At the 2014 Technology-Enabled Personalized Learning (TEPL) Summit hosted by the Friday Institute for Educational Innovation at NC State University in collaboration with Digital Promise, the Software & Information Industry Association (SIIA), and the Michigan Association of Intermediate School Administrators (MAISA), participants discussed challenges and potential solutions for implementing TEPL. The outcomes of the Summit have now been released in a report,Technology-Enabled Personalized Learning: Findings and Recommendations to Accelerate Implementation.
Focusing on technology as a key component to accelerate learning in a personalized-learning education model, the report says that TEPL includes teacher and machine using three main tools.
- Multiple, ongoing assessments and other data to dynamically identify each student’s needs and strengths relative to learning goals, including around the universal design for learning (UDL) spectrum
- Dynamic matching of students with a customized playlist of content and interventions (digital and analog) from multiple sources based on relevant connections to prior learning, interest, experience, etc.
- Ongoing evaluation of what works best (#2) with which types of students (#1) to inform the development of ever smarter educational systems.
In addition, the paper identifies three priorities that would be effectively addressed by the education community.
- Development and adoption of technical standards for tagging content, defining and exchanging data, and easing integration of the myriad components of the TEPL ecosystem needed to support educators, recommendation engines, and related pedagogical research.
- Data policies, agreements, and research protocols needed to scale R&D across data silos about what works with which types of students in which conditions.
- Redefining educator roles and supporting their professional development to ensure the human capacity needed to shift from a traditional teaching model to a student-centered TEPL model.