Digital native is the term used to classify people born after ±1984 who have been exposed to and immersed in digital technologies all of their lives. This simple exposure / immersion, according to Marc Prensky (2001), has bestowed them with unique characteristics that set them apart from all other previous generations, such as sophisticated technical skills and learning preferences for which traditional education is unprepared. In his view, the result of this digital immersion is that how these children think and process information makes it difficult for them to excel academically using outdated teaching methods in schools. As I’ll explain later, a part of this is true but in a way that Prensky definitely did not mean nor expect. These digital natives, along with their counterparts members of the tribe of Homo zappiëns, have been attributed powers and abilities different from and far beyond those of their predecessors. According to some, they are a generation for whom “learning is playing”, where “school is for meeting friends rather than learning” and who have the “skill to construct meaningful knowledge from discontinued audio-visual and textual information flows” (Veen, 2006). The Homo zappiëns learns in networks, is a creative problem solver, an experienced communicator, a self-directed learner, an accomplished experimenter, a digital thinker, can effectively process discontinuous information… (ibid.).

And now for the bad news. A recent review article in The Neuroscientist by Loh and Kanai (2015) paints a disturbing picture of what is happening to this group, one that is quite different from the idyllic one of the technologically sophisticated digital native and the skilful, social, knowledge constructing Homo zappiëns. In their words,

[G]rowing up with Internet technologies, “Digital Natives” gravitate toward “shallow” information processing behaviors characterized by rapid attention shifting and reduced deliberations. They engage in increased multitasking behaviors that are linked to increased distractibility and poor executive control abilities. Digital natives also exhibit higher prevalence of Internet-related addictive behaviors that reflect altered reward-processing and self-control mechanisms. Recent neuroimaging investigations have suggested associations between these Internet-related cognitive impacts and structural changes in the brain.

Taking this problem by problem:

• Shallower information processing: Nicholas Carr wrote in 2011 that along with intensive use of the Internet (i.e., a text with hyperlinks to other texts) we see a concomitant increase in shallow information processing where the ‘reader’ constantly shifts her/his attention, examines the text only superficially, thinks less about what (s)he reads, and retains the information more poorly than if the information is deeply processed. This has been corroborated, for example, by Sparrow, Liu, and Wegner (2011) who noted that having information at your fingertips (i.e., relying on Google® or other search engines) goes hand-in-hand with lower rates of information retention. According to Loh and Kanai – citing much solid empirical research show increased browsing going hand in hand with decreased sustained attention – is this in line with Craik and Lockhart’s (1972) position that “lower processing depths, with reduced attention allocation and elaborative thinking, would result in worse information learning”. A second problem with the nonlinearity of texts containing hyperlinks is that cognitively processing them requires a great deal of extra non-productive cognitive effort (i.e., increased extraneous cognitive load), reducing the cognitive resources available to the reader for deep learning and efficient memory consolidation. Preliminary neuroimaging studies have shown that interrupting the development of deep reading skills and a concomitant shift toward shallow information processing may affect brain circuitry necessary for these skills.

Finally, Salomon and Almog (1998) referred to this as the Butterfly Defect. They state

…hypermedia programs offer frail and casual webs of information that lead to the cultivation of similarly flimsy mental networks…intensive interaction with the latter [hypermedia] might facilitate the construction of rather shallow associationist cognitive networks. Such networks would consist of trivial, frail connections, having no intellectual merit. One piece of information leads to another by virtue of some fleeting association without much rational justification, reflecting the aimless, visually-lured wandering though the screens of a hypermedia program… a butterfly-like hovering from item to item without really touching them. (pp. 222, 234, 235)

Jeroen van Merriënboer and I (2013), with our tongues firmly in our cheeks, refer to this as a new form of ADHD (Attention Deficit Hyperlink Disorder).

• Increased distractibility and poor executive control: In 2009, Ophir, Nass, and Wagner showed that high multitasking (actually task-switching since a human only has one brain and can’t cognitively process two things at once) is negatively associated with executive control abilities. The research showed that heavy media multitaskers (HMMs) cannot – or possibly have lost the ability to – filter out irrelevant stimuli. Clifford Nass illustrates this nicely in a short video. There is also an abundance of experimental research findings showing that a strong association between multitasking either during a lesson or while studying outside of school on the one hand and poorer learning on the other. Loh and Kanai conclude that – based upon research evidence – HMMs are worse at inhibiting distracting perceptual information than light media multitaskers. The research also suggested that HMMs adopt a “breadth-biased form of attention control” which seems to be involuntary as HMMs “were found to persist in processing distracting information even when instructed otherwise.” In other words, HMMs are distracted, maintain a shallow (breadth-biased approach) and cannot stop processing distractions and concentrate, even when instructed to do otherwise.
• Altered reward-processing and self-control mechanisms: Loh and Kanai posit that the Internet conditions its users according to the best behaviourist practices of F. Skinner, namely it rewards its users according to a variable ratio schedule. The rewards come at “unpredictable frequencies (e.g., occurrences of Facebook “likes,” YouTube “views,” etc.) and magnitudes (e.g., the quality of Google search matches, blog reviews or comments, etc.)” leading to an increase in Internet addiction with its associated behaviours; that is, altered reward processing and decreased self-control (i.e. the drive for and the receiving of immediate rewards leading to even more Internet use even when the addict is aware of the detriments of the Internet use). In neuroimaging studies, these changes were associated with “alterations in brain networks involved in self-control and reward-processing”.

With respect to the social side of the coin, a recent Canadian study by Sampasa-Kanyinga and Lewis warns that frequent social media use may also affect the psychological well-being of young adolescents. Their study finds that teens – grades 7-12 – who use social media sites for 2 or more hours a day are significantly more likely to suffer from poor mental health, psychological distress, and suicidal thoughts than teens using social media fewer than 2 hours a day. While the study is correlational in nature and thus doesn’t prove causality it does give pause to thought. It could, of course, be the case that adolescents struggling with their psychological well-being may be more likely to use social media frequently, it could just as well be the case – seeing the effects of frequent multitasking and Internet use described above – that excessive use of social media use over time contributes to poor mental health. These findings are in line with a 2012 study that found a correlation between the time spent on social networking in high school students and the risk for clinical depression.

In other words, there might really be the case that the result of this digital immersion is that how these children think and process information makes it difficult for them to excel academically, but NOT because of outdated teaching methods in schools but rather to due to the changes in their brains that impede learning.

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References

Carr, N. (2011). The shallows: what the Internet is doing to our brains. New York, NY: WW Norton.

Craik, F. I. M., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning Verbal Behavior, 11, 671–684.

Kirschner, P. A., & van Merriënboer, J. J. G. (2013). Do learners really know best? Urban legends in education. Educational Psychologist, 48(3), 1-15. doi:10.1080/00461520.2013.804395

Loh, K. K. & Kanai, R. (2015). How has the Internet reshaped human cognition? The Neuroscientist, online first, 1-15. doi: 1073858415595005

Ophir, E., Nass, C. I., & Wagner, A. D. (2009). Cognitive control in media multitaskers, Proceedings of the National Academy of Science of the United States of America, 106, 15583–15587. doi: 10.1073/pnas.0903620106

Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon (NCB University Press, Vol. 9 No. 5, October 2001).

Salomon, G., & Almog, T. (1998). Educational psychology and technology: A matter of reciprocal relations. Teachers College Record, 100, 222-241.

Sampasa-Kanyinga, H. & Lewis, R. F. (2015). Frequent use of social networking sites is associated with poor psychological functioning among children and adolescents. Cyberpsychology, Behavior, and Social Networking, 18, 380-385. doi:10.1089/cyber.2015.0055.

Sparrow, B., Liu, J., & Wegner, D. M. (2011). Google effects on memory: Cognitive consequences of having information at our fingertips. Science, 333(6043), 776-778. doi: 10.1126/science.1207745

Veen, W. (2006). Homo Zappiens. Retrieved March 16, 2011 from http://www.hansonexperience.com/blog/2006/12/slides_van_de_p.htmlLiu