Smart is no longer just an adjective. It is now the pseudonym for anything and everything that enhances functioning in the multi-device ecosystem; by easing our day-to-day tasks, accelerating the speed of information flow, and enabling us to do things in a matter of seconds (or micro-seconds!) that would not have been possible otherwise. Be it smartphones, smart watches, or smart glasses—they are all here to make things easy and us smart! With the capabilities evolving astonishingly over time, it doesn’t come as a surprise that devices are only getting “smarter.” The impending discussions on machine learning and AI evolution support this claim. However, it’s our growing dependency on smart devices that fuels it, and that includes smarter learning.

Smart everything, everywhere

Deloitte’s Mobile Consumer Survey 2017—The Australian Cut, touches upon a very important question, “What did we ever do before smartphones? Today our phones are indisputably indispensable, and smartphone and smart devices are helping to redefine the future of work.” The report brings together various elements that build the smart ecosystem, which starts from the changing device landscape.

“Eighty-eight percent of Australians now own a smartphone. Globally, Norway, Netherlands, Ireland, and Luxembourg have surpassed the 90 percent threshold. UK penetration rates are up four percent from 2016 to 85 percent.” The smartphone penetration is real and ever increasing and is no longer just about the younger generation. According to the report, “Silver Surfers (the older generation who are proficiently using mobile devices now) are now a new and growing market for mobile phone providers and operators.”

Inferring from the Internet trends report for 2017 by Mary Meeker from Kleiner Perkins, “In the US alone, the average adult spends almost six hours every day engaged with digital media of which the greater part goes into interaction on mobile devices” (Figure 1). 


Figure 1: Adults in the USA are spending an increasing amount of time with digital media 

The second element is the data and content consumption. IDC estimates that by 2025, approximately 80 billion devices will be connected to the internet and the total amount of digital data generated worldwide will hit 180 zettabytes (source: Forbes).  The Deloitte report states, “Data usage is up, demand and exceeding limits is up, video watching is up, and most of all—streaming video on demand and live TV is up. Consuming our favorite content on our smartphone is the new norm.”

Driving this further is the sizable increase in data packages, with network operators competing to create lucrative packages and investing heavily in the quality and coverage of their networks to make it work.

Smartphones are undoubtedly everywhere, inevitably the first and last of anything we do. So, it doesn’t come as a surprise that, “Smartphones are emerging as an essential work tool. Of the 67 percent of respondents who use their smartphones for work, email (48 percent), making standard calls (47 percent), and calendar management (29 percent) are the most popular activities.” But the invasiveness of mobile devices doesn’t end there. According to a research publication in the IJLM by Agnes Kukulska-Hulme, “Learning with mobile devices is rapidly entering the mainstream of education (Johnson et al. 2011, 2014), but years of intensive research activity as well as innovation in classroom and out-of-classroom practices have produced many conceptualizations of ‘mobile learning’ (Traxler 2007), including some that focus strongly on the affordances of mobile technology.”

Smarter learning

Undoubtedly mobile learning has tangible value and unique features, mostly piggybacking on its affordances, of which IoT and machine learning hold a major share. Predictive text, route suggestions (location-based service), voice assistants, and more, the scope of machine learning in smartphones is vast. But, how then does this support smarter learning?

While automated news or information updates are the classic examples of pop-up notifications that can trigger learning, mobile learning apps (including but not limited to mobile LMSs), micro-learning, video-based learning, augmented reality, etc. take smart learning further ahead. As Hulme notes, “In a world in which cell phones have quickly evolved from being merely “mobile” to the more elevated status of ‘smart,’ all human users would do well to understand the implications. As phones and other portable devices gradually become more context-aware, accumulating and continually analyzing information about a person’s whereabouts and interactions, the degree of smartness is increasing. Augmented Reality perceived through the smartphone imbues familiar objects with additional layers of data and meaning, setting new cognitive and intellectual challenges. Sensors in the phone or embedded in a person’s surroundings can deduce mental states, moods, and intentions by monitoring physical symptoms, activity patterns, and behaviors (Pavel, Callaghan, and Dey 2011).”

Mobile learning accelerates the learning process through easy accessibility, shareability, engagement, and just-in-time capability, amongst other factors. Beyond this too, mLearning now focuses on learning analytics, that analyzes the data created by each learner to track their personal likes and dislikes related to the content type, format, and depth of information covered in the courses. Adding to this is the intensive association with technologies like blogs, social media apps, etc. for knowledge sharing, collaboration, and community learning that sets precedence to a whole new smarter, interactive, and mobile learning.

Smarter learning is not just about the technology, but about the way it is utilized to enhance the process of learning. Undoubtedly, the proliferation of IoT ecosystems, emergence of wearable technology, one touch and voice-based activation, virtual assistants, the applications of machine learning and its integration with mobile technology could revolutionize the way we learn. The trick lies in utilizing the smarter devices for delivering pervasive, contextual, collaborative, and personalized smarter learning to create a seamless learning process to aid the smart learners.