an instructional sequence featuring tasks that include context-setting descriptions, rules, examples, and non-examples. |
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You Have the Big Idea, Concept, and Examples: Now What? |
| (Theory) |
| JANET S. TWYMAN (blast) |
| Abstract: How do you take a concept/content analysis and figure out the sequence of what to teach when? Even after performing the necessary analytical components for teaching a concept we still have to figure out how to best teach it. The sequence in which skills are taught is instrumental for success. Learning new concepts can be made easier or more difficult depending on the order in which stimuli are introduced. Critical design aspects of how to teach include the sequence and arrangement of examples and non-examples (juxtaposition), the use of clear instructions (faultless communication), the judicious presentation of “interruptions,” and the selection of teaching routines based on the learner's current repertoire (response teaching strategies). This presentation will outline five Direct Instruction (DI) principles for sequencing and ordering examples to maximize learning, and it will consider their ties to behavior analysis. |
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| Adopting Direct Instruction Principles to Design and Deliver Generative Language Instruction via Narratives |
| (Service Delivery) |
| TRINA SPENCER (Rightpath Research & Innovation Center, University of South Florida) |
| Abstract: Narratives are large unit verbal operant responses that are extremely important to the academic and social development of children, with and without disabilities. Many Direct Instruction (DI) principles are applied in the design and delivery of a narrative-based academic language curriculum called Story Champs. In order to develop such a program, the content analysis requires an understanding of the autoclitic controls inherent in storytelling and the sophisticated nature of narrative language. The “Big Ideas” of narrative language (e.g., structures of stories and sentences) facilitate generative language learning and optimize concept teaching. During Story Champs instruction, learners practice storytelling and retelling in flexible groups as teachers/interventionists use consistent instructional formats and standardized correction procedures (i.e., model-lead-test and 2-step prompting). During guided practice, children practice retelling a strategically sequenced series of stories (aka, multiple exemplars). Then, to facilitate a quick transfer, children generate personal stories using the story structures, linguistic structures, and vocabulary that they learned during retells. Some aspects of Story Champs are guided by scripts while others are trained loosely (not trained to mastery). Choral responding and brisk pacing maximize active responding during the instructional delivery. Story Champs is just one example of how DI principles are adaptable for a broad range of behavior analytic teaching. |
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