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Preservice Teachers' Changing Perceptions on Mobile Phone Use in the Classroom

Listen and learn

Listen and learn : Research paper
Roundtable presentation

Thursday, December 3, 11:15 am–12:00 pm PST (Pacific Standard Time)
Presentation 2 of 3
Other presentations:
Technology Acceptance Model and Use of Twitter by Preservice Teacher Candidates
Energizing Language Teaching and Learning with VR Games and AI Characters

Dr. Kevin Thomas  
Dr. Michael Hylen  
Dr. Beth Carter  

This study examined the perceptions of 158 preservice teachers to determine their support for the use of mobile phones in the classroom. Results indicated that 89% used their phones for school-related work, over half (55%) supported their use in the classroom, and age and school policy affected participants’ perceptions.

Audience: Chief technology officers/superintendents/school board members, Teachers, Teacher education/higher ed faculty
Attendee devices: Devices useful
Attendee device specification: Smartphone: Windows, Android, iOS
Laptop: Chromebook, Mac, PC
Tablet: Android, iOS, Windows
Topic: Teacher education
Grade level: PK-12
Subject area: Higher education, Preservice teacher education
ISTE Standards: For Educators:
  • Advocate for equitable access to educational technology, digital content and learning opportunities to meet the diverse needs of all students.
  • Mentor students in safe, legal and ethical practices with digital tools and the protection of intellectual rights and property.
  • Stay current with research that supports improved student learning outcomes, including findings from the learning sciences.
Additional detail: ISTE author presentation

Proposal summary


Preservice teachers today offer a unique perspective on mobile phones in the classroom. Many of these candidates are only a few years removed from being students in P-12 schools. As students, their perspectives on the instructional value of mobile phones have been shaped by their personal use as well as the myriad of policies at their schools regarding use of mobile phones. As teaching candidates, their perspectives on the instructional value of mobile phones in the classroom continues to be shaped by personal use as well as the knowledge, skills and dispositions learned in their teacher preparation programs. Granted, prior preservice teachers have had access to mobile phones during their P-20 education; however, increased access to mobile phones and online content, significant growth in instructional applications, and evolving school policies make current preservice teachers’ perspective on this topic unique.
Mobile phones have always had the potential to be a beneficial classroom technology, and this potential has increased over time. For example, increased access to mobile phones is an important benefit. In 2011, 35% of adults (Mobile, 2018) and 31% of teenagers between 14-17 had a smartphone (Lenhart, 2012). Today, 95% of adults own a mobile phone and 77% of adults own a smartphone. For adults between the ages of 18-29, smartphone ownership is 94%. Ninety-five percent of teens have access to a smartphone (Mobile, 2018). As the ubiquity of mobile phones increases so does the potential for teachers and students to access technology for schoolwork.
Likewise, access to online content has increased over time. In 2009, 25% of mobile phone owners were accessing the internet via their phones (Smith, 2012). Today, more than two-thirds of Americans access the internet via a mobile device (Bauman, 2018), and 91% of teens age 13-17 access the internet using a mobile device (Lenhart, 2015). Increases have also been seen in the availability of educational applications. For example, in 2010 the Apple store listed 150,000 apps; by 2017, this number had increased to more than 1.5 million (Statista, 2018a)—almost 200,000 of these are educational apps. In 2018, the most popular apps on the Google Play store were educational (Statista, 2018b). The assessment app Kahoot alone has over 50 million users a month and over 830 million have played it since 2013 (Manning, 2017).
Perhaps in response to the increase ubiquity and instructional application, many schools in the U.S. are no longer banning mobile phones. According to a 2017 report by the National Center for Education Statistics (NCES), bans on mobile phones in schools have been steadily dropping since 2010 (Snyder, de Brey, & Dillow, 2019). Approximately ninety percent of U.S. schools banned mobile phones in 2010. By 2014, the number of the schools banning phones dropped to 75.9% and dropped another 10.1% (65.8) by 2016. During this same period, high schools banning mobile phones dropped from 80% to 35%.
This study examined the perceptions of preservice teachers from three teacher preparation programs regarding the use of mobile phones in the classroom. More specifically, it examined their level of support for mobile phones in the classroom and their ability to support student learning. Additionally, this study examined the impact of age and school policy on participants’ perspectives on mobile phone integration.

While educators have long recognized the instructional benefits of technology, including improved students’ engagement, motivation and learning (Roblyer, 2016), these benefits are contingent upon teachers and students using technologies appropriately. Mobile technologies provide teachers with a vast array of benefits including “new and enhanced learning opportunities such as personalized and adaptivity, context-awareness and ubiquity, interactivity, communication and collaboration among learners, and seamless bridging between context in both formal and informal learning” (Nikou & Economides, 2018, p. 102). However, some of the inherent characteristics of mobile technologies, specifically mobile phones, have made it difficult for teachers to manage their appropriate use and created barriers to their integration in classrooms and schools.
The primary instructional benefit of mobile devices is their ability to engage students in meaningful learning opportunities anywhere (Traxler, 2009); therefore, teachers can use mobile phones to engage students in mobile learning (m-learning). M-learning is defined as “a type of learning that enables learners to learn anywhere, anytime using wireless technologies” (Alioon & Delialioğlu, 2019, p. 656). M-learning supports personalized learning (Lindsay, 2016), scaffolding (Hung, Hwang, Lin, Wu & Su, 2013), collaboration (Jeno et al., 2019), increased engagement (Lin, Fulford, Ho, Iyoda & Ackerman, 2012), and increased motivation (Jeno, Grytnes, & Vandvik, 2017). Research has demonstrated the use of m-learning to support student learning in P-12 content areas including math (Song & Kim, 2015), history (King, Gardner-McCune, Vargas, & Jimenez, 2014), science (Kantar & Dogan, 2015), and art (Katz- Buonincontro & Foster, 2014). Nikou and Economides (2018), in a study of students participating in a mobile assisted intervention, found a significant increase in learning in low-achieving students.
M-learning has the potential to engage students in self-directed learning. Self-directed learning is a process in which the individual determines learning needs and defines the task, sets learning goals, enacts study strategies, adapts studying, and evaluates learning outcomes (Saks & Leijen, 2014). Lindsay (2016), surveyed teachers in twenty-four schools about their use of mobile technologies for m-learning. Teachers reported one of the most frequent m-learning activities they engage students in was accessing content via the internet. Teachers reported that students used their mobile technologies to access the internet to “investigate theory, ideas, concepts and to access teacher created content at school nearly every day” (p. 886).
As noted by Jeno et al. (2019), mobile applications (apps) lend themselves to self-directed learning because of their relation to the Cognitive Evaluation Theory (CET) of Self-Directed Learning. CET maintains students’ needs for autonomy is satisfied in learning tasks that engage them in meaningful choices, and their need for competence is satisfied when students are challenged and provided feedback (p. 671). Some apps support students’ need for autonomy and competence and enhance student motivation and performance. For example, Jeno et al. (2019) examined the effects of mobile applications (apps) on 58 students’ achievement and well-being. They found that students using mobile apps had higher levels of perceived competence, autonomy, motivation, and positive affect than students who did not use mobile apps. Another example of how mobile apps create an environment where students’ motivation and achievement are enhanced is through assessment apps.
Mobile devices support both teacher generated formative (Hwang & Chang, 2011) and summative (Arthur, Doverspike, Muñoz, Taylor, & Carr, 2014) assessments and can be used by students for self- and peer-assessments (Lai, Hwang, & Tu, 2018). In a review of literature on the use of mobile-based assessment in education, Nikouo and Edomedies (2018) found that most of the studies on the use of mobile assessment technologies demonstrated a “significant positive impact on student learning performance” (p. 113). Instructional benefits include providing instant feedback to teachers and students, which allows teachers to adjust instruction in real time, increased engagement, attention, and motivation (Kay & LeSage, 2009) as well as supporting student interaction, communication, and collaboration (Sung et al., 2016). Assessment technologies save time, and data can be stored for later use (Adams & Howard, 2009). Additionally, they can be used for polling (Stowell, 2015) to generate discussions and increase participation by allowing normally quiet students to provide feedback (Adams & Howard, 2009). Mobile assessment also allows teachers to introduce game-based assessment into their classrooms, which are distinguished from other forms of assessment by the energy, engagement, and motivation they generate in the classroom (Wang, 2015).
Mobile technologies prepare students for lifelong learning because learning occurs in many places and times (Waycott, Jones, & Scanlon, 2005), and as noted by Sha et al. (2012), preparing “students with knowledge and skills for lifelong learning is regarded as a major goal of contemporary education in which mobile learning is subsumed” (p. 368).


Research Design
Researchers at Asbury University and Bellarmine University in Kentucky and Methodist University in North Carolina used a quantitative descriptive research method to investigate the perceptions of preservice teachers regarding mobile phone usage in the classroom. This study utilized a validated survey (see Appendix A) for data collection (O’Bannon, Dunn, Park, 2017). Survey research was the preferred method of data collection because of its economy, rapid turnaround, and the standardization of the data (Babbie, 2012). Participants had the option of either completing the survey in a hard copy format or online. The online survey program used for this study was QuestionPro.

The subjects for this study consisted of candidates enrolled in the Preservice Teacher Preparation programs at three small liberal arts universities: Bellarmine University and Asbury University in Kentucky and Methodist University in North Carolina. Overall, 367 subjects viewed the online survey with a total of 183 (49.9%) providing some level of participation in the study. Of these participants, 158 (86.89%) completed the study.
The preservice teachers who comprised this sample were distributed between the states, with 126 (69%) located in Kentucky, 41 (22%) located in North Carolina, and 16 (9%) located in other states. The 16 candidates located in others states were comprised of students enrolled in an online degree program and most often lived in a bordering state (e.g. Indiana and Ohio). Of the 158 participants who completed the survey, one hundred and twenty-two participants (77%) were female, and 36 (23%) were male.
One hundred and twenty-six (79.75%) were Caucasian, 12 (7.59%) were African American, six (3.8%) were Latino/Hispanic, five (3.16%) were more than one race, four (2.53%) were Asian, one (.63%) was American Indian/Alaskan Native, and four (2.53%) were other. The greatest percentage of students were between 18 and 21 years of age (N=97, 61.4%), with the overwhelming majority (N=129, 81.6%) reporting they were under the age of 30. The mean age was 24.21. All one hundred and fifty-nine participants (100%) owned smartphones.

Data Source  
The survey used was developed by author (2014). The survey gathers data on participants’ demographics, phone ownership, and mobile phone usage as well as support for the use of mobile phones in the classroom, opinion on use of mobile phones for school-related work, allowing students to use mobile phones for school-related work, and the ability of mobile phones to support student learning. Data was also collected on participants’ perceptions of the benefits and barriers associated with mobilee phones in the classroom. The survey contained a variety of question types including Yes/No, checklists, open-ended, and Likert-scaled questions using 5-point scales (SD = strongly disagree, D = disagree, N = neutral, A= agree, and SA = strongly agree). Likert scaled items were classified in themes.
Participants had the option of taking the survey in hard form or online. The online survey was created using QuestionPro, and a link to the anonymous survey was shared with participants in person during class.

Data Analysis
An email requesting student participation in the study was sent to all faculty teaching initial certification courses in the education programs at each of the three institutions. Once a faculty member agreed to allow her/his students to participate in the study, the researcher at that institution attended the class and explained the purpose of the study to students. Participants then selected which format they would use to complete the survey. Students selected either a hard copy of the surveyor a handout which provided the URL and a QR code to the survey. Both forms of the survey required participants to provide consent.
Accordingly, the independent variable is pre-service teacher perception of mobile phone usage in the classroom. To analyze the data in this study, a number of statistical tests were utilized. In order to characterize the data, descriptive statistics (reported below) were first generated on each question. The descriptive statistics were used to assist in describing and summarizing the data.


Support for use of Mobile Phones. In this study, questions five to eight asked pre-service teachers their level of support for use of mobile phones in the classroom. Based on the responses from 158 participants who completed the survey, the results indicated that more than half (55%) of preservice teachers supported the use of mobile phones in the classroom while less than one-fourth (20%) did not support their use, and one-fourth (25%) were neutral. As stated previously, in order to characterize the data, descriptive statistics (see Table 1) were first generated on each question. The descriptive statistics were used to assist in describing and summarizing the data.
For the purpose of testing whether the participant age correlated with participant perception response, a Pearson Correlation Coefficient was calculated for each set of responses (see Table 2). While the results of the Pearson Correlation Coefficient did not reveal a statistically significant relationship between age and perception, they did reveal a slight correlation between the two (older candidates tended to disagree more than younger candidates).
 Participants were given an opportunity to provide open-ended comments to address how they would allow their students to use mobile phones for school related work. The primary uses identified by participants were for conducting research and utilizing educational apps. Preservice teachers also identified Google tools, Kahoot, recording video and audio as primary school related uses of mobile phones. They also noted that mobile phone use was more appropriate for middle and high school.
School Mobile Phone Policy. In order to determine if school-related policy on mobile phone usage had an influence on pre-service teacher perceptions on mobile phone use in schools, participants were asked to indicate the type of mobile phone policy at their school. The category of “Use for instructional purposes throughout the day” had the largest number of participants (n=66) with “Not allowed” having the fewest (n=2). Once again, in order to characterize the data, descriptive statistics were generated for each policy type on each of the four questions for the purpose of describing and summarizing the data (see Table 3). Mean results did not appear to reveal a direct correlation between school policy and participant perception.
For the purpose of testing whether the school policy correlated with participant perception response, a Pearson Correlation Coefficient was calculated for each set of responses (see Table 3). While the results of the Pearson Correlation Coefficient did not reveal an overall statistically significant relationship between policy and perception on each question, they did reveal a small correlation between the candidates’ school policy and their response to support mobile phone use (R = 0.302).
Participants were also asked to provide open-ended comments about mobile phones being banned from schools. The majority of respondents cited the inability to manage students’ use and the resulting distraction mobile phones cause in the classroom, including in their personal experience, as their primary concern and reason why mobile phones should not be allowed in the classroom.
I find it very difficult to use cellpones in the classroom because many of the
students are not using them in the instructional method that is being asked of them.
I believe it serves as a major distraction between the content the teachers are trying very hard to teach.
I grew up with it, so I completely agree with it. I've seen cell phone in high school
classes and a lot of students don't pay attention.
Additional concerns included lack of security, cyberbullying, and student addiction to mobile phones.
 Preservice teachers also provide comments in support of allowing phones in schools, again citing professional and personal experiences.
I think cell phones can be highly effective for use in the classroom. I would use them for Kahoot (online, teacher created quiz), calendar, camera for notes or needed things, audio recording when I was sick or a teacher talked too fast. I know that they can be used for other things, but it contributed highly to my knowledge and high school experience.
Cell phones and being connected are apart of life in 2018, and I do not feel that it makes sense, or is effective to take away a tool that can be useful in a classroom.
In today's society and from personal experience, I was relieved to have my phone
in class in the event of many lockdowns. With the ability to have my phone in
class, I was able to notify my parents that I was safe as well as being able to find
current information about our status during the lockdown.
Additional reasons given for support included student engagement, overcoming barriers like lack of access, and parents’ ability to contact their children. Again, preservice teachers noted that the use of mobile phones in the classroom is more appropriate for middle/high schools and not elementary schools.
Mobile Phone Features for School-Related Work. Eighty-nine percent of the preservice teachers reported using their phones for school-related work. As part of this study, participants were asked to specify how strongly they agree or disagree with specific features of mobile phones for use in the classroom. As with previous questions, in order to characterize the data, descriptive statistics were first generated on each question for the purpose of describing and summarizing the data. Of the 22 listed features, pre-service teachers identified ‘access to the Internet’, ‘use of educational applications’, ‘use of a calculator’, ‘use of a calendar’, and ‘watching videos’ as the five most beneficial applications for classroom usage (see Table 4).
When descriptive data was delineated by age groups, those 18-29 and those 30+, there was one change in the top five rankings of the features. While participants ages 18 to 29 ranked the top five features exactly as those of the whole group, those thirty years and older replaced “watch a video” (m = 3.54) with “use clock/alarm/timer” (m = 3.57) as the fifth highest ranking feature. We found it no surprise those ages 18 to 29 had the same rankings as the whole group since the number of participants in this age range was over four times as large as the number in age grouping of 30 and older.
Once again, for the purpose of testing whether the participant age correlated with pre-service teacher perception response, a Pearson Correlation Coefficient was calculated for each of the top responses (see Table 5). As in the previous case, the results of the Pearson Correlation Coefficient did not reveal a statistically significant relationship between age and perception of mobile phone usage in the classroom.
 Participants also provided open-ended answers to how they use their mobile phones for school related work. Preservice teachers indicated that they use their phones to communicate, with instructors and peers, as well as collaborate on and create course work.
I record student progress and images of completed projects on my phone. I use the Google Docs app for store written papers on my phone which can also be quickly emailed from my phone if need be. I have also used my phone to create a portfolio of all my artwork over the years.
I connect with other classmates to share information or work on projects when we are unable to meet in person. I access the internet very often to answer questions or look up new information. I use my calendar to remind me on important dates, when my computer cannot alert me or is not with me. I access my email on my phone.
Participants indicated that regardless of school policy or teachers’ integration of mobile phones, they used their mobile phones to engage in a variety of school related activities.

The age of preservice teachers participating in this study appeared to influence their perception of the use of mobile phones for school-related work. Results indicated a small correlation between age and preservice teachers’ perceptions of mobile phone use in schools, and while not statistically significant, substantial gaps exist in the level of support between the younger and older participants. For example, fifty-nine percent (m = 3.54) of participants age 18-29 supported the use of phones in the classroom, compared to 36% (m = 2.84) of the participants over age 30. There was a 25% difference in participants’ beliefs that mobile phones support learning: 93% (m = 3.91) of the younger participants in contrast to 68% (m = 3.5) of those 30+ participants. Likewise, 86.8% (m = 4.17) of participants under 30 indicated they would use mobile phones in their classrooms, compared to 68% (m = 3.4) of older preservice teachers. An even greater discrepancy between younger and older participants was demonstrated in their lack of support.
For all but one of the survey questions about mobile phone use, older respondents were twice or more than twice as likely to oppose mobile phones. For example, when asked if they would use mobile phones for school-related work, 40% (m = 3.4) of older respondents indicated that they would not, compared to 8.5% (m = 4.17) of younger preservice teachers. Similarly, 32% (m = 3.27) of older preservice teachers opposed allowing their students to use their mobile phones for school-related work, whereas only 16.3% (m = 3.81) of younger teachers did not support student use.
There are several explanations for the discrepancies in support for school-related use of mobile phones based on age. Perhaps the most obvious is the amount of use and degree of comfort younger participants feel with mobile phones. According to Pew (Jiang, 2018), Millennials lead older Americans in their adoption and use of technology. In particular, “more than nine-in-ten Millennials (92%) own smartphones, compared with 85% of Gen Xers (those who turn ages 38 to 53 this year), 67% of Baby Boomers (ages 54 to 72).” While all of the participants in this study owned a smartphone, access has increased over the last decade (Lenhart, 2012; Mobile 2018), affording younger participants access to mobile learning during more of the formative years and formal education. Likewise, mobile phones have seen a tremendous increase in access to the internet (Bauman, 2018) and educational applications (Statista, 2018b) over the last decade. Research indicates that both the internet (Lindsay, 2016) and educational apps (Jeno et al., 2019) support student engagement in m- and self-regulated learning. All of participants identified the use of educational apps and the internet as the top two tools they used on their mobile phones for school-related work; however, participants under 30 were more likely to use these tools than were their older colleagues.
Like age, the mobile phone policy at the schools attended by participants had a small correlation with their perceptions on the use of mobile phone in their future classrooms. Preservice teachers who attended schools that allowed teachers and students to utilize mobile phones for school-related work were more likely to support the use of phones in their future classrooms. Furthermore, they were more likely than their colleagues who attended schools that banned mobile phones in the classroom to believe that mobile phones support student learning and indicate that they would allow students to use them in their future classrooms. Over the last decade, the percentage of high schools banning mobile phones has dropped from 80% to 35% (Snyder et al., 2019). In fact, only two (1%) of the 158 participants attended schools that completely banned phones. The majority of participants (n = 66, 41%) attended schools that allowed mobile phones to be used for instructional purposes throughout the day. One explanation for this increase in support from students attending schools that allowed mobile phones in the classrooms is the removal of the primary barrier to integration, school climate (Bitner & Bitner, 2002). Additionally, these preservice teachers had access to instructional models for appropriate instructional integration of mobile phones. Combined with their coursework in their respective TPP, participants observing and interacting with instructional models of integration in their P-12 classrooms could have assisted them in building the necessary knowledge and self-efficacy to use mobile phones in the classroom (Ertmer & Ottenbreit-Leftwich, 2010).

The population of the study is small, which limits the generalizability of the study. Further, the study uses a convenience sample of participants, which also limits generalization of the findings and creates the potential for sampling bias. There was a small number of older participants. There were a large number of female participants; however, this is characteristic of a population of students in a school of education.


Implications for Practice
The findings of this study have implications for educational stakeholders and the field of teacher education/technology. More than half of the preservice teachers who completed the survey support the use of mobile phones in the classroom, and based on the research, a number of factors may have contributed to their perceptions including access to mobile phones and online content, significant growth in instructional applications, and evolving school policies. However, the school districts where they choose to teach must also see the benefits of incorporating this technology and allow mobile phones as instructional tools. Further studies are needed to determine the perceptions of school administrators.
Another factor is the age of teachers. Findings indicate a slight correlation between age and perception; older candidates tended to disagree more with the listed uses than younger candidates did. Further studies are needed to determine if this trend will continue. The results of this study may serve as a guide for faculty in educational technology. Teacher education programs should incorporate training in how to manage the appropriate use of technologies such as mobile phones to achieve the benefits of collaboration, engagement, motivation, and achievement. In addition, the results of this study will benefit teacher educators and higher education faculty as they learn to incorporate mobile phones into their curriculum and instruction.


Adams, H. & Howard, L. (2009). Clever clickers: Using audience response systems in the classroom. Library Media Connection, 28(2), 54–56.
Alioon, Y. & Delialioğlu, Ő. (2019). The effect of authentic m-learning activities on student engagement and motivation. British Journal of Educational Technology, 50(2), 655–668.
Arthur, W., Doverspike, D., Muñoz, G. J., Taylor, J. E., & Carr, A. E. (2014). The use of mobile devices in high-stakes remotely delivered assessments and testing. International Journal of Selection and Assessment, 22, 113–123.
Babbie, E. R. (2012). The basics of social research (6th ed.). Belmont, CA: Wadsworth.
Bauman, K. (2018). More than two-thirds access Internet on mobile devices: New survey questions do a better job capturing mobile use. US Census Bureau. Retrieved from
Bitner, N., & Bitner, J. (2002). Integrating technology into the classroom: Eight keys to success. Journal of Technology and Teacher Education, 10(1), 95-100.
Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal or Research in Teacher Education, 42(3), 255-288.
Hung, P. H., Hwang, G. J., Lin, Y. F., Wu, T. H., & Su, I. H. (2013). Seamless connection between learning and assessment-applying progressive learning tasks in mobile ecology inquiry. Educational Technology & Society, 16(1), 194–205.
Hwang, G. J., & Chang, H. F. (2011). A formative assessment-based mobile learning approach to improving the learning attitudes and achievements of students. Computers & Education, 56(4), 1023–1031.
Jeno, L. M., Adachi, P. J. C., Grytnes, J., Vandvik, V., & Deci, E. L. (2019). The effects of m-learning on motivation, achievement on well-being: A self-determination theory approach. British Journal of Educational Technology, 50(2), 669–683.
Jeno, L. M., Grytnes, J. A., & Vandvik, V. (2017). The effect of a mobile-application tool on biology students’ motivation and achievement in species identification: a self-determination theory perspective. Computers & Education, 107, 1–12.
Jiang, J. (2018). Millennials stand out for their technology use, but older generations also embrace digital life. Pew Research Center: Internet and Technology. Retrieved from
Kantar, M., & Dogan, M. (2015). Development of mobile learning material for 9th grade physics course to use in FATIH project: Force and motion unit. Participatory Educational Research.
Katz-Buonincontro, J., & Foster, A. (2014). Integrating the visual arts back into the classroom with mobile applications: Teaching beyond the ‘click and view’ approach. Journal of Digital Learning in Teacher Education, 30(2), 52-59.
Kay, R. H., & LeSage, A. (2009). Examining the benefits and challenges of using audience response systems: A review of the literature. Computers & Education, 53(3), 819-827.
King, L., Gardner-McCune, C., Vargas, P., & Jimenez, Y. (2014). Re-discovering and re-creating African American historical accounts through mobile apps: The role of mobile technology in history education. Journal of Social Studies Research, 38(3), 173-188.
Lai, C. L., Hwang, G. J., & Tu, Y. H. (2018). The effects of computer-supported self-regulation in science inquiry on learning outcomes, learning processes, and self-efficacy. Educational Technology Research & Development, 1–30.
Lenhart, A. (2012). Cell phone ownership. Pew Research Center: Internet and Technology. Retrieved from
Lenhart, A. (2015). Teens, Social Media & Technology Overview 2015. Washington, DC: Pew Internet & American Life Project.
Lenhart, A., Ling, R., Campbell, S., & Purcell, K. (2010). Teens and mobile phones. Washington, DC: Pew Internet & American Life Project, 20.
Lin, M. F., Fulford, C. P., Ho, C. P., Iyoda, R., & Ackerman, L. K. (2012). Possibilities and challenges in mobile learning for K-12 teachers: a pilot retrospective survey study. In Wireless, Mobile and Ubiquitous Technology in Education (WMUTE), 2012 IEEE Seventh International Conference on (pp. 132–136). IEEE.
Lindsay, L. (2016). Transformation of teacher practice using mobile technology with one-to-one classes: M-learning pedagogical approaches. British Journal of Educational Technology, 47(5), 883–892.
Manning, E. (2017). Out with the old school? The rise of ed tech in the classroom. The Guardian. Retrieved from
Mobile Fact Sheet. (2018). Pew Research Center: Internet and Technology. Retrieved from
Nikou, S. A., & Economides, A. A. (2018). Mobile-based assessment: A literature review of publications in major referred journals from 2009 to 2018. Computers & Education, 125, 101–119.
O'Bannon, B., Dunn, K. & Park, Y. (2017). Validation of Mobile Phone Use in the Classroom Survey. In P. Resta & S. Smith (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 1033-1041). Austin, TX, United States: Association for the Advancement of Computing in Education (AACE).
Roblyer, M. D. (2016). Integrating educational technology into teaching (7th ed.). Boston, MA: Allyn and Bacon/Pearson.
Saks, K., & Leijen, A. (2014). Distinguishing self-directed and self-regulated learning measuring them in the e-learning context. Social and Behavioral Sciences, 112, 190-198.
Sha, L., Looi, C.-K., Chen, W., & Zhang, B. H. (2012). Understanding mobile learning from the perspective of self-regulated learning. Journal of Computer Assisted Learning, 28(4), 366–378.
Smith, A. (2012). 17% of cell phone owners do most of their online browsing on their phone, rather than a computer or other device. Washington, DC: Pew Internet & American Life Project.
Snyder, T. D., de Brey, C., & Dillow, S. A. (2019). Digest of Education Statistics 2017 (NCES 2018-070). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.
Song, D., & Kim, P. (2015). Inquiry-based mobilized math classroom with Stanford mobile inquiry-based learning environment (SMILE). In H. Crompton, & J. Traxler (Eds.), Mobile learning and STEM: Case studies in practice (pp. 150-161). New York: Routledge.
Statista. (2018a). Cumulative number of apps downloaded from the Apple App Store from July 2008 to June 2017 (in billions). Retrieved from
Statista. (2018b). Most popular Google Play app categories as of 1st quarter 2018, by share of available apps. Retrieved from
Stowell, J. R. (2015). Use of clickers vs. mobile devices for classroom polling. Computers & Education, 82, 329–334.
Sung, Y., Chang, K., & Liu, T. (2016). The effects of integrating mobile devices with teaching and learning on students' learning performance: A meta-analysis and research synthesis. Computers & Education, 94, 252-275.
Author. (2014). Standing in the schoolhouse door: Teacher perceptions of mobile phones in the classroom. Journal of Research on Technology in Education, 46(4), 373-395.
Traxler, J. (2009). Current state of mobile learning. In M. Ally (Ed.), Mobile learning: Transforming the delivery of education and training (pp. 247–264). Edmonton, Alberta, Canada: Athabasca Press.
U.S. Department of Education, Office of Educational Technology, Reimagining the Role of Technology in Education: 2017 National Education Technology Plan Update, Washington, D.C., 2017. Retrived from
Wang, A. I. (2015). The wear out effect of a game-based student response system. Computers & Education, 82, 217-227.
Waycott J., Jones A., & Scanlon E. (2005). PDAs as lifelong learning tools: an activity theory based analysis. Learning, Media & Technology, 30, 107–130.

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Dr. Kevin Thomas, Bellarmine University
Dr. Beth Carter, Methodist University

Beth Carter is a professor of education at Methodist University in Fayetteville, North Carolina, where she teaches undergraduate and graduate education courses. She also serves as associate vice president for academic affairs overseeing the evening and e-learning programs. Her research interests include adult learning and technology including mobile learning. Please address correspondence to Beth Carter, 5400 Ramsey Street, Methodist University, Fayetteville, NC 28311. Email:

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