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Four Key EdTech Trends

ASU-GSV is the leading gathering of edtech companies, entrepreneurs, investors and end-users spanning all sectors of education. Over three days in mid-April, more than 5,000 delegates attend the conference in San Diego each year.

Having attended the conference over the last four years, ASU GSV provides a fantastic insight into that state of the edtech sector in the US. It is fast and furious, with seemingly hundreds of panels, pitch sessions and thought-provoking plenaries.

This year’s theme was ‘bending the arc of human potential’. The premise is that we are reaching a critical inflection point in human history whereby technological progress will outstrip human progress. In this context, ‘bending the arc’ refers to using education and training across all sectors to improve human potential – such that human progress and technological change merge rather than intersect.

In this context, four key themes stood out:

Trend 1: Artificial Intelligence

There is no doubt that a huge focus of the edtech sector in the US is now on how education can harness the benefits of AI and machine learning. In general, the education sector has been a late adopter of AI, but the expectation is that the gains to education through AI will be material. In years gone by, much of what is referred to as AI today, was called ‘second level adaptive learning’. That is, optimising the individual’s learner experience based on the performance of like-students thereby generating better outcomes more efficiently. Now, the application of AI and machine learning in education has moved beyond adaptive learning and into a range of other applications.

In K-12, there was a focus on how AI might reduce the administrative burden on teachers, freeing up time to be more productive in the classroom. As with all new step-change technologies, we cannot yet precisely predict which current or future tasks might be automated with AI.

In previous years ASU-GSV was dominated by ‘personalised’ and ‘adaptive’ in-class technology solutions. This year there was a conspicuous absence of both. In general, there seemed to be a shift away from a reliance on in-class technology that aims to compensate for ‘deficiencies of teachers’, towards AI technology that would build the capabilities of teachers to deliver better outcomes for students. Further, some leading commentators questioned whether students studying individualised digital content in isolation is really ‘personalised’ as content consumption and retention is only one aspect of learning, particularly as the focus shifts to meta-cognitive skills and broader capabilities.

In tertiary education, one key focus area is how AI can create ‘richness at scale’. As one commentator noted, to date online learning in higher education has been focused on creating simplicity to facilitate economies of scale. In contrast, AI has the potential to provide a more individualised, complex and engaging experience at scale.

However, AI presents a number of challenges. One panel member noted that 60% of US data science PhD graduates work for only four companies. The talent shortage is acute. Likewise, access to data sets large enough to generate meaningful AI is problematic as are the comparatively long feedback cycles in education. At the same time, a number of prominent thought-leaders highlighted important ethical concerns and consideration in the application of AI to education.

Our prediction:

Over the last decade there has been a ‘land grab’, as edtech companies - largely operating on SaaS-type subscription business models - have sought to secure and retain districts and schools as customers. It feels as though two new land grabs are underway. First, there will be fierce competition for districts that provide access to large datasets. Second, the competition for talent in AI is going to significantly intensify and new providers of skills-based training, outside of formal education, are going to emerge.

More information

Trend 2: Social and Emotional Learning

Last year, Social and Emotional Learning (SEL) received a high profile at ASU-GSV with Marc Brackett, Founding Director of the Yale Center for Emotional Intelligence, delivering a standing-room only plenary session. This year, SEL was off-the-scale.

The hypothesis is that a child’s academic performance is closely tied to their social and emotional well-being. As a result, there has been an explosion of SEL frameworks, programs, assessments and tools available to schools, teachers and parents. Where school districts originally saw the demand for SEL programs emerge following a crisis event (such as suicide), now increasingly districts see SEL interventions as both preventative and performance-enhancing.

This year there was a strong focus on the neuroscience of learning. With 120 years of learning science, it has only been in the last two decades that we have gained insights into how the brain learns. Fantastic sessions by leading neuroscience researchers consistently highlighted the importance of the brain’s executive function – the ability to control emotions, thoughts and attention – on learning performance and social and emotional well-being. Studies show that executive function is inhibited by a range of factors, including poverty, trauma, malnutrition and sleep deprivation in children. Excitingly, researchers believe that executive function can be developed through specific programs. One leading researcher hypothesised that perhaps differences in executive function would explain the significant achievement gaps in US schools. The critical question now is whether the plethora of SEL programs are actually building executive function in children.

Another development this year, was the focus on SEL programs and tools for teachers. Providing teachers with professional development that addresses their own social and emotional well-being. Importantly, this is seen as essential to teacher effectiveness, learner performance and teacher retention.

Two key challenges for SEL programs stand out First, the primary challenge for SEL is evidence of efficacy. According to a number of leading advocates, the evidence varies considerably – from ‘smoke and mirrors’ to rigorous scientific Randomised Control Trials (RCTs). This challenge is compounded by the iterative nature of digital product development, such that a product is not static long enough to conduct a lengthy RCT. Second, it is apparent that a wide range of digital and analogue programs are entering the market at the same time that existing products are being ‘re-badged’ under the SEL mantra. This is creating a crowded and confused market place for schools.

Our prediction:

We think you will see mainstream publishers and the major education platform companies acquiring or building SEL programs to integrate alongside their existing products in the near future. Consolidation is likely as small niche providers struggle gain the scale necessary to build an effective marketing and sales team. Data analytics and AI will be increasingly pointed towards SEL assessment.

More information:

Trend 3: The Future of Work is Here

In previous years, there was a consistent theme at ASU GSV regarding the mismatch between workforce demands and the typical graduate outcomes for university or college students. This year, there was a new sense of urgency on the part of industry and employers with the lack of talent becoming acute in some industries and professions.

A number of commenters called out the ‘signalling tension and paradox’. That is, universities are no longer an accurate ‘signal’ or filter for relevant skills required in the workforce. This is creating a real tension for employers and is driving demand for a range of disruptive technologies to help measure the cognitive and meta-cognitive skills of applicants, independent of their qualifications and experience. The calls for ‘bottom up skills-based credentials’ are getting louder and more urgent.

The signalling paradox emerges from the continued over-credentialization in the labour market. It is now common place for low wage and low skill jobs to require candidates to have a four-year degree. This has two effects. First, the return on investment in tertiary education is expected to significantly decline (which will put pressure on tuition fees). Second, this trend is further embedding systemic inequality, given the inherent biases and inequities endemic within the schooling and higher education systems.

There was a real sense that the impacts of automation that may have been hypothesised in previous years, are now being realised. Task automation is having a material impact on workers and employers, with some commentators estimating that in 60% of jobs, 30% of tasks are being automated. The result is employers are now indexing creative skills and thinking processes. One commentator described this as the ‘Four Ds’:

  • Discovery-driven thinking (hypothesis, experimentation)

  • Develop commercial acumen (understanding the whole business)

  • Design thinking (value of STEAM)

  • Data acumen (understanding data is essential in all roles)

Commentators also noted the dominant role of SMEs in current and future job creation – with 60% of the global workforce employed in SMEs.

Finally, it is evident that companies are also grappling with the transition to new ways of work. Collaboration, innovation, agile, product management, lean are all terms well understood, however putting them into meaningful action is proving more complex.

Our Prediction:

There is widening gap between ‘skills’ and ‘degree qualifications’. Skills-based training providers will flourish. Partnerships between skill-based providers and traditional tertiary providers will increase significantly (see Trilogy Education as an example). A new skills taxonomy will emerge out of industry to better enable employers to identify and assess skills, independent of formal qualifications.

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Trend 4: Going Global

The global edtech market is now much more prominent in the US. According to HolonIQ, the China and India now account for 70% of the global edtech venture capital. These two countries represent 30% of the global student population. China and India are home to 90% of global edtech unicorns. Some analysts predict 2019 will see the emerging Asian edtech giants make major acquisitions within the US.

Here are the largest edtech deals in 2018 according to EdSurge:

Our Prediction:

Given the high growth currently being experienced in emerging markets, we would expect to see US edtech investors increasingly pursue opportunities in the global markets. At the same time, we think there the large non-US edtech companies will start to consider opportunities to expand into the US market (organically or in-organically). Finally, we support the view from EdWeek that US edtech firms will also increasingly look at opportunities to expand their existing products and services into international markets.

More information:

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