[In this special report from Edsurge, you’ll hear about several schools that have implemented computer-based programs that provide tools that “adapt” to student learning needs. In my work at the Fox Chapel Area School District I witnessed the benefits of this approach with the Carnegie Learning math program that provided one of the first blended learning environments for K-12. ]
Third-graders from Joseph Weller Elementary School, Milpitas (CA) | Photo Credit: Paty Gomes/EdSurge
Meet Aaron Cheng, my daughter’s sixth-grade math teacher. He’s a smart, technically savvy 28 year-old at the Alameda Community Learning Center, a progressive charter school just fifteen minutes from the tech mecca of San Francisco. I asked him the other day if ACLC was thinking of using any adaptive learning software.
“What’s that?” Cheng asks.
Thirty five miles south at Joseph Weller Elementary School in Milpitas, everyone knows about adaptive learning. When EdSurge reporter, Paty Gomes, and I visit, third graders are sitting on bright red plastic chairs in an expansive, airy learning lab, each quietly reading a book they selected from Reading Counts, an adaptive program that suggests titles that can help them improve in a certain area—say, vocabulary. So many reporters and educators have visited this cutting-edge lab that teacher Diane Semrau doesn’t bother to introduce the camera-laden visitors, and the kids could hardly care less. After they go off to lunch, district superintendent Cary Matsuoka and director of technology Chin Song sit for an interview, reeling off information about the program.
[In this EdTech article five trends are highlighted that may make a major impact on both K-12 and higher education in 2016. I’m teaching an Osher course for senior adults at Carnegie Mellon University that will look at six trends that are making a difference – coding, personalized learning, flipped learning, game-based learning, virtual reality, and robotics. It’s interesting to see how the two merge.]
The technologies of tomorrow are already making headway into education, and others are poised for mass distribution in 2016.
Frank is a social media journalist for the CDW family of technology magazine websites.
Science-fiction author William Gibson once said, “The future is already here — it’s just not very evenly distributed.”
The technologies of tomorrow are already being tested in select classrooms today, laying the seeds for the future of how students could learn. With 2016 fast approaching, technology analysts have been busy prognosticating the top technology trends. A few of these technologies have already made headway into education, and others are poised for mass distribution, with the promise of ground-shaking change in their wake.
We’ve reviewed a few of these trends through the lens of how they could affect classrooms in both K–12 and higher education.
[In this article from EvoLLLution Michael Horn, the Co-founder and Executive Director of the Clayton Christensen Institute for Disruptive Innovation, shares his insights into how tools, like Knewton, are opening the door for personalizing learning.]
July 31, 2015
Improved data collection and analysis is critical to the expansion of personalized learning in higher education, which itself is central to the move towards a more hybrid and online post-secondary environment.
The evolution of technology and technological tools over recent years has positively impacted the effectiveness of online learning, which has transformed into a highly engaging, highly integrated platform for students to pursue post-secondary credentials with maximum flexibility. Of course, as with any technology, there is still room for improvement and growth. Online learning has the space to become even more personalized. In this interview, Michael Horn discusses the current state of personalization in the online learning space and shares his thoughts on what the future might hold for online education.
The EvoLLLution (Evo): How truly personalized is online programming today?
Michael Horn (MH): Online learning today is personalized in the sense that it starts to give students control over the pace of their learning and the time when it occurs. It can offer much more flexibility given the asynchronous technologies.
Where there is still a lack of personalization is in the different pathways that students take towards mastery. Certain programs are certainly addressing this and we’re seeing adaptive learning engines like Knewton appear to do some exciting things to better target and personalize for different students. It still feels like we’re really in the early beginnings of the dramatic revolution that we’ve seen in a lot of other technology sectors where really smart recommendation engines come in and assist the student in picking and choosing their unique path.