Albert Bandura’s social learning theory (1977) emphasized the importance of observing, modeling, and imitating the behavior of others for learning. This theory has inspired the development of many strategies for learning, including video modeling (VM) interventions. VM interventions involve individuals watching video demonstrations of desired, appropriate behaviors and imitating the model, either immediately or at a later time. Given a long history of strong empirical evidence, researchers have determined that VM meets criteria to be designated as an evidence-based practice (Steinbrenner et al., 2020).
VM interventions comprise a group of interventions in which a video is used to model a target skill or behavior in place of in-vivo modeling. There are a variety of ways that VM can be implemented. For instance, the model could be a familiar person, an unfamiliar person, or even the target individual. Incorporating the target individual as the model, called video self-modeling, involves recording them successfully engaging in the desired behavior, having them watch their own behavior in the video, and instructing them to imitate that behavior (Dowrick, 1999). Video self-modeling interventions have been widely used among individuals with autism of all age ranges to teach a variety of skills including motor, social, communication, self-monitoring, academic, play, functional, vocational, athletic, and emotional regulation (Steinbrenner et al., 2020). For example, video self-modeling might be used to teach a child to tie their shoes where the child watches a video depicting them tying their own shoes prior to being asked to tie their shoes.
In addition to its effectiveness for a wide range of behaviors, VM is very accessible and easy to implement. With the popularity of computers and smartphone devices, the procedural steps of recording, editing, and watching the videos are very feasible and the intervention is cost effective. Further, this intervention has a low likelihood of being stigmatized in public, as using technological devices is widely accepted in society. Additionally, video self-modeling can be used in conjunction with other evidence-based practices, such as prompting or task analysis, to create an individualized treatment program.
Finally, an added benefit of video self-modeling is that it can be easily individualized for specific learners and for specific target behaviors. Professionals and family members can follow these six major steps to develop and implement a video self-modeling intervention (adapted from Wilson, 2013):
- Decision-making. This first step involves making the decision to use video self-modeling. To determine if video self-modeling is appropriate, the individual’s skills should be assessed. Prior research has suggested that video self-modeling interventions are effective for individuals who possess the following prerequisite skills: visual attending, imitation, visual and hearing acuity, and visual information processing and comprehension skills (Shukla-Mehta et al., 2010).
- Determine the target behavior. The next step is to decide which behavior will be targeted. The target behavior must be (a) observable, (b) measurable, and (c) successfully performed by the target individual. Although the individual must successfully engage in the behavior for video self-modeling, it may be a behavior that they require prompting to perform or perform infrequently. For instance, when working on shoe tying it is critical to ensure the learner has the fine motor ability to complete the individual steps of the skill, but they do not need to be able to independently tie their shoe.
- Record and edit the video. In this step, the video is recorded, edited, and evaluated. In general, the video should take place in the setting or settings in which the individual is expected to perform the target behavior, as this has been found to produce greater effects (Bellini et al., 2007). Next, when recording the video, the individual can either be recorded while naturally performing the behavior or performing the behavior with prompting. If the behavior is prompted, it is important to edit the prompts out of the video so that the video shows the individual independently engaging in the behavior. When the video is completed, it can be evaluated for any necessary edits such as sound quality adjustments. If there are distractions or disruptions to the video or audio quality that cannot be edited, it should be rerecorded. Again, using the above scenario of shoe tying, when making the video, someone can tell the learner exactly what to do for each step (e.g., tell them to hold the laces in each hand, to make an X, and so on) and provide additional prompts for how to perform steps (e.g., physically prompt the learner to pinch the laces, model looping one lace around the other). Once the entire sequence of steps has been completed, the video can be edited so that the final video shows the learner tying their shoes unaided.
- Implement the intervention. Prior to actually implementing the intervention, it is critical to determine who will implement it, when it will be implemented, and how frequently the individual will receive the intervention. Further, it is necessary to decide if and what additional practices will be incorporated into the intervention (e.g., task analysis, prompting, reinforcement). Once these decisions have been made, you are ready to implement. The individual should watch the video immediately before they are expected to use the skill (e.g., watching a video of tying shoes before getting ready to go outside). Additionally, research suggests that individuals should view the video two to four times per session (Shukla-Mehta et al., 2010).
- Monitor progress. It is important to set a goal for the individual and collect data so that progress can be monitored. Goals should be clear, objective, and attainable. With video self-modeling, it may be especially appropriate to include self-monitoring data to involve the individual in the progress monitoring process.
- Plan next steps. Lastly, upon reviewing the data, a decision should be made to continue, make adaptations to, or discontinue the intervention. If the intervention was effective, it could be expanded upon to target a new skill. If the individual was not making sufficient progress with the intervention in place, adaptations to the intervention should be made to make it more effective. If the intervention was not effective at all, it should be discontinued and an alternative intervention should be implemented.
Video modeling interventions, including video self-modeling, have proven to be effective for varying age ranges and skills while incorporating observation, modeling and imitation, the key elements of Bandura’s social learning theory (Bandura & McClelland, 1997). VM is easily implemented, following the basic steps presented above, individualized, and can be used with other practices as part of a treatment package. With advancements in technology, the ease of implementation of VM and acceptability of using technology within society demonstrates the adaptability of VM as an effective intervention across ages and behaviors.
Christina Wood, MEd, BCBA, and Amy Thatcher, MEd, RBT, are Registered Behavior Technicians and Elise Settanni, MEd, BCBA, LBS, is a Behavior Analyst at Lehigh University Autism Services.
If you would like more information about Lehigh University Autism Services please contact our office via phone at (610) 758-2441 or visit our website at https://ed.lehigh.edu/center-for-promoting-research-to-practice/autism-services-clinic.
Bandura, A., & McClelland, D. C. (1977). Social learning theory (Vol. 1). Prentice Hall: Englewood Cliffs.
Bellini, S., Akullian, J., & Hopf, A. (2007). Increasing social engagement in young children with autism spectrum disorders using video self-modeling. School Psychology Review, 36(1), 80-90.
Dowrick, P. (1999). A review of self-modeling and related interventions. Applied and Preventive Psychology, 8, 23–39.
Shukla-Mehta, S., Miller, T., & Callahan, K. J. (2010). Evaluating the effectiveness of video instruction on social and communication skills training for children with autism spectrum disorders: A review of the literature. Focus on Autism and Other Developmental Disabilities, 25, 23–36.
Steinbrenner, J. R., Hume, K., Odom, S. L., Morin, K. L., Nowell, S. W., Tomaszewski, B., Szendrey, S., McIntyre, N. S., Yücesoy-Özkan, S., & Savage, M. N. (2020). Evidence-based practices for children, youth, and young adults with autism. The University of North Carolina at Chapel Hill, Frank Porter Graham Child Development Institute, National Clearinghouse on Autism Evidence and Practice Review Team.
Wilson, K. P. (2013). Incorporating video modeling into a school-based intervention for students with autism spectrum disorders. Language, Speech, and Hearing Services in Schools, 44, 105-117.