Educator Perceptions of Digital Devices, Multitasking and Distractions in the Classroom
Listen and learn : Research paper
Tuesday, June 25, 4:15–5:15 pm
Location: 121AB, Table 5
Presentation 5 of 5
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Examining Preservice Teachers' Technology Integration Development via Their Problem-Centered Learning Experiences
Dr. Julie Delello Dr. Deborah Kerby Dr. Jean Kiekel Dr. Rochell McWhorter Dr. Susan Poyo Dr. Mia Kim Williams
This presentation will describe how 143 educators teaching in global K-16 classrooms perceive the use of digital devices. The discussion centers on the kinds of devices students use, the types of distracted habits students have, the policies campuses use to deter such distractions and what preventative strategies educators recommended.
|Audience:||Teachers, Teacher education/higher ed faculty, Technology coordinators/facilitators|
|Attendee devices:||Devices not needed|
|Participant accounts, software and other materials:||No software is needed for this research presentation.|
|Topic:||Safety, security and student data privacy|
|Subject area:||Higher education, Inservice teacher education|
|ISTE Standards:||For Students:
In this study, we utilized the Limited Capacity Model of Mediated Message Processing (LC4MP) and a media multitasking framework. The LC4MP is an explanatory theory that suggests humans have a limited capacity to process information (Lang, 2000). A media multitasking framework characterizes individuals who constantly switch back and forth engaging with different media, and who are unable to filter out extraneous distractions (Ophir, Nass, & Wagner, 2009).
In this study, we employed a descriptive approach using a mixed-method survey design. This study involved the collection of data using a single survey, which yielded both quantitative and qualitative data through the use of both closed and open-ended questions (Yin, 2014).
Participants in this study consisted of 143 educators who were employed in K-16 schools located around the globe. Members of the research team contacted educators through postings on the International Society for Technology in Education (ISTE) Connect professional learning network (PLN) community board and invited them to complete an online survey. Additionally, an invitation to participate along with the survey link was posted to the social media platform Twitter. Before beginning the research, the study was approved by the University Institutional Review Board (IRB) and consent was obtained from the participants.
An 18-question, mixed-methods survey was created assessing educators’ perceptions of technology usage in the classroom. Specifically, there were 7 demographic questions which assessed gender, ethnicity, grade level and subject area taught, location, years of experience, and education level. Three additional questions asked about the types of devices their students used, seven questions were related to multitasking and distractions, and an additional question was related to the schools’ policies. Furthermore, each question had an open-ended comment box to allow participants the opportunity to provide additional feedback.
For purposes of this study, our analyses focused on examining educators’ perceptions regarding student multitasking and what strategies they perceived would help students to reduce classroom distractions. Analysis of the data involved the examination of surveys completed within the online survey management program Qualtrics (Qualtrics.com). Descriptive statistics were computed. The sample was stratified by gender, years of experience, and age of students taught. Transcripts were created from the open-ended survey responses and further analyzed to look for patterns in the data.
Demographics of Survey Participants
Participant demographics represented a cross section of educators with respect to gender (Male = 35%, Female = 65%), teaching area (Higher education = 24 %, High School = 17%, Middle School = 9%, Elementary = 13%, and other = 37%), and ethnicity (White = 92%, Hispanic = 2%, African-American = 3%, Asian = 1%, Native American = 1%, and other = 1%).
The majority of participants were located in the United States (93%) representing 33 states. U.S. Respondents were from Alabama, Alaska, Arkansas, Arizona, California, Colorado, District of Columbia, Florida, Georgia, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Montana, Nebraska, New Jersey, New Mexico, New York, North Carolina, Ohio, Pennsylvania, Tennessee, Texas, Utah, Virginia and Wisconsin. Seven percent of educators were from outside the U.S. and included those from Austria, New Zealand, Azerbaijan, Turkey, Venezuela, South Africa, Sweden, Australia, Korea, and Uruguay.
Twenty-four percent of participants had a doctoral degree, 61% had a professional or master’s degree, 14% had a bachelor’s degree, and less than 1% noted they had some college experience. When asked how many years of experience in education they had, the majority of participants (21%) reported between 11 and 15 years, followed by 6-10 years (18%), 16-20 years (17%), 21-25 years (13%), 26-30 years (10%), and 0-5 (9%). Eleven percent reported working over 30 years in education. Of those that responded to the survey, 13% were elementary teachers (PK-5), 9% were middle school teachers (6-8), 17% were high school teachers (9-12), 12% were assistant professors, 6% were associate professors, 7% were full professors, and 37% reported other. The other occupations noted a wide range of positions from technology specialists, librarians, to adjunct professors. The respondents taught a variety of subject areas including English, math, science, history, fine arts, physical education, nursing, theology, computer science, technology, business, library, and foreign languages.
RQ1. How do educators perceive digital distractions in the classroom?
When educators were asked whether students were allowed to bring their own devices (BYOD) to class, 66% noted yes; 34% reported no. Some of the devices used were brought to class by the students (47%) while others were provided by the school (53%). For those educators that allowed devices in class, 30% of those devices were tablets, 26% were laptops, 17% were Smartphones, 12% were cell phones, 11% were desktop computers, and 4% were listed as other (Nook, Kindle). When educators were asked whether they felt distracted when students used electronic devices (e.g. iPhone, iPad, laptop, tablet) during class, 35% marked yes while 65% reported no. Of the habits perceived as distracting, texting (26%), playing games (25%), emailing (13%), browsing the Internet (12%), and social media (10%) use were reported. Participants also noted other (14%) distracting habits varied from items such as listening to music to instant messaging. When educators were asked specifically why devices were or were not distracting to those in the classroom, the reactions were mixed. In an open-ended text box, 50 participants described why they felt devices were distracting whereas 94 of the educators described their views as to why devices were not distracting. These answers were multifaceted in that many educators perceived that students were disengaged when devices were allowed and noted that students “go to other sites and work on other things besides what we are working on as a class.” Others reported that they felt that technology should be built into the learning experience with guidance. For example, “Its use is planned for in all of my classes.”
When educators were asked whether they believed students multitasked, 49% stated “yes, a lot” while 31% stated, “yes, but rarely”, 12% reported students did not multitask, and 8% stated they were unsure if students multitasked (performing two or more tasks simultaneously). However findings revealed that when students multitasked at the same time as instruction was taking place, they were most often were seen texting (25%), browsing the Internet (24%), listening to music (20%), using social media (14%), playing games (8%), streaming movies (2%), watching television (1%), or other uses such as applications (apps) (8%) including those for supplementary classroom support (e.g. Quizlets). Sixty-one percent of the educators participating felt that multitasking affected a student’s ability to learn, 31% reported that it rarely affected students learning, 6% felt it had no effect on a student’s ability to learn, while 2% felt students never multitask.
RQ2. What types of policies exist for instructor and student technology use?
When educators were asked if their campus had policies and if so, whether those policies were followed, 55% reported yes. However, 12% of participants also noted that sometimes, policies were their own utilized for their individual classrooms while others (2%) reported they did not have technology policies. Eight percent listed “other” and revealed that many times, “campus policies do exist but they are not followed- always a struggle!” Other respondents were unaware of policies because they “had not looked it up.” One educator noted, “Honestly, not fully sure but I have been told device policies are unique to the instructor” while a second stated, “Who knows?” An additional educator noted, “I believe so. But individual use in courses is no doubt up to professors.”
RQ3. What recommendations do educators have to limit digital distractions in the classroom?
When educators were asked what strategies they recommended to limit or prevent multitasking and distractions in the classroom, 24% of them suggested students should turn devices off while another 24% supported the notion of giving students breaks during class to check their technology. Twenty-three percent supported students silencing devices, while 7% suggested having a strong ban on technology, which is stated in policy. An additional 3% of educators stated that no action should be taken to limit distractions. Forty-eight (20%) of participants listed other and reported additional strategies in the open-ended response box. The responses were mixed and the primary themes found were those of having clear expectations, digital citizenship training, effective classroom engagement, device regulation, device restrictions, and tolerance.
Research has shown that the use of digital devices improve student engagement and help with active learning. However, this study highlighted that there are side-effects to such use including multitasking, distractions, and lack of focus on class instruction. In this generation of ubiquitous computing, the use of devices will continue to penetrate schools. It is important that as educators, we have strategies in place to manage the use of such devices to maximize learning for all students.
The Alberta Teachers’ Association (2015). Technology promise and peril: Growing up digital. Alberta. Retrieved from https://www.teachers.ab.ca/Public%20Education/EducationResearch/Pages/ResearchPublications.aspx
Anderson, J., & Jiang, J. (2018). Teens, social media & technology 2018. Retrieved from http://www.pewinternet.org/2018/05/31/teens-social-media-technology-2018/
Anderson, J., & Rainie, L. (2014). Internet of things. Pew Research Internet Project. Retrieved from http://www.pewinternet.org/files/2014/05/PIP_Internet-of-things_0514142.pdf
Campus Technology (2018, September). Survey: 1 in 4 professors ban mobile phone use in class. Retrieved from https://campustechnology.com/articles/2018/09/19/survey-1-in-4-professors-ban-mobile-phone-use-in-class.aspx
Common Sense Media (2016). What parents need to know about technology addiction. Retrieved from https://www.commonsensemedia.org/blog/what-parents-need-to-know-about-technology-addiction
Dalton, K. (2013). Their brains on Google: How digital technologies are altering the millennial generation's brain and impacting legal education. SMU Science and Technology Law Review, 16, 409-501.
Delello, J. A., Mokhtari, K., &, Reichard, C. (2016). Multitasking among college students: Are freshmen more distracted? International Journal of Cyber Behavior, Psychology and Learning, 6(4), 1-12.
Fox, S. & Rainie, L. (2014). The web at 25 in the US: The overall verdict: The internet has been a plus for society and an especially good thing for individual users. Pew Research Center’s Internet and American Life Project. Retrieved from http://www.pewinternet.org/2014/02/25/the-web-at-25-in-the-u-s.
Goleman, D. (2013). Focus: The hidden driver of excellence. New York: HarperCollins.
Keiser Foundation (2013). Generation M2: Media in the lives of 8-to-18-year-olds. Retrieved from https://kaiserfamilyfoundation.files.wordpress.com/2013/04/8010.pdf
Howard, J. (2017). When kids get their first cell phones around the world. Retrieved from
Lang, A. (2000). The limited capacity model of mediated message processing. Journal of Communications, 50, 1, 46–70.
Lawson, D., & Henderson, B. B. (2015). The costs of texting in the classroom. College Teaching 63(3), 119-124. doi:10.1080/87567555.2015.1019826.
Lewandowski, J. (2018). Back to school without mobile phones: France imposes nationwide ban. Retrieved from https://www.newsweek.com/back-school-without-mobile-phones-france-imposes-nationwide-ban-1104060
Mokhtari, K., Delello, J. A., & Reichard, C. (2015). Millennial multitasking: Constantly Connected yet Distracted. Journal of College Reading & Learning, 45(2), 164-180. doi: 10.1080/10790195.2015.1021880
Ophir, E., Nass, C., & Wagner, A. D. (2009). Cognitive control in media multitaskers. Proceedings of the National Academy of Sciences, 106(37), 15583–15587.
Pahomov, L. (2015). In pursuit of a cell phone policy. ASCD. Retrieved from http://www.ascd.org/publications/educational-leadership/may15/vol72/num08/In-Pursuit-of-a-Cell-Phone-Policy.aspx
Rosen, L. D., Cheever, N. A., & Carrier, L. M. (2012). iDisorder: Understanding our obsession with technology and overcoming its hold on us. New York, NY: Palgrave Macmillan.
Rosen, L. D., Carrier, M. L., & Cheever, N. A. (2013). Facebook and texting made me do it: Media-induced task-switching while studying. Computers in Human Behavior, 29(3), 948-958. doi:10.1016/j.chb.2012.12.001
Shochat, T. (2012). Impact of lifestyle and technology developments on sleep. Nature and Science of Sleep, 4, 19-31.
Smith, A. (2015). U.S. smartphone use in 2015. Pew Research Center’s Internet & American Life Project. Retrieved from http://www.pewinternet.org/2015/04/01/us-smartphone-use-in-2015/
Strauss,V. A. (2018). Schools are banning smartphones. Here’s an argument for why they shouldn’t--and what they should do instead. The Washington Post. Retrieved from https://www.washingtonpost.com/education/2018/09/21/schools-are-banning-smartphones-heres-an-argument-why-they-shouldnt-what-they-should-do-instead/?noredirect=on&utm_term=.322c4563af0e
Yin, R. K. (2014). Case study research: Design and methods (5th ed.). Thousand Oaks, CA: Sage.
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