A Developmental Model for Adaptive and Differentiated Instruction Using Classroom Networking Technology

  • Allan BellmanEmail author
  • Wellesley R. Foshay
  • Danny Gremillion
Part of the Mathematics Education in the Digital Era book series (MEDE, volume 2)


This paper presents a detailed explanatory model for adaptive and differentiated instruction. The model combines current practices for mathematics instruction with recommended practices for formative assessment. The model can best be implemented using classroom network technologies (such as TI-Nspire Navigator with TI handhelds), but it can also be used with manual data collection means such as personal whiteboards for each student. The model is presented for mathematics, but could be easily extended to science instruction or other subjects. Experience with adaptive and differentiated instruction suggests that teachers grow to full master level proficiency over time, often over a period of years, and that some teachers never reach that level. Accordingly, two transitional models are presented, an immediate (entry-level) model and an expert model for adaptive instruction. Fully differentiated instruction is incorporated in the ‘Master’ model. Growth from immediate, to expert, to master level requires development of skill with the technology, but more important are critical changes we infer in the teacher’s beliefs, as well as growth in their pedagogical content knowledge (PCK).


Adaptive learning Classroom networking Connected classroom Differentiated instruction Mathematics education STEM education 


  1. Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5, 1.CrossRefGoogle Scholar
  2. Center for Technology in Learning, S. I. (2009). Does teacher knowledge of students’ thinking in a network-connected classroom improve mathematics achievement? TI EdTech Research Note #14. Dallas: Texas Instruments.Google Scholar
  3. Charmaz, K. (2000). Grounded theory: Constructivist and objectivist methods. In N. Denzin & Y. Lincoln (Eds.), Handbook of qualitative research (2nd ed., pp. 509–535). Thousand Oaks: Sage.Google Scholar
  4. Clark-Wilson, A. (2009). Connecting mathematics in the connected classroom: TI-Nspire™ Navigator™. Chichester: The Mathematics Centre- University of Chichester.Google Scholar
  5. Clark-Wilson, A. (2010a). Emergent pedagogies and the changing role of the teacher in the TI-Nspire Navigator-networked mathematics classroom. ZDM, 1–15. doi: 10.1007/s11858-010-0279-0CrossRefGoogle Scholar
  6. Clark-Wilson, A. (2010b). Emergent pedagogies and the changing role of the teacher in the TI-Nspire Navigator-networked mathematics classroom. ZDM, 42(7), 747–761. doi: 10.1007/s11858-010-0279-0.CrossRefGoogle Scholar
  7. Cox, S. (2008). A conceptual analysis of technological pedagogical content knowledge. Ph.D. dissertation, Brigham Young University, Provo.Google Scholar
  8. Dwyer, D. C., Ringstaff, C., & Sandholtz, J. H. (1992). The evolution of teachers’ instructional beliefs and practices in high-access-to-technology classrooms first-fourth year findings ACOT. Cupertino: Apple Computer, Inc.Google Scholar
  9. Graham, C. R. (2011). Theoretical considerations for understanding technological pedagogical content knowledge (TPACK). Computers in Education, 57(3), 1953–1960. doi: 10.1016/j.compedu.2011.04.010.CrossRefGoogle Scholar
  10. Hall, G., Loucks, S., Rutherford, W., & Newlove, B. (1975). Levels of use of the innovation: A framework for analyzing innovation adoption. Journal of Teacher Education, 26(1), 52–56.CrossRefGoogle Scholar
  11. Heritage, M., & Stigler, J. W. F. R. W. (2010). Formative assessment: Making it happen in the classroom. Thousand Oaks: Sage.Google Scholar
  12. Hill, H. C., Ball, D. L., & Schilling, S. G. (2008). Unpacking pedagogical content knowledge: Conceptualizing and measuring teachers’ topic-specific knowledge of students. Journal for Research in Mathematics Education, 39(4), 372–400.Google Scholar
  13. Niess, M. L., Ronau, R. N., Shafer, K. G., Driskell, S. O., R., H. S., Johnston, C.,… Kersaint, G. (2009). Mathematics teacher TPACK standards and development model. Contemporary Issues in Technology and Teacher Education, 9(1), 4–24.Google Scholar
  14. Penuel, W. R., Beatty, I., Remold, J., Harris, C. J., Bienkowski, M., & DeBarger, A. H. (submitted). Pedagogical patterns to support interactive formative assessment with classroom response systems. Journal of Technology, Learning, and Assessment.Google Scholar
  15. Penuel, W., & Singleton, C. (2010). Classroom network technology as a support for systemic mathematics reform: Examining the effects of Texas instruments’ MathForward Program on student achievement in a large, diverse district. Journal of Computers in Mathematics and Science Teaching (JCMST), 30(2), 179–202.Google Scholar
  16. Popham, W. J. (2008). Transformative assessment. Alexandria: ASCD.Google Scholar
  17. Roschelle, J. (2009). Towards highly interactive classrooms: Improving mathematics teaching and learning with TI-Nspire Navigator. Menlo Park: SRI Center for Technology and Learning, SRI International.Google Scholar
  18. Roschelle, J. (2011). Improving student achievement by systematically integrating effective technology. Journal of Mathematics Education Leadership, 13, 3–11.Google Scholar
  19. Ruthven, K. (2009). Towards a naturalistic concepualisation of technology integration in classroom practice: The example of school mathematics. Education & Didactique, 3(1), 131–149.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Allan Bellman
    • 1
    Email author
  • Wellesley R. Foshay
    • 2
    • 3
  • Danny Gremillion
    • 2
    • 3
  1. 1.University of MississippiOxfordUSA
  2. 2.Walden UniversityMinneapolisUSA
  3. 3.Texas Instruments Education Technology GroupDallasUSA

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