{"id":12053,"date":"2018-06-22T07:44:55","date_gmt":"2018-06-22T11:44:55","guid":{"rendered":"https:\/\/edtechteacher.org\/?p=12053"},"modified":"2019-02-19T09:41:40","modified_gmt":"2019-02-19T13:41:40","slug":"learner-variability-the-why-of-personalized-learning-from-tom-driscoll","status":"publish","type":"post","link":"https:\/\/edtechteacher.org\/learner-variability-the-why-of-personalized-learning-from-tom-driscoll\/","title":{"rendered":"Learner Variability: The Why of Personalized Learning"},"content":{"rendered":"

Learn more from Tom by following him on Twitter: @Mr_Driscoll<\/a><\/p><\/blockquote>\n

Over the past few years, in several different roles, I have researched and experimented with various frameworks and approaches to Personalized Learning. \u00a0Despite the vast amount of resources out there that describe what personalized learning is and how to implement it, it is often difficult to find quality research that gets to the \u201cwhy\u201d of personalization. \u00a0<\/span><\/p>\n

One of the most compelling arguments I have seen thus far relates directly to the\u00a0idea of \u201clearner variability.\u201d \u00a0In short, the concept of learner variability implies that all learners are inherently different across various domains, whether it be academic, social, emotional or other areas. \u00a0It can also be argued that each year, our classrooms are becoming increasingly diverse across these domains. \u00a0Personalized learning, with its focus on meeting students where they are, actively embraces learner variability and provides various pathways to success that are optimized for each student. \u00a0<\/span><\/p>\n

\n

Learner variability defines personalized learning\u2026.The culture of personalization is built on embracing all comers and providing paths for success for each student.<\/span><\/p>\n<\/blockquote>\n

Source: http:\/\/digitalpromise.org\/wp-content\/uploads\/2018\/01\/lps-policies_practices-r3.pdf]<\/a><\/span><\/p>\n

Personalized learning also advocates that instruction is tailored to students specific needs and interests, particularly\u00a0what<\/span>\u00a0they learn,\u00a0when<\/span>\u00a0they learn,\u00a0how<\/span>\u00a0they learn, and\u00a0how<\/span>\u00a0they demonstrate understanding. \u00a0Much of this overlaps with\u00a0Universal Design for Learning<\/a><\/span>\u00a0(UDL). \u00a0The UDL framework and associated guidelines help educators\u00a0\u201caddress the predictable variability in learning that we know will be present in any environment.\u201d<\/a><\/span>\u00a0UDL designates three distinct cognitive areas of variability: Engagement (The \u201cWhy\u201d of Learning), Representation (The \u201cWhat\u201d of Learning), and Action & Expression (The \u201cHow\u201d of Learning.)\u00a0\u00a0Is a theme emerging?<\/span><\/p>\n

\"\"<\/p>\n

While at a recent Digital Promise League of Innovative Schools summit (BWRSD<\/a><\/span>\u00a0is a member district), I had the fortunate opportunity of joining a \u201cChallenge Collaborative<\/a><\/span>\u201d that is diving into the concept of learner variability. \u00a0We kicked things off by viewing the video below by\u00a0David Rose\u00a0of Harvard University, a key contributor to the development of the UDL field. \u00a0In this video, he suggests that we actively design schools that embrace learner variability and build upon students strengths, as opposed to \u201cstandardizing\u201d students and designing to the mythical average.<\/span><\/p>\n

https:\/\/youtu.be\/BxLz_fSvBqU<\/a><\/span><\/p>\n

\"\"<\/p>\n

At the DPLIS meeting, we also had the opportunity to test out a new\u00a0Learner Positioning System platform<\/a><\/span>\u00a0that can help connect emerging research in cognitive science, neuroscience, and social-emotional learning with classroom practices that can help address learner variability.\u00a0As you can see in the screenshot above from the PK-3 Reading section, educators can visualize how one factor (in this case sleep) impacts learning in key areas across domains. Educators can then drill down and select strategies suggested via this platform that address those specific factors. \u00a0LPS can also be viewed emerging tool that can help edtech developers design products that more effectively address learner variability. \u00a0(Example Here of Partnership with ReadWorks)<\/a><\/span>\u00a0Digital\u00a0Promise has also published\u00a0a new series of white papers\u00a0that highlight emerging learning science research related to learner variability along with practical strategies for educators and policymakers to refine personalized learning strategies across various educational contexts. (Reports can be found here<\/a><\/span>.)<\/p>\n

In the Bristol Warren Regional District, I can already envision this emerging research helping us in several ways. \u00a0First, we have developed strong practices regarding student interventions that include data meetings to identify and close student learning gaps. \u00a0A tool like the LPS can help us identify research-based strategies to address gaps in student learning across multiple domains.\u00a0\u00a0It also can provide insights regarding the connections and relationships between gaps in one domain and how it affects another. \u00a0As a district, we are also\u00a0taking a deeper dive\u00a0into social-emotional learning and how to best design learning experiences for students from that lens. \u00a0This research can help us make the connections between effective personalized learning strategies and designing with social-emotional needs as a key component of learner engagement<\/p>\n

\n

\u201cIt is critical for us to make sure that as personalized learning evolves and grows we are leveraging research to explicitly design for the full diversity of learners.\u201d<\/span><\/p>\n<\/blockquote>\n

Source:\u00a0http:\/\/digitalpromise.org\/wp-content\/uploads\/2017\/02\/lps-research-promise-personalized-learning.pdf<\/a><\/span>]<\/p>\n

Taking a step back from the complexity of learner variability and its relationship to personalized\u00a0learning, here is broad view of how I conceptualize these developments: \u00a0<\/span><\/p>\n

    \n
  1. Learner variability (academic, social and emotional) is growing in classrooms across the United States.<\/span><\/li>\n
  2. Learning science research is helping us identify the key factors that influence learner variability.<\/span><\/li>\n
  3. This research, once translated into practice, can help educators determine which personalized learning strategies to use for which students, and in which context. \u00a0<\/span><\/li>\n
  4. Technologies (such as the LPS) can help provide the structures and supports for educators to design and scale effective personalized learning practices that address learner diversity.<\/span><\/li>\n<\/ol>\n

    Although this remains a relatively new and emerging field, it holds tremendous promise to personalize student learning in more effective and purposeful ways for students across the country. \u00a0<\/span><\/p>\n

    \"Sign<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

    Learn more from Tom by following him on Twitter: @Mr_Driscoll Over the past few years, in several different roles, I have researched and experimented with various frameworks and approaches to 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