“It is a thous and times better to have common sense without education than to have education without common sense.”
– Robert G. IngersollChapter contents
7.2 Typical Behavior of Users
7.3 Ways of Using Mobile Devices
7.4 Challenges with Mobile Devices
7.5 Design of Mobile Learning
A rather general definition of mobile learning (or m-learning) is the acquisition of knowledge or a skill through mobile technology that results in an alteration of behavior or attitude.1
Initially, when considering the tiny screens of mobile phones and restricted internet speeds, we had some doubts about the efficacy of mobile learning. However, with the rapid growth in usage and sophistication of mobile devices, we are convinced that this will become one of the dominant forms of learning.
Attributes of mobile technologies include them being highly portable (e.g. weight and power), individualized, unobtrusive, available anywhere, reliable across different devices and connections, open throughout a range of vendor products, adaptable and matched to a user’s changing skills and knowledge, useful and practical to work and personal life, coherent and persistent across a lifetime in keeping track of the accumulated resources and intuitively easy to use.2
Besides mobile and smart phones and tablets, other typical mobile devices include iPods, MP3 players, personal digital assistants (PDAs), mobile computers, handheld gaming devices and calculators with mobile connections.
Figure 7.1: Typical mobile devices
There are now (2011) well over five billion mobile phone subscriptions with over 5,000 unique types of mobile devices.3 In Europe, over 90% of young people (16-24) own a mobile phone, so it’s safe to assume that mobile learning, in some form, is here to stay.4
• Analog cellular telephony (1G).
• Digital mobile communications (2G).
• Wideb and mobile communications (3G).
• Broadb and fourth generation networks (4G).
Although many engineering education apps exist in the mobile environment, a challenge is that the different apps don’t operate seamlessly and holistically in terms of accessibility and sharing of data.7 Inevitably, being new, there is also limited evidence about the learning effectiveness of these mobile apps.
In the following section we will examine typical behavior of mobile users and ways of using mobile devices. The chapter will be concluded by detailing the ever-present challenge of mobile technologies, design and applications.
7.2 Typical behavior of users
Users today want immediate access to real-time information, technical stability and reliability in their applications and up-to-date information that they can trust.8
Typical behavior takes the forms of:
• Activity in short bursts.
• Moving from one device to another very quickly.
• Multitasking when working with devices.
• A spike in device use between 8.30am and 1.00pm.
According to recent research from Yahoo!, there are seven mobile modes:
• Connect (where most users spend time–40%)
• Manage (e.g. banking)
• Navigate (e.g. directions)
Searching and Informing would probably be the dominant mode for learning.
There is a myriad of different ways to use mobile devices. A reasonably exhaustive list will be provided in the next section.
7.3 Ways of using mobile devices
The portability, ease of use, spontaneity of use and quality of recording of mobile phones means that there are many opportunities to use them for education. The main disadvantages are in the lack of compatibility with different phones and computers (e.g. mobile image aspect ratio), lack of resolution in low light and poor audio quality.9
An excellent use of mobile phones is the creation of videos. Millions of videos (often two or three minutes in duration) are just a click away for the adept user with often excellent quality despite the small viewing screen.10
Mobile phones are useful in creating digital narratives in planning a story, creating and editing it and finally sharing the output on a YouTube type site. In essence, the opportunities for mobile technologies are to combine collaborative, constructionist and contextual elements with the learning process.
Categories of use for mobile technologies include administrative (e.g. calendaring and timetabling), referencing (eBooks and dictionaries), interactive (contact, response and feedback), simulations and games, data collection, location aware (e.g. GPS) and collaborative (instant messaging, web and videoconferencing).11
A rather exhaustive list
• As a communications tool (instant messaging and emails).
• For accessing or modifying information.
• As an assessment tool (e.g. quizzes and photos of workplace scenarios).
• For connecting to an LMS or related system (e.g. as whiteboards/web browsers).
• To create augmented reality scenes (using GPS properties to add further data to a real scene, or superimposing text and graphics on a view).
• To create and play back learning content (e.g. podcast/blogging).
• To read data in the environment (e.g. using a GPS/RFID system or quick response tagging),
• To verify identity of users.
• As virtual tour guides (using GPS capabilities).
• As an instantaneous community or personal organizer (e.g. managing groups in the field).
• As the learner’s personal context identifier (e.g. body movement, pulse and blood pressure).
• As a calendar and reminder for commencing or initiating events.
• To facilitate communication between instructors and learners.
• To allow learners to collect photos, audio and video evidence of their training.
• To allow learners to access learning content including that required for assignments (through an LMS or the internet).
• For undertaking written assignments or tasks.
• For communication between instructors and learners.
• For trend tracking and analysis.
• For text messaging.
• For social networking.
• For formation of communities.
• For information retrieval.
• For collection of data.
• For audio, video and web conferencing.
• For proximity identification and detection to other mobile users.
• For geographical location (geolocation) identification.
• For the creation of videos and graphics (including audio).
• To remotely control other devices.
• For simulation.
• For performance support and live coaching.
• For recording, archiving of live sessions and the environment.
• For learning games.
• For web browsing.
• Allowing mobile review of PowerPoint, Excel and Word Documents.
• For instantaneous or fast self-organization of individuals.
• To store and transmit data for later analysis.
• For security due to location tracking.
• For continuous operation and communications (worldwide roaming).
• To allow online payment flexibility (e.g. fees paid by SMS).
• For unique mobility identification (with a device that has a unique identifier).
• As affordable computing capacity (e.g. far cheaper than netbook).
• To form a semi-permanent relationship with telecoms provider (thus allowing for rapid dissemination of intelligence to a wider audience with some credibility).
• To provide a slightly higher degree of immunity to viruses and security issues (although phone hacking is alive and well).
• For easy connection to other “more intimate” information already on your device (e.g. contact details of others).
• For easy-to-use tools such as calculator, contact list, geo location and camera.
• To allow multiple channels of communications (e.g. SMS and GPRS).
• For recording of key course events for later review.
• For interviews with students.
• For recording feedback from other instructors.
• For recording of reflections.
• To record student performance.
• To send encouraging messages to other instructors.
• For responding to progress reports.
• For timing analysis of experiments.
• For text messaging to respond to surveys.
• For identifying definitions for new terms.
• To record lab experiments (using mobile phone camera).
One final suggestion for using mobile phones in a learning environment included youngsters (16-24) who were not currently engaged in any schooling but who showed enthusiasm for learning English and Mathematics using mobile phone games.16
Typical job roles using mobile learning
Typical job roles where mobile learning would be ideal would be field engineers or technical support technicians fixing a photocopier to an instrument engineer looking up key information on how to configure the device. Retail employees who are unsure about the operation of a particular item of merchandise could look it up. Sales personnel who are travelling and need to review a particular approach to provide greater credibility when talking to a client would also find this useful.
Challenges with mobile devices can be quite severe but these have to be dealt with in achieving an effective implementation.
7.4 Challenges with mobile devices
There are some problems in implementing a mobile learning system and these include:17
• Poor acceptance. This can be because the technology is so new that individuals (and management) are dubious about the effectiveness. Privacy of information can be an issue as the devices are mobileand thus more easily accessible. Others worry about the breakdown in life-work balance due to excessive use.
• Instructional Design Weaknesses. The tiny screen size and keyboards require significant modifications to the traditional approach to learning.
• Technical problems. This includes problems with bandwidth, reliability of communications, security of messages (and indeed of the device), lack of a coherent environment (e.g. different devices–screen, keyboard / batteries / bandwidth) and wide range of costs in different environments.
A set of suggestions on optimizing your mobile learning design is considered in the next section.
7.5 Design of mobile learning
Designing effective mobile learning necessitates a different way of operating. Some overall suggestions for creating successful mobile learning include:18
• Allow sufficient time to explore the mobile technologies to apply them competently.
• Blend mobile with online learning as well as the classroom and lab settings.
• Ensure that the technology can be applied spontaneously.
• Leverage its portability to use in unusual hard to reach places for normal learning.
• Apply in both an individual and group approach.
• Exploit the affordances of mobile technology even where the results may be suboptimal compared to a more measured traditional approach.
• Emphasize the use of the learner’s own mobile technology.
• Leverage the ease of production of learning to increase consumption of learning and vice versa.
Seize the moment
Some suggestions on seizing a quick moment in time in using mobile learning include waiting at airports, medical waiting rooms, travelling in a car, plane or train, in a queue and while exercising.19 This should be kept in mind in the design process.
Specific implementation tips for designing mobile learning
The following are a few specific suggestions when implementing mobile learning.20 The user often has a very short and fractured experience in undertaking any mobile learning and has limited bandwidth (due to cost and technical access).
• Follow the well-trodden KISS principle in keeping the design as simple as possible and thus avoiding complex navigation and interaction and with an absolute maximum of a few minutes (perhaps five is the limit).
• Keep information density very low and select content that can match this.
• Use multimedia sparingly such as splash animations and unnecessary glitz.
• Harness the power of collaboration. This is a key strength of a mobile device so try and build this into the learning experience.
• Apply the tools that come with the device such as geolocation/customized calculators/games and simulations.
• Use existing facilities and content already available on your LMS.
• With connectivity so much more reliable and cheaper, ensure you wring every ounce out of this facility.
• Watch out for small screens with limited resolution.
• Note that networks are unreliable.
• Remember that mobile learning is still virgin unknown territory.
• Think about total cost of design and actual return (i.e. is the work worth it?).
• Ensure that learning is in micro chunks.
• Underst and the gestures and actions of the user.
• Try to use an external server (or the ‘cloud’) to optimize performance.
• Remember that emulators are a great way to test out your design.
• Test and test again in different situations and different networks (including when your device is updating itself).
Mobile programming languages
Despite the relative youth of mobile phones, there is a large choice of programming languages to work with. Mobile phones (such as the Blackberry and iPhone) can provide facilities far more than mere voice and text messaging with multimedia playback, document editing and audio/video streaming and are challenging the traditional computer for many activities. There is thus a growing need for programmers with skills in developing software for mobile applications. There are a number of challenging characteristics of mobile phones such as bandwidth, screen size/resolution, processor speed /type, memory consumption, battery life and input tools.
There are a number of programming languages used in mobile phone development.21 These include:
• Java (used in the Blackberry, Google Android Operating system and Nokia Symbian mobile phones).
• Flash (from Adobe–however, they are now discouraging it for mobile applications).
• Objective C (for the Apple iPhone to be used with the Apple iPhone SDK).
• C++ (used in some Nokia Symbian mobile phones).
• .Net/C# (Microsoft’s Windows Mobile).
• GO (Google’s programming language).
• BREW (proprietary from Qualcomm).
• VoiceXML (from the World Wide Web Committee’s standard XML).
• XHTML-MP (Extensible Hypertext Markup Language: Mobile Profile–main protocol used in conjunction with CSS – Cascading Style Sheets).
• WAP and WML (Wireless Access Protocol and Wireless Markup Language–early standard and works on most basic phones).
Java is a complex language and can be broken down into several sections:
• Java Micro Edition (Java ME): open source, widely supported and many open-source tools for developing mobile applications.
• Sun Java Wireless Toolkit for Connected Limited Device Configuration (CLDC): an easy-to-use development environment (including simulation tool) to develop mobile applications based on Java ME.
• Blackberry Java Development Environment: development environment and simulation tool for building Java ME and Blackberry-based applications.
Learning management systems
Learning Management Systems that have been adapted to mobile usage include:22
• Blackboard Learn.
• Cell Cast (from onPoint Digital).
• Chalk Pushcast (for the Blackberry platform).
• eXact iTutor (wearable, wireless mobile learning platform from Giunti Labs).
• KMx (Knowledge Management Solutions).
• Sakai (open source)
• MLE-Moodle (a plug-in for Moodle–the open source LMS).
• Mobile Moodle for the iPhone.
• MOMO (Mobile Moodle)–install a Java-based MOMO client on a mobile phone. A few selected applications will be discussed in the next section.
Bring Your Own Device (or BYOD)
Many employees are bringing their own tablets and smartphones to the workplace–not only for personal use but to access company resources (such as database/email and servers).23 Three issues need to be considered here. These include security (of data and physical device), costs (of installing Wi-Fi facilities and paying for the use of the personal smartphone on company business) and support for a plethora of new portable devices (which the help desk may be utterly unfamiliar with). Clearly new company-wide policies and procedures are required to deal with this new issue.
Different university approaches
The Blackberry was used for the programming applications of students at the University of Guelph, although with the rapid growth of the iPhone and Android devices, this may obviously change.24 Typical programming assignments for students included a mobile quiz application, calculator, address book and text editor.
At Tuskegee University, a survey of using mobile phones together with the Blackboard Mobile Learn LMS in the undergraduate engineering courses was investigated.25 The technology was used in the classroom for homework, exams and use of images and video clips. Outside the classroom the mobile application was used to access course materials and tools. While students appreciated the added flexibility there was some doubt as whether this would replace the standard Blackboard LMS in the near future.Mobile learning for a chemistry program
Memorization of numerous molecular structures, functional groups and reactions can be challenging for undergraduate organic chemistry courses. Traditionally, cardboard-based flash cards have been used in the past; but this was replaced at Georgia Gwinnett College by smart cell phones with Mobile Powerpoint.26 Students could flip through their electronic flash cards while sitting on a bus or in a car or train or anywhere with a few minutes to spare. Student reaction to this was very positive and this facility was extended to other courses and topics.Mobile learning on digital signal processing
Apple’s devices such as the iPhone, iPod and iPad (based on the iOS operating system) are becoming important tools for engineering and science education.27 An application called i-JSP executed directly on the iOS and was coded at Arizona State University. This was based on an earlier software package (J-DSP) that was web-based and platform independent and provided positive feedback on improved student learning and involvement with digital signal processing (DSP). This allowed for functions for Fast Fourier Transforms, filtering and spectral analysis though an easy to use graphical user interface. In addition, concepts such as MIDI, DTMF and sound capture and playback could be tested and demonstrated. The simulations were formed by using block diagrams through multi-touch and drag-and-drop procedures. This software was used by the undergraduate students to perform the required laboratory exercises in DSP.
Arizona State University and Spring collaborated in creating a University ID smart portal which contained several applications (with a focus on STEM subjects) including Blackboard Mobile Learn, MATLAB, IEEE Xplore, LabVIEW educational content, the J-DSP environment, YouTube and Facebook.
The mobile lab (based on the A-JDSP sourced from the J-DSP) is an Android based app providing an interactive signal processing simulation environment. Students can log in to the university ID portal using username and password that then provides access to all the apps listed above. This makes it easy for students to look at homework and configure and execute code (e.g. MATLAB and J-DSP).
Responses from students were generally positive about the convenience and flexibility of this resource but as expected, the smaller device screens were problematic (3 to 4 inches).
The Android operating system was used to develop a graphical-based application, A-JDSP for signal processing simulation. It was considered that running J-DSP over the web to be too data intensive; hence the simulations were executed directly on the mobile device. Other options such as MATLAB required an installation on a remote machine and a high speed connection for access. The application was developed using Android SDK–a Java based development framework with the user interfaces developed using XML. The blocks in A-JDSP could be accessed through a function palette or user interface. The different blocks comprised a signal generator (square, triangular, sinusoids as well as random signals), an FFT (with different length FFTs), filtering (incl. rectangular, Bartlett, Hamming, Hanning and Kaiser windows and FIR and IIR filters) and plots (basic, frequency and pole-zero).
The approach to use this tool would be to provide a lecture on the relevant signal processing concepts, a pre-quiz on the lab concepts, a simulation exercise using J-DSP and a post quiz to test the concepts.Image processing on the mobile phone
At the University of Texas, San Antonio, a template of image processing algorithms was incorporated into a course on mobile phone application development and training (based around Java and Android OS).28 The toolkit was simple and easy to learn and helped to underst and image processing concepts without having to develop them in code right from the beginning.
Typical (generally advanced) image processing routines included Fast Fourier Transforms (based on the Discrete Fourier Transform) for transformation of signals and images to the frequency domain, discrete Cosine Transforms (for image and video compression), Histograms, Hough Transforms (for identifying lines, circles and ellipses) and Gaussian and Mean filters (filtering on noisy images).
A review of students before and after using this template in a Wireless Communication course showed a change in student attitudes to the technology and encouraged student interest in a career in mobile application development.
Key points and applications
The following are the key points and applications from this chapter entitled: Mobile Learning.
1. Mobile learning (or m-learning) is the acquisition of knowledge or a skill through mobile technology that results in the alteration of behaviour or attitude.
2. There are seven mobile modes: Connect (40% of the time spent here), search, entertain, manage (e.g. banking), inform, shop and navigate (locating a route).
3. Some ways in which mobile devices are used as a learning tool:
• Communications tool.
• Assessment tool.
• Reading data in the environment.
• Undertaking written assignments.
• Social networking.
• Collection of data.
• Remote control.
• Recording lab experiments (including using camera).
4. Specific Implementation Tips:
• Apply the KISS principle.
• Focus on micro-chunks for learning.
• Keep information density low.
• Minimal multimedia (especially animations).
• Take care with small screens with limited resolution.
• Assess ROI in terms of return against total cost of implementation.