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Intentionally mobile pedagogy: the M-COPE framework for mobile learning inhigher educationVanessa P. Dennena & Shuang Haoa

a Educational Psychology & Learning Systems, Florida StateUniversity, Tallahassee, FL, USAPublished online: 12 Aug 2014.

To cite this article: Vanessa P. Dennen & Shuang Hao (2014) Intentionally mobile pedagogy: theM-COPE framework for mobile learning in higher education, Technology, Pedagogy and Education,23:3, 397-419, DOI: 10.1080/1475939X.2014.943278

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Intentionally mobile pedagogy: the M-COPE framework formobile learning in higher education

Vanessa P. Dennen* and Shuang Hao

Educational Psychology & Learning Systems, Florida State University, Tallahassee, FL, USA

(Received 16 August 2013; final version received 20 June 2014)

Increasingly, the education world finds itself working in an environment that isfull of mobile devices and tools. Students are likely to own smartphones andtablets and instructors are faced with the challenge of integrating mobile devicesinto their course activities, whether as a full delivery medium, an enhancementor an optional tool. The M-COPE framework prompts instructors to consider fivecritical areas related to mobile learning: Mobile affordances, Conditions, Out-comes, Pedagogy and Ethics. This framework can be integrated with any instruc-tional design process to help instructors engage in the informed design of mobilelearning activities. This paper presents the framework and how it can be usedwith the ADDIE model of instructional design, and provides two case examplesof how M-COPE influenced the success of two mobile learning activities.

Keywords: mobile learning; informed design; instructional design

Introduction

Mobile devices have heavily infiltrated higher education settings. In the UnitedStates, most university students carry a phone, and some have tablets. By 2010,ownership rates in the United States exceeded 95% for cell phones and were at 5%for tablets (Smith, Rainie, & Zickuhr, 2011). In terms of diffusion of innovation, thereach of mobile devices has extended well past both the early adopters, whomRogers (2003) defined as the 13.4% of people who use a technology immediatelyafter its invention, and the early majority, the next 34% of the population, who aresimilarly deliberate in their decision to adopt.

Using these mobile devices, students increasingly engage in learning-relatedinformation access and communications. At the institutional level, mobile applica-tions have been deployed to support use of learner management systems and accessto a variety of institutional resources and information. These trends, highlighting thepossibilities of incorporating mobile learning into classes as an enhancement orextension of the learning experience, are encouraging. However, mobile learningcurrently tends to be used on an ad hoc basis in many classrooms, which may reflectinstructor preparedness to select, design and implement mobile learning resourcesand activities.

To intentionally design mobile learning experiences – whether they are meant todirectly support formal learning or to more informally extend the formal learning

*Corresponding author. Email: vdennen@fsu.edu

© 2014 Association for Information Technology in Teacher Education

Technology, Pedagogy and Education, 2014Vol. 23, No. 3, 397–419, http://dx.doi.org/10.1080/1475939X.2014.943278

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experience – requires careful consideration of myriad factors. Some of these factorsare practical and contextual (e.g. device ownership, access) whereas others arepedagogical (e.g. learning objectives, assessment needs). In this paper, we presentthe M-COPE framework, which was created to support instructors and designers asthey engage in the informed design of mobile learning-based resources, activitiesand tools. First, we establish the manner in which this framework may be used withexisting instructional systems design (ISD) models. Then we describe the methodused to develop and refine the framework. Next we describe the framework’s fiveelements in detail and demonstrate how it is situated within a basic ISD model.Finally, we close with two illustrative cases to demonstrate how the frameworkapplies to mobile learning activities.

Background

The basic concept of mobile learning is not new, but rather experiencing a rebirth asmobile devices become increasingly multifunctional and widespread. During the late1990s, with the rise of personal digital assistants (PDAs), educators began toexamine how handheld devices could be used to support learning (see Sharples,2000; Vahey & Crawford, 2002 for examples). As PDAs merged with mobilephones, smartphones were born. Internet-enabled tablet computers further bridge thedifference between larger computing devices and those that truly support flexibleuse and movement through an environment. The primary differences in functionbetween smartphones and tablets are negligible, and studies of the effects of devicesize on learning and engagement are varied, with some showing no differences(Furió, González-Gancedo, Juan, Seguí, & Costa, 2013) and others indicating aneffect (Nicholas, Clark, Rowlands, & Jamali, 2013).

Although mobile learning holds much promise for use in informal settings, withuse driven by individual learners and their interests and needs (Jones, Scanlon, &Clough, 2013), instructor-led mobile learning has been a less-researched area (Gikas& Grant, 2013). There are two main kinds of research being done on mobile learn-ing in formal settings, research on the design of mobile applications and research onmobile learning effectiveness (Wu et al., 2012). Both types tend to focus on theimplementation of custom-developed applications (e.g. Ahmed & Parsons, 2013;Y. S. Chen, Kao, & Sheu, 2003; Chu, Hwang, & Tsai, 2010; de-Marcos et al., 2010;Hwang & Chang, 2011). These studies, and the software developed for them, areimportant for furthering our knowledge of how mobile applications might best bedesigned and implemented to support particular kinds of learning. However, thesoftware developed for these studies is not within reach of the average instructor.Thus, it is more likely that most class-based student exposure to mobile learning willoccur using off-the-shelf applications.

Many conditions are right for increased mobile integration to occur, andtechnology forecasters have earmarked mobile learning as a growth area that willhave long-term impact on education (Martin et al., 2011). Off-the-shelf learningapplications and tools have proliferated during the last few years, and digital text-book initiatives (Kim & Lee, 2012; Weider, 2012) are rapidly putting devices intoclassrooms. However, other conditions remain uncertain. Some instructors are notprepared to integrate mobile learning into their classrooms. Age is one factor toconsider; in general, teachers aged over 50 are less likely both to own smartphonesand to voluntarily support the use of mobile devices in their classes (O’Bannon &

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Thomas, 2014). However, even among younger, preservice teachers self-efficacyissues related to teaching with technology can influence technology adoption (R.-J.Chen, 2010). Essentially, teachers need assistance to be effective at integratingmobile learning, and assistance involves not only learning how to operate thedevices but also helping them plan mobile learning activities (Ally, Grimus, &Ebner, 2014).

Our framework is designed to help these educators. It focuses specifically on thedesign of mobile learning activities, which may be situated in a formal class settingin an instructor-facilitated context or which may occur in an informal, learner-initi-ated setting such as a museum. Although devices and apps are critical to the mobilelearning experience and should be designed with careful consideration of pedagogy(Dennen & Hao, 2014), our framework is not intended for the designers of thoseproducts. Rather it is meant for instructors or instructional and technology designers(from this point onward merely referred to as instructors for simplicity) who wish tobuild learning activities that incorporate devices and apps and, perhaps, require somemobile content design and development within existing apps. As suggested byKukulska-Hulme and Jones (2012), a focus on learning design alone will notaccount for the full range of considerations necessary for successful mobile learningexperiences. Instead, the design process should investigate and be responsive tomyriad aspects of the complex mobile learning environment and context.

Mobile learning and instructional design

Instructional design models

There are various existing models to help guide and support the design of effectiveinstruction. These process models include the Dick and Carey model (Dick, Carey,& Carey, 2005), which is perhaps the most well-known systematic instructionaldesign model, the ASSURE model (Smaldino, Russell, Heinich, & Molenda, 2005),which has been readily adopted and taught in teacher education settings, and theRapid Prototyping model (Tripp & Bichelmeyer, 1990), which supports a highlyiterative design process that is desirable in technology-based environments.

Each model has been developed to address the nuances of particular instructionalcontexts. Gustafson and Branch (1997) suggested that instructional systems design(ISD) models such as these might helpfully be taxonomised as being best suited foruse in either classroom (e.g. lesson), product development or systems (e.g. curricu-lum) contexts. However, they also noted – as have many others (Larson & Lockee,2014) – that at their core these models share many process-oriented attributes. Fur-ther, Merrill (2002; Merrill, Barclay, & van Schaak, 2008) noted that the modelsshare a common core of principles used to set an instructional foundation, such asthe ideas that activation of knowledge and demonstration are important componentsof learning.

These existing ISD models, most of which were developed when mobile learningas it exists today was not even a concept, essentially promote a focus on five keyprocess – analysis, design, development, implementation and evaluation – duringthe larger process of instructional design. Collectively these processes form the acro-nym ADDIE, which is typically considered the generic or baseline ISD model. Theprocess within the ADDIE model and other process models are often referred to asphases, and some visual depictions of ISD models may imply linearity, the totality

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of the ISD process should be flexible and iterative to fit the context (Gustafson &Branch, 1997), relying on the best judgement of the designer (Dick et al., 2005),and perhaps should be termed activities rather than phases to achieve this form ofiterative flexibility (Larson & Lockee, 2014).

These models have sustained through various technological innovations and edu-cational technology trends, which raises the question of whether new models areneeded for designing instruction that incorporates mobile learning. We believe thatour existing models, which guide the activities or processes of design, continue tobe sufficient. The mobile platform is a delivery medium, and although it may incor-porate different technological affordances than other instructional media it does notalter the nature of learning and instruction (see Cochrane & Bateman, 2010 for dis-cussion of the affordances of mobile devices in a learning context). In fact, mobilelearning applications and activities can and should be designed with consideration ofexisting learning theories and pedagogical approaches (Buchanan & Hvizdak, 2009).The exception may be in the case of transformative uses of mobile learning, uses sodifferent that they represent a paradigm shift in either formal or informal learning. Itis too early to tell if mobile learning will create a paradigm shift in education, but aparadigm shift would likely be related to instructional design theory rather thanprocesses, and any necessary changes in process would likely be driven by thechange in theory (see Reigeluth, 1999 for a fuller discussion of paradigm shifts ininstructional design theory and resulting effects on processes). Most current uses ofmobile learning situate it in well-established learning contexts.

Mobile learning frameworks and ISD process models

Although mobile learning design does not require new models or processes, mobiletechnologies and the learning interactions that they support are sufficiently uniquethat special considerations are warranted as part of the design process.

For this reason, we propose the use of a framework situated within an ISD modelto prompt educators and instructional designers to examine mobile-specific issuesthat may impact the success of their instruction and to make informed design deci-sions as a result. It is not unusual for instructional designers to combine processmodels with other models, frameworks or principles to achieve their desired designresults. For example, the 4C-ID model (van Merriënboer, Clark, & Croock, 2002) isused to help design instruction in complex domains; the ARCS model (Keller, 1987)is used to support motivational design; Bloom’s Taxonomy (Bloom, Engelhart,Furst, Hill, & Krathwohl, 1956) and Gagné’s Conditions of Learning (Gagné, 1985)propose preferred instructional methods for learning in different domains; andMayer’s (2009) multimedia principles guide developers as they create instructionalmedia. Each may be readily used alongside an ADDIE-based ISD process model.

Whereas instructional design models, such as ADDIE, provide guidance for exe-cuting the design process, frameworks provide guidance for organising and thinkingabout concepts in the design context. Models and frameworks can be used togetherin an instructional design setting, with the former suggesting how to approach thetask of design (Reigeluth, 1999) and the latter guiding practical design consider-ations and decisions (Perkins & Unger, 1999). To date, several mobile learningframeworks have been proposed, each with a specific use. Table 1 summarises theseframeworks, noting the main purpose of each. The focus of these frameworks rangesfrom classification and categorisation (e.g. Motiwalla, 2007; Park, 2011) to

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supporting different uses of mobile learning (e.g. computer-supported collaborativelearning in Zurita & Nussbaum, 2007).

Our purpose in developing a new framework was to address a different issue: tohelp instructors, instructional designers and technology designers view the systemicinterplay of critical components of the mobile learning context, thereby enablingsound decision making each step of the design process. It is a response to Cochrane’s(2014) review of research, which highlighted the need for design frameworks thatcan be shared and used by a wide audience and an alignment between the pedagogy,technological affordances and outcomes. Essentially, individuals designing mobile-based learning experiences, whether their role is that of instructor-as-designer orinstructional designer, need an easy-to-use framework that can be incorporated inalready-familiar instructional design processes. This framework should help themmake informed design decisions by taking a systems view of mobile learning andguiding careful consideration of critical, interrelated elements of the mobile learningexperience. It also should work whether they are designing activities that incorporateexisting mobile learning content and applications, or designing new mobile learningcontent and applications.

Method

The M-COPE framework was developed via a process that followed Reigeluth andFrick’s (1999) guidelines for formative research in a naturalistic setting. We drewupon both in vivo and post facto cases in which mobile learning experiences hadbeen designed and implemented in classes. A total of nine cases were consideredduring this process, drawn from the authors’ experiences developing and testingmobile learning apps; designing and teaching a course on mobile learning; and

Table 1. Summary of mobile frameworks.

Framework title Author Purpose

(no title) Kearney, Schuck,Burden, &Aubusson (2012)

Support for socio-cultural mobilelearning pedagogy.

Framework for the RationalAnalysis of MobileEducation (FRAME)

Koole (2009) Broad guidance for mobile learningthrough the consideration of threeaspects of the learning context –device, learner and social – and thepoints at which they intersect.

An m-learning framework Motiwalla (2007) Classification and evaluation ofparticular tools and how they functionwithin the push/pull and personal/collaborative dimensions of mobilelearning content.

A pedagogical frameworkfor mobile learning

Park (2011) Classification of mobile learning viathe nature of the pedagogicalinteractions it supports and the relatedtransactional distance.

Mobile CSCL framework Zurita andNussbaum (2007)

Activity theory-based guidance fordesigning mobile computer-supportedcollaborative learning.

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implementing mobile learning activities to support both formal and informal learn-ing. From these cases, we extracted the key mobile-specific considerations that eitherwere a part of the design process or that, upon evaluation of outcomes, should havebeen a part of the design process. Across the cases, we reviewed these consider-ations and grouped them by topic. The five key areas of the current version of theframework emerged, each presenting a category of unique considerations throughoutthe ISD process. Prompting questions for each framework area were developed torepresent the specific issues that arose within the cases.

Framework validation occurred via two means, a review of literature and anexpert review process. The review of literature was used to confirm inclusion ofeach of the five key areas as well as the descriptions of concerns from within eacharea during the different parts of the ISD process. For example, studies in which cer-tain problems arose during a mobile learning project highlighted and confirmedareas where mobile-specific considerations are needed.

During the expert review process, five experts were asked to review the frame-work and the framework-based prompting questions provided for each part of theISD process and comment on its soundness. Two of the experts were university fac-ulty who teach instructional design courses and who are familiar with mobile learn-ing. Two of the experts were practising instructional designers who incorporatemobile learning in their instruction. The final expert was a university faculty mem-ber who has experience incorporating tablets into the classroom. The experts allindicated that the M-COPE framework prompts educators and instructional designersthrough necessary considerations for designing effective mobile learning experi-ences, and their comments helped clarify and refine some of the prompting ques-tions. Further, one expert noted that the framework is a useful tool for encouragingeducators to consider the reasons why they are incorporating mobile learning intotheir instruction, to help avoid pitfalls that occur when technology is used fortechnology’s sake.

Finally, we developed two descriptive cases of how M-COPE is applied to learn-ing activities, drawing upon our experiences engaging students in mobile learning.These brief cases demonstrate the types of information that is generated anddecisions that may be made when M-COPE guiding questions are used within theinstructional design process.

The M-COPE framework

The M-COPE framework consists of five key elements, each of which is discussedin detail below: Mobile, Conditions, Outcomes, Pedagogy, and Ethics. Each elementrepresents a set of considerations to be made about a particular learning context. Itwas designed to help instructors engage in informed design processes when eitherbuilding learning activities around mobile resources and applications orincorporating mobile tools and resources into existing activities.

The framework was created on the premise that design guidelines for mobilelearning activities and experiences should not be overly prescriptive, given thediverse definitions and manifestations of mobile learning. Instead, we believe thatinstructors will benefit from a flexible framework that both prompts them throughcontinuous consideration of learning needs and constraints and readily integrateswith established instructional design process models. Each component of the frame-work is described below.

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Mobile

Some activities are mobile by circumstance; they simply occur on a mobile devicewhen they might as well use another technology. Others are mobile by necessity andby design, taking advantage of the unique qualities and tools associated with mobil-ity, location, and mobile input and output devices. This section of the frameworkpushes educators to consider why they are choosing mobile learning. Using technol-ogy for technology’s sake is rarely a good idea, although new technologies may berushed into use without fully considering their pedagogical merits (Burnett &Meadmore, 2002). The overarching question is: What value does using a mobiledevice add to the learning context? This value may take the form of enabling newtypes of interactions and serving as cognitive tools (W. Chen, Tan, Looi, Zhang, &Seow, 2008). If there are no clear advantages or new affordances enabled by usingmobile devices, then cost–benefit consideration is necessary. If the learners alreadyhave mobile devices and are familiar with their operation, then a mobile activitymight be easily implemented. However, if great cost or effort is involved there is noextra effort expended to design a mobile-inclusive activity. However, in instanceswhere there is no evident value added to using a mobile device, except perhaps thatability to claim that one is engaged in mobile learning, then careful considerationshould be given before going to the trouble.

The added value of mobile integration is evident in many learning scenarios.Gay, Rieger, and Bennington (2002) highlighted four levels at which mobile learn-ing tools might assist learners: productivity, flexible physical access, capturing andintegrating data, and communication and collaboration. For example, learning duringfield-based experiences such as museum visits, nature walks or internships may begreatly enhanced by the ability to access or record information or interact with oth-ers in a just-in-time manner (Y. S. Chen et al., 2003; Chu, Hwang, Tsai, & Tseng,2010). Mobile devices also might be used to connect learners with experts locatedelsewhere (Dede, 2011). When mobile devices are used to support learning in theseways, as opposed to just providing an alternative to using a computer, their value inthe educational context is clear.

The input and output methods integrated into mobile devices may offer uniqueways of interacting with learning content and settings (W. Chen et al., 2008). Geolo-cation tools may allow for greater customisation or accuracy for learning contentduring field-based experiences, providing transformative experiences (Chu, Hwang,Tsai, & Tseng, 2010; Denk, Weber, & Belfin, 2007). Embedded cameras combinedwith mobility and Internet connections support augmented reality, just-in-time audio-visual communication and flexible documentation of events and discoveries. Finally,the availability of touchscreen and sensor-based inputs, such as swipes, pinches, tiltsand shakes, can increase the authenticity of a simulated environment.

Assuming there is a clear added value to integrating a mobile device, instructorsneed to determine if their learning activity is truly mobile dependent, e.g. requiringuse of the unique qualities of a mobile device, or simply mobile enhanced or mobilesupported. In the latter cases, mobile devices are not necessary to meet the activity’slearning objectives, and parts of the activity may either be discarded or supported byother means should mobile devices not function as planned or become unavailable.In this sense, mobile-dependent activities are not as flexible as, and are thussomewhat riskier than, mobile-enhanced or mobile-supported ones.

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Conditions

The conditions dimension, as defined by Reigeluth (1999), involves consideration oflearning environment, learners, the topic to be learned and situational constraints.We explicitly add technology as a condition, because it is critically central to amobile learning activity. Reigeluth and colleagues (Reigeluth & Carr-Chellman,2009a; Reigeluth & Keller, 2009) stressed the importance of conditions withininstructional theories, since they influence what instructional methods are mostappropriate. Further, Reigeluth (1999) highlighted the importance of adjustinginstructional design theories so they provide guidance for the types of learning andinstruction that are enabled by new technology systems.

Mobile learning activities warrant a new look at conditions. The role of technol-ogy in the learning context is more complex than just making an adoption decision(Dillenbourg, 2008), and there is an inherent tension or gap between what research-ers find via empirical studies and what classroom teachers believe is effective intheir local setting (Dillenbourg & Jermann, 2010). Dillenbourg and Jermann (2010)suggested teachers consider dimensions of classroom orchestration, such asteacher-centrism, time and physical space, to determine which methods might be afit. Roschelle and colleagues had similar findings in their handheld computer-supported collaborative learning project, TechPALS (Roschelle, Rafanan, Estrella,Nussbaum, & Claro, 2010); when shifting setting, some elements of their learningactivity also needed to be adjusted.

Some of the conditions that may affect mobile learning activities include learnerpreparedness, environmental suitability, time and disruption. In terms of learner pre-paredness, individual differences in technology use and attitudes are importantbecause intentionality affects motivation and learning expectations (Terras &Ramsay, 2012). Attitude, subjective norm and behavioural control all are factors thatinfluence this intentionality (Cheon, Lee, Crooks, & Song, 2012). Learners whohave not previously used mobile devices may be at a disadvantage and initiallyfocus more on the technology rather than the learning task.

Sharples (2013) noted how mobile learning can occur across a range of temporaland environmental conditions, and suggested that learning experiences should bedesigned with these considerations in mind. Wifi availability may be a major envi-ronmental concern, along with lighting (i.e. glare issues), noise and other distrac-tions. Further learning experiences may occur over various time periods, and groupinteractions may be synchronous or asynchronous.

Disruption is an issue that spans multiple conditions and may also be consideredan unintended outcome. Mobile devices typically are multifunctional, and learnersmay struggle to keep on task. Further, learners may struggle with multi-taskingbetween the physical and mobile environments – even when doing so is a criticalpart of the learning process (Roger, Connelly, Hazlewood, & Tedesco, 2010).Further disruption may occur when learning on a personal device owing to incomingalerts, text messages and phone calls.

Other technology issues that arise include device availability and standardisation,the effectiveness of small-screen displays and input limitations. For example, anyactivity that requires downloading an app might be more challenging to implementwhen learners are using their own devices rather than institution-supplied ones, andsome student-owned devices might be insufficient for the activity. When devices areshared, the student operating the device might feel unfairly burdened (Roger et al.,

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2010). Activities that require heavy text input might require an external keyboard.And wifi-dependent learning experiences in remote field locations may not bepossible.

Outcomes

For this framework we purposely focus on outcomes, a broad term that reflects whatactually happens in a context over objectives, a narrower term often associated withwhat learners can do at the end of a learning experience. This does not mean thatlearning objectives are unimportant to this framework. They are one component ofthe outcomes, and are typically developed as part of an instructional design processor perhaps prescribed at the outset by a curriculum plan. As per Gikas and Grant(2013), the mobile learning literature mostly reflects a focus on information accessand transmission activities, which would suggest that mobile devices are most oftenbeing used to support lower order cognitive skills. However, their study and others(e.g. Hwang & Chang, 2011) demonstrate that mobile learning activities supporthigher order skills. Regardless of where the objectives fall within Bloom’s Taxon-omy (Bloom et al., 1956), ensuring that mobile use supports rather than detractsfrom meeting the objectives is critical. Further, instructors might consider whetherdeveloping mobile technology skills is an explicit objective or, if not, a worthwhileancillary one if any time will be spent teaching learners how to use mobile hardwareand software.

Unintended outcomes, although sometimes difficult to anticipate, are importantto consider. Although some unintended outcomes are positive, such as learning newtechnology skills, others are negative, causing disruption and distraction (Nworie &Haughton, 2008). If potential negative outcomes seem probable or even somewhatpossible and would cause discomfort or harm to the learners or instructor, then theactivity might be altered. For example, instructors might worry about mobile-basedcyberbullying (Ahn, Bivona, & DiScala, 2011) or students engaged in other poorbehaviour in a public virtual space. The solution might include using a single, tea-cher-controlled account or using a tool that restricts interactions to a closed networkof users.

Unintended outcomes also may be related to ethical dilemmas, which are dis-cussed below. For example, in a medical education context, having patient informa-tion stored on a mobile device might be a privacy risk (Wallace, Clark, & White,2012). Vavoula and Sharples (2009) shared the example of mobile learners whochose to be selectively engaged with an assignment, possibly because of the intru-siveness of the technology into their personal lives. Given the need for instruction tomeet stated learning objectives, it is important to consider whether these unintendedoutcomes are likely, whether they might derail the learning experience and how theymight be avoided.

Pedagogy

Pedagogy is critical to all learning, and can really only be selected once the condi-tions and outcomes are known. The number of potential instructional methods isvast (see Reigeluth & Keller, 2009 for an extensive listing of methods), and theselected method should reflect the values and conditions of the instructional situation(Reigeluth & Carr-Chellman, 2009a; Reigeluth & Keller, 2009). Similarly, more

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specific instructional approaches may vary, anchored around active presentation, dis-cussion, experiences, problem solving or simulations (Reigeluth & Carr-Chellman,2009b). Current frameworks for mobile knowledge construction (e.g. Peng, Su,Chou, & Tsai, 2009) similarly incorporate considerations of learners and tools (i.e.conditions) with a vision (i.e. outcomes) and pedagogy.

Pedagogical beliefs can shape the way that technology is used in a givenenvironment. Thus, the selected pedagogy and technology need to work together(Cochrane, 2010). As Koschmann (1996) indicated in his discussion of paradigmshifts in education and the related changing use of instructional technologies, eachparadigm has an underlying learning theory and that theory drives the pedagogicalchoices that are made. Taylor (1980), working in the context of computers, labelledthe roles that technology might play tutor, tool and tutee. Koschmann (1996)expanded these roles to account for the computer-supported collaboration that wasbecoming increasingly prevalent among individuals who believe in social construc-tivism as a learning theory. Mobile devices can be used to support each of theseinteractions, with apps that serve as tutors, information sources, simulators and col-laboration enablers (Dennen & Hao, 2014) as well as those that can be used for cre-ation and documentation. It is in these last areas, where social constructivism is theguiding theory and the activities support knowledge sharing and construction, thatmobile learning activities may hold the greatest promise for enabling transformativelearning experiences.

Putting these pieces together, for instructors the pedagogy dimension requiresdeveloping a clear sense of the underlying learning theory that will drive theirchoice of instructional method and approach. The method and approach will, in turn,lead to different choices about how mobile devices might be integrated into a learn-ing activity. When the process of activity design becomes intentional and pedagogydriven, rather than technology driven, instructors are able to find the activities, mate-rials and applications that will help learners best achieve the desired outcomeswithin their particular conditions.

Ethics

The seemingly ubiquitous nature of mobile devices in so many parts of the world,particularly phones, may at first glance suggest that there should be no real ethicalconcerns, particularly since people exert free will when using these devices. How-ever, in some instances mobile learning activities might cause learner frustration ordiscomfort. Learner comfort is a critical part of mobile learning adoption (Liu, Han,& Li, 2010), and these instances are cause for concern. Further, in a networked envi-ronment small actions can have unexpected and unintentional outcomes which arenot always positive (Kukulska-Hulme & Jones, 2012).

Ethics is a complicated area for many educators. To be an ethical instructor orinstructional designer is a matter of perception as much as of thoughtful action; theremay be no absolute rules to follow, but rather judgements to be made. When mobiletechnologies are used, a unique set of issues arises, and decisions must be made abouthow learners are expected to use and interact via the technology. Educators shouldexplore these issues in a, context-sensitive manner, and should strive for solutions thatbest meet the safety, comfort, learning and environmental needs of the constituents.

Ethical issues faced by mobile educators include ownership of educationalproducts (including archived conversations and social media contributions) occurring

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and the appropriateness of potentially ubiquitous and non-stop engagement(Kukulska-Hulme, Sharples, Milrad, Arnedillo-Sanchez, & Vavoula, 2009). Thissecond point alludes to a downside of mobile devices: since they are multipurpose,they can allow schoolwork to intrude upon home life and personal time (and viceversa) in uninvited ways. Wishart (2013) touched on additional concerns in herdiscussion of ethics for mobile learning researchers, including authorship issues forstudent- and teacher-created content and participant naivety about safety issues anddevice capability.

Device ownership is another sensitive issue. In some settings, a bring your owndevice (BYOD) approach is used, capitalising on the high degree of personal deviceownership. However, learners who lack devices or who have older devices may feelfrustrated and perhaps embarrassed if they are unable to use a required app or haveto share with someone else. Further, these learners may fall behind or miss a criticalexperience if they lack a device for doing homework or do not get direct experiencemanipulating the device during class activities.

Finally, many mobile activities require accounts, particularly those that permitinteraction or store data about learner performance. These accounts generate dataand create digital footprints. How and by whom these data are then used (e.g. arethey for teacher and student only, or might companies use them?) have becomegrowing concerns for many people in light of the big data movement.

Integrating M-COPE and ISD process models

Throughout this section we use the ADDIE model as a baseline for demonstratinghow the M-COPE framework may be interwoven into the instructional systemsdesign process. ADDIE has been selected because it is widely accepted as a genericrepresentation of the instructional systems design process (Molenda, 2003). As notedearlier, one can readily identify the five main components of ADDIE within otherISD models. In the instance of an instructor who lacks familiarity with instructionaldesign models or who tends to design more by instinct than by following a model,the framework will gently push the design process to be a more systematic andinformed one.

An instructor would begin at the initial analysis phase, considering the answersto the prompting questions. Then, in each subsequent phase of the instructionaldesign process, the instructor would be similarly encouraged to address the prompt-ing questions as well as to refine answers to questions asked in earlier phases, itera-tively adjusting the design vision as necessary based on the new data. To that end,the prompting questions presented below might be collected into one document andused as a checklist.

Figure 1 presents a flowchart of how an instructor might use the M-COPE frame-work to determine if a mobile learning activity is truly suitable for their context.This flowchart, along with the prompting questions for each phase, might be used asa job aid to guide instructors through the intentional design of mobile learning activ-ities. Instructors might add other prompting questions to suit their contexts. Themain point is that during each part of the design process, an instructor should beconcerned with ensuring that the activity should be making use of mobile technolo-gies, has aligned conditions, outcomes and pedagogy and falls within theexpectations of ethical practice.

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Analysis

Although in practice relatively little time may be devoted explicitly to analysis, thisphase is critical because it allows the instructor to explore the contextual factors thatmay enable learning possibilities or serve as constraints. Many instructors have lar-gely internalised this phase; if they are designing instruction in a familiar context,they already may have a clear sense of the learners, learning environment andoutcomes.

During the analysis phase, it is important to not start with a solution (e.g. I willuse an app to help students practise their geography skills), even if such a concept

Figure 1. Flowchart for using M-COPE to determine mobile learning suitability.

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has already been proposed, unless the solution is absolutely pre-determined. Keepingan open mind during analysis and considering the full context in general termsrather than through the lens of any one solution can help illuminate additional,previously unconsidered mobile learning options during the design phase. SampleM-COPE prompting questions to be asked during the analysis phase are presentedin Table 2.

Design

During the design phase, the overall concept for the learning activity is fleshed out,with full consideration of results of the analysis phase. The application of theM-COPE framework becomes both cumulative and iterative. Questions in this phasebuild on those from the previous one, and instructors also might revisit their earlierfindings from the analysis or ask additional analysis questions as the situationdemands. Table 3 presents M-COPE prompting questions related to design. At theend of the design phase, and with the assistance of these questions, the instructorshould have a clear lesson plan or roadmap.

Development

The development phase is where the actual production work for a mobile learningactivity occurs. In a mobile learning context, development activities might rangefrom selecting and adapting mobile apps and resources and building lesson plansaround them to developing one’s own mobile apps and resources. Both mobile andother media – including print – may be developed to support the full learning activ-ity. M-COPE prompting questions during this phase focus on usability and function-ality issues, ensuring that the final lesson will work under the class conditions,achieve the outcomes and support the pedagogy (see Table 4).

Table 2. M-COPE prompting questions for the analysis phase.

Topic Questions

Mobile How can a mobile device enable learning interactions that are not otherwisepossible in this environment? In this content area?What mobile tools or applications have inspired you to consider a mobilelearning activity?

Conditions What is the learners’ prior experience with mobile devices and mobile learning?What is the learners’ attitude toward mobile devices?

Outcomes Do any of the required learning objectives relate to mobile devices? If so, inwhat way?Are there other desired outcomes related to mobile devices?

Pedagogy Why do you believe a mobile activity will support learning in this context?Ethics Are the learners likely to be voluntary participants?

Will teaching the learners how to use a mobile device take away from otherlearning activities?What are the Internet safety and digital footprint concerns when working withthis learner group?

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Implementation

The implementation phase is when the learners are actually engaged in the mobilelearning activity. Although a well-planned activity simply needs to be executed atthis stage, the execution process still requires its own preparation. Further, an activ-ity can go awry when unexpected things happen, and whenever technology and peo-ple are involved unexpected things can and do happen. Attention to items such asthose listed in Table 5 can help ensure greater implementation success.

Evaluation

The evaluation phase occurs at the end of the process. It sometimes gets overlookedbecause the learning activity itself is considered the main event, but evaluation isnonetheless a very important part of the design process. It is through evaluation thatinstructors can make informed decisions about whether an activity should be usedagain and what revisions are necessary for the activity to be more successful infuture iterations. Additionally, evaluation findings might be applied during thedesign of other, similar activities.

Table 3. M-COPE prompting questions for the design phase.

Topic Questions

Mobile What role will the mobile device play in the activity (e.g. main channel,learning resource, assistive tool)?What existing mobile tools, apps or resources serve as an inspiration for thisactivity?What unique elements of mobile devices (e.g. inputs, mobility, geolocation) arenecessary to support the learning activity?

Conditions Will you need to adopt, adapt or create the mobile resources used in thislearning activity?Will learners each need their own devices? Who will supply devices?Where and when will the activity take place?

Outcomes How does using a mobile device enable learners to meet the learning outcomes?Pedagogy In what ways can a mobile device support the desired instructional methods and

approaches?Ethics If a bring your own device model is being used, might anyone be left out?

Table 4. M-COPE prompting questions for the development phase.

Topic Questions

Mobile Is all of the desired mobile functionality possible?Conditions Do the mobile resources work across platforms and device types?Outcomes Is the activity still aligned with the learning objectives?

Is any technology being used that is not related to one or more of the intendedoutcomes?

Pedagogy Are there any conflicts between the desired methods and approaches and themobile functionality?

Ethics Is the mobile tool easy to use? Secure?

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The mobile-focused prompting questions presented in Table 6 mostly focus onone key issue: Was the learning experience successful? Also worth noting, however,is the possibility of using data that were automatically generated by the mobiledevices (e.g. learner records in some apps), digitally created by learners (e.g. interac-tion artefacts) or otherwise collected via the mobile devices (e.g. end-of-activityonline survey) to help evaluate the activity from multiple perspectives.

Case examples

The following brief cases demonstrate how M-COPE can be applied when designingmobile learning activities. Although both cases are situated in a university environ-ment – the setting in which most of our work is done – just like an ISD model, theframework can be applied in any instructional context.

Case 1: Creating ebooks

We developed and have twice co-taught a graduate-level online course on mobilelearning in which students were introduced to different mobile technologies (e.g.

Table 5. M-COPE prompting questions for the implementation phase.

Topic Questions

Mobile Are the devices prepared for the lesson (e.g. updated, correct apps installed)?Conditions Is the Internet connection sufficient for the activity?

Do learners have sufficient devices for the activity?Are learners sufficiently prepared for using the devices?

Outcomes What learning supports are necessary to ensure that the learning outcomes aremet?

Pedagogy How will mobile interactions be facilitated? What teacher actions are necessaryto ensure that students are learning?

Ethics Are the learners leaving behind digital footprints? Who can access thesefootprints, and how? For what purposes?Does everyone have the technology access that they need to easily complete theactivity?Is anyone overwhelmed or uncomfortable with the activity?

Table 6. M-COPE prompting questions for the evaluation phase.

Topic Questions

Mobile Can evaluation data be automatically collected and analysed via mobile tools?Did the devices and apps function as anticipated?

Conditions How did mobile devices support learning in this context? What were learnerattitudes toward the technology?

Outcomes Were the anticipated outcomes achieved? Were there any unanticipatedoutcomes?

Pedagogy Did the mobile devices enhance or detract from the learning experience?Ethics Was anyone overwhelmed or uncomfortable using the mobile devices? What

has happened to the data generated by the mobile learning activity?

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QR codes, ebooks, apps) for the purpose of designing and, in some cases, develop-ing learning interventions. Table 7 presents some of the basic analysis informationabout the class within the M-COPE framework.

The biggest challenge that we faced revolved around device ownership andteaching online. Although you might think that students signing up for a course onmobile learning would be likely to already own a smartphone or tablet, that was notthe case either time that we taught the course, and fortunately we had the foresightto survey students during the first week of the course, which gave us time to makeadjustments to learning activities and assessments as needed. Most students did owna device, but those devices varied in age and operating system. This challenge meantthat we needed to approach the learning activity in a flexible manner, to not excludeanyone or cause any undue frustration.

We were able to visualise an ideal learning activity – one in which the learnerswould have all of the desired technology – and then build in options to accommo-date the many learners who did not have the ideal technology set-up. Our preferredmobile development environment for the activity was to use iBooks Author, whichworks on Apple computers and then outputs for iPads and iPhones. Alternative out-put options are available, but they limit the interactivity. Only a small handful of stu-dents owned both an Apple computer and mobile device, and unfortunately there isnot a corollary ebook authoring tool for Windows computers that is both robust andfree.

To adjust the learning activity, we focused on two main things. First, we neededto provide examples in a format that would be accessible to all students, whichincluded being able to share the kinds of interactivity that might be possible in anebook. Since the class was taught online, we opted to use webinars for live demon-strations of ebooks and their features. Also, we shared screen shots of ebooks withstudents, with different design features annotated. This way even students wholacked the ability to download and examine an interactive ebook themselves couldget a reasonable sense of the form and function.

Second, we developed multiple possible production paths and tools for studentsto try, accommodating every possible combination of technology and access that we

Table 7. Analysis of Case 1.

Topic Case analysis

Mobile The ideal scenario would be for students to use a tool like iBooks Author(http://www.apple.com/ibooks-author) to create an interactive ebook. Mobiledevices were not necessary to create the ebook, but desirable for both gettinginspiration via reviewing ebooks and being able to test one’s own work andreview others’ work in an authentic manner.

Conditions Online class. Learners need to use their own devices. Not all learners own amobile device or have prior experience with a mobile device.

Outcomes All learners should create an interactive ebook that could be loaded and used ona mobile device.

Pedagogy Students are expected to work on an applied project. Tutorials can help buildbasic technology skills, but the final product will involve problem solving.Formative peer feedback will be used to help improve student work.

Ethics Students who lack mobile devices might feel excluded or at a disadvantage, yetin an online class there is no way to provide those students with access toinstitution-owned mobile devices.

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could envision. Additionally, we had students accompany their ebook with adebriefing paper that explained their audience, design rationale, development processand any ideas that they could not realise in the final product owing to technologicallimitations.

In the end, all students were able to successfully meet the learning objectives.Unfortunately, a few students were frustrated by their personal technology accesslimitations and the impact on their ability to fully develop their design visions,although they did not blame the class for these limitations. An unintended positiveoutcome was that everyone developed more extensive knowledge about differentebook creation options than they would have if we had simply been able to useApple products for development and testing.

Case 2: Homework and mobile devices

The first author has taught a graduate-level online course on analytics. One objectivein this course was to provide students with direct experience by exposing them tothe analytic tools that currently are integrated in our everyday lives. Table 8 presentssome of the basic details of the course.

Many mobile and online tools currently make user analytics available. Forexample, SlideShare (slideshare.net), a document-sharing site, provides users withinformation on how many people have viewed and downloaded their documents.Bloggers can get reports about who has visited their sites. Third-party applicationscan tell you all about your interactions and friends on Facebook. MyFitnessPal(myfitfnesspal.com) allows users to enter diet and fitness information and providesanalytic reports on that data. Simple devices such as a Fitbit tracker (fitbit.com)record users’ movements (e.g. steps taken, flights of stairs) and share thatinformation with apps that in turn provide analytics.

In this course, modelling and encouraging the use of mobile tracking tools andapps is desirable, and many students were eager to use their smartphones in newways. Students were shown examples of the analytic functions and reports from

Table 8. Analysis of Case 2.

Topic Case analysis

Mobile Many analytic tools include mobile versions. Mobile tracking of data, whetherautomatic and integrated (e.g. a GPS-based walk tracker or the user statistics foran app), automatically synched with another device (e.g. a Bluetooth bathroomscale) or input by the user can be very convenient.

Conditions Online class. Not all learners own a mobile device.Outcomes All students are expected to use tools to track personal data and then interpret

the analytic reports that they receive.Pedagogy Mobile devices are being used as tools in this context, to enable students to

collect and analyse data. Instructional content is being presented and discussedin other forums and formats.

Ethics Students who lack mobile devices might feel excluded or at a disadvantage, yetin an online class there is no way to provide those students with access toinstitution-owned mobile devices.Student may be concerned about having personal information stored or sharedin an online environment.

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various mobile apps and websites. They also were provided with a lot of choice. Forexample, a student who wished to engage in fitness tracking did not need to investin an expensive gadget, such as a Fitbit, but might select from among various freeapps. ‘Free’ is a relative term, and students were made aware that they would needto carefully read the terms of service of any tool to understand whether their datamight be used for other purposes.

Not all students had mobile devices or were eager to have their data recorded inan online environment. Before designing the assignment, and based on earlier expe-riences with this student population (see Case 1 above), the first author took care todevelop several options for the assignment. Fortunately, there were no platformissues; most consumer tracking apps have both iOS and Android versions. Therewere web-based options for students who lacked mobile devices – and in thisinstance, even if the course had met on campus where mobile devices may bechecked out for classroom lab sessions, students could not have been provided withdevices to carry around continuously for personal tracking.

Additionally, there were options for students who were concerned about theirdigital footprint. They were heavily encouraged to discuss their privacy concernswith the instructor to ensure that their privacy was being sufficiently protected dur-ing the learning activity. Those students, even if they owned a smartphone or tablet,could opt out of using those devices to record their data.

All students were able to successfully complete the learning activity, and mostchose to use mobile apps. Some students commented that web-based versions oftools were not always as attractive or sophisticated as the mobile apps, although insome instances the inverse was true. Ethical issues related to privacy and big datawere the biggest concerns with this activity, and an unintended positive outcomewas that many students develop a greater awareness of the ways in which theirprivacy may be compromised when signing up for a new online or mobile service.

Discussion

These two case examples demonstrate how the M-COPE framework can be used toanalyse mobile learning activities. The framework is being applied to these cases ina post-hoc capacity, since they were cases used in the development of the frame-work. Had the framework been available during the design process, we might havebeen able to better anticipate and prepare for some of the device-related issues thatarose during the first case. Since developing the framework, the first author has usedit twice to support the design of mobile learning activities. In one case, a rapid pro-totyping process was used for developing a mobile-based activity and in the other aclassroom-based mobile-enhanced activity was designed via a process closely emu-lating the ASSURE model. In both instances, the framework effectively highlightedelements of the learning context that required special consideration. These experi-ences, along with the validating feedback from our five expert reviewers, have sup-ported our belief that the framework can be a useful tool when designing mobilelearning activities.

At this point, additional validation of the framework is needed. We intended tofurther test the framework the next time we teach our mobile learning class, withstudent designers using the framework to guide decision making in their design pro-jects, which focus both on designing mobile-based learning experiences and onmobile applications. The M-COPE framework will help these student designers by

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promoting a systemic, iterative view of the design context (i.e. continual consider-ation of each element of M-COPE).

Further research on this model may be done to systematically test it in a varietyof contexts. Although we developed it with higher education in mind, it likely istransferrable to the K–12 learning context. It may also be useful for the intentionaldesign of professional development experiences.

Conclusion

The M-COPE framework provides instructors and designers with organised promptsfor fully exploring the mobile learning context. As such, it is a useful tool whendesigning mobile learning experiences, and may be used in conjunction with theinstructor’s preferred instructional design process or model. M-COPE fosters carefulconsideration of the affordances of mobile technology as well as how the conditionsof learning, desired outcomes and pedagogical approach relate to mobile technolo-gies and the potential ethical issues that arise in a mobile learning context. Thesefive areas are critical to an informed design experience and instructional activitieswill reflect responsive solutions to the contextual factors and needs that are illumi-nated via the framework.

Notes on contributorsVanessa Dennen is an Associate Professor of Instructional Systems at Florida State Univer-sity, where she teaches courses on instructional design and research methods for new andemerging technologies. Her research investigates the nexus of cognitive, motivational andsocial elements in computer-mediated and mobile environments.

Shuang Hao is a doctoral candidate at Florida State University. Her research interests includeonline and mobile learning strategies and performance improvement technologies.

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