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Using a Mobile Device for Early Childhood Classroom Behavior Data Collection

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Abstract

Over one-third of preschoolers with disabilities are fully included in the classroom with their typically developing peers and another large percentage receive some instruction in the inclusive classroom. In order to support young children and increase the likelihood of the desired learning and behavior outcomes, teachers must use individual data for each child to guide decisions regarding instructional and behavioural interventions. Many early childhood special educators are busy and struggle to find an efficient way to collect data on a regular basis. One solution is the use of smartphone or tablet tools. This article provides early childhood special educators with recommendations for individual child data collection through the use of easy-to-use tools that can be customized to meet teacher and classroom needs. Specifically, we recommend the use of: (a) Google forms, (b) video and audio recordings, (c) speech-to-text technology, (d) counter apps, and (e) the smartphone stopwatch function.

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References

  • Bardhoshi, G., Swanston, J., & Kivlinghan, D. M. (2020). Social-behavioral stories in the kindergarten classroom: An app-based counseling intervention for increasing social skills. Professional School Counseling, 23(1), 215.

    Google Scholar 

  • Bicard, S. C, Bicard, D. F., & the IRIS Center. (2012). Measuring behavior. http://iris.peabody.vanderbilt.edu/wp-content/uploads/pdf_case_studies/ics_measbeh.pdf

  • Brawley, S., & Stormont, M. A. (2014). Investigating reported data practices in early childhood: An exploratory study. Journal of Positive Behavior Interventions, 16(2), 102–111.

    Article  Google Scholar 

  • Bruhn, A. L., Rila, A., Mahatmya, D., Estrapala, S., & Hendrix, N. (2020). The effects of data-based, individualized interventions for behavior. Journal of Emotional and Behavioral Disorders, 28(1), 3–16.

    Article  Google Scholar 

  • Collier-Meek, M. A., Sanetti, L. M. H., Gould, K., & Pereira, B. (2021). An exploratory comparison of three treatment fidelity assessment methods: Time sampling, event recording, and post-observation checklist. Journal of Educational and Psychological Consultation, 31(3), 334–359. https://doi.org/10.1080/10474412.2020.1777874

    Article  Google Scholar 

  • Dillon, M. B. M., Radley, K. C., Tingstrom, D. H., Dart, E. H., Barry, C. T., & Codding, R. (2019). The effects of tootling via ClassDojo on young child behavior in elementary classrooms. School Psychology Review, 48(1), 18–30.

    Article  Google Scholar 

  • Elswick, S., Casey, L. B., Zanskas, S., Black, T., & Schnell, R. (2016). Effective data collection modalities utilized in monitoring the good behavior game: Technology-based data collection versus hand collected data. Computers in Human Behavior, 54, 158–169.

    Article  Google Scholar 

  • Esposito, M., Sloan, J., Tancredi, A., Gerardi, G., Postiglione, P., Fotia, F., Napoli, E., Mazzone, L., Valeri, G., & Vicari, S. (2017). Using tablet applications for children with autism to increase their cognitive and social skills. Journal of Special Education Technology, 32(4), 199–209.

    Article  Google Scholar 

  • Evans, J. A. (2018). The educational equity imperative: Leveraging technology to empower learning for all. https://tomorrow.org/

  • Gage, N. A., Haydon, T., MacSuga-Gage, A. S., Flowers, E., & Erdy, L. (2020). An evidence-based review and meta-analysis of active supervision. Behavioral Disorders, 45(2), 117–128.

    Article  Google Scholar 

  • Gischlar, K., Hojnoski, R., & Missall, K. (2009). Data-based decision making to improve child outcomes: Interpreting and using data. Young Exceptional Children, 13(1), 2–18.

    Article  Google Scholar 

  • Gridley, N., Bywater, T. J., & Hutchings, J. M. (2018). Comparing live and video observation to assess early parent-child observations in the home. Journal of Child & Family Studies, 27(6), 1818–1829.

    Article  Google Scholar 

  • Gulec-Aslan, Y. (2020). Experiences of Turkish preschool teachers for including children with autism spectrum disorders: Challenges faced and methods used. International Journal of Psychology and Educational Studies, 7(2), 37–49. https://doi.org/10.17220/ijpes.2020.02.004

    Article  Google Scholar 

  • Halle, J. W., & Sindelar, P. T. (1982). Behavioral observation methodologies for early childhood education. Topics in Early Childhood Special Education, 2(1), 43–54. https://doi.org/10.1177/027112148200200109

    Article  Google Scholar 

  • Hershfedlt, P. A., Pell, K., Sechrest, R., Pas, E. T., & Bradhshaw, C. P. (2012). Lessons learned coaching teachers in behavior management: The PBISplus coaching model. Journal of Educational and Psychological Consultation, 22(4), 280–299. https://doi.org/10.1080/10474412.2012.731293

    Article  Google Scholar 

  • Horner, R. H., Sugai, G., Todd, A. W., & Lewis-Palmer, T. (1999–2000). Elements of behavioral support plans: A technical brief. Exceptionality, 8(3), 205–215.

  • Jasper, A. D., & Doughty, T. T. (2014). Special educators and data recording: What’s delayed recording got to do with it? Focus on Autism and Other Developmental Disabilities, 30(3), 143–153.

    Article  Google Scholar 

  • Jung, P. G., McMaster, K. L., & delMas, R. C. (2017). Effects of early writing intervention delivered within a data-based instruction framework. Exceptional Children, 83(3), 281–297.

    Article  Google Scholar 

  • Kovacs, K. (2020). Inclusion of intellectually disabled children in early childhood education in Hungary in light of the law. International Dialogues on Education, 7(2), 70–79.

    Google Scholar 

  • Krasch, D., & Carter, D. R. (2009). Monitoring classroom behavior in early childhood: Using group observation data to make decisions. Early Childhood Education Journal, 36(6), 475–482.

    Article  Google Scholar 

  • Kubina, R. M., & Lin, F. Y. (2008). Defining frequency: A natural scientific term. The Behavior Analyst Today, 9(2), 125–129.

    Article  Google Scholar 

  • Ledbetter-Cho, K., O’Reilly, M., Lang, R., Watkins, L., & Lim, N. (2018). Meta-analysis of tablet-mediated interventions for teaching academic skills to individuals with autism. Journal of Autism & Developmental Disorders, 48(9), 3021–3036.

    Article  Google Scholar 

  • Lewis, T. J., Scott, T. M., Wehby, J. H., & Wills, H. P. (2014). Direct observation of teacher and behavior in school settings: Trends, issues, and future directions. Behavioral Disorders, 39(4), 190–200.

    Article  Google Scholar 

  • Lynne, S., Radley, K. C., Dart, E. H., Tingstrom, D. H., Barry, C. T., & Lum, J. D. K. (2017). Use of a technology-enhanced version of the good behavior game in an elementary school setting. Psychology in the Schools, 54(9), 1049–1063.

    Article  Google Scholar 

  • Martella, R. C., Nelson, J. R., Marchand-Martella, N. E., & O’Reilly, M. (2012). Comprehensive behavior management: Individualized, classroom, and schoolwide approaches. SAGE Publications.

    Book  Google Scholar 

  • Merbitz, C. T., Merbitz, N. H., & Pennypacker, H. S. (2016). On terms: Frequency and rate in applied behavior analysis. The Behavior Analyst, 39(2), 333–338.

    Article  Google Scholar 

  • National Center for Education Statistics. (2021). Meeting the challenges of data collection. https://nces.ed.gov/pubs2002/safety/chapter2.asp

  • Outhwaite, L. A., Faulder, M., Gulliford, A., & Pitchford, N. J. (2019). Raising early achievement in math with interactive apps: A randomized control trial. Journal of Educational Psychology, 111(2), 284–298.

    Article  Google Scholar 

  • Prenger, R., & Schildkamp, K. (2018). Data-based decision making for teacher and young child learning: A psychological perspective on the role of the teacher. Educational Psychology, 6, 734–752.

    Article  Google Scholar 

  • Robacker, C. M., Rivera, C. J., & Warren, S. H. (2016). A token economy made easy through ClassDojo. Intervention in School and Clinic, 52(1), 39–43.

    Article  Google Scholar 

  • Ruble, L. A., McGrew, J. H., Wong, W. H., & Missal, K. N. (2018). Special education teachers’ perceptions and intentions towards data collection. Journal of Early Intervention, 40(2), 177–191.

    Article  Google Scholar 

  • Rutherford, R. B., & Nelson, C. M. (1988). Generalization and maintenance of treatment effects. In J. C. Witt, S. N. Elliot, & F. M. Gresham (Eds.), Handbook of behavior therapy in education. Springer.

    Google Scholar 

  • Sax, L. J., Gilmartin, S. K., & Bryant, A. N. (2003). Assessing response rates and non response bias in web and paper surveys. Research in Higher Education, 44(4), 409–431.

    Article  Google Scholar 

  • Smith, B., & Mader, J. (2015). Collaborative data collection via Google Forms. The Science Teacher, 82(1), 3.

    Article  Google Scholar 

  • Tiger, J. H., Miller, S. J., Mevers, J. L., Mintz, J. C., Scheithauer, M. C., & Alvarez, J. (2013). On the representativeness of behavior observation samples in classrooms. Journal of Applied Behavior Analysis, 46(2), 424–435.

    Article  Google Scholar 

  • Weisz, J. R., Chaiyasit, W., Weiss, B., Eastman, K. L., & Jackson, E. W. (1995). A multimethod study of problem behavior among Thai and American children in school: Teacher reports versus direct observations. Child Development, 66(2), 402–415.

    Article  Google Scholar 

  • Yoke-Yean, L. F., Soo-Boon, N., Poai-Hong, W., Hui-Shen, C. L., MohdMultazamKhair, N. S., Haq, F. S., Dhamotharan, M., & Mustafa, M. C. (2021). The impact of national policies on accessibility to quality early childhood care and education in Malaysia: Policymaker’s perspectives. Southeast Asia Early Childhood Journal, 10(1), 63–76. https://doi.org/10.37134/saecj.vol10.sp.6.2021

    Article  Google Scholar 

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Correspondence to Marla J. Lohmann.

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Lohmann, M.J., Riggleman, S. & Higgins, J.P. Using a Mobile Device for Early Childhood Classroom Behavior Data Collection. Early Childhood Educ J 52, 427–434 (2024). https://doi.org/10.1007/s10643-023-01443-5

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