Corporations, especially large ones, increasingly recognize the potential of artificial intelligence, cloud computing, big data analysis, apps and robots, as well as augmented and virtual reality-based solutions to solve complex organizational challenges.
Amid such technological revolution, higher bars for talent and leadership development are being set within corporations and across the learning and development industry. Pressure is mounting on learning and development professionals to continually innovate, design and develop personalized learning that caters to each individual’s learning aptitudes, preferences and performance; maximizes learning impact; and brings learners to peak performance in the shortest possible time.
Corporate learning leaders are looking to the technology to keep pace with these demands. They hope to enhance each individual’s learning experience and boost achievement of business objectives through high-tech, machine-driven approaches that enable learning and development departments to develop and implement smarter, customized learning and development.
With these hopes in mind, the L&D industry is attempting to shift toward learning that is online, web-based and mobile as opposed to traditional face-to-face learning sessions. While it remains the largest delivery methodology, the amount of instructor-led and classroom training has indeed dropped from 47 percent to 41 percent in the past three years, according to Training magazine’s “State of the Industry” reports.
But as learning organizations pursue technology-driven transformation they risk falling prey to the assumption that organizations can only change through technology. The solution is not just technological or financial.
The Case of Adaptive Learning
Adaptive learning is one online approach that is being looked at as part of the solution to the learning and development challenges confronting learners and corporate performance.
Adaptive learning is the customization of the design and delivery of learning based on each learner’s individual learning needs and performance in real time. This approach is built on research that shows different people have different aptitudes, skills and orientations to learn when exposed to the same content and learning environments. By offering personalized learning, adaptive learning platforms recognize and embrace the diversity that is part of any learning ecosystem.
A learning ecosystem is made up of people, technologies, processes and physical resources. On the people side, there are learners, learning solution architects, instructors, subject matter experts, instructional designers, graphic developers, programmers and administrators who develop and manage the learning ecosystem. The technological component of a learning ecosystem includes the learning management systems, authoring tools, learning record systems, content management systems, internet, computers, telecommunication tools as well as mobile-based platforms and apps. The processes include training needs analysis, curriculum design and development, course delivery, training administration, evaluation and financial management. Physical resources refer to the quality, quantity and access to content, devices, locations, classrooms, paper-based learning tools as well as factors like travel and weather.
Yet even within a single corporation, a learning ecosystem cannot be considered a homogenous entity. As different learners attend the same learning session, they come with different foundational knowledge and experience on a topic. They learn and engage with each other as well as with their instructor differently and with varying professional and emotional intelligence and competencies, as psychologist Daniel Goleman has noted. Their diverse educational, professional and personal experiences and learning preferences impact how they approach, understand, assimilate and apply the same learning content and at what pace.
The Technocentric View of Innovation
The adaptive learning platforms that have proliferated over the past few years address the promise of adaptive learning through a technocentric viewpoint. These platforms draw upon and integrate cognitive psychology, instruction and learning, statistical modeling and software programming theories and techniques.
Learner profiles are generated scientifically and performance baselines and assessment criteria are established. Multiple learning pathways and decision trees that are flexible and uniquely responsive to different learners’ knowledge, skills and competency levels are designed. Learner performances are captured and the corresponding data is analyzed in real time, triggering rapid customization of the content and creation of unique learning pathways.
As such, adaptive learning platforms are an inclusive learning medium. Despite how advanced or preliminary their knowledge, skill sets or competencies, each learner can theoretically achieve the same learning objectives while taking different routes to get there. Learners receive customized content, personalized pathways and ongoing assessment and feedback, continually adapted in real-time based on what the learner already knows or does not know and on demonstrated mastery of the course material. Data analysis techniques, algorithm-based learning models and AI have made adaptive learning platforms a reality for organizations.
However, adaptive learning platforms are not a new development nor has the application of such platforms been restricted to corporate learning ecosystems. For more than a decade, the education industry has incorporated adaptive learning approaches. Nonprofit organizations including the Bill & Melinda Gates Foundation have played a critical role in encouraging adoption of adaptive learning within the public education system. K-12 schools, colleges and universities in the United States have been using and experimenting with adaptive learning platforms to personalize courses and lesson plans for their students.
These approaches contribute to the widespread belief that technology is the prime enabler of adaptive learning. The discourse around adaptive learning within and outside the corporate learning community has therefore mainly centered on technological innovation.
This technocentric recognition and popularization of adaptive learning can drive an implicit and incorrect assumption: That organizations can implement adaptive learning solutions only if they invest in innovative technological platforms. For many organizations with limited resources, that prospect can seem out of reach.
According to the 2016 “Training Industry Report,” there is a tenfold difference in the average learning budget for large (10,000+ employees) and midsize (1,000-9,999 employees) organizations. That’s not to mention that for organizations of any size, there is considerable pressure to improve results with existing infrastructure. The fourfold difference between the average budget size between midsize organizations and small companies (100-999 employees) exacerbates this pressure for those organizations that comprise the overwhelming majority of the learning landscape.
Limitations of the Technocentric View
While there is legitimacy in adopting the technocentric view of adaptive learning, such an approach is limiting. It confines the opportunities of adopting adaptive learning solutions to only those corporations that have the financial power to afford those technological platforms. The hurdles to adopting adaptive learning platforms are not just financial, though.
A technocentric view downplays the challenges of human engagement that drive any successful learning and development mission. In this view, corporate learning leaders have to be willing to cede control of their learning to an outside organization who owns the proprietary adaptive learning technology. They depend on external vendors and consultants for specialties like machine learning, artificial intelligence, software programming and cognitive psychology to provide expertise in designing and implementing adaptive learning.
So unless the corporation has in-house expertise to independently understand, operate and manage adaptive learning platforms, the process of demystifying adaptive learning and making learners adapt to it can be a resource-intensive change-management process in itself. Moreover, companies may need to refine the technological platform based on their particular context and operating and instructional environment, if that is even possible within the platform.
The technocentric view also downplays the importance of social innovation. Corporations can use existing resources within their traditional learning ecosystems to harness the true potential of adaptive learning, as noted by Thomas Arnett, a senior research fellow for education at Clayton Christensen Institute. New windows of learning and development innovation would open up as corporations started rethinking and reviewing adaptive learning as a philosophy rather than as a technology.
Adaptive Principle as a Philosophy
Using the philosophical underpinnings of adaptive learning, learning leaders for small, midsize and large businesses can create personalized learning solutions that engage and empower employees to achieve business outcomes. Existing technologies, resources, processes and infrastructures can be creatively utilized to create adaptive learning opportunities. Indeed, traditional ecosystems should be considered adaptive learning systems.
Take the example of instructor-led or classroom training. Given that many subjects and performance objectives are best conveyed through person-to-person interaction, it is unlikely that all companies will fully transition to online training in the near future. Adaptive learning principles can be applied to traditional instructor-led sessions without breaking the bank and without radically modernizing existing training delivery media. Progressive organizations can take advantage of the affordability and portability of content delivery and connectivity to transform classrooms from traditional didactic environments to more adaptive ones.
Operating within the existing infrastructure, the artifacts of traditional classroom learning such as instructor-led lectures, PowerPoint slides and binders of materials can be transitioned to a flexible interactive system that makes the classroom experience more adaptive. The system includes a closed Wi-Fi system for the classroom, interactive e-books, leader-led learning, leaderboard gaming, electronic knowledge checkpoints and Level 1 evaluations. Such an environment enables real-time sampling of students and allows interactive questions to be inserted into the teaching materials.
As the instructor asks a question, students respond on their tablets. The instructor then views the results instantly. This capability is being used to sample a learner’s knowledge before or after a discussion topic and has proven extremely valuable in gauging student comprehension during instruction.
Regular knowledge checks can determine student comprehension and if more detailed instruction is appropriate. Electronic checkpoints and daily quizzes test comprehension of topics taught the previous day. Results are provided to the instructors immediately for remediation. Results are also reviewed after each class to identify where curriculum should be adjusted and modules changed to improve comprehension.
Through proper design, organizations also can use their existing LMS to deliver students personalized learning experiences in areas beyond compliance-based offerings. Modular design, test-in/test-out, pre-assessments, structured branching and structured repetition are all less elegant but effective means to provide students with a customized or adaptive learning experience.
Given what organizations have already spent on learning technology, proper investment in the utility of the current infrastructure could yield the greatest near-term results. This requires organizations to devote time to analysis and design to balance the needs of the learner with the capabilities of existing infrastructure.
While many types of learning can be adapted to machine learning, not all learning should be. This does not absolve learning professionals from still offering the most effective and efficient path for learners.
Adaptive learning should not be considered a privilege of global corporations that have the financial wherewithal to purchase and implement it. With these principles, the existing learning ecosystem in any organization can be optimally utilized to design and deliver learning that maximizes performance and growth.
Any company can be an adaptive learning company, not just those that have additional capital to buy and implement adaptive learning technology platforms.
Aarti Sharma is a corporate strategist with nearly 20 years of experience in advising global corporations. Bob Szostak is a program manager for Raytheon Professional Services. They can be reached at editor@CLOmedia.com.Filed under: Learning Delivery, TechnologyTagged with: adaptive learning, Adaptive Principle, apps and robots, artificial intelligence, augmented reality, big data analysis, cloud computing, Limitations of the Technocentric View, Technocentric View, Technocentric View of Innovation, virtual reality