What are the Challenges of Mobile Learning?
Educational change is challenging work, particularly if the effort is a wide-reaching, pedagogical shift. The implementation of Mobile Learning as a means to create differentiated, personalized, and creative instructional practice in face-to-face classrooms, has many challenges to overcome and may not be possible because the school system is still entrenched with traditional classroom and teaching models.
As previously stated, introducing technology into classrooms is only effective if the context or ‘culture’ of the classroom also changed (Horn & Staker, 2014, p. 127). This means that the educational context of the classroom and school created by administration, schedules, budgets, professional development, etc., need to evolve to support transformative learning pedagogies. The research identified four main challenges Mobile Learning encounteres in traditional schools and face-to-face classrooms:
As previously stated, introducing technology into classrooms is only effective if the context or ‘culture’ of the classroom also changed (Horn & Staker, 2014, p. 127). This means that the educational context of the classroom and school created by administration, schedules, budgets, professional development, etc., need to evolve to support transformative learning pedagogies. The research identified four main challenges Mobile Learning encounteres in traditional schools and face-to-face classrooms:
- School mobile device policies
- Teacher perceptions of mobile devices in the classroom
- Access and cost
- Mobile device and software heterogeneity
School Mobile Device Polices
Figure 1. Policies regarding students’ use of personal devices in school (Consortium for School Networking (CoSN, 2018).
Despite efforts to increase the availability of technologies within K-12 classrooms, there were many challenges associated with the integration of mobile devices into curriculum. One of the primary barriers to the successful implementation of Mobile Learning was that mobile devices are banned in many schools (Barbour et al., 2012; Parsons & Adhikar, 2016; Project Tomorrow, 2011; Rubin, 2016; Steeves, 2014). As a potentially disruptive, non-educational device, many school and district administrators have seen the potential problems that mobile devices could cause in a classroom. U.S. school administrators reported that 52 percent of their districts banned student-owned mobile devices in classrooms (Grant et al., 2015). A reduction in this number can be seen in a more recent study that reported, “83 percent of U.S. school districts have policies, or plan to have policies, allowing student devices to be used in the classroom for learning” (Kolb, 2018, para. 1). Figure 1 displays a recent survey of personal device policies in school by the CoSN, that supports these statistics. But even this leaves a significant percentage of school districts that have mobile device bans in place. Reasons for the banning of mobile devices concentrated on students being off-task and distracted (Parsons & Adhikar, 2016; Rubin, 2016), misusing them to cheat, using ‘textese’ in place of Standard English, cyberbullying, and sexting (Shuler, West, & Winters, 2013; Thomas & McGee, 2012).
Although these concerns were not completely without merit, they were largely based on “anecdotal evidence and [ignored] the fact that while [mobile devices] may make it easier for students to engage in certain inappropriate behaviours, they are not the cause of these behaviours” (Thomas & McGee, 2012, p. 19). Unfortunately, negative experiences with ML have stuck in the collective mind of teachers and school policy-makers because “the majority of mobile learning initiatives have been small-scale and short-lived, [and] many teachers have not yet witnessed the benefits of ML in their own classrooms. Furthermore, some teachers have had negative experiences with mobile learning interventions” (Shuler et al., 2013, p. 30). As a result, experts on the topic of ML were concerned that many opportunities to optimize student learning with mobile devices would be missed due to these persisting negative perceptions impacting school policy on acceptable usage, boundaries, and bans (McQuiggan et al., 2015). Rubin (2016, para. 26) asserted that there needs to be a policy shift from “ban and contain” to “manage and support.”
Although these concerns were not completely without merit, they were largely based on “anecdotal evidence and [ignored] the fact that while [mobile devices] may make it easier for students to engage in certain inappropriate behaviours, they are not the cause of these behaviours” (Thomas & McGee, 2012, p. 19). Unfortunately, negative experiences with ML have stuck in the collective mind of teachers and school policy-makers because “the majority of mobile learning initiatives have been small-scale and short-lived, [and] many teachers have not yet witnessed the benefits of ML in their own classrooms. Furthermore, some teachers have had negative experiences with mobile learning interventions” (Shuler et al., 2013, p. 30). As a result, experts on the topic of ML were concerned that many opportunities to optimize student learning with mobile devices would be missed due to these persisting negative perceptions impacting school policy on acceptable usage, boundaries, and bans (McQuiggan et al., 2015). Rubin (2016, para. 26) asserted that there needs to be a policy shift from “ban and contain” to “manage and support.”
Teacher Perceptions of Mobile Devices in the Classroom
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School policy and teacher perceptions on mobile devices and their potential uses in the face-to-face classroom often mirror one another. Teacher attitudes and underlying beliefs about teaching and learning creates a substantial barrier to ML and could be a serious impediment to fundamental change (Thomas & McGee, 2012). It could be an overwhelming challenge for teachers to redefine their role from lecturer to facilitator (Raths, 2013). But negative and outdated perceptions were found to be progressively changing as ML projects from around the world were gaining more credibility as they demonstrated successful implementation of new teaching and learning practices. Projects such as, Project Tomorrow, Khan Academy, and EdX, displayed how learning models that utilized Mobile Learning could be replicated and delivered to more schools and students (Shuler et al., 2013). Mobile Learning initiatives were huge opportunities for education “to provide an experience that is relevant and engaging” for both teachers and students (McQuiggan et al., 2015, para. 2). As more organizations, corporations, and schools fund and develop technological initiatives, “more exemplars of successful mobile learning projects will be available as models for educators, policy-makers and others” (Shuler et al., 2013, p. 28).
As discussed on the 3 Key Considerations of Mobile Learning page, successful Mobile Learning integration required educators to receive the proper resources and training, which were areas that educators commonly cited as missing or inadequately provided (Grant et al., 2015). One study found that the largest concern teachers have about technology integration in schools is that they do not feel supported (Kuzo, 2015). To address this, Grant et al. (2015, p. 34) suggested that teachers should experience “intensive and ongoing staff development that provides opportunities for modelling, practice, and reinforcement of technology use with curricula, which should be linked to curriculum goals and objectives from the onset of technology implementation efforts.” There must be a clear vision for how a particular technology like mobile devices, could be used to achieve instructional goals. It was noted that educators needed to try out their new ideas about teaching and learning with technology in order to for meaningful integration to happen (Thomas & McGee, 2012). Best instructional practice required educators to “examine the underlying pedagogy of the technology they [selected] and focus on aligning the pedagogic design of the technology to their intended classroom goal” (Stevenson et al., 2015, p. 376) and to do that they needed sufficient resources, time, training, and administrative support.
The Myth of the 'Digital Native'
An important observation of educators that falls under the challenge of teacher perceptions, is that many of their students are not ‘digital natives’ and do not naturally work effectively with technology without considerable guidance (Parsons & Adhikar, 2016). There was a false expectation that young people would arrive in the classroom with equal experience and proficiency in these technologies. While students were immersed in technology in their everyday lives, using it to communicate, express themselves and learn in novel ways, they did not implicitly know how to use these devices to learn educationally beneficial material (Peluso, 2012). Students’ lack of conceptual or content knowledge was not compensated by any supportive features in most applications available, which highlighted the risk in assuming that meaningful learning was taking place while students were interacting with mobile devices (Falloon, 2014). When using online tools and applications on mobile devices, educators had an important role in teaching and fostering skill development to ensure students knew the relevant information to effectively engage with these resources (Falloon, 2014).
As discussed on the 3 Key Considerations of Mobile Learning page, successful Mobile Learning integration required educators to receive the proper resources and training, which were areas that educators commonly cited as missing or inadequately provided (Grant et al., 2015). One study found that the largest concern teachers have about technology integration in schools is that they do not feel supported (Kuzo, 2015). To address this, Grant et al. (2015, p. 34) suggested that teachers should experience “intensive and ongoing staff development that provides opportunities for modelling, practice, and reinforcement of technology use with curricula, which should be linked to curriculum goals and objectives from the onset of technology implementation efforts.” There must be a clear vision for how a particular technology like mobile devices, could be used to achieve instructional goals. It was noted that educators needed to try out their new ideas about teaching and learning with technology in order to for meaningful integration to happen (Thomas & McGee, 2012). Best instructional practice required educators to “examine the underlying pedagogy of the technology they [selected] and focus on aligning the pedagogic design of the technology to their intended classroom goal” (Stevenson et al., 2015, p. 376) and to do that they needed sufficient resources, time, training, and administrative support.
The Myth of the 'Digital Native'
An important observation of educators that falls under the challenge of teacher perceptions, is that many of their students are not ‘digital natives’ and do not naturally work effectively with technology without considerable guidance (Parsons & Adhikar, 2016). There was a false expectation that young people would arrive in the classroom with equal experience and proficiency in these technologies. While students were immersed in technology in their everyday lives, using it to communicate, express themselves and learn in novel ways, they did not implicitly know how to use these devices to learn educationally beneficial material (Peluso, 2012). Students’ lack of conceptual or content knowledge was not compensated by any supportive features in most applications available, which highlighted the risk in assuming that meaningful learning was taking place while students were interacting with mobile devices (Falloon, 2014). When using online tools and applications on mobile devices, educators had an important role in teaching and fostering skill development to ensure students knew the relevant information to effectively engage with these resources (Falloon, 2014).
Access and Cost
Figure 2. Importance of digital equity outside of school (CoSN, 2018).
Access and cost were two prominent challenges frequently cited in discussions of instructional applications of technology.
There were reasonable concerns over the costs associated with many mobile devices and their associated data plans (Grant et al., 2015), along with the inadequate coverage provided by cellular companies, particularly in rural districts (Imazeki, 2015). Also, as more users accessed a wireless network, bandwidth was compromised, which affected internet access and speed (Hutchinson et al., 2008). A recent project on Mobile Learning demonstrated that there were still many schools without adequate wireless internet connectivity to allow mobile devices to function to their full capability, displaying the necessity for increased connectivity (Project Tomorrow, 2015). Capable infrastructure and adequate internal district resources were necessities when integrating mobile device use in the face-to face classroom and overcoming the potential barriers of access and cost (Kuzo, 2015). Mobile Learning initiatives that would help offset these challenges were district owned mobile devices being assigned to each student at the beginning of the school year, issuing class sets of mobile devices such as Chromebooks or tablets to students, or BYOD policies. 1:1 BYOD initiatives were of particular interest to districts with limited funding as the mobile device cost was not placed on the school, keeping costs low (Shuler et al., 2013). Research clearly indicated that limited funding for technological innovations and professional development directly affected the pace and path of Mobile Learning and pedagogical innovation in face-to-face schools and classrooms.
As BL and ML pedagogies have become more prevalent in education, educators and policymakers have begun to ask questions regarding the associated costs (Battaglino, Haldeman, & Laurans, 2012). “Many inputs go into the costs behind a BL school: the number of teachers and administrators; their specific salaries; the instructional materials and technologies; student services; and other school operations” (Horn & Staker, 2012, para. 5). There was no simple answer to what a particular BL program, such as a 1:1 Mobile Device initiative, would cost due to the wide variety of models being implemented and the different policies in place that determined pay scales and school budgets. In a recent report, The Costs of Online Learning, based in the U.S. educational and economic context, the estimated costs of BL models currently operated in the U.S. had an average overall per-pupil cost that was significantly lower than the $10,000 national average for traditional brick-and-mortar schools, with a range of $7,600 to $10,200 U.S. Dollar (USD) per-pupil (Battaglino et al., 2012). Calculation of the current USD/Canadian Dollar (CAD) exchange rate brought the cost of BL per-pupil within the range of $10,019 to $13,452 CAD. In a Fraser Institute Report, per-student spending in Canadian public schools was $12,070 CAD and in B.C. public schools this cost was $11,836 CAD per-student (Clemens, Neven Van Pelt, & Emes, 2015), making the implementation of BL and ML financially comparable and feasible.
Student Equity
Another challenge within the parameters of access and cost was student equity. As schools implement more ML initiatives, “ensuring that all students can use the same technology regardless of their socioeconomic status [is increasingly important]. In the fast-moving tech world of K–12 schools, equal student access is critical” (Steckner, 2017, Equality of student access section, para. 1), and has now extended past the classroom into students’ Internet access at home. While most students had access to Internet enabled mobile devices at school and at home, “not all phones are created equal; functionality and phone plans vary widely” (Kolb, 2018, para. 1). Moreover, there were still students that had basic cell phones or no cell phones at all. Figure 2 clearly displays the growing concern that educators have about digital equity outside of school.
Opportunely, mobile devices are steadily becoming more affordable. This important development would partially address challenges surrounding student equity and access to mobile devices. There were a variety of Android Smartphones for under $50, which were comparable to the cost of a class textbook. With unlimited resources, information, and relationships easily accessible through the internet (Richards, 2013) via mobile devices, it was predicted that there would be a decreased need for textbooks in the future (Thomas & McGee, 2012). Research confirmed that there was also a growing competitive market for mobile devices and their applications, which would continue to drive costs down, helping to close the digital divide and improve accessibility for underserved students (Richards, 2013). “The future of mobile learning depends on a globally connected world in which information is freely accessible to all” (Shuler et al., 2013, p. 31). Mobile devices were a low-cost way to give universal access to the digital world to all students.
There were reasonable concerns over the costs associated with many mobile devices and their associated data plans (Grant et al., 2015), along with the inadequate coverage provided by cellular companies, particularly in rural districts (Imazeki, 2015). Also, as more users accessed a wireless network, bandwidth was compromised, which affected internet access and speed (Hutchinson et al., 2008). A recent project on Mobile Learning demonstrated that there were still many schools without adequate wireless internet connectivity to allow mobile devices to function to their full capability, displaying the necessity for increased connectivity (Project Tomorrow, 2015). Capable infrastructure and adequate internal district resources were necessities when integrating mobile device use in the face-to face classroom and overcoming the potential barriers of access and cost (Kuzo, 2015). Mobile Learning initiatives that would help offset these challenges were district owned mobile devices being assigned to each student at the beginning of the school year, issuing class sets of mobile devices such as Chromebooks or tablets to students, or BYOD policies. 1:1 BYOD initiatives were of particular interest to districts with limited funding as the mobile device cost was not placed on the school, keeping costs low (Shuler et al., 2013). Research clearly indicated that limited funding for technological innovations and professional development directly affected the pace and path of Mobile Learning and pedagogical innovation in face-to-face schools and classrooms.
As BL and ML pedagogies have become more prevalent in education, educators and policymakers have begun to ask questions regarding the associated costs (Battaglino, Haldeman, & Laurans, 2012). “Many inputs go into the costs behind a BL school: the number of teachers and administrators; their specific salaries; the instructional materials and technologies; student services; and other school operations” (Horn & Staker, 2012, para. 5). There was no simple answer to what a particular BL program, such as a 1:1 Mobile Device initiative, would cost due to the wide variety of models being implemented and the different policies in place that determined pay scales and school budgets. In a recent report, The Costs of Online Learning, based in the U.S. educational and economic context, the estimated costs of BL models currently operated in the U.S. had an average overall per-pupil cost that was significantly lower than the $10,000 national average for traditional brick-and-mortar schools, with a range of $7,600 to $10,200 U.S. Dollar (USD) per-pupil (Battaglino et al., 2012). Calculation of the current USD/Canadian Dollar (CAD) exchange rate brought the cost of BL per-pupil within the range of $10,019 to $13,452 CAD. In a Fraser Institute Report, per-student spending in Canadian public schools was $12,070 CAD and in B.C. public schools this cost was $11,836 CAD per-student (Clemens, Neven Van Pelt, & Emes, 2015), making the implementation of BL and ML financially comparable and feasible.
Student Equity
Another challenge within the parameters of access and cost was student equity. As schools implement more ML initiatives, “ensuring that all students can use the same technology regardless of their socioeconomic status [is increasingly important]. In the fast-moving tech world of K–12 schools, equal student access is critical” (Steckner, 2017, Equality of student access section, para. 1), and has now extended past the classroom into students’ Internet access at home. While most students had access to Internet enabled mobile devices at school and at home, “not all phones are created equal; functionality and phone plans vary widely” (Kolb, 2018, para. 1). Moreover, there were still students that had basic cell phones or no cell phones at all. Figure 2 clearly displays the growing concern that educators have about digital equity outside of school.
Opportunely, mobile devices are steadily becoming more affordable. This important development would partially address challenges surrounding student equity and access to mobile devices. There were a variety of Android Smartphones for under $50, which were comparable to the cost of a class textbook. With unlimited resources, information, and relationships easily accessible through the internet (Richards, 2013) via mobile devices, it was predicted that there would be a decreased need for textbooks in the future (Thomas & McGee, 2012). Research confirmed that there was also a growing competitive market for mobile devices and their applications, which would continue to drive costs down, helping to close the digital divide and improve accessibility for underserved students (Richards, 2013). “The future of mobile learning depends on a globally connected world in which information is freely accessible to all” (Shuler et al., 2013, p. 31). Mobile devices were a low-cost way to give universal access to the digital world to all students.
Mobile Device and Software Heterogeneity
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There was a notable lack of common platforms among the various manufacturers and mobile devices available, which further complicated the development of ML content and curriculum (Hutchinson et al., 2008). The sheer number of applications available presented both conceptual and practical challenges for educators seeking to visualize and explain the learning process (Stevenson et al., 2015). As potential solutions to this complex issue, some schools have chosen to create a set of “core apps” for common purposes across the school context, while other schools have left the decisions about which applications to use in the learning process to individual teachers and learners (Stevenson et al., 2015). In School District 68, they are using the Google Suite for Education (GSFE) as a set of core apps.
When students come to class bearing devices on multiple platforms, sharing resources has the potential to get complicated. To ease these collaboration issues, one communications and digital learning expert suggested that teachers should use cloud-based online tools and applications that are device neutral, such as GSFE and Learning Management Systems, such as Moodle, Desire2Learn, Canvas, and Blackboard (Sood, 2018). As collaborative learning has become more normative in classrooms and software development continues to progress and improve, Norris & Soloway (2015, p. 17) predicted that by the year 2020, “developers will produce truly device-agnostic applications. Thus, in a heterogenous BYOD environment, the software can be homogenous.”
Ultimately, technology use should not be about the device, but what that device allows students to achieve. Educators must not sacrifice sound pedagogy by focusing solely on technology, or resources will be wasted and opportunities for student learning will be missed (Kuzo, 2015). Mobile Learning should be approached with this in mind and “teachers should select appropriate activity types and assessment strategies before making a final selection about which technology tool will be most useful” (Stevenson et al., 2015, p. 376).
When students come to class bearing devices on multiple platforms, sharing resources has the potential to get complicated. To ease these collaboration issues, one communications and digital learning expert suggested that teachers should use cloud-based online tools and applications that are device neutral, such as GSFE and Learning Management Systems, such as Moodle, Desire2Learn, Canvas, and Blackboard (Sood, 2018). As collaborative learning has become more normative in classrooms and software development continues to progress and improve, Norris & Soloway (2015, p. 17) predicted that by the year 2020, “developers will produce truly device-agnostic applications. Thus, in a heterogenous BYOD environment, the software can be homogenous.”
Ultimately, technology use should not be about the device, but what that device allows students to achieve. Educators must not sacrifice sound pedagogy by focusing solely on technology, or resources will be wasted and opportunities for student learning will be missed (Kuzo, 2015). Mobile Learning should be approached with this in mind and “teachers should select appropriate activity types and assessment strategies before making a final selection about which technology tool will be most useful” (Stevenson et al., 2015, p. 376).
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