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| A Generative Learning Assessment and Intervention Program Based on Skinner’s Verbal Behavior (1957) |
| Monday, May 26, 2025 |
| 8:00 AM–9:50 AM |
| Marriott Marquis, M2 Level, Marquis Salon 12-13 |
| Area: VBC/AUT; Domain: Service Delivery |
| Chair: Mark L. Sundberg (Sundberg and Associates) |
| Discussant: David C. Palmer (Smith College) |
| CE Instructor: Mark L. Sundberg, Ph.D. |
| Abstract: The language skills of a typically developing toddler accelerate rapidly between 18 and 36 months of age. At the root of this language burst is an effect Wittrock (1974) termed generative learning. Wittrock suggested that toddlers are active learners who generate linguistic meaning and understanding by integrating new information with their existing cognitive frameworks. A behavioral interpretation (Skinner, 1957) of this important linguistic effect suggests that the contingencies of reinforcement establish generative linguistic meaning and understanding for a toddler. However, some children with autism or other intellectual disabilities have trouble acquiring new language skills through generative learning. For these children, an assessment of the various types of generative learning may reveal that a child is missing a prerequisite or component repertoire of a generative learning skill or that there is some other cause of the problem. The first two presentations in this symposium will describe a generative learning assessment tool based on Skinner’s (1957) analysis of verbal behavior. The next two presentations will focus on applying the assessment results to developing intervention programs that can help establish generative learning repertoires for those who fail to acquire them. These presentations will be followed by comments from our discussant, David Palmer. |
| Instruction Level: Intermediate |
| Keyword(s): generative cusps, generative learning, language assessment/intervention, verbal behavior |
| Target Audience: Participants should be familiar with Skinner's analysis of verbal behavior and the VB-MAPP assessment. |
Learning Objectives: 1. Behaviorally define and exemplify generative learning.
2. Describe methods to increase social approach behaviors.
3. Describe the role of themed curriculum in creating ongoing contexts for generative learning instruction. |
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The VB-MAPP Generative Learning Assessment |
| MARK L. SUNDBERG (Sundberg and Associates), Andresa De Souza (University of Missouri-St. Louis), Caio F. Miguel (California State University, Sacramento) |
| Abstract: Once a child demonstrates speaker and listener generative learning repertoires, her language acquisition accelerates rapidly (e.g., observational learning, generative manding, bidirectional naming). However, some children with autism or other intellectual disabilities have trouble acquiring new language skills through the process of generative learning. For these children, an assessment of generative learning may reveal that a child is missing a prerequisite or component repertoire or that there is some other cause of the problem. If these causes can be identified and rectified, they can potentially lead to improved generative learning (Aragon et al., 2024; DeSouza et al., 2019; Rodriguez et al., 2022). The VB-MAPP Generative Learning Assessment (GLA) uses Skinner’s (1957) analysis of verbal behavior to identify, define, and measure generalized and generative learning repertoires that provide a foundation for a typically developing child’s rapid language acquisition. The GLA Guide contains definitions, examples, supporting research, and scoring instructions for several different generative learning domains, and the GLA Protocol contains the scoring forms for an individual child. The assessment tool will be described, and examples of completed scoring forms will be presented and analyzed. |
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| Developing the VB-MAPP Generative Language Assessment: A Behavior-Analytic Approach to Language Generativity |
| ANDRESA DE SOUZA (University of Missouri-St. Louis), Caio F. Miguel (California State University, Sacramento), Mark L. Sundberg (Sundberg and Associates) |
| Abstract: Assessing the repertoire essential for language generativity requires a precise examination of specific skills and their behavioral components. Each skill should be conceptualized from a behavior-analytic perspective and assessed based on the foundational behaviors that comprise a broader domain. This process involves a thorough review of both conceptual and empirical literature, alongside the establishment of clear criteria for analyzing each domain. Another key aspect is ensuring the feasibility and practicality of the assessment, which demands clear operational definitions of observable behaviors and a detailed technical description of the assessment procedures. The development of the VB-MAPP Generative Language Assessment (GLA) entails a comprehensive and meticulous analysis of each generative domain. This includes the creation of guidelines for direct assessment of the component skills within each domain, a detailed description of assessment procedures and scoring criteria, and the collection of feasibility and predictive validity data. In this presentation, we will provide examples of the outcomes of this process as applied to different GLA domains, such as joint attention and bidirectional naming. We will present specific information on the key aspects of the assessment for each domain, along with preliminary data supporting the feasibility of these procedures. |
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| Enhancing Social Interest as a Foundation to Generative Learning |
| ALICE SHILLINGSBURG (Munroe-Meyer Institute, UNMC), Sarah Frampton (University of Nebraska Medical Center; University of Nebraska Omaha), Danielle LaFrance (Verbale; ABA Technologies) |
| Abstract: Participating with others in activities across a variety of contexts creates new opportunities for learning and ways of accessing reinforcement. Whether in adult-led instruction, group games, or free-play contexts- cooperation enhances the potential of interacting with others successfully and, therefore, enhances opportunities to learn new things. As such, cooperating with instruction can be viewed as an important cusp skill and starting point for intervention. One way to improve cooperation with instruction involves increasing social interest in others. As social interactions become more reinforcing or enjoyable, children may be more willing to work with or cooperate with others. Further, as instructors are frequently paired with reinforcement, instructor behavior takes on discriminative functions, which accelerates learning. The current presentation examines the principle that social interest, or motivation to engage with others, is foundational for establishing instructional control as an outcome. Procedures to develop a social approach and its subsequent effect on cooperative behaviors will be described. Implications for effective curricular design to establish generative learning across contexts will be discussed. |
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| Intervention Tactics to Promote Generative Learning in Practice |
| DANIELLE LAFRANCE (Verbale; ABA Technologies), Sarah Frampton (University of Nebraska Medical Center; University of Nebraska Omaha), Alice Shillingsburg (Munroe-Meyer Institute, UNMC) |
| Abstract: Effectively teaching generative learning cusps requires a combination of appropriate contexts for instruction, evidence-based tactics, and meaningful content. However, balancing these priorities and bringing them into the realities of practice may be overwhelming. Thematic instruction is an integration of applied verbal behavior and equivalence-based instruction that can creatively, flexibly, and readily be applied by practitioners. Thematic instruction provides ongoing opportunities for assessing a variety of generative learning cusps while teaching educationally and clinically relevant content. We will describe the steps for developing a thematic curriculum and deploying it across contexts using multiple exemplar training. For some learners, more intensive instructional approaches may be required, such as multiple exemplar instruction. Multiple exemplar instruction may be applied to establish a variety of generative learning cusps by integrating speaker and listener behaviors. We will detail this procedure and its application to produce critical learning outcomes. Recommendations for supporting implementers delivering these approaches in ongoing service delivery and educational contexts will be provided. |
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