Personalized Learning

This week in CEP 811, we revisited learning theories discussed in CEP 810 such as Bransford, Brown, and Cocking’s How People Learn and O’Donnell’s chapter on Construtivism. Additionally, we watched Richard Culatta’s Ted talk about the digital divide to guide our thinking of how we can use technology to reimagine teaching and learning in our classrooms. Culatta discusses the importance of using technology to transform learning as opposed to using technology to digitize traditional learning practices. One recommendation included using data collection to personalize learning. Below I’ve included a summary of two articles related to personalized learning and commentary on how this research extends to maker education.

The first article I read about personalized learning, tailoring instruction to the needs of each learners’ interests and academic needs, explored how to implement this style of instruction into a classroom of diverse learners. Research was conducted to determine how to operationalize personalized learning and to determine the potential levels of success students with disabilities demonstrate in a personalized learning environment. Elements of personalized learning that can lead to growth outcomes for students with disabilities include include highly self-regulated environments, transparent and actionable data, student voice, and diversified assessment (Basham et al, 2016). A driving factor of effective personalized learning environments included planning with  UDL framework, understanding the how, what, and why students are learning. Intentional planning with multiple pathways to acquire information was key to promoting success for diverse learners (Basham, Hall, Carter, & Stahl, 2016).

The second article explores personalized learning in relation to the corporatization of K-12 education. The article argues that personalized learning technologies reflect corporate-driven educational policies and priorities such as high-stakes testings and privatization without achieving an innovative learning environment (Roberts-Mahoney, Means, & Garrison, 2016). The research analyzes documents including U.S. Department of Education reports, learning analytics, and personalized learning advocacy papers to explore narratives relating to the purpose of education, role of data in education, the role of the teacher and conceptualize learning. All of the documents emphasized education as a means to prepare career readiness as opposed to preparing informed active citizens (Roberts-Mahoney et al, 2016). It also states that the rhetoric around personalized learning included that it was a service or customizable based on data collection of standardized test scores and cognitive measures of performance without including non-cognitive data points relating to interpersonal and intrapersonal skills.

After reading the two articles about personalized learning, it is apparent the teacher must create opportunities to make learning accessible to students in an innovative way. The first article identifies self regulation as an important component of personalized learning, which relates to Culatta’s discussion of student agency to give students the opportunity to make decisions about how they learn. The key to personalized learning  as discussed by Culatta is to “reimagine learning.” The second article states that personalized learning technologies reflect corporate-driven ed policies, however it is important to consider the idea of repurposing technology for classroom use rather that solely seeking out technologies created for personalized learning. Both articles left me wondering: How can I use technologies to reimagine learning in my classrooms? What does reimagination look like in an ELA classroom? How will the idea of “reimagination”be received by students who may have limited experiences with student driven inquiry?

Maker education and personalized learning fit nicely together. Maker education gives agency to the student creator by allowing students to explore content in a creative way. It allows for a diversified assessment that steps away from digitized assessment practices. It promotes student voice in the design process and encourages peer collaboration and feedback. The challenge is for teachers to intentionally plan learning experiences that meet the needs of all learners and to collect formative and summative assessment data to continue to tailor learning experiences to the needs of the individual learner. After all this reading, it seems like I have my work cut out for to add more innovation into my practices. I’m excited for the challenge.


Basham, J. j., Hall, T. E., Carter Jr., R. A., & Stahl, W. M. (2016). An Operationalized Understanding of Personalized Learning. Journal Of Special Education Technology, 31(3), 126-136.

Roberts-Mahoney, H., Means, A. J., & Garrison, M. J. (2016). Netflixing human capital development: personalized learning technology and the corporatization of K-12 education. Journal Of Education Policy, 31(4), 405-420.

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