By John Mullin, Enlearn CEOĀ
With one out of five students not finishing high school, ourĀ current models for school-based learning still arenāt working for too many ofĀ our youth. Enormous amounts of effort and money have been expended tryingĀ toĀ address thisāto leave no child behindābut the challenge persists. And our collective failure to solveĀ this problem steals opportunity from millions of students every year.
One area receiving a great deal of focus and investment thatĀ could potentially address part of this challenge is adaptive learningādigitized curriculum and courseware that can adjust or adapt what comes next forĀ each student based on their degree of mastery with previous work. Unfortunately,Ā efforts toĀ successfully personalize learning through adaptive curricula will fail manyĀ students for several key reasons:
- They are designed for individual studentsĀ working in isolation on a computer or device, but thatās not how kids spend their time in schools.Ā Classrooms are dynamic (and sometimes disruptive) environmentsĀ with many, many variables that affect each studentās learning every day. To truly optimize learning, you need toĀ optimize the entire classroom ecosystem.
- The exercises and problems within any oneĀ adaptive curriculum are limited to those chosen by a particular group ofĀ authors, editors, and publishersātheir best attempt at a one-size-fits-allĀ subset for each content area. But this is still a small subset of all theĀ problems that could be presented, which limits the learning paths that can be traveled, and, therefore, the students for whom a given adaptive curriculumĀ will be effective.
- They focus only on student mastery. Did you get the problem right? If so,Ā you move on; if not, you repeat or go back. But this gated approach ignores the deep-engagement measuresĀ and growth mindsetĀ needed for students to actually want to continueāto fosterĀ sustained learning and progress.
- Current adaptive methods ignore theĀ critical role of the teacher, who happens to be the single greatest determinantĀ of student success inside of schools. If you want to help struggling students succeed, thenĀ adaptivity needsĀ to be designed to enhance teaching, not bypass it.
Transforming school learning
We can do betterāby harnessing theĀ power of real-time classroom data to not just adapt, but to actuallyĀ create, curricula unique to each student and each specific classroom. We can adapt, not just for one student working inĀ isolation on a computer, but also for the entire classroom working with theirĀ teacher, together, in real time.
This breakthrough technologyāwhich weĀ call generative adaptationādoesnāt just re-organize content like a playlistĀ for each student, it generates new content to fill in the gaps in a curriculumāit makes eachĀ curriculum virtually infinite. And then it continuously identifies andĀ refines personalized pathways through that coursewareāpathways that optimizeĀ both engagement and mastery for each learner.
Because this approach is capable of adapting in real time for every student in the classroom, and filling in any content gaps for each student, we can now deliver one-size-fits-oneāa personalized curriculum that isĀ continuously created for and adapted to the individual.
Making sure that every student has his or her needs met
Why doesĀ generating new content matter? WhyĀ is it better than simply enabling existing content to be re-organized perĀ student?
To our knowledge, no single text or courseware has been ableĀ to cover the myriad learning paths and progressions best suited for everyĀ unique student, regardless of how the content is sequenced or adapted. If suchĀ texts existed, we wouldnāt have math wars, or battles between whole languageĀ and phonics, etc. Those battles occur precisely because the expertsĀ creating the curricula disagree on the subset and sequence ofĀ content to beĀ delivered to studentsāand they donāt have the means to include all possibleĀ learning pathways and progressions, so they make choices based on theirĀ pedagogical beliefs/preferences. Itās their bestĀ effort at one-size-fits-all.
We now have the ability to finally blow apart the one-size-fits-all model of content and learning, and to replace it with a truly personalized learning experience for each student, classroom, and teacher
By definition, this choice leaves out potential learningĀ pathways and progressions, which means that some subset of students will beĀ forced through a sub-optimal learning path for their specific needs.
For decades, weāve accepted this as the best we couldĀ possibly do. We donāt have toĀ accept it any longer. Through technology, we can now deliver the best path forĀ each studentāagain one-size-fits-one.
Hereās an interesting illustration of the potential: Recently, our partners at theĀ Center for Game Science at the UniversityĀ of Washington found through theirĀ algebra challengesĀ that nearly 95 percent of students participating were able to reach concept mastery of linearĀ equations using theĀ generative adaptive version of the content. But some students needed as much asĀ sixĀ timesĀ the practice to reach those mastery levels. Furthermore,Ā the additional practice material that any twoĀ students required was differentāit was specific to each studentās unique learning pathway and progression. ThisĀ means providing six times the content, tailored specifically to theĀ moment-by-moment learningĀ challenges of each student. A fixed text isĀ incapable of generatingĀ anyĀ new content, let alone six times theĀ content.
By providing the generative adaptive version, 95 percent ofĀ students were able to achieve mastery, versus about 30 percent in the non-generativeĀ version. If we have the ability toĀ more than double the number of students achievingĀ mastery in a given concept,Ā we not only have the opportunity to dramatically change learning outcomes, butĀ the responsibility to do so as well.
Supporting teachers so they can help individual students
A static or fixed text is no friend of the teacher. Formative assessment has been widelyĀ shown to be one of the most effective teaching strategies for increasing student learning, yet the information available toĀ teachers from traditionalĀ texts is limited to results on worksheets or homework or quizzesāthere isĀ little or no real-time data provided to help the teacher understand whether orĀ not students are learning in the moment.
With the generative, adaptive technologyĀ model Iāve discussed,Ā teachers now have access to continuous, real-time formativeĀ data. Not after grading theĀ assignments for the day, or after the unit test, but as a windowĀ into ongoingĀ student learningāhow is each student doingĀ right now? What could or should I do to have the greatest impact onĀ their learningĀ right now?
In a recent trial, our self-adaptiveĀ platformās real-time data enabled teachers to assistĀ individual students three times more frequently than occurred in traditional paper-based classrooms. The continuous formative feedback also enabled the teachers to target their assistance to the students who needed it the most atĀ that moment, versus a more random delivery of assistance in the traditionalĀ classrooms.
But none of this can happen with a static or finite old-fashioned textāwhether itās adaptive or notābecause this restricts the number ofĀ potential learning pathways for a given concept or subject, and itās limited toĀ the content and progressions agreed upon by a particular group of authors,Ā editors, and publishers. Again, simply re-ordering static or fixed contentĀ doesnāt address the needs of all learners.
So, to cover all potential pathways, and ensure that everyĀ student gets his or her specific learning needs met, content must be generatedĀ and adapted in the moment. Over time, this self-adaptive technology platformĀ will improveĀ with each additional learning experience captured. And, as the platform continuously and automatically adapts based onĀ real-time data, it accelerates the potential rate and degree of engagement andĀ mastery in every learning opportunity.
TheĀ bottom line here is simple: We now have the ability to finally blow apart theĀ one-size-fits-all model of content and learning, and to replace it with a trulyĀ personalized learning experience for each student, classroom, and teacher. If weĀ want toĀ help an entire generation of young people learn in the 21stĀ century, we need to make schoolwork for the kids who are being failed by theĀ current model. Generative adaptation has the potential to help solve thisātoĀ create learning pathways created for,Ā and specialized to, each learner.
