The concept of mobile learning surfaced in the 70s, and became a hot topic around the 2000s amongst academics, who explored its potential to promote learning outside of the classroom. However, it was only around 2010, when smartphones had just enough battery power to support a few hours of calls, texting and the odd round of Angry Birds, that mobile learning exploded onto the market as a commercially exciting product.
The predominant theory was: if the devices can support it, acceptance of mobile technology could transfer to acceptance of mobile learning, especially among students with high self-efficacy (Irby & Strong, 2015). In addition, as Sharples, Taylor, and Vavoula (2007) pointed out, mobile learning has some unique benefits: it is personalised, learner-centered, situated, collaborative, ubiquitous, and highly contextual.
The language learning app Duolingo, propelled by a beta waiting list of 500 000 users elbowing each other to get access, dropped their iOS app in November of 2012 after securing multiple rounds of funding. At EdTech conferences across the world, mobile learning enthusiasts ruminated on the possibility of becoming the next Duolingo. The fun, gamified format, excellent use of core mobile technology (audio and microphone) and unintimidating micro-lesson structure seemed like an elegant solve to the issues of motivation and throughput that had plagued the MOOCs of preceding years. Why not take advantage of the device that is already in the learner’s hand, and already has their attention? Well, turns out there are a few good reasons, depending on what you are trying to achieve.
Due to the constant temptation to check their smartphones, today’s students are spending less time focused on their schoolwork, taking longer to complete assignments, and feeling more stressed in the process.Dr. Larry Rosen, Professor Emeritus and Research Psychologist, 2017
We’ve all heard the rumours: smartphones and attention span are not friends. The youth can’t concentrate. I’ve always turned my more skeptical eye towards articles that profess the detrimental psychological effects of mobile phones. I’ve considered them to be mostly alarmist and technophobic; ignorant of how the benefits can outweigh the risks. However, as the years ticked past, more and more robust and diverse studies have been published, and I’m afraid I’ve got some evidence to show you.
There are two core themes in the literature on the connection between smartphones and reduced attention span. The first is that smartphones create a lot of distraction, both through notifications, but also through temptation primarily driven by a fear of missing out (Rosen 2017). The second is that smartphones have encouraged an increase in multitasking behaviours, which has been shown to reduce concentration and efficacy (Rosen 2017). We can see both of these patterns of behaviour as inherent to the fundamental design of a smartphone: multiple applications, which represent tasks, behaviours and habits, are all located within a small 15 cm x 8 cm rectangle.
It’s worth noting that laptops and desktop computers do present similar challenges to mobile technology when it comes to enabling multitasking and distraction, which can “decrease academic performance and learning” (Haughton et al, 2013). However, so far it would appear that these challenges are more pronounced in mobile technologies, as computers are still used for more substantive tasks that require concentration for long periods of time.
The smartphone will never be a place for one thing to happen for a long period of time. Many things happen on phones, all the time, at the same time. Here are some numbers on how that impacts how people use them:
students will spend 30% of a 15 minute study session being distracted (Rosen et al, 2016, USA)
of the times when a student is distracted, social media was responsible for the distraction (Rosen et al, 2016, USA)
the number of times college students unlocked their phones per day (Rosen et al, 2017, USA)
the number of hours college students spent on their phones per day (Rosen et al, 2017, USA)
the number of minutes a moderate smartphone user can be restricted from accessing their phone before feeling anxious (Cheever et al, 2014, USA)
Now, these behavioural patterns work quite well for a number of different activities, particularly the most popular uses of the smartphone: social media, texting, calling and searching the internet. Where these activities are interactive, they are usually initiated by something either in the world (“I have to post a photo of this pigeon”, or “Who was the lead actress in The Queen’s Gambit?”) or they are initiated by something on the smartphone itself (“I have to reply to this text from Stephanie”, or “I wonder who looked at my Linkedin Profile”). These interactions are therefore usually quite reactive in nature (even if the reaction does devolve into passive, mindless scrolling a lot of the time).
So, we’ve established that smartphones encourage us to multitask, distract us with notifications, temptation and anxiety, and generally put us into a reactive mindset. How does this context perform as a learning environment? Most types of formal learning require a sense of proactive drive: I am completing this learning for a future benefit of some kind. The exception here is inquiry-based learning, which is very prevalent on phones (e.g. “can I feed bread to my ducks?”), but usually not part of a formal learning intervention. Most types of formal learning also requires some uninterrupted time on-task. By asking someone to use a smartphone to learn, you are at risk of asking them to use a tube of glue to cut through a piece of paper.
So when is mobile learning a good idea?
But yes, of course, there have been some great examples of mobile learning being a huge success. Duolingo, Brilliant, even YouTube – it CAN work, but not for everything, and not for everyone. You are not going to solve your low compliance training throughput rate by creating an app.
There are two broad sets of considerations when deciding whether a learning programme will work well as a mobile learning intervention, both of which should be explored during your needs analysis: the type of learner, and the type of content. As mentioned earlier, mobile learning shows the most promise for learners who have high levels of familiarity with mobile learning and high levels of self-efficacy (can motivate and organise themselves). I can perhaps add here that, in some contexts, mobile learning is your only choice because your learners just don’t have access to computers and stable wifi, and in these cases, of course, mobile learning is better than no learning at all. As for the types of content that can work well delivered as mobile learning, these can be summarised as follows:
In addition, inquiry-based learning also works well as a mobile learning intervention (think, for example, subreddits and topical Facebook groups), as well as topics that require rote learning to master (of which a new language is a good example).
It is also important that topics covered in mobile learning can be broken up into short, bite-sized pieces, as these are more compatible with typical mobile user behaviours. If done well, this could greatly improve the chances of mobile learning succeeding, as learners don’t need to be able to remain on task for as long. Highly complex topics often require extensive didactic explanation to be covered coherently, and assignments that can accurately assess their outcomes may take multiple days to complete. Therefore, you will be hard pressed to find a student with the concentration skills and perseverance to complete a master’s in Financial Engineering on their smartphone.
Mobile learning emphasizes the centrality of learners and close integration of learning with other aspects of their lives and work, so that education is no longer seen as a separate activity that has to take place in a school, college, university or other establishment.Kukulska-Hulme, 2010
As you have likely deduced from your own experiences of mobile learning, as well as from the examples discussed so far, mobile learning generally works best outside of formal learning contexts as a means to provide personalized life-long learning (Gu et al., 2011, Wu, Hwang, & Chai, 2013). However, there are definitely ways for instructional designers in more formal learning contexts to make appropriate use of mobile learning. We’ve outlined some examples for different sectors below.
Job aids are a good example of inquiry-based learning that can be delivered very effectively as mobile interventions, especially when paired with a social learning platform where employees can answers each others’ questions in a Reddit-style context. Also consider options for exploiting the contextual nature of mobile learning, such as an audio-based virtual tour of the office during onboarding. A weekly email (no longer than a 5-minute read) or small chunks of well designed, visually appealing content might also be a good way to drip-feed a topic that can easily be broken down into small chunks, such as leadership skills or onboarding (see Stephanie’s article on the success of a well-designed mobile learning onboarding programme here).
Additional languages, with its heavy reliance on rote learning, active participation and core smartphone technology (audio and a microphone), is the perfect candidate for mobile learning, as evidenced by Duolingo’s success. In addition, math and general problem-solving skills also do well in mobile learning, as these are also highly interactive and can easily be broken up into small, bite-sized chunks of engagement, but other topics that can easily be broken into short, bite-sized chunks could also perform well on mobile. Again, also look for opportunities to introduce mobile learning in a supplementary fashion, for example by teaching a geography or history module through a contextual audio tour.
Higher education is more tricky, as the concepts covered are more complex and can therefore not be broken into short, 5-minute chunks as easily while maintaining coherence. However, again mobile learning can serve an important supplementary function through things like peer-to-peer support forums, audio tours of specific sites, and drip-feed email campaigns.
Have you created an amazing example of well-designed mobile learning? Drop it in the comments below, we’d love to see it.
Sources and further reading
Cheever, N.A., Rosen, L.D., Carrier, L.M., & Chavez, A. (2014). Out of sight is not out of mind: The impact of restricting wireless mobile device use on anxiety levels among low, moderate, and high users. Computers in Human Behavior 37:290-297.
Gu, X., F. Gu and J.M. Laffey. (2011). Designing a mobile system for lifelong learning on the move. Journal of Computer Assisted Learning 27: 204-215.
Kukulska-Hulme, A. (2010). Uniqueness of mobile learning; http://www.search-document.eom/doc/1 /3/m-learning- 2010.html .
Lee, K., Kim, S., Ha, T., Yoo, Y., Han, J., Jung, J., & Jang, J. (2016). Dependency on Smartphone Use and Its Association with Anxiety in Korea. Public Health Reports 131 (3): 411-419.
Haughton, N., Yeh, K., Nworie, J., & Romero, L. (2013). Digital Disturbances, Disorders, and Pathologies: A Discussion of Some Unintended Consequences of Technology in Higher Education. Educational Technology, 53(4): 3-16.
Hwang, G. J., Wu, P. H., Zhuang, Y. Y., & Huang, Y. M. (2013). Effects of the inquiry-based mobile learning model on the cognitive load and learning achievement of students. Interactive Learning Environments 21(4): 338-354.
Irby, T., & Strong, R. (2015). A Synthesis of Mobile Learning Research Implications: Agricultural Faculty and Student Acceptance of Mobile Learning in Academia. NACTA Journal 59(1): 10-17.
Rosen, L.D., Carrier, L.M., Miller, A., Rokkum, J., & Ruiz, A. (2016). Sleeping with technology: Cognitive, affective, and technology usage predictors of sleep problems among college students. Sleep Health: Journal of the National Sleep Foundation 2: 49.
Rosen, L.D., The distracted student mind – enhancing its focus and attention. The Phi Delta Kappan 99(2): 8-14.
Rosen, L.D., Carrier, L.M., & Cheever, N.A. (2013). Facebook and texting made me do it: Media-induced task-switching while studying. Computers in Human Behavior 29 (3).
Sharples, M., Taylor, J., & Vavoula, G. (2007). A theory of learning for the mobile age. In R. Andrews & C. Haythornthwaite (Eds.), The Sage handbook of elearning research pp. 221-247. London: Sage.
Wu, P. H., Hwang, G. J., & Chai, W. H. (2013). An expert system-based context-aware ubiquitous learning approach for conducting science learning activities. Educational Technology & Society 16(4): 217-230.