5 Ways Tech Can Strengthen Social and Emotional Learning

Are social-emotional learning (SEL) and technology schoolyard friends or foes?

SEL consultant Jessica Berlinski says in-person learning and technology can play together. Here, excerpted from her popular post on GettingSmart.com, are five ways tech can strengthen SEL:

1. Self-Directed Learning

Kids are more engaged and learn better when they have a say in the process, whether it’s choosing the content or learning at their own pace and in their own style.

See PREP, the first self-paced, adaptive resilience education intervention designed specifically to meet the learning styles and SEL needs of students with high-functioning autism spectrum disorder (HF-ASD).

Comic book scene from Stories in Motion social visualization game

2. Assessment

There are a wide range of web-based tools for measuring SEL skills and mind-sets, including performance-based assessment and data collection.

See Quest, a child-friendly online data collection system that transforms traditional surveys into an engaging, game-like experience with accommodations for learning challenges.

3. Personalization

Adaptive technology individualizes instruction, so students are neither bored because the content is too easy, nor lost because they can’t keep up.

See Zoo U, a social skills role-play game for grades 2–5 that uses adaptive technology to adjust the difficulty level for each student, challenging and supporting the child as needed.

4. Ensuring Fidelity

Adherence-monitoring tools help providers implement evidence-based programs as intended to achieve the desired outcomes.

See Centervention, a powerful suite of customizable web-based tools to support quality implementation of evidence-based programs in schools, clinics, and community agencies.

5. Building Agency

Digital learning games are a popular and effective option for engaging, motivating, and empowering students.

See Stories in Motion, an online game that empowers elementary students with autism spectrum disorder to improve their social skills by creating illustrated narratives around challenging social scenarios (see sample scene above).

Read the full article.

Contact us at services@3cisd.com or 888.598.0103 to discuss how our programs and technologies can support your work in social and emotional learning.

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    DEB CHILDRESS, PHD

    Chief of Research and Learning Content

    BIOGRAPHY

    Dr. Childress obtained her PhD in psychology at the University of North Carolina at Chapel Hill. Prior to coming to 3C Institute, she served as a research associate and a postdoctoral fellow in the Carolina Institute for Developmental Disabilities at the University of North Carolina at Chapel Hill working on a longitudinal imaging study aimed at identifying the early markers of autism through behavioral and imaging methodologies. She has 19 years of autism research experience, during which she has examined the behavioral, personality, and cognitive characteristics of individuals with autism and their family members. Dr. Childress also has experience developing behavioral and parent report measurement tools, coordinating multi-site research studies, and collecting data from children and families. She has taught courses and seminars in general child development, autism, and cognitive development at the University of North Carolina at Chapel Hill.

    Expertise

    • autism
    • early development
    • behavioral measurement
    • integrating behavioral and biological measurement

    Education

    • Postdoctoral fellowship, Carolina Institute for Developmental Disabilities (Institutional NRSA-NICHD), University of North Carolina at Chapel Hill
    • PhD, developmental psychology, University of North Carolina at Chapel Hill
    • BS, psychology (minor in sociology), University of Iowa

    Selected Publications

    • Elison, J. T., Wolff, J. J., Heimer, D. C., Paterson, S. J., Gu, H., Hazlett, H. C., Styner, M, Gerig, G., & Piven, J. (in press). Frontolimbic neural circuitry at 6 months predicts individual differences in joint attention at 9 months. Developmental Science.
    • Wassink, T. H., Vieland, V. J., Sheffield, V. C., Bartlett, C. W., Goedken, R., Childress, D. & Piven, J. (2008). Posterior probability of linkage analysis of autism dataset identifies linkage to chromosome 16. Psychiatric Genetics,18(2),85-91.
    • Losh, M., Childress, D., Lam K. & Piven, J. (2008). Defining key features of the broad autism phenotype: A comparison across parents of multiple- and single-incidence autism families. American Journal of Medical Genetics (Neuropsychiatric Genetics), 147B(4):424-33.
    • Wassink, T. H., Piven, J., Vieland, V. J., Jenkins, L., Frantz R., Bartlett, C. W., Goedken, R., … Sheffield, V.C. (2005). Evaluation of the chromosome 2q37.3 gene CENTG2 as an autism susceptibility gene. American Journal of Medical Genetics (Neuropsychiatric Genetics), 136, 36-44.
    • Barrett, S., Beck, J., Bernier, R., Bisson, E., Braun, T., Casavant, T., Childress, D., … Vieland, V. (1999). An autosomal genomic screen for autism. American Journal of Medical Genetics (Neuropsychiatric Genetics), 88, 609-615. doi: 10.1002/(SICI)1096-8628(19991215)88:63.0.CO;2-L
    • Piven, J., Palmer, P., Landa, R., Santangelo, S., Jacobi, D. & Childress, D. (1997). Personality and language characteristics in parents from multiple-incidence autism families. American Journal of Medical Genetics (Neuropsychiatric Genetics), 74, 398-411.
    • Piven, J., Palmer, P., Jacobi, D., Childress, D. & Arndt, S. (1997). Broader autism phenotype: Evidence from a family history study of multiple-incidence autism families. American Journal of Psychiatry, 154, 185-190.