October 24th, 2012
Over the next weeks, I will be writing about personalized learning and how that applies to different learning populations. At first I’ll address K12 learning, then I’ll address how personalization affects a high-skill knowledge workforce, and a service workforce.
Is K12 ready for Personalized Learning?
After 50 years of stagnation, the crisis in education and urgency to fix it has propelled the education sector into leaps of innovation. Personalization, and the technologies that support it, are innovations that threaten to upend the entrenched interests in learning content and technology. What does it take to reinvent our learning systems to give our kids the education they need to compete in the 2020 market?
Personalization meets each student where they are – whether at the center of the bell curve, or at the margins – with a learning program that is continually adapted to their unfolding needs and preferences. Each learner is guided to mastery of a subject in his or her own way with a different blend of content, activities, and tools.
Personalization isn’t a new concept; good teachers have been doing this all along.
Personalization has gained a lot of traction in the past few years driven by educational reform efforts such as the federal Race To the Top (RTT) competition, which has made personalization “Absolute Priority 1.” To date, $3.5B of $4B has been awarded.
Most applicants are addressing the RTT personalization requirement with technology that uses data analytics to identify learning needs, and tools to manage a student’s personal learning plan.
Pioneering educators are creating personalized learning experiences by experimenting with blended learning approaches that mix up live classroom interaction with self-paced and virtual classroom activities.
The “flipped-classroom” is an example of this. Lectures are delivered as a video and done as homework at night, and class-time is reserved to project and small group work. When the lectures are done as homework, students’ watch when they want, and at their own pace. They can stop, replay sections, and discuss it with their peers in online forums and chats. At the end, they are given comprehension questions that measure what they understood. This ensures that every student is engaged in the lecture, and the results of post-lecture comprehension questions provide the instructor with an understanding the effectiveness of the lecture for each student. Armed with this knowledge, the teacher then devotes class time to coaching and providing personalized attention.
Traditional Publishers, eLearning Companies and LMS Systems are Locked into Antiquated Approaches and Technologies
The question is: are the content providers ready to support personalization? Are traditional learning platforms able to support these new, highly flexible requirements?
Let’s start with content. To support personalization, teachers must be able to dynamically adjust a student’s assignments based on changing needs and learning styles. For this to work, there must be a diversity of modular content that can be matched to the unique, discrete needs of a learner. The content must be created in small chunks to be combined with other materials as needed, and be richly tagged with metadata that correlates it to educational objectives so that it can be easily accessed by its intended learning audience. A recent study found that personalizing algebra and contextualizing the problems to the areas the interests of the student had a big impact on engagement and comprehension of the subject matter. For example, simply re-framing algebra questions to use sports references engaged kids that liked sports more than the generic versions of the problems.
Until this point, publishers have followed a one-size-fits-all approach. In K12, the business model of pursuing exclusive district adoptions meant that the content was designed broadly to serve the average learners. Those at the margins of the bell curve are not served. This content was never designed to be modular, nor serve anyone other than the “average” student.
Thus, few traditional publishers are ready for the leap to personalization. First, the content was never designed to be modular and stand-alone. Second, most of their content is created for print delivery. Moving to a digital, mobile-ready format is in itself a huge hurdle.
eLearning content publishers also face challenges of retrofitting their content to support personalization. Much of their existing content was developed in Flash, which doesn’t run on Apple iOS tablets and smartphones. Also, the eLearning content tends to be monolithic and difficult to chunk into modular, assignable units.
Personalized learning is also creating challenges for the established learning technology providers. The traditional LMS is ill-suited for personalization.
“Traditional” eLearning courses support a one-size-fits-all approach, where all students follow the same path, and mastery of the knowledge is based on completion and score of the course. In contrast, in a personalized learning environment, each learner can have a different curricular path and success is measured by mastery of discreet learning objectives. The path to mastery can be different for every learner. Legacy platforms are simply unable to support an individualized learning program.
A Modular, Mobile Approach is the Key to New Learning Modalities
For far too long, there has been stagnation in the K12 market. However, personalization and related educational reforms are propelling rapid innovation in the craft of teaching and how students learn. It is forcing the hand of content providers to re-architect their content for personalization, and is forcing technology providers to re-imagine learning delivery and moving away from courses to flexible paths to knowledge mastery. The list of market leaders in a few years may look very different than what we see today.
In contrast to the traditional publishers, those providers who are-architecting their content to make it digital, granular, and specialized for specific learning populations have an unprecedented opportunity to capture market share away from the monopolistic grip of the major publishers.
A new breed of Personalized Learning Environments (PLE) is coming to market that designed from the ground up for personalized learning. These platforms use assessments and analytics to help measure gaps, and provide teachers the tools to manage individual learning plans and offer students methods of self-directed discovery.
Personalization is driving adoption of new teaching and learning methodologies, new ways of developing content, and new technologies to deliver learning.
As these new ways take root, our notions of how we create and deliver learning will also evolve. After 50 years of stagnation, finally, we are seeing some real change and hopefully see some real results as our student’s have the education and skills they need in the new economy.
Authored by Jeff Katzman, Founder and CLO at Xyleme, Inc.
November 26th, 2012
This is the 2nd in a 3 part series addressing the impact of personalization in the education and training markets. In the first post, I addressed the application of personalization in K12. In this post I address use cases that apply to a high-skilled knowledge workforce.
Personalization for the high-skill knowledge worker
Personalized learning has different applications for different audiences. In the previous post, I discussed how personalization is a key plank in the educational reform movement.
Personalization in the K12 context is used to enable each student to learn at his or her own pace, and the curriculum is tailored on-the-fly to the meet the unfolding needs.
The subject of this post is a vision of personalized learning in the 2013 workplace. To start, let’s look at the profile of a high skilled worker and view personalization through this lens.
The Collaborative, High-Skill Worker
The 2013 high-skill knowledge worker is connected, mobile, global, dispersed and relies the new breed of communication, and collaboration technologies to do business.
This describes myself, and most of my friends and colleagues in the post dot.bomb shake out. Almost everyone I know has changed jobs several times in the past ten years. When the bubble popped, it caused creative destruction and spurned a new, and sustainable business model: one built from the ground up to be distributed and virtual.
This is the story of Xyleme. We’ve adopted a philosophy of hiring the talent where it is, promote hard work and high quality of life, and have cultivated a virtual culture of global collaboration and communication. I work in teams with my colleagues in the US, Europe, Central America, Czech Republic, Russia, and the UK – many of whom I’ve met only on conference calls.
Our work model is indicative of a trend in both small and large companies. Our employees, like those in other distributed organizations, are highly adaptable, responsive and must continually acquire new skills and competencies. In our virtual workplace, we assume our employees to be self-starters, who take upon themselves the responsibility for their personal learning and development.
The flip side of working in a virtual workplace is the loss of the opportunities for tried and true methods of informal learning: those acquired by osmosis over the water cooler, or by shadowing more experienced colleagues.
Personalization in the Ad Hoc Workplace: Matching No More, No Less
So what is the appropriate modality for learning in this type of work environment? The answer, I believe, lies at the intersection between performance support, personalization, and collaboration.
Personalization in the corporate context must support an ad-hoc modality of learning.
The objective is to help the employee cut through the corporate knowledge repository and match the content with the unique needs of each employee. Each user will have a “living” learner profile that captures and tracks who the employee is, what they responsibilities they have, and their learning requirements. With this knowledge about each user, the personalized performance support solution matches the users with the most relevant content – wherever they are, when they need it, on the device they have.
While the learners’ needs and the nature of the content may vary by business and profession, the fundamental personalized learning use case in the corporate context is to match each user with the specific corporate resources needed to be effective in the work they do.
It is a user-aware system that provides opportunities to learn, and build skills – as they are needed. A next-gen, user-aware performance support solution will support an ad-hoc modality that lets people learn at the moment they can best absorb and retain it – when they need to use it.
Perpetual Content Improvement
Personalization is only as good as the content that is available. If no content matches the user’s needs, the solution will be rejected. Those companies that have existing classroom, or eLearning products can quickly realize value by simply disaggregating materials into their constituent parts.
When content is broken into discrete learning objects – rather than buried in large courses – I believe users will willingly access specific lessons, assessments, topics, procedures, and videos – as they are needed. Because the modularized content is enriched with descriptive metadata that correlates it to the company’s knowledge domain, it makes it possible to programmatically match it to the needs of the learner. For example, a products company may tag their content with metadata that describes the products or services to which it pertains; the competencies or skills to which it relates; and the geography to which it applies. With this information tagged on the content, the system can precisely suggest content appropriate for a sales rep selling a specific product line, within a specific geography.
Social commenting, ratings, and analytics on the granular bits of content provides the curators of the content (the training development teams) with the business intelligence to drive a continual improvement process. It engenders a “living” repository where problems are fixed as soon as they are identified, and gaps filled as they become apparent.
User generated content will increasingly become a key part of a living repository. In a sense, this will be the virtual return of “over-the-shoulder,” informal learning. Employees, with smartphones, can turn a camera on themselves to describe or demonstrate areas of expertise. Shared with their peers – who can comment, and rate it. This exchange has the potential to fuel and enrich the iterative, training development process.
Corporate Learning Use Cases
There are as many use cases as there are unique businesses. Here are just a couple of examples.
- Professional Certifications & Test Prep For employees that must maintain professional certifications, personalization is similar to the academic use case. The system can track the set of competencies the covered within the certification exam, and provide assessments to benchmark cognition levels. With the gaps identified, the personalization engine can recommend a set of resources tailored to fill the gaps.
- Product and Service Support For employees that support a company’s products and services, the system can track the responsibilities of the employees and match them with the appropriate product or services content.
- Regulated Industries and Audits In regulated industries, such as Pharma, the system can know who is responsible for what products. When there are changes to rules, or procedures, the system can identify affected individuals, and push updates to them, track receipt, and even test comprehension. This provides a means to keep affected employees up-to-date, and provides a clear audit trail.
- XML Learning Objects: The Foundation for Next Generation Corporate Learning Systems Personalization is underpinned by granular, semantically rich content. So how do we get there? A good place to start is by mining existing learning materials entombed in the 3-ring binders, and monolithic eLearning courses and disaggregate them into their usable parts. For some organizations this will relatively easy, for others it may be more difficult due to the way the content was created and formatted.
Moving forward with new content development, organizations will have to adopt content strategies that support personalization. As I’ve said many times in previous posts – this must be done using XML. XML is rich with semantics, can be easily modularized, and flexibly published to meet the needs of each user.
It is clear to me that the delivery channel, too, must evolve. The LMS-centric model of monolithic courses is out of step with the way professionals want to learn. For this modality of learning to be affective on the corporate front, the access to content must be instantaneous and available on the devices we use.
Personalized Performance Support has the power and potential to provide high skilled knowledge workers the responsiveness and flexibility to learn what they need to learn, when they need to learn it. The ability to profile employees by their responsibilities and learning requirements presents rich opportunities to personalize, and optimize the value of, the enterprise learning resources. Quick access to the most relevant, expert resources will, I envision, enhance both the employee organization’s ability to thrive.
Xyleme is on a development path to enable this very vision. The LCMS provides a development environment for the development of modular, semantically rich XML that can be flexibly published. This content can be deployed to Bravais – the Cloud-based delivery system from which end users can access and comment on the content. Bravais is aware of a user’s needs and can programmatically match those needs with the base of learning content. Our customers are already using this platform to create pioneering, first-generation personalized performance support applications.
December 9th, 2012
This is the 3rd in a series of 3 pertaining to how personalized learning can be applied to education and training. In the first I explored the application of personalization in K12, and in the second how personalization can be applied to high-skill knowledge workers. In this post, I explore how personalization is already enabling service workers in the retail industry learn job skills at a fraction of the cost of traditionally-developed training.
Personalization: The Training Solution for Service-Oriented, High Employee-Turnover Industries
For service-sector retail chain or franchise operations – businesses ranging from chain restaurants to hotel and hospitality to call centers to hardware stores - employee training is the foundation for delivering a consistent standard of performance and service. Employee training is critical to the brand, and very expensive to deliver. It’s in this sector where personalized training is already making inroads with big benefits.
Service Industry Training: Constant, Ever-Changing, Expensive and Imperative
Training in the retail sector has its own, unique training challenges. A one-size-fits-all approach to training is overtly wasteful for a number of reasons.
Workers may be less skilled, may or may not speak English, and may or may not be invested in their job. Some fast food restaurants report over 100% turnover every six months. Multiply the cost of training by the rate of turnover, and the numbers skyrocket.
In addition, there is a real cost to training employees on material that doesn’t directly affect them, both in lost time on the job and lost focus on the content that really matters. To be truly effective, task-oriented training needs to be highly focused, providing exactly what’s needed – no more, no less.
Delivery also matters. Classroom training, even eLearning, is less effective for task-oriented training than training at point of performance.
Learning to process a refund is more effective when done at the register, learning to restock a shelf is best done in the aisle. The 1000 page 3-ring binder or the clunky old back-office computer just aren’t effective training media.
Compounding the problem is the highly competitive nature of the industry requiring the constant introduction of new products and services: retailers are constantly updating menus, offering seasonal specials, testing new products. Employees have to be trained on each and every change.
Making things even more complicated for the training departments, each brick and mortar store or franchise is a unique combination of location, language, special equipment, geography, and menu of products and services.
Complicated and expensive as training for this population of workers may be, it’s here, in retail, where personalized training is already being implemented to slash overall training costs. Even better, the actual training, delivered at point of performance via tablets and mobile phones, is boosting employee productivity.
A Personalization Use Case: A Major Fast Food Chain Uses Single Source to Keep it SIMPLE
Like the other use cases that we’ve explored, the key to personalization is to have a granular base of content and be able to match that base of content to the needs of the employee. In the case of a major fast food chain, Personalization is already improving service by customizing training down to the most granular and efficient level.
Previously, the training groups supporting franchise operations would create enormous training binders that contain ALL procedures and training materials for ALL configurations of a franchise and ship it to EVERY store. A kiosk in an airport would receive the same training materials as a sit-down restaurant. It was incumbent on the manager to go through the binders and pull out the extraneous pages. The printing and shipping costs alone were enormous.
To support personalization, the learning designers disaggregated content in the mega-binder down to its parts. Each procedure was tagged with metadata correlating it to the pertinent service, product, geography, language. These granular objects were uploaded into a centrally accessible repository.
Now, individual store managers are creating unique store profiles that define their store’s unique configuration of on-site equipment, menu offerings, store hours, local geographic preferences, and languages. Once specified, the system creates a custom set of materials specifically for that store that can be accessed online, from a mobile device, or printed.
Now, onboarding employees receive personalized, highly-targeted and highly efficient training delivered directly at the point of performance from a SmartPhone or tablet.
As this is a first-generation, pilot application, we don’t have an ROI on the project. However, the expansion plans of the client indicates the project is delivering powerful savings in terms of printing, reduction of time employees spend in training, and more effective training.
Single Source XML is the Technology Foundation for The Next Generation of Personalized Training Applications
As I have repeatedly said, the only path to support this is to develop the content using a single source XML development methodology. This allows it to be modularized, published to multiple formats and devices, and tagged with the metadata needed to drive personalization. XML is also the optimal format to manage language translations and localization. The XLIFF (XML Localization Interchange File Format) is the most cost effective means to translate content using Translation Memory services.
Personalization, the method of matching the user’s needs to the most relevant content, on the device the user has, is the same regardless of whether we’re talking about the K12 student, the knowledge worker, or the service employee.
The retail application, with its focus on providing a very focused slice of the content, is the first stage in this new paradigm. In the very near future, Xyleme will be delivering applications that engage workers more broadly.
Personalization is where the world is heading, and we are proud to be leading the way.
This post was authored by Jeff Katzman, CLO & Founder at Xyleme, Inc.