How Can Edtech Address Evolving School and Workforce Needs?

The education-to-employment gap continues to be the subject of much discussion, often surfacing in policy debates across both the developed and the developing world. The gap, which centers on skill acquisition, has led to relatively high levels of youth unemployment worldwide, as is visible in recent data from the Organisation for Economic Co-operation and Development (OECD) and the 2018 QS report "The Global Graduate Skills Gap in the 21st Century," which calls the skills gap "a global and significantly widespread issue." "The Future of Jobs Report 2018" from the World Economic Forum (WEF) also elaborates on the problem by emphasizing the skills with which the current and future workforce must be equipped in order to succeed in an increasingly technology-driven workplace, including communication, problem solving, and critical thinking, along with the ability to be agile and empathetic and possess a growth-oriented mind-set.

This gap can be addressed throughout K–20 education. Indeed, the mismatch between educational skills and workplace needs presents a number of opportunities upon which education technology (edtech) in particular can build. According to research from Microsoft and McKinsey & Company's Education practice, adequate workforce preparation will require an emphasis on personalized learning environments that promote emotional and cognitive skill acquisition [https://educationblog.microsoft.com/en-us/2018/01/class-of-2030-predicting-student-skills/] in primary and secondary education, as well as postsecondary education.

Edtech businesses have the potential to meaningfully contribute to job readiness and employability for existing, emerging, and future professional roles. Those edtech solutions that are specifically designed to enable the cultivation and honing of broadly applicable skills appealing to industry—such as those highlighted in the WEF report—will likely be highly sought after by educators.

In this regard, employing existing learning sciences research on how people process and encode knowledge could have significant implications for the design and development of effective edtech solutions. Taking recent research into consideration, below are four insights to inform learning designs for the 21st century:

1. Design for deeper learning that ties in-class experiences to real-world problems.

   Deeper learning, as defined by the William and Flora Hewlett Foundation, involves a framework of six competencies: "master core academic content, think critically and solve complex problems, communicate effectively, work collaboratively, learn how to learn, develop academic mindsets." The framework includes fostering key competencies for success in work and life through activities that build strong connections between classroom and real-world learning. This includes industry collaborations, co-designed learning solutions, mentoring and apprenticeship-based learning, as cited in the 2018 report "Connecting the Worlds of Learning and Work."

2. Embrace a "learning from failure" approach.

   Productive Failure (PF) Learning Design offers an alternative to traditional teaching and learning approaches. This methodology focuses on the premise that learning through failure entails higher and deeper learning gains for students. The PF learning environment is designed to create failure. In this context, learners generate and explore complex and novel problems while innovating solutions. This guided exploration replaces early direct instruction by allowing learners to activate and differentiate relevant prior knowledge, generate multiple representations of problems, and thereby develop skills needed to solve "wicked" real-world problems. This emphasis on learning from failure and embracing a collaborative learning cycle readies students for 21st-century learning needs.

3. Reevaluate existing technology offerings using a learning sciences lens.

   In order for the inclusion of edtech—both in formal curricula and in our daily lives—to be meaningful and sustainable, solutions that enable superficial learning should be eschewed in favor of those that enable deeper learning. In this regard, reexamining and reevaluating edtech offerings based on evidence from the learning sciences will be critical. When considering the suitability of digital learning products for students at any level, one must know what qualities to look for—the aim should be to examine the tools' overall quality of learning, learner interaction, and the mode of instruction.

4. Introduce simulations as a key feature of a successful learning design strategy.

   Realistic simulations, including those that incorporate virtual or mixed reality, comprise the types of experiential learning that accelerate skill acquisition. Putting students in action-oriented roles allows for greater understanding of the underlying behaviors, functions, and abstract knowledge of the learning process through manipulations, causal thinking, and observing the results of actions over time. According to the Science Education Research Center at Carleton College, a well-executed simulation "includes a strong reflection summary that requires students to think about how and why [species/agents in a 2D/3D simulation] behaved as they did during the simulation."

   For instance, a study of learning designs on climate change as a complex system using Productive Failure coupled with agent-based computer models was reported to produce deeper learning gains among learners. In another relevant example, ecoMUVE, a middle school curriculum developed at the Harvard Graduate School of Education, illustrates how the study of ecosystem science concepts through authentic virtual simulations enabled deeper scientific inquiry by requiring learners to think about complex causality. Such modeling, simulation environments, and trial scenarios enable learners to examine each scenario and emergent phenomena, thereby requiring them to think critically about alternative viewpoints in a manner that supports deeper understanding and thinking.

   Platforms that provide learners with the requisite professional tools, structures for interactions like scientific data collection, and pedagogical supports for specific needs related to demanding epistemic tasks will best prepare graduates for increasingly complex workforce challenges.

These suggestions on edtech design may further enable the development of collaboration, problem solving, and communication skills, as well as the learning, unlearning, and relearning of information—critical skills that students can use to address the rapidly evolving technological environments of the 21st century and the future of work. Meanwhile, edtech creators across the K–20 spectrum would do well to keep in mind that today's learners should be treated not as passive consumers but rather as active co-creators of their own epistemic knowledge.

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Nilanjana Saxena is a learning design professional who creates research-driven learning experiences for an institution of higher education in Singapore.