PS560 Discussion

PS560 Discussion

Emergent Relations and Generative Learning

This week's readings and tutorials provide you with a continued investigation of stimulus control via emergent relations (aka derived stimulus relations) and how these relations contribute to generative learning and cognition of an individual. Considering your own experiences, either personal or professional, give an example of how mutual entailment, combinatorial entailment, and transformation of function may have contributed to that learning experience and any generative effects. You may also choose to include a visual representation (via a Word document or PowerPoint slides) of each relation with a brief description of that relation and attach to your discussion posting.

Review two of your classmate's responses using following ideas as a guide:

• Review the emergent relations presented and note whether the relations are discussed accurately and extend beyond basic stimulus equivalence concepts. Provide feedback or alternate suggestions for consideration.
• Provide feedback on the notion of the generative learning that is discussed.
• Ask at least one thoughtful follow up question. Reply to Kaylah Healy: In my work in applied behavior analysis (ABA), I have seen derived stimulus relations develop while teaching self-management skills, specifically when following directions such as “clean up.” Initially, a client was taught that a visual schedule icon (A) meant “clean up” (B), which demonstrates a directly trained relation between two stimuli (Cooper et al., 2020). After this was established, the client demonstrated mutual entailment by correctly identifying the icon when I gave the verbal instruction “clean up,” even though this direction was not directly taught. According to Barens-Holmes et al. (2018), mutual entailment refers to the emergence of a bidirectional relationship between stimuli after only one direction has been taught. This showed that the client formed a two-way relationship between the visual and the spoken instruction.I then introduced a third component, which was the actual routine (C), such as putting preferred items away and pushing in their chair. The client demonstrated combinatorial entailment by connecting all three stimuli—the visual icon, the verbal instruction, and the sequence of actions—without needing each relation to be taught separately. Combinatorial entailment occurs when two or more learned relations combine to form new, untrained relations among stimuli (Barens-Holmes et al., 2018). Over time, I observed transformation of function when the client began cleaning up across settings such as the art area, kitchen, and playroom when hearing “clean up,” even without visual supports. Transformation of function refers to a change in how a stimulus influences behavior based on its relation to other stimuli, rather than through direct reinforcement (Perez et al., 2021). In this case, the meaning of “clean up” transferred across environments and instructions, showing that the client understood the concept rather than simply responding to a single prompt.This experience demonstrated clear generative learning. The client did not just learn one specific instruction or routine; they were able to apply the concept of cleaning up across different environments and with various staff. Reflecting on this experience reinforced how important it is to go beyond teaching isolated skills and instead focus on building connections between stimuli. Research supports this idea, as derived stimulus relations allow learners to respond to new situations without direct teaching (Barens-Holmes et al., 2018). Additionally, transformation of function plays a key role in generalization, as stimuli take on new meaning through their relations with other stimuli (Perez et al., 2021). These processes are especially important for individuals with autism, as they promote flexible and meaningful skill use across environments (Ming et al., 2014). Overall, this example demonstrates how mutual entailment, combinatorial entailment, and transformation of function work together to support independence and real-world learning.ReferencesBarens-Holmes, D., Finn, M., McEnteggart, C., & Barnes-Holmes, Y. (2018). Derived stimulus relations and their role in a behavior-analytic account of human language and cognition. Perspectives on Behavior Science, 41(1), 155–173.Cooper, J., Heron, T., & Heward, W. (2020). Applied behavior analysis (3rd ed.). Pearson.Ming, S., Moran, L., & Stewart, I. (2014). Derived relational responding: Applications and future directions for teaching individuals with autism spectrum disorders. European Journal of Behavior Analysis.Perez, W. F., de Azevedo, S. P., Gomes, C. T., & Vichi, C. (2021). Equivalence relations and the contextual control of multiple derived stimulus functions. Journal of the Experimental Analysis of Behavior, 115(1), 405–420. Reply to Matt Dipietro : The central theme of Unit 9 is how derided stimulus relations can extend beyond direct teaching. This allows individuals to demonstrate complex and generative behavior without given explicit instruction. This discussion will analyze the frameworks outlined by Barens-Holmes et al. (2018), Cooper et al. (2020), and Perez et al. (2021). These 3 frameworks all emphasize the idea that stimulus control evolves through relational networks, specifically through mutual entailment, combinatorial entailment, and transformation of function. These concepts all provide a functional account of how learning can generalize in an adaptive and meaningful way.Mutual entailment is the bidirectional relationship between stimuli once a relationship is trained. In other words, If A is related to B, then B is derived to be related to A without direct teaching (Barens-Holmes et al., 2018). In my own experience working in a learning environment, I have observed this when new coworkers learn organizational terminology. When they were taught that A-B-C refers to a longer procedural name (Antecedent-Behavior-Stimulus), they quickly understood the reverse relationship, identifying the acronym ABC when hearing the full phrase out loud– without explicit instruction. This aligns with the Cooper book when they discuss the concept of mutual entailment as a fundamental property of derived relational responding which reduces the need for rote memorization (Cooper et al., 2020). This efficiency reflects how relational learning supports rapid acquisition of verbal repertoires (Barens-Holmes et al., 2018).Combinatorial entailment takes this concept further through linking many trained relationships into a larger relational network. Back to my example, If A relates to B and B relates to C, then A and C are related without any direct training (Perez et al., 2021). I have experienced this as well while taking this graduate course and learning various theoretical concepts. For example, when I learned that positive reinforcement (A) was associated with operant conditioning (B), and that operant conditioning (B) was linked to behavior intervention plans used in applied settings (C) without needing explicit instructions. This showcases how combinatorial entailment nurtures generalization through allowing learners to derive novel relationships from previously established relationships (Barens-Holmes et al., 2018). Perez and colleagues (2021) take this concept further through emphasizing that such relational networks are contextually controlled, meaning that the strength and relevancy of these derived relationships depend upon the learning history and environmental cues around an individual.Transformation of function is said to be the most impactful process in terms of behavioral outcomes and occurs when the function of a stimulus changes based on its relation to another stimulus (Cooper et al., 2020). In a personal experience, I remember developing anxiety toward using a specific software system at work. At first I had a negative experience (i.e., repeating errors) using one part of the system. Over time other related parts, despite not being directly associated with errors, began to evoke similar negative responses. This scenario depicts how aversive function transforms across stimuli within the same broadened relational network (Perez et al., 2021). Barens-Holmes and colleagues (2018) also emphasize that transformation of function is key to understanding complex human emotions, language, and cognition, because it allows stimuli to gain meaning and behavioral significance indirectly (Barens-Holmes et al., 2018). This concept is heavily relevant in applied settings, where both adaptive and maladaptive behavior can emerge through relational framing (Cooper et al., 2020).These three processes all contribute to generative learning. Instead of requiring direct reinforcement for every possible response, individuals can derive novel knowledge and behaviors through relational networks. Barens-Holmes et al. (2018) further argue that this capacity underlies human language and symbolic thought, ensuring flexible and adaptive responding across contexts. In the Cooper book, they emphasize how emergent relations reduce instructional demands while also increasing behavioral complexity (Cooper et al., 2020). Perez and colleagues (2021) take this further through demonstrating how contextual variables shape which derived relations are expressed, showcasing the dynamic nature of stimulus control (Perez et al., 2021).ReferencesBarens-Holmes, D., Finn, M., McEnteggart, C., & Barnes-Holmes, Y. (2018). Derived stimulus relations and their role in a behavior-analytic account of human language and cognition. Perspectives on Behavior Science, 41(1), 155–173.Cooper, J., Heron, T., & Heward, W. (2020). Applied behavior analysis (3rd ed.). Pearson.Perez, W. F., de Azevedo, S. P., Gomes, C. T., & Vichi, C. (2021). Equivalence relations and the contextual control of multiple derived stimulus functions. Journal of the Experimental Analysis of Behavior, 115(1), 405–420.