What is Next for Mobile Learning?
In December 2015, there were 4.3 billion mobile phone subscribers in the world. In North America, 77% of families have at least one smartphone and 46% have access to a tablet at home. Worldwide, even though only 75% of the world has ready access to electricity, 75% of the world’s population has access to a mobile phone. Some of the most remarkable learning development projects in the world, such as the Commonwealth of Learning’s Learning for Farmers initiative, use mobile phones and simple messaging systems to transform the livelihoods of thousands of families. Learning through mobile devices is possible anywhere and at anytime and is happening now.
Laptops – now lightweight and low cost, yet very powerful – are ubiquitous in many developed countries and are the device of choice for college and university students in North America. According to a major 2015 study of mobile learning amongst North American students conducted by Pearson, 87% of college and university students use a laptop on a regular basis for their studies, often supplemented by use of a smartphone, tablet or hybrid. While many are seeking to switch to hybrids – larger sized smartphones, often called “phablets” – much will depend on price and functionality of these devices.
Then there are wearable devices such as digital watches, body worn cameras, smart garments, health monitors and wearable simultaneous translation devices. 232 million of these devices were sold in 2015 worldwide and revenue estimates for 2016 suggest this range of devices will secure US$28.7 billion in sales, with a significant component of these sales being smart watches. By 2017 some 322 million devices will be sold worldwide. Mobile devices, all of which can be connected to smartphones, tablets and laptops, could be significant components within a mobile learning program or strategy, especially programs and courses which require locational intelligence or personal health data.
Demand for these devices is strong and getting stronger
From these basic facts, we can deduce three things:
Mobile devices of all kinds are growing in use and demand for these devices is strong – it in fact outstrips demand for desk-top devices.
Students are using these devices in large numbers – for many, laptops, smartphones and tablets are the devices used to read, search, connect and explore.
Learning will increasingly require use of, and access to, these devices, since blended learning and online learning are now the norms for how college and university students learn.
On this last point, some recent summary data has become available. In the United States, there are over 2.85 million individuals studying their entire college or university program online and over 5.8 million will register for one or more online course as part of their studies in 2016. Blended learning is now a part of the fabric of teaching in every college and university in North America and Europe, with some now systematically engaged in flipped classroom teaching. In the United States, it is now the case that more than twice as many students now take a class online as live on campus. There are more undergraduates enrolled in an online class than there are graduate students enrolled in all Masters and Ph.D. programs combined.
At the current rate of growth, half the undergraduates in the United States will have at least one online class on their transcripts by the end of the decade. This is the new normal. The situation in Canada, so far as we can tell, is basically the same. Online learning is part of the standard mix of programs and course offerings across Canada, with very few higher education institutions not engaged in offering online learning to some degree.
Exactly what are students doing with their mobile devices?
But what is it exactly that students are doing with their mobile devices? How are they using them to engage in the work of learning?
On average, students report spending 0.8 hours with a tablet or laptop, up from half-an-hour last year. They are also spending an average of 3.6 hours a day with their smartphones. A recent survey shows 50% reported they do schoolwork daily from smartphones or tablets, which is a relatively small percentage compared to the ownership statistics. Also, students are not as adept at using mobile technology as their popularity suggests. In short, ownership does not have a direct relationship to proficiency.
The primary uses of the devices are:
Accessing the learning management system (LMS) for the course(s) they are taking, especially when this is a key feature of the system.
Using online collaboration tools.
Using the devices (especially laptops and tablets) for note taking, searching for relevant material or checking facts, with a small percentage using lecture capture software or apps.
Accessing e-textbooks, library services or readings shared online.
Using social media.
Accessing simulations and games.
Using e-portfolios to record their work and capture competencies, assessment and feedback.
When they do access the LMS and other tools provided by their college or university, they are focused on accessing course content, assignments (submission, tracking and feedback) and tracking their progress towards their desired qualification. They are also increasingly using mobile devices for peer-to-peer connectivity and for connections to their instructor. These findings are confirmed in a range of studies, most notably in a multi-year study by Chen et al (2015).
Use of the devices is clearly impacted by three key features:
Reliable access to fast broadband – use changes when access is not available or when the services available are slow.
Instructor use and efficiency with respect to these technologies.
Student proficiency in the use of the device functionality and software.
This last point has been the focus for some substantial research. For example, Kaminski, Seel, and Cullen (2003) conducted a survey of freshmen at Colorado State University, and reported professors should not assume students have prior knowledge of the most basic information technology skills. Students, who are more prepared for the rigor of college, perform better than those who lack the necessary skills to perform in this environment. However, many students entering college “do not develop effective learning strategies unless they receive explicit instruction and the opportunity to apply these skills” (Rachal, Daigle & Rachal, 2007, p. 191).
A more recent Jisc (formerly the Joint Information Systems Committee in the United Kingdom) presentation by Knight et al (2015) suggest, at least in a vocational learning setting, students tend to use technology in passive and unimaginative ways. Indeed, as the Higher Education Quality Council of Ontario suggested in an review paper by Lopes and Dion (2015), the idea of the “digital native” who is adept in the effective and creative use of technology is a myth and, further, just like anyone developing new skills and competencies, students need instruction and support in the effective use of technology for learning (Ng, 2012).
Creative and Imaginative Uses of Mobile Learning
There are some remarkable examples of the effective use of mobile devices for learning. One of the largest deployments was led by MoLeNet in the United Kingdom for trades and vocational students between 2007 and 2010. This team supported initiatives across 104 projects involving approximately 40,000 students and over 7,000 post-secondary vocational teaching staff. Evaluation studies show this work increased retention, learning outcomes and employability of students, although the studies also point out these impacts varied by project and by type of student: one size of design does not fit all.
But not all of the research is positive. Some research has shown that students who text in class generally recall less about the classroom content than those who do not. Similarly, those who used mobile devices in class took notes of poorer quality, detracting from another cognitive process by which students integrate new material. Only when the instructor designs texting and other uses of mobile devices into the experience of learning do the benefits of mobile devices in blended classrooms show themselves. That is, learning design and intentionality of the instructor shape student behaviour.
The evidence is also clear that when a college or university adopts m-learning as a core strategy for their growth and development, then a significant number of new developments follow. Colleges and universities which have adopted m-learning and blended learning strategies have seen enrollment growth, secured wider levels of adoption of technology enabled learning amongst faculty and a higher level of student engagement with technology. The majority of studies also show, when intentionally designed, the use of mobile devices in conventional classrooms, blended learning and online learning has a positive impact on learning outcomes.
For example, an important study of students in China using mobile devices showed the planned use of these devices. Students became better engaged in the learning process. Students in this class changed from passive learners to truly engaged learners who are behaviourally, intellectually and emotionally involved in their learning tasks.
What is Next for Mobile Learning?
The field of m-learning is not static – it is rapidly developing, especially given the emergence of low cost virtual reality technologies (3600 cameras and virtual reality enabled smartphones, headsets for virtual reality). Several m-learning developments are anticipated in the near term.
Five in particular are the subject of investment activities and new product development:
Smartphones, tablets and other devices come equipped with sensitive GPS software which is linked to intelligence about the location.
A student standing outside a historical building can be provided with information, images, video and learning resources related to that building. Equipment in a factory can be equipped with sensors which “speak” to mobile devices, providing intelligence about how best to use the equipment, how to read the instruments on the equipment or how to make adjustments to the equipment to ensure the effective operation of that equipment. Geology students on field trips can be provided with maps, information about geological formations, chemical and other kinds of analysis of the landscape. Historians can see images of a place going back in time.
There are many other applications of location based learning which are now being deployed.
Augmented Reality (AR)
AR takes real-life physical environments and mixes them with virtual environments to create an immersive experience for students.
A medical student can be walked through a procedure; architectural students can be shown a building but have layered over it drawings, comments, feedback from building users and comments from the architects who built in sharing their design thinking and assumptions or from those who built it commenting on how the design played out during construction.
New products enabling this work began to appear in 2014 and more are scheduled for the next few years. Microsoft’s HoloLens, Facebook’s Rift, Google’s Cardboard, Samsung’s Galaxy S7 smartphone and other devices will accelerate use and adoption.
Apart from enhancing voice and visual experiences for students with disabilities, wearable devices (including smart watches, fitness trackers, headsets, video glasses) and garments can be used to create new forms of learning for students.
For example, sensors in clothing could detect radiation, subsonic waves, local gravity feeds and other environmental conditions to permit rapid environmental assessments. Wearable video glasses can be used to capture skills and activities for apprentices on the job site – feeds can be viewed by supervisors, teachers and peers for feedback.
Many of these developments are already occurring, but many more will follow with the release of the new products in this category.
Ambient Intelligence and Learning
The Internet of Things, where a great many devices are both wireless-enabled and equipped with intelligent software, will enable devices to connect to a student’s mobile devices and be used for learning and skill development.
A chef in training could be alerted to the heat of a cake cooking in the oven or the need for additional mixing of ingredients to meet the needs of a specific recipe; an apprentice electrician could be alerted to potential difficulties with an appliance or wiring layout because the systems she is dealing with are “intelligent” devices; a scientist working on an experiment could be alerted to the changing state of chemicals or gasses as they occur.
There are a great many applications which are now the subject of significant investments by a variety of organizations, including the European Union.
“Apps” for Learning
There are already a great many learning apps in use for students (mainly K-12) and these are growing in number.
EduApp Center gathers a great many apps focused on learning in one place. These include well known apps like SlideShare, ClassroomReplay and StudyMate which can be readily integrated into a learning management system. A growing number of these apps are collaboration apps and an increasing number of apps seek to collect video, audio and text materials which the student has collected during a day and place them intelligently into either their own learning pages or into shared spaces.
New apps, enabling the use of data analytics to support assessment for learning, are in development at this time.
All of these developments require investment in faculty and student proficiency in both the design of learning and the use of digital tools to aid learning. Given we know that proficiency is a challenge, it is learning needs and intentional design which drives adoption and use not the fact the technology exists and is developing.
What are the key lessons for Higher Education?
Given these developments in m-learning since the first iPhone was launched in 2007, what can colleges and universities learn from the deployment of mobile learning? What are the key lessons? The relevant literature suggests that there are eight lessons from the world of m-learning:
Purposeful planning for mobile device usage
While many may be using mobile devices for their teaching and learning, the more purposeful this work is – the more “designed in” rather than “tacked on” the better. When m-learning is integrated into the design of a class, program or learning experience, then students have better outcomes than if the m-learning is more optional and casual.
Leveraging content and curriculum that is mobile-empowered
Not all resources used for a class are mobile-enabled. For example, not all text or video or audio works in the same way on all devices unless transcoded for universal device use. If the institution is deliberate in it use of m-learning – if it is strategically focused on m-learning as a route to learning outcomes –there must be an insistence across the institution that all learning resources should be available on any device. This is even more important as devices become more sophisticated and more institutions have adopted a policy of bring your own device
Understanding the power of Internet access
Students can find open educational resources which sometimes are superior to their experience of a specific class or subject in college and university – iTunes University, for example, has a very large body of such resources, with Oxford University alone offering 5,360 hours of material in this space.
Students can also readily fact check on their devices and provide updates to their class on recent developments in a discipline or field of study. They are also able to share materials and resources quickly and effectively, capture lectures and share them, Tweet key points and access global networks for ideas and suggestions for assignments.
With emerging technology – especially machine and artificial intelligence – faculty members, instructors and students will be able to do more with the Internet than they can now, including immersive experiences and competency-based assessment. It is key to any strategy for learning design within a college or university that deliberate choices are made about how, when and when the Internet will be a resource and when it will not be.
Preparing educators effectively
Several studies make clear faculty and instructor are not always as enamoured with technology as are their students and they are more cautious about it use and integration into their programs and courses .
Some are not impressed with the quality of the online resources they have seen and still prefer more traditional textbooks and learning materials. Many faculty and instructors are also rightly concerned about the proficiency of their students in the effective use of technology for learning, critical analysis and review and writing. Several studies show both faculty/instructors and students need significant training so as to ensure the design of learning, effective deployment of m-learning and the delivery and support of learning on digital platforms is effective and efficient. Investment in the professional development of faculty and instructors and workshops for students in effective use of technology and software are all essential.
Securing leadership buy-in
Take up for online and m-learning increases when the college or university sees online and m-learning as central to their strategies for securing learning outcomes, growth and employer recognition. Student use and faculty/instructor adoption increases when the leadership of the organization are advocates and demonstrate by their behaviour their own commitment to the appropriate use of technology.
Building personal learner efficacy and capacity for self-directed learning
A variety of studies show we need to do more to invest in student skills and abilities with respect to m-learning technologies but also we need to foster and enable, by design, self-reliance and self-directed learning as more and more professions are moving to competency-based life-long learning requirements. Being intentional, systematic and deliberate about these soft skills is just as important as being effective in using the devices and software.
Measuring project results with meaningful metrics
So few of the projects, which start with respect to m-learning, are systematically evaluated for both learning outcomes and impact, although there are a lot of reviews and evaluations of processes and use of technology. What the sector needs are persuasive, independent learning outcome and behavioural impact studies which demonstrate the efficacy of m-learning. There are some, but few.
Creating an ecosystem that is sustainable and scalable
While many individual faculty and instructors are experimenting with m-learning and some colleges and universities have embraced m-learning as a core strategy for their development and growth, getting to scale is a challenge both technologically and pedagogically. There is a need to think through courses getting to a large scale (moving from 30 students a year to 5,000) and moving from local to national or global.
Colleges and universities need to determine what stage they are at in the development of m-learning. This is necessary to determine when to upgrade its services and technologies, identify what training may be required and to build obsolescence into its planning. Some technologies – Google Glass, for example – may not make it and a college or university may not want to be the last to buy, first to discard.
These eight lessons require the systematic use of strategic foresight in terms of technologies for learning and development in the sector, investments in people and a focus on outcomes and impacts – all core to the work of the leadership team of the college or university.
A key vehicle for “learning on the go”
m-Learning is growing and adapting both to the needs of students, the changing landscape for learning around the world and developments in technology. It will continue to grow and develop, with more and more functionality coming to devices. Student learning “on the go” will become richer and better resourced. Institutions which seek to ignore m-learning, and see it is something at the margins, misunderstand the shift away from digital devices as receivers of transmitted knowledge to devices which are significant vehicles for student engagement.
 Source: Mobile Learning – Why Tech Savvy Educators are Turning to Podcasts available at https://www.buzzsprout.com/blog/2015/01/15/mobile-learning
 Pearson Student Mobile Device Survey, June 2015 available at http://www.pearsoned.com/wp-content/uploads/2015-Pearson-Student-Mobile-...
 Source: The Digital Revolution in Higher Education Has Already Happened – No One Noticed. Available at https://medium.com/@cshirky/the-digital-revolution-in-higher-education-has-already-happened-no-one-noticed-78ec0fec16c7 (Retrieved November 5th 2015).
 Source: College Students Own an Average of 7 Tech Devices available at http://www.marketingcharts.com/online/college-students-own-an-average-of...
 Emily Wright, "EDU Survey: How Are University Students, Faculty and Administrators Using Technology?" blog, Box Blogs, August 8, 2013.
 Dahlstrom, E. and Bichsel, J. (2014) ECAR Study of Undergraduate Students. https://net.educause.edu/ir/library/pdf/ss14/ers1406.pdf
 Chen, B., Seilhamer, L. and Bauer, S. (2015) Students’ Mobile Learning Practices in Higher Education: A Multi Year Study available at http://er.educause.edu/articles/2015/6/students-mobile-learning-practices-in-higher-education-a-multiyear-study
 Kaminski, K., Seel, P., & Cullen, K. (2003). Technology literate students? Results from a survey. EDUCAUSE Quarterly, 26 (3).
 Rachal, K. C., Daigle, S. & Rachal, W. S. (2007). Learning problems reported by college students: Are they using learning strategies? Journal of Instructional Psychology, 34(4), 191-199. Retrieved from EBSCO host database.
 Knight, S., Webber, E, Fuller, C., Holder, J. Bond, T. and Melo, N. (20150 Further Education Learners’ Expectations and Experience of Technology. Available at http://www.slideshare.net/JISC/what-the-learners-say-fe-learners-expectations-and-experiences-of-technology-jisc-digital-festival-2015
 Lopes, V. and Dion, N. (2015) Pitfalls and Potential: Lessons from HEQC-Funded Research on Technology Enhanced Instruction. Toronto: Higher Education Quality Council. Available at http://www.heqco.ca/SiteCollectionDocuments/Technology@Issue.pdf
 NG, W. (2012) Can We Teach Digital Natives Digital Literacy? Computers and Education, Vol 59(3), pages 1065-1078.
 The Impact of Mobile Learning – Examining What It Means for Teaching and Learning. Available at http://media.cornwall.ac.uk/ostube/media/document/83.pdf
 See Peverly, S. T., Vekaria, P. C., Reddington, L. A. Sumowski, J. F. Johnson, K. R. & Ramsay, C. M. (2013). The Relationship of Handwriting Speed, Working Memory, Language Comprehension and Outlines to Lecture Note-taking and Test-taking among College Students. Applied Cognitive Psychology, 27, 115-126. Published online 4 November 2012 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/acp.2881
 The impact of mobile learning on students' learning behaviours and performance: Report from a large blended classroom. Available from: https://www.researchgate.net/publication/249379893_The_impact_of_mobile_learning_on_students'_learning_behaviours_and_performance_Report_from_a_large_blended_classroom [accessed Feb 21, 2016].
 See, for example, the study reported here: https://www.insidehighered.com/news/2016/02/22/study-faculty-members-skeptical-digital-course-materials-unfamiliar-oer