By Matt Harrington, BCBA · Behaviorist Book Club · April 2026 · 12 min read

Social Emotional Learning and Executive Functioning in Autism and IDD: Integrating Technology with Behavioral Practice

Overview & Clinical Significance

Social Emotional Learning (SEL) and Executive Functioning (EF) skills represent two of the most clinically significant — and underaddressed — domains in programming for autistic individuals and those with intellectual and developmental disabilities. While discrete trial training and naturalistic developmental behavioral interventions have produced well-documented gains in communication, adaptive behavior, and academic skills, learners with ASD and IDD continue to show persistent challenges with emotion recognition, perspective-taking, impulse regulation, cognitive flexibility, and planning — skills that are fundamental to independence, employment, and quality of life.

Chris Dudick's presentation, focused on the Silas platform by CentralReach, makes the case for an integrated approach that combines technology-based curricula with traditional tabletop programming. This integration is clinically meaningful because different learner profiles respond differently to modality, and the motivational properties of well-designed technology platforms can enhance engagement with skill content that learners find difficult or aversive in traditional formats.

For BCBAs, SEL and EF programming raises both conceptual and practical challenges. Behavior analysis has historically been more comfortable with discrete, observable targets than with constructs like emotional regulation or working memory. However, behavior analytic frameworks are well-suited to these domains when the abstract constructs are operationally defined and broken into teachable component behaviors. Emotion regulation, for example, can be decomposed into identifying physiological signals of arousal, labeling emotional states, selecting coping responses, and implementing them — each a teachable behavior chain with behavioral reinforcement contingencies.

The growing availability of technology platforms designed specifically for SEL and EF instruction creates both opportunity and responsibility for BCBAs. The opportunity is access to structured, engaging curricula with built-in data collection. The responsibility is ensuring that technology use is governed by the same principles of individualized assessment, data-based decision making, and treatment integrity that govern all behavior analytic practice.

Background & Context

Executive functioning is an umbrella term for a set of cognitive control processes mediated primarily by the prefrontal cortex, including working memory, cognitive flexibility, inhibitory control, planning, and goal-directed behavior. Neuropsychological research consistently documents EF differences in autism, with particular challenges in cognitive flexibility and inhibitory control. These differences have cascading effects on social behavior, academic performance, and adaptive functioning across environments.

Social Emotional Learning encompasses the ability to recognize and manage emotions, develop empathy, establish positive relationships, make responsible decisions, and navigate social situations effectively. The Collaborative for Academic, Social, and Emotional Learning (CASEL) framework identifies five core SEL competencies: self-awareness, self-management, social awareness, relationship skills, and responsible decision-making. Each of these domains contains component behaviors that can be assessed and targeted through behavior analytic methodology.

The intersection of EF and SEL is significant: poor inhibitory control contributes directly to social difficulties (impulsive responses in social situations), working memory limitations affect the ability to track social rules and conventions across contexts, and cognitive inflexibility is associated with the restricted and repetitive behavior that characterizes ASD. Addressing EF deficits is therefore not purely cognitive — it has direct downstream effects on social behavior and emotional regulation.

The use of technology in ABA has expanded significantly over the past decade. Applications range from data collection tools to AI-powered skill acquisition platforms. For SEL and EF specifically, technology offers several advantages: interactive, gamified formats that increase engagement with abstract content; consistent stimulus presentation that supports skill acquisition for learners who benefit from predictable learning environments; and built-in progress monitoring that generates data suitable for behavioral analysis. The challenge is ensuring that technology use is not substituted for individualized assessment and that platform curricula are adapted to each learner's specific profile rather than applied uniformly.

Clinical Implications

Programming for SEL and EF within a behavior analytic framework begins with careful operational definition of target skills. "Emotion regulation" must be broken into component behaviors — each with clear stimulus conditions, response definitions, and reinforcement contingencies — before it can be effectively taught. For example, identifying internal signals of frustration (stimulus control), labeling the emotion (tact training), selecting a coping response from a repertoire (rule-governed behavior), and implementing the response (motor behavior chain) are distinct target behaviors with distinct training procedures.

For learners with ASD, perspective-taking — a core SEL competency — presents particular challenges due to differences in Theory of Mind development. Behavior analytic approaches to perspective-taking draw on Relational Frame Theory and research on deictic relations (I/you, here/there, now/then). Training perspective-taking requires careful shaping of stimulus-stimulus relations and response generalization across novel social scenarios. Technology platforms that provide varied, interactive social scenario presentations can support this generalization in ways that static tabletop materials may not.

Working memory training has a more complex evidence base. While cognitive training programs targeting working memory in isolation have produced mixed results in neuropsychological research, behavioral approaches that embed WM demands within functional skill training — such as following multi-step instructions, maintaining topic during conversation, or tracking game rules — have more direct clinical relevance. The Silas platform's integration of traditional curriculum and technology may allow for this kind of embedded WM practice within meaningful skill contexts.

Practitioners should assess learner responses to technology-based instruction at the outset of programming. Some learners are highly motivated by screen-based formats; others are distracted, overwhelmed, or show reduced attending. Technology should not be used because it is available — it should be used because data indicates that the individual learner responds favorably and shows skill acquisition in this format. Baseline sessions using both technology and tabletop formats, with data on accuracy, latency, and engagement, provide the basis for individualized format decisions.

Ethical Considerations

The integration of technology platforms into behavioral programming raises important ethical questions about data privacy, informed consent, and the equitable use of educational resources. When platforms collect learner data — including performance metrics, session duration, and behavioral patterns — practitioners must ensure that caregivers understand what data is collected, how it is stored, and who has access to it. The BACB Ethics Code's provisions on confidentiality (Code 3.04) apply to electronically collected data as much as to paper records.

There is also an equity dimension to technology-based programming. High-quality platforms like Silas require institutional or agency licenses that may not be accessible to all providers, creating disparities in the quality of SEL and EF programming available to learners in under-resourced settings. BCBAs who have access to these tools should advocate for expanded access and document outcomes in ways that support the evidence base for coverage and funding.

The use of engaging technology formats raises a related concern about stimulus preference and motivation. When a learner is highly motivated by a technology platform, practitioners must ensure that reinforcer potency is tracked and that reinforcement schedules are maintained at levels that sustain learning rather than becoming so rich that the curriculum loses its instructional structure. Technology that functions primarily as a preferred leisure activity without producing skill acquisition is not a clinical tool — it is entertainment, and its use during therapy time requires justification.

Code 2.01 (competence) applies to practitioners who implement technology-based curricula without training in the platform's design principles or the SEL and EF domains it targets. Adequate training in both the technology and the underlying skill domains is a prerequisite for ethical implementation. Where practitioners lack EF or SEL expertise, consultation with school psychologists, neuropsychologists, or developmental specialists is appropriate.

Assessment & Decision-Making

Assessment of SEL and EF skills in learners with ASD and IDD should use multiple methods: standardized rating scales completed by caregivers and teachers (such as the BRIEF-2 for executive functioning), direct observation in natural settings, and structured skill probes using both tabletop and technology-based formats. Standardized measures provide normative comparisons and can track change over time; direct observation provides ecological validity; skill probes identify the specific component behaviors that require instruction.

When selecting between technology-based and traditional tabletop approaches, the decision should be data-informed and learner-specific. Factors to consider include the learner's history of skill acquisition in different formats, current level of attending and task engagement with screen-based stimuli, the availability of trained staff to supervise technology sessions and ensure instructional integrity, and the alignment between the platform's curriculum sequence and the learner's current skill level.

Progress monitoring for SEL and EF targets requires behavioral operationalization of each target, systematic data collection across settings, and regular review of data against mastery criteria. The challenge with SEL and EF targets is that performance in structured teaching sessions does not always generalize to natural settings — a learner who identifies emotional expressions correctly on a tablet may not use that skill in a real social interaction. Practitioners must plan generalization probes from the outset and build cross-setting data collection into the program design.

Decision rules for modifying programming should be established in advance. If a learner shows no meaningful skill acquisition across a defined number of sessions, the intervention must be modified — whether by changing the instructional format, breaking the target into smaller steps, adjusting the reinforcement schedule, or reconsidering whether the skill is appropriate for instruction at this time. Technology platforms should not be exempt from these standard data-based decision rules.

What This Means for Your Practice

If you are not currently programming for SEL and EF skills with your clients, this presentation is an invitation to examine whether you should be. Challenges in emotional regulation, cognitive flexibility, and social cognition are among the most significant barriers to independence and quality of life for many individuals with ASD and IDD — and they are teachable when approached with behavior analytic rigor and appropriate individualization.

For practitioners who already address these domains, the technology integration perspective offers a practical tool for diversifying instructional formats and increasing learner engagement. If you have access to platforms like Silas or comparable technology-based curricula, building in systematic A/B comparisons between technology and traditional formats using your own data can generate clinical knowledge about which formats work for which learners in your caseload.

For supervisors and program directors, this is a domain where staff training is often insufficient. BTs and RBTs may receive training in discrete trial procedures and naturalistic teaching but have limited exposure to the conceptual or procedural content of SEL and EF programming. Building competency in this area through staff training, modeling, and supervised practice is an investment that expands the range of skills the team can effectively address.

Finally, collaborating with school teams and occupational therapists on SEL and EF programming is both clinically advantageous and ethically appropriate. School psychologists bring EF assessment expertise; occupational therapists contribute knowledge of sensory-motor regulation that intersects with EF development; behavior analysts bring the instructional technology that produces reliable skill acquisition. Interdisciplinary collaboration in this domain is not redundancy — it is the most efficient path to comprehensive, effective programming for your clients.