With the turn of the decade I have read a lot of pessimistic articles about education and learning technology. Most start with the lamentation that there has been little overall progress in student achievement over the last couple of decades – which is true, unfortunately. But what they fail to note are the many small and medium scale successes.
Take, for example, Seaford School District in Delaware. The community has been economically challenged since DuPont closed its Nylon plant there. Three of its four elementary schools were among the lowest performing in the state just a few years ago. Starting with a focus on reading, they ensured a growth mindset among the educators, gave them training and support, and deployed data programs to track progress and inform interventions. They drew in experts in learning science to inform their programs and curriculum. The result: the district now matches the state averages in overall performance and the three challenged elementary schools are strongly outperforming the state in reading and mathematics.
My friend, Eileen Lento, calls this a lighthouse because it marks the way toward the learning successes we’re seeking. For sailing ships, you don’t need just one lighthouse. You need a series of them along the coast. And each lighthouse sends out a distinct flash pattern so that navigators can tell which one they are looking at. By watching educational lighthouses, we gain evidence of the learning reforms that will make a real and substantial difference in students’ lives.
What does the evidence say?
Perhaps the most dramatic evidence-based pivot in the last decade has been the Aurora Institute, formerly iNACOL. In 2010 their emphasis was on online learning and virtual schools. But the evidence pointed them toward competency-based learning and so they launched CompetencyWorks; they renamed the symposium; and, ultimately, renamed the whole organization.
Much criticism has been leveled at No Child Left Behind, and its successor, the Every Student Succeeds Act. The beneficial results of these federal interventions are the state standards, which form the foundation of competency-based learning; and consistent annual reports that indicate how well K-12 schools are performing. On the downside, we’ve learned that measuring and reporting performance, by themselves, are not enough to drive improvement.
Learning science has made great gains in general awareness over the last decade. We’ve learned that a growth mindset makes a critical difference in how students respond to feedback and that the form of praise given by teachers and mentors can develop that mindset. We have evidence backing the notion that deliberate practice and feedback are required to develop a new skill. And we’ve gained nuance about Bloom’s Two Sigma Problem – that tutoring must be backed by a mastery-based curriculum and that measures of mastery must be rigorous in order to achieve the two standard deviation gains that Benjamin Bloom observed.
Finally, we’ve learned that the type of instructional materials doesn’t matter nearly as much as how they are used. Video and animation are not significantly better at teaching than still pictures and text. That is, until interactivity and experimentation are added. To those, we must also add individual attention from a teacher, opportunities to practice, and feedback.
Learning Technology Responding to the Challenge
A common realization in this past decade is that technology does not drive learning improvement. Successful initiatives are based on a sound understanding of how students learn best. Then, technology may be deployed that supports the initiative.
A natural indicator of what technology developers are doing is the cross-vendor standards effort. In the last couple of years there has emerged an unprecedented level of cooperation not just between vendors but also between the technology standards groups.
Here’s what’s up:
Learning Engineering
A properly engineered learning experience requires a coalescence of Instructional Design, Learning Science, Data Science, Competency-Based Learning and more. The IEEE Learning Technology Standards Committee (LTSC) has sponsored the Industry Consortium on Learning Engineering (ICICLE) and I’m pleased to be a member. We held our conference on Learning Engineering in May 2019, proceedings are due out in Q1 of 2020, the eight Special Interest Groups (SIGs) meet regularly and we have a monthly community meeting.
Interoperable Learner Records (ILR)
The concept is that every learner (and that’s hopefully everyone) should have a portable record that tracks every skill they have mastered. Such a record would support learning plans and guide career opportunities.
- The T3 Innovation Network, sponsored by the US Chamber of Commerce Foundation, includes “Open Data Standards” and “Map and Harmonize Data Standards” among their pilot projects. These projects are intended to support use of existing standards rather than develop new ones.
- Common Education Data Standards (CEDS) define the data elements associated with learner records of all sorts and the various standards initiatives continue to align their data models to CEDS.
- IMS Global has published the Comprehensive Learner Record (CLR) standard.
- The PESC Standards define how to transfer student records to, from, and between colleges and universities.
- The Competency Model for Learning Technology Standards (CM4LTS) study group has been authorized by the IEEE LTSC to document a common conceptual model that will harmonize current and future IEEE LTSC standards. The model is anticipated to be based on CEDS.
- The Advanced Digital Learning Initiative (ADL) has launched the Total Learning Architecture (TLA) working group seeking to develop “plug and play” interoperability between adaptive instructional systems, intelligent digital tutors, real-time data analytics, and interactive e-books. Essential to the TLA will be a portable learner record that functions across products.
- The HR Open Standards Consortium defines standards to support human resource management. The standards include competency-oriented job descriptions and experience records.
While these may seem like competing efforts, there is a tremendous amount of cooperation and shared membership across the different groups. In fact, A4L, PESC, and HR Open Standards have established an open sharing and cooperation agreement. Our goal is a complementary and harmonious set of standards.
Competency Frameworks
A Competency Framework is a set of competencies (skills, knowledge, abilities, attitudes, or learning outcomes) organized into a taxonomy. Examples include the Common Core State Standards, Next Generation Science Standards, the Physician Competency Reference Set, the Cisco Networking Academy Curriculum, and the O*Net Spectrum of Occupations. There are hundreds of others. Interoperable Learner Records must reference competency frameworks to represent the competencies in the record.
- The Achievement Standards Network (ASN) is a registry of competency frameworks from many different domains in a browsable and machine-readable format.
- The IEEE LTSC is renewing the Reusable Competency Definitions Standard IEEE 1484.20.1. A key part of this project is the “Best Practices for Developing Competencies.”
- IMS CASE is an interoperable format for representing competency frameworks and the IMS CASE Network Registry is a registry of competency frameworks in CASE format.
- The Credential Registry by Credential Engine is an open library that describes credentials in terms of the associated competencies. Credentials are machine readable in the Credential Transparency Description Language (CTDL).
- The T3 Innovation Network Pilot Projects 5 and 6 (Competency Data Collaborative and Competency Translation and Analysis) seek to harmonize competency use across existing frameworks, registries, and formats like those listed above. (I'm pleased to be contributing to the T3 Competency Data Collaborative.)
Learning Resource Metadata
Metadata can indicate that a piece of content (text, audio, video, interactive activity, etc.) is intended to teach or assess a particular competency or set of competencies. So, when a person completes an activity, their interoperable learner record can be updated with evidence that they have learned or are learning those competencies.
- The Learning Resource Metadata Initiative (LRMI) is a working group within the Dublin Core Metadata Initiative (DMCI) to define and learning-related metadata properties included in DMCI and Schema.org. (I've been a contributor to LRMI since its inception.)
- IEEE Learning Object Metadata (LOM) is a standard published by the IEEE LTSC and incorporated into many other learning data standards.
Standards Advocacy
All of this interoperability effort will be of little use if the developers of learning activities and tools don’t make use of them.
- Project Unicorn advocates for U.S. school districts to require interoperability standards from the vendors that supply their educational tools.
- EdMatrix is my own Directory of Learning Standards. It is intended to help developers of learning tools know what standards are applicable, to help learning institutions know what to seek or require, and to help standards developers know what related efforts are underway and to support cooperation among them.
Looking to a New Decade
It can be discouraging to look back on the last decade or two and compare the tremendous investment society has put into education with the lack of measurable progress in outcomes.
I prefer to look forward and right now I’m optimistic. Here’s why:
Our understanding of learning science has grown. In daily conversation we use terms like “Growth Mindset,” “Competency-Based Learning,” “Practice and Feedback,” and “Motivation”.
Online and Blended Learning, and their cousin, Adaptive Learning Platforms, have progressed from the “Peak of Inflated Expectations” through the “Trough of Disillusionment” (using Gartner Hype Cycle terms) and are on their way to the “Plateau of Productivity.” Along the way we’ve learned that technology must serve a theory of learning not the other way around.
Technology and standards efforts are now spanning from primary, and secondary education, through higher education and into workforce training and lifelong learning. This reflects a rapidly changing demand for skills in the 21st century and a realization that most people will have to retrain 3-4 times during their lifetime. I expect that lasting improvement in postsecondary education and training will be driven by workplace demands and that corresponding updates to primary and secondary education will be driven by the downstream demand of postsecondary.
So, despite a lack of measurable impact in standardized tests, previous efforts have established a foundation of competency standards and measures of success. We have hundreds of “lighthouses” - successful initiatives worthy of imitation. On the foundation of competencies and standards, following the lighthouse guides we will build successful, student-centric learning systems.
What do you think? Are the investments of the last couple of decades finally about to pay off? Let me know in the comments.