Skip to main content

Advertisement

SpringerLink
Log in

Evaluating Assistive Technology in Early Childhood Education: The Use of a Concurrent Time Series Probe Approach

  • Published:
Early Childhood Education Journal Aims and scope Submit manuscript

Abstract

As assistive technology applications are increasingly implemented in early childhood settings for children who are at risk or who have disabilities, it is critical that teachers utilize observational approaches to determine whether targeted assistive technology-supported interventions make a difference in children’s learning. One structured strategy that employs observations and which has powerful child progress monitoring implications is the concurrent time series probe approach. Requiring multiple performance measures of a child engaged in a targeted task over time—both with and without a specific assistive technology device—the concurrent time series probe approach can be used to evaluate the effectiveness of assistive technology tools in supporting skill acquisition in the classroom. This approach is described in the context of a case study, with accompanying explanations of how to interpret data and make decisions regarding the effectiveness of the technology.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Alberto, P. A., & Troutman, A. C. (2009). Applied behavior analysis for teachers (8th ed.). Upper Saddle River, NJ: Pearson Education, Inc.

    Google Scholar 

  • Anderson, D., & Lignugaris/Kraft, B. (2006). Video-case instruction for teachers of students with problem behaviors in general and special education classrooms. Journal of Special Education Technology, 21(2), 31–45.

    Google Scholar 

  • Bagnato, S. J., & Neisworth, J. T. (1991). Assessment for early intervention: Best practices for professionals. New York: Guilford.

    Google Scholar 

  • Barton, E. E., Reichow, B., & Wolery, M. (2007). Guidelines for graphing data with Microsoft® PowerPoint™. Journal of Early Intervention, 29, 320–336. doi:10.1177/105381510702900404.

    Article  Google Scholar 

  • Blum, C., & Watts, E. H. (2008). Ready-to-go curriculum. Normal, IL: Illinois State University.

    Google Scholar 

  • Brassard, M. R., & Boehm, A. E. (2007). Preschool assessment. Principles and practices. New York: Guilford.

    Google Scholar 

  • Butler, C. (1986). Effects of powered mobility on self-initiated behaviors of very young children with locomotor disability. Developmental Medicine and Child Neurology, 28, 325–332.

    Article  Google Scholar 

  • Carnine, D., Grossen, B., & Silbert, J. (1995). Direct instruction to accelerate cognitive growth. In J. Block, S. Everson, & T. Guskey (Eds.), Choosing research-based school improvement programs (pp. 129–152). New York: Scholastic.

    Google Scholar 

  • Center for Technology in Education Technology, Media Division. (2005). Considering the need for assistive technology within the individualized education program. Columbia, MD and Arlington, VA: Author.

    Google Scholar 

  • Cohen, D., Stern, V., & Balaban, N. (1997). Observing and recording the behavior of young children (4th ed.). New York: Teachers College Press.

    Google Scholar 

  • Coleman, M. R., Buysse, V., & Neitzel, J. (2006). Recognition and response: An early intervening system for young children at-risk for learning disabilities. Executive summary. Chapel Hill, NC: University of North Carolina at Chapel Hill.

    Google Scholar 

  • Cook, R. E., Klein, M. D., & Tessier, A. (2008). Adapting early childhood curricula for children in inclusive settings. Upper Saddle River, NJ: Pearson Merrill Prentice Hall.

    Google Scholar 

  • Copple, C., & Bredekamp, S. (2009). Developmentally appropriate practice in early childhood programs serving children from birth through age 8 (3rd ed.). Washington, DC: National Association for the Education of Young Children.

    Google Scholar 

  • Daniels, L. E., Sparling, J. W., Reilly, M., & Humphrey, R. (1995). Use of assistive technology with young children with severe and profound disabilities. Infant-Toddler Intervention, 5, 91–112.

    Google Scholar 

  • Division for Early Childhood. (2007). Promoting positive outcomes for children with disabilities: Recommendations for curriculum, assessment, and program evaluation. Missoula, MT: Author.

    Google Scholar 

  • Edyburn, D. (2002). Measuring assistive technology outcomes: Key concepts. Journal of Special Education Technology, 18, 1–14.

    Google Scholar 

  • Grisham-Brown, J., Hemmeter, M. L., & Pretti-Frontczak, K. (2005). Blended practices for teaching young children in inclusive settings. Baltimore: Brookes.

    Google Scholar 

  • Helm, J. H., Beneke, S., & Steinheimer, K. (2007). Windows on learning: Documenting young children’s work. New York: Teachers College Press.

    Google Scholar 

  • Howell, R. D., Erickson, K., Stanger, C., Wheaton, J. E. (2000). Evaluation of a computer-based program on the reading performance of first grade students with potential for reading failure. Journal of Special Education Technology, 15(4), Retrieved January 26, 2009, from http://www.intellimathics.com/pdf/research/Research_Literacy.pdf.

  • Individuals with Disabilities Education Improvement Act. (2004). 20 U.S.C. §§ 1400 et seq.

  • Intellitools®. (2007a). IntelliTools ® Classroom Suite 4 [computer software]. Petaluma, CA: Cambium Learning, Inc.

  • Intellitools®. (2007b). The research basis for Intellitools products. Petaluma, CA: Cambium Learning, Inc.

  • Judge, S. (2006). Constructing an assistive technology toolkit for young children: Views from the field. Journal of Special Education Technology, 21(4), 17–24.

    Google Scholar 

  • Judge, S. L., & Parette, H. P. (Eds.). (1998). Assistive technology for young children with disabilities: A guide to providing family-centered services. Cambridge, MA: Brookline.

    Google Scholar 

  • Kazdin, A. E. (1982). Single-case research designs: Methods for clinical and applied settings. New York, NY: Oxford University Press.

    Google Scholar 

  • Lane, S. J., & Mistrett, S. G. (1996). Play and assistive technology issues for infants and young children with disabilities: A preliminary examination. Focus on Autism and Other Developmental Disabilities, 11, 96–104. doi:10.1177/108835769601100205.

    Article  Google Scholar 

  • Lehrer, R., Harckham, L., Archer, P., & Pruzek, R. (1986). Microcomputer-based instruction in special education. Journal of Educational Computing Research, 2, 337–355.

    Google Scholar 

  • Meisels, S. J., & Atkins-Burnett, S. (2005). Developmental screening in early childhood: A guide (5th ed.). Washington, DC: National Association for the Education of Young Children.

    Google Scholar 

  • Mistrett, S. (2004). Assistive technology helps young children with disabilities participate in daily activities. Technology in Action, 1(4), 1–8.

    Google Scholar 

  • Mistrett, S. G., Lane, S. J., & Ruffino, A. G. (2005). Growing and learning through technology: Birth to five. In D. Edyburn, K. Higgins, & R. Boone (Eds.), Handbook of special education technology research and practice (pp. 273–308). Whitefish Bay, WI: Knowledge by Design.

    Google Scholar 

  • Mulkey, L. M. (1988). Using two instruments to measure student gains in reading achievement when assessing the impact of educational programs. Evaluation Review, 12, 571–587. doi:10.1177/0193841X8801200506.

    Article  Google Scholar 

  • National Association for the Education of Young Children and the National Association of Early Childhood Specialists in State Departments of Education. (2004). Early childhood curriculum, assessment, and program evaluation. Building an effective, accountable system in programs for children birth through age 8. Washington, DC: Author.

    Google Scholar 

  • Neuman, S. B., & Dickinson, D. K. (Eds.). (2001). Handbook of early literacy research. New York: Guilford.

    Google Scholar 

  • No Child Left Behind Act. (2001). 20 U.S.C. §§ 6301 et seq.

  • Odom, S. L., Brantlinger, E., Gersten, R., Horner, R. H., Thompson, B., & Harris, K. R. (2005). Research in special education: Scientific methods and evidence-based practices. Exceptional Children, 71, 137–148.

    Google Scholar 

  • Parette, P. (2006). Assessment for assistive technology. Workshop presented at the National Association of School Psychologists 2006 Annual Convention, Anaheim, CA.

  • Parette, H. P., Blum, C., Meadan, H., Watts, E. (2008). Implementing and monitoring assistive technology: How to use concurrent time series designs and interpret outcomes. Poster presentation to the National Association for the Education of Young Children 2008 Annual Conference and Expo, Dallas, TX.

  • Parette, H. P., Hourcade, J. J., Boeckmann, N. M., & Blum, C. (2008b). Using Microsoft® PowerPoint™ to support emergent literacy skill development for young children at-risk or who have disabilities. Early Childhood Education Journal, 36, 233–239. doi:10.1007/s10643-008-0275-y.

    Article  Google Scholar 

  • Parette, H. P., Peterson-Karlan, G. R., Smith, S. J., Gray, T., & Silver-Pacuilla, H. (2006). The state of assistive technology: Themes from an outcomes summit. Assistive Technology Outcomes and Benefits, 3, 15–33.

    Google Scholar 

  • Parette, H. P., Peterson-Karlan, G. R., Wojcik, B. W., & Bardi, N. (2007). Monitor that progress! Interpreting data trends for assistive technology decision-making. Teaching Exceptional, 39(7), 22–29.

    Google Scholar 

  • Parette, H. P., & VanBiervliet, A. (1991). Assistive technology guide for young children with disabilities. Little Rock, AR: University of Arkansas at Little Rock. (ERIC Document Reproduction Service No. ED324888).

    Google Scholar 

  • Rosenshine, B. (1986). Synthesis of research on explicit teaching. Educational Leadership, 43, 60–69.

    Google Scholar 

  • Sandall, S., Hemmeter, M. L., Smith, B. J., & McLean, M. E. (2005). DEC recommended practices. A comprehensive guide for practical application in early intervention/early childhood special education. Missoula, MT: Division for Early Childhood.

    Google Scholar 

  • Schepis, M., Reid, D., Behrmann, M., & Sutton, K. (1998). Increasing communicative interactions of young children with autism using a voice output communication aid and naturalistic teaching. Journal of Applied Behavior Analysis, 31, 561–578. doi:10.1901/jaba.1998.31-561.

    Article  Google Scholar 

  • Schermerhorn, P. K., & McLaughlin, T. F. (1997). Effects of the add-a-word spelling program on test accuracy, grades, and retention of spelling works with fifth and sixth grade regular education students. Child & Family Behavior Therapy, 19, 23–35. doi:10.1300/J019v19n01_02.

    Article  Google Scholar 

  • Sindelar, N. (2006). Using test data for student achievement. Lanham, MD: Rowman & Littlefield.

    Google Scholar 

  • Smith, R. O. (2000). Measuring assistive technology outcomes in education. Diagnostique, 25, 273–290.

    Google Scholar 

  • Watts, E. H., O’Brian, M., & Wojcik, B. W. (2004). Four models of assistive technology consideration: How do they compare to recommended educational assessment practices? Journal of Special Education Technology, 19, 43–56.

    Google Scholar 

Download references

Acknowledgments

This article is supported through a grant from the Illinois Children’s Healthcare Foundation to the Special Education Assistive Technology (SEAT) Center at Illinois State University. Content presented is based on a presentation at the National Association for the Education of Young Children 2008 Annual Conference and Expo.

Author information

Authors and Affiliations

  1. Department of Special Education, Illinois State University, P.O. Box 5910, Normal, IL, 61790-5910, USA

    Howard P. Parette & Craig Blum

  2. Department of Communication Sciences and Disorders, Illinois State University, P.O. Box 4720, Normal, IL, 61790-4720, USA

    Nichole M. Boeckmann

Authors
  1. Howard P. Parette
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Craig Blum
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nichole M. Boeckmann
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Howard P. Parette.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Parette, H.P., Blum, C. & Boeckmann, N.M. Evaluating Assistive Technology in Early Childhood Education: The Use of a Concurrent Time Series Probe Approach. Early Childhood Educ J 37, 5–12 (2009). https://doi.org/10.1007/s10643-009-0319-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10643-009-0319-y

Keywords

Search

Navigation