One of the most compelling arguments for personalized learning is the importance of providing an appropriate education to students with special needs. Such students challenge the system, with unexpected strengths and weaknesses that are out of scale with the norm. Simply slowing down (or speeding up) the pace of instruction won’t serve their needs, particularly as they may be exceptional on more than one dimension and in more than one direction. For them, personalized learning that decouples different skills is imperative, a way to serve their needs and extend their abilities at the same time.
While special-education laws are limited in scope due to their approach of simply setting minimum requirements, they do provide critical safeguards for supporting students at the K-12 level. As they graduate to adulthood, these students are expected to assume more responsibility to advocate for and seek accommodations for their needs if they pursue advanced study at institutions of higher education (IHEs). Even so, these minimum accommodations only grant access, and sometimes may not do enough to constitute effective instruction that enables success. Simply fulfilling minimum requirements may allow IHEs to avoid litigation, but failing to adequately serve their students is a failure to invest their resources wisely.
Challenging though it may be to (re)design instructional materials with different constraints, IHEs may find that special-needs students can provide a valuable test case, instantiating extremes on the spectrum of students they serve. These adjustments will also help them support English language learners, disadvantaged-but-capable students with gaps in their backgrounds, returning students who remember some lessons but forgot others, and career changers in search of very specific skills to flesh out their resume—deserving students whom the traditional system fails, all too often. Not all students fit the same mold, nor should they. Adapting instruction around their needs develops their potential and gives them the opportunity to give back.
A fundamental challenge in implementing personalized learning is in determining just how much it should be personal—or interpersonal, to be more specific. Carlo Rotella highlights the tension between the customization afforded by technology and the machine interface needed to collect the data supporting that customization. He narrows in on the crux of the problem thus:
For data to work its magic, a student has to generate the necessary information by doing everything on the tablet.
That invites worries about overuse of technology interfering with attention management, sleep cycles, creativity, and social relationships.
One simple solution is to treat the technology as a tool that is secondary to the humans interacting around it, with expert human facilitators knowing when and how to turn the screens off and refocus attention on the people in the room. As with any tool, recognizing when it is hindering rather than helping will always remain a critical skill in using it effectively.
Yet navigating the human-to-data translation remains a tricky concern. In some cases, student data or expert observations can be coded and entered into the database manually, if worthwhile. Wearable technologies (e.g., Google Glass, Mio, e-textiles) seek to shorten the translation distance by integrating sensory input and feedback more seamlessly in the environment. Electronic paper, whiteboards, and digital pens provide alternate data capture methods through familiar writing tools. While these tools bring the technology closer to the human experience, they require more analysis to convert the raw data into manipulable form and further beg the question of whether the answer to too much technology is still more technology. Instructional designers will always need to evaluate the cost-benefit equation of when intuitive human observation and reflection is superior, and when technology-enhanced aggregation and analysis is superior.
David Warlick muses on the distinction between individualized instruction and personalized learning, noting that the former is decreasing while the latter is increasing in popularity, according to Google Trends. As he summarizes:
Personalized learning, in essence, is a life-long practice, as it is for you and me, as we live and learn independent of teachers, textbooks, and learning standards. Individualized instruction is more contained.
Part of me is tempted to wonder what a word-cloud analysis would reveal as the key differences between how the two phrases get used. Absent such an analysis, I would focus on the two dimensions highlighted by the words themselves: personalized vs. individualized, and learning vs. instruction. The latter distinction is quite straightforward, with instruction emphasizing what others do to the student and learning emphasizing what the student does to learn.
The former distinction highlights the learner as a person, not merely an individual. As articulated in my earlier post explaining personalized learning, the core of personalization is the role of the learner as an intelligent and social person making choices for herself and interacting with others in order to learn. I would thus add to Warlick’s matrix, under “student’s role,” an explicit expectation for the student to direct her own learning and collaborate with and challenge fellow learners in making sense of the world. Warlick already emphasizes the role of the teacher’s expertise in deciding how to craft the learning environment; here, under “teacher’s role,” I would also add the responsibility to create and guide learning experiences within social settings. This highlights the importance of how students learn from communicating and collaborating with each other in an environment that truly recognizes them as intelligent, interdependent people.