What I Read for the Week of September 2, 2024

As I continue my journey in the Doctorate in Educational Technology (DET) program, Week 2 brought an equally thought-provoking set of readings focused on educational research and its various challenges and methodologies. Below, I’ve summarized the key points from the articles I reviewed, highlighting how they align with my interests in creating AI-driven platforms for special education, particularly for autistic students.

1. Educational Research: The Hardest Science of All (Berliner, 2002)

In this article, Berliner argues that educational research is more complex than research in the hard sciences due to the variability and unpredictability of human behavior. Unlike physical sciences, where controlled environments are possible, educational settings are influenced by countless factors, making it difficult to apply universal standards. Berliner’s perspective is particularly relevant to my work, as the challenge of addressing diverse needs in special education highlights the importance of flexible, adaptable learning platforms.

2. The Peculiar Problems of Preparing Educational Researchers (Labaree, 2003)

Labaree identifies three core challenges in preparing educational researchers: the balance between theory and practice, the tension between scientific rigor and practical utility, and the difficulty of navigating the academic and practical realms of education. These insights remind me that as I develop educational tools for autistic students, I must ensure that they are not only theoretically sound but also practical and easy to implement in real-world settings.

3. Relevance to Practice as a Criterion for Rigor (Gutierrez & Penuel, 2014)

Gutierrez and Penuel argue that relevance to practice should be a core criterion for rigor in educational research. They emphasize that educational research must engage with real-world problems and collaborate with practitioners to ensure that research findings have practical utility. This article strongly aligns with my research goal of developing platforms that address practical challenges faced by educators in special education, ensuring that the technology I create is both effective and implementable.

4. Disciplines of Inquiry in Education: An Overview (Shulman, 1981)

Shulman provides an overview of various research methodologies used in education, emphasizing the interdisciplinary nature of the field. He highlights the need for balance between qualitative and quantitative approaches, a perspective that resonates with my interest in integrating data-driven insights with human-centered approaches when designing learning platforms for autistic students.

5. Computer Applications in Teaching Play Skills to Children with Autism Spectrum Disorder (2020)

This article explores how technology can be used to teach essential social and play skills to children with autism. It emphasizes the importance of personalized and adaptive learning tools, which align with my research focus on leveraging AI to create customized educational programs for autistic students. The findings support my belief that AI-driven platforms can improve engagement and learning outcomes for students on the autism spectrum.

References

  • Berliner, D. C. (2002). Educational research: The hardest science of all. Educational Researcher, 31(8), 18-20.
  • Labaree, D. F. (2003). The peculiar problems of preparing educational researchers. Educational Researcher, 32(4), 13–22.
  • Gutierrez, K. D., & Penuel, W. R. (2014). Relevance to practice as a criterion for rigor. Educational Researcher, 43(1), 19-23.
  • Shulman, L. S. (1981). Disciplines of inquiry in education: An overview. Educational Researcher, 10(6), 5-12, 23.
  • 2020. Computer Applications in Teaching Play Skills to Children with Autism Spectrum Disorder. Journal of Special Education Technology.
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