Learning Distraction and Smartphones

Learning Distraction

While there is reason to be optimistic about the potential for the smartphone to support learning, the learning distraction potential is unquestioned. What began as the occasional untimely ringing of a phone in class has morphed into dozens of more subtle notifications cascading throughout the room. These notifications might take the form of a gentle vibration of the phone, the buzz of a smartwatch, or a dull blinking light emanating from a corner of the device. Regardless, it indicates to the user that something has happened that requires some level of attention. Up to that point, attention was focused on the topic at hand. This is just one example of how the smartphone might be less than ideal for optimum learning. This post will address three areas of challenges presented by smartphone in the learning environment. These will include cognitive challenges, smartphone addiction and the myth of multitasking. As with the categories presented for learning engagement, these are not intended to be comprehensive. It is also clear that the distinctions between learning distraction categories are less distinct.

Cognitive Challenges

Our cognitive limitations were documented many years ago by George Miller in his famous article, The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information (Miller, 1956).  Sixty years later, neuroscientists have provided an explanation based upon what is known about how the brain transmits information in waves (Miller & Buschman, 2015).

In particular, researchers have identified the limited capacity of working memory. At any given time, learners can only hold and manipulate a limited number of items or tasks in working memory. The limitation is pronounced and has been widely demonstrated as critical to the design and implementation of effective instruction (Mayer, 2014; Van Merrienboer & Sweller, 2005). In particular, instructional designers avoid the introduction of any extraneous cognitive load. This is defined as any design element that does not directly contribute to learning but yet draws attention (e.g., the flashing advertisement on news web-site). One has to wonder how much extraneous cognitive load is introduced by the mere presence of the smartphone.

The Myth of Multitasking

The introduction of multitasking operating systems in the late 1980’s seemed to be a boon for computer users. The capacity to run two programs at once could save time by permitting the switching between tools without having to shut down and restart the necessary programs. Given the propensity to equate computer models with human memory (e.g., information processing model of memory), multitasking seemed destined for a larger role in the human experience. This ongoing human experiment has been a nearly unequivocal failure. With the exception of only the most routine and automated tasks, such as riding a stationary bike, a person’s ability to complete more than one task simultaneously is very limited.

“The path forward is to learn more about our vulnerabilities and design around them. To do that, we have to clarify our purpose. In education, learning is the focus, and we know that multitasking is not helpful. So it’s up to us to actively choose unitasking.” Turkle, 2015. para 11.

Turkle argues that we are becoming too accustomed to bite-sized pieces of information. She notes that the average web video is viewed for 6 minutes, regardless of the total duration. To combat this, we need to actively cultivate the capacity for deep attention. Students need to confront the tendency to parcel out attention to multiple devices and people.

Smartphone Addiction

The level of smartphone use varies. In spite of the seemingly ubiquitous nature there are the rare students who only have a simple flip-phone or no mobile phone at all. At the opposite end of the spectrum is the student who finds it very difficult to have the smartphone out of sight for even a moment. Students at this end of the spectrum may be suffering from what has been termed nomophobia, or no-mobile-phone-phobia (Yildirum & Correia, 2015). Extreme nomophobia is associated with increased anxiety and a strong desire to almost constantly attend to the smartphone. The capacity of these students to attend to a lecture in a meaningful way is highly suspect. Casual observations of college students suggest that most suffer from at least a mild form of nomophobia. For these students, the use of the smartphone becomes more impulsive than conscious. In other words, the smartphone has become so intertwined with daily activities for some that using it is an automatic activity akin to spinning a pencil around the thumb or doodling on the margins of the page.

Conclusion

Weighing the costs and benefits of the smartphone for learning is difficult. An elaborate study of smartphone use amongst undergraduate students by Tossell, Kortum, Shepard, Rahmati and Zhong (2014) provides some interesting insights. 24 undergraduate students who did not have a smartphone were given iPhones with data, text and voice plans for one year. The phones had logging software that tracked the phone usage. Pre and post survey results indicated that the students felt that the phone was more of a distraction than an educational asset. The students also felt that the phone did not help them get better grades. The one positive outcome was that the students felt like it helped them stay up to date with academic work. The study also analyzed the app usage and web browsing activities. 32% of the web-sites visited were education related. However, games were by far the most popular app category. 48% of the users installed game applications. This compared to 3% of users installing educational apps.

Given the challenges presented and apparently limited benefits, some have chosen to ban smartphones from the classroom (Mandel, 2015). There is limited research about the prevalence of this view and it is something worthy of pursuit. However, given the recent adoption of more sophisticated wearable technologies (e.g., Apple Watch and FitBit) and the likelihood that embedded technologies will follow, the decision to ban the use of these types of technologies may be moot.

Note: This post is based upon a previously published paper from the Proceedings of the Building Bridges 2016 Conference.

REFERENCES

Mandel, H. (2015, July 6) No phones, please, this is a communications class. Chronicle of Higher Education. Retrieved from http://chronicle.com/article/No-Phones-Please-This-Is-a/231235

Mayer, R. E. (2014). Cognitive theory of multimedia learning. In Mayer, R. (Ed.), The Cambridge handbook of multimedia learning, (31-48). New York: Cambridge University Press.

Miller, E. K., & Buschman, T. J. (2015). Working memory capacity: Limits on the bandwidth of cognition. Daedalus, 144(1), 112-122.

Miller, G. A. (1956). The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychological Review, 63(2), 81-97.

Roberts, J., Yaya, L., & Manolis, C. (2014). The invisible addiction: Cell-phone activities and addiction among male and female college students. Journal of Behavioral Addictions, 3(4), 254-265.

 

Tossell, C. C., Kortum, P., Shepard, C., Rahmati, A., & Zhong, L. (2014). You can lead a horse to water but you cannot make him learn: Smartphone use in higher education. British Journal of Educational Technology, 46(4), 713-724.

Turkle, S. (2015, October), How to teach in an age of distraction. Chronicle of Higher Education. Retrieved from http://chronicle.com/article/How-to-Teach-in-an-Age-of/233515

Van Merrienboer, J. J., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17(2), 147-177.

Yildirim, C., & Correia, A. P. (2015). Exploring the dimensions of nomophobia: Development and validation of a self-reported questionnaire. Computers in Human Behavior, 49, 130-137.

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