In a two part publication by Marc Prensky (2001a, 2001b), he outlined changes he believes have been affecting the decline of education in the US. Prensky makes the assertion that the thinking patterns and brains of today's students have fundamentally and irreversibly changed, to a point where our education system is not designed to teach to the new thinking patterns. "Digital Immigrants," those instructors of the pre-digital age, struggle to teach "Digital Natives," who's "native language" is grounded in electronics. Though Prensky cites some indirect evidence to reinforce his claims, he confesses he had not directly observed Digital Natives (2001b). This study concentrates on investigating Prensky's specific claim that Digital Natives prefer their graphics before text (2001a).

His list of causes for change includes computers, video games, digital music players, video cams, cell phones, and other digital toys. He also makes the claim that students are spending six times more of their time playing video games and watching TV than reading. Prensky named his new breed of student the "Digital Native." The remaining population, who was not born into a digital lifestyle, is conversely named "Digital Immigrant."

The evidence Prensky (2001b) cites for why Digital Natives think differently is based in neuroplasticity, social psychology, and studies of children using games for learning. He discusses psychological malleability, attention span, and the design of games as variables within each respective category of evidence. He claims the difference between Natives and Immigrants is evident in teaching styles and is the cause of why Natives can't pay attention to instructors.

Prensky identifies Digital Immigrants as a population more likely to use the Internet as a secondary resource, print documents rather than review them on a computer screen, and call email recipients to confirm receipt of emails. Part of the claim of difference between Natives and Immigrants is a language barrier, much like children might only know about turntables or phonographs from a history class. Digital Natives are accused of having "the attention span of a gnat" for old ways of learning, favoring instead anything else (2001b). As such, Prensky outlines five generalizations for the preferences of Natives and Immigrants which he thinks affect learning.

Prensky (2001a) believes Digital Natives prefer to receive information quickly, parallel process, and multi-task. He contends Natives prefer random access to resources, graphics in presentations before text, do best when they are networked, and have instant gratification, with frequent rewards. Finally, natives prefer games to "serious" work. Conversely, Prensky's Immigrants prefer performing linear tasks slowly, individually, as part of a serious process.

One explanation Prensky offers for the evolution of digital migration relates back to adoption in cultural migration theory. In cultural migration, children easily adopt new ways of the culture, forcibly resisting the old. It is the older members of the population who are forced to adopt the new ways.

Eggen and Kauchak (1999) say a learning experience involves dispositions and attitudes, metacognition, and general transfer of knowledge. In fact, the more widely recognized process of learning is more complex. The Modal Model (Bruning, Schraw, Norby, & Ronning, 2004; Healy & McNamara, 1996) defines information processing in terms of sensory memory, short-term memory, and long-term memory. Sensory and short-term memory is limited by attention, prior knowledge, and the context in which experiences occur (Bruning et.al., 2004).

Attention is important for converting cues in sensory memory to working memory to be processed for long-term memory (Ormrod, 2006). Without the transfer of inputs from sensory memory to the higher parts of the memory chain, learners cannot rehearse information in short-term memory to remember the inputs in long-term memory (Bruning et.al., 2004; Eggen & Kauchak, 1999). Complaints of students not paying attention in the classroom is not new (Kassinove & Summers, 1968; Wetstone & Friedlander, 1974). Gagné (1969) made his attention research the top-most important part of his instructional strategy. Research of graphics in education before the "digital age," shows evidence that students prefer colors in presentations (Gaines, 1970). The Gaines publication references 29 publications related to color-forms acting as a instinctual stimulus or preference for children. The placement of items on the screen determines the importance of the content; items higher on the screen appear to the viewer to be more important and attract attention (Thorsen, 2006). The content at the top of the screen should be used to grab students' attention.

Schema theory relates to reader expectations for inputs (Garner, 1987). When incoming information fits readers' expectations, the information can be encoded into memory quickly (Garner, 1987). In technical prose, comprehension schemas are based on the extraction of information based on extracting the microstructure from text and deriving a macrostructure to serve as the "gist." The macrostructure parts are stored in memory and are used for future memory expansion, recall, and inferences (Kintsch & van Dijk, 1978). Readers' goals are based on their within-culture "textual-schemata", which can be predicted based on what readers consider relevant based on their existing macrostructure (Garner, 1987). Readers' existing schema classifies all propositions of inputs as either relevant or irrelevant (Kintsch & van Dijk, 1978).

Motivation is a key component behind the dispositions and attitudes of learning situations (Mueller, 1992). The field of behavioral psychology, or more simply Ivan Pavolv's conditioned response study, may serve as some explanation for graphical preferences of Digital Natives. Combined with cognitive psychology, or the relationship between environmental events and their outcomes, organisms learn particular situations produce particular results (Mueller, 1992). Digital Natives' experience with favorable results from graphical activities may also have a link in cognitive psychology.

All living organisms must categorize experiences to survive since not every situation should be treated the same (Smith, 2004). Learners also have a general state of prediction and expectation (Smith, 2004). The result is that we are far more likely to care about what is going to happen in the future than what is happening right now. Smith says prediction is the core of reading because it cuts down on the number of possible alternatives when we decide what to do with what our eyes are looking at. One of the constraints of prediction is prior experience and knowledge (Smith, 2004).

Smith goes on to discuss two sides of reading, which he names visual and non-visual. The more non-visual information a person has, the less visual information they need to understand what their eye are seeing and vice versa. When reading is difficult, it is because of a deficit in one of the two areas of visual or non-visual input, the link between the brain and visual input can be a bottleneck and cause functional blindness. The functional blindness causes critical information for understanding to not be passed down the memory chain: sensory memory, short-term memory, long-term memory. This point is only exasperated by the link to prior experience where Klausmeier, Ghatala, and Frayer (1974) found prior experience can lead subjects to ignore parts of a later task. Here, the preference of Prensky's Digital natives to have graphical presentation first is a result of the failure for the learners to analyze text stimuli in sensory memory as a cue fore relevant response (Mueller, 1992). On the other hand, noise in a message, irrelevant details, or lack of relevant prior knowledge may serve as a distraction, disruption, or activation of the wrong prior knowledge in a learning experience (Clark & Lyon, 2004).

To date, there are no theories or conceptual frameworks to link Prensky's observations with a solid foundation of research. The preferences of learners may be impacted as a result of conditioning to specific environments; however, even with differing backgrounds of electronic exposure, digital immigrants and digital natives should have statistically insignificant differences exposed to a similar, base set of optimal learning conditions which fit the learning abilities of students outside the window of digital aptitude. Clark and Lyons (2004) give a formula of conditions to support learning with six psychological events, which may support higher level framework of learning. They also put differences between learners on the same level of importance for creating optimal learning conditions, citing prior knowledge and special ability as limiting variables. While using Doom, a classic computer game, in a lesson to teach 20-year-olds may not have the same impact on Digital Immigrants, the reason Digital Immigrants may not have similar impact is not because of limited digital experience per-say, but rather that they simply don't share the same prior knowledge as the Digital Natives who played Doom. There would be a similar situation within a group of Digital Natives if some had not played Doom when others had; the link to building on prior knowledge would be different.

References

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Clark, R. E. (1994). Media will never influence learning. Educational Technology Research and Development, 42(2), 21-29. Retrieved on July 27, 2006, from the University of Southern Queensland Web site: http://www.usq.edu.au/material/unit/resource/clark/media.htm

Clark, R. C., & Lyons, C. (2004). Graphics for learning: Proven guidelines for planning, designing, and evaluating visuals in training materials. San Francisco, CA: Pfeiffer.

Eggen, P., & Kauchak, D. (1999). Educational psychology: Windows on classrooms (4th ed.). Upper Saddle River, NJ: Merrill Prentice Hall.

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Gaines, R. (1970 December). Children's selective attention to stimuli: Stage or set? Child Development, 41(4), 979-991.

Garner, R. (1987). Metacognition and reading comprehension. Norwood, NJ: Ablex Publishing Corporation.

Healy, A. F, & McNamara, D. S. (1996). Verbal learning memory: Does the modal model still work? Annual Review of Psychology, 47, 143-172.

Kassinove, H., & Summers, M. (1968 January). The developmental attention test – A preliminary report on an objective test of attention. Journal of Clinical Psychology, 24(1), 76-78.

Kintsch, W., & van Dijk, T. A. (1978). Toward a model of text comprehension and production. Psychological review, 85(5).

Klausmeier, H. J., Chatala, E. S., & Frayer, D. A. (1974). Conceptual learning and development: A cognitive view. New York, NY: Academic Press, Inc.

Mueller, R. J. (1992). Instructional psychology: Principles and practices. Champaign, IL: Stipes Publishing Company.

Ormrod, J. E. (2006). Essentials of educational psychology. Upper Saddle River, NJ: Pearson Merrill Prentice Hall.

Prensky, M. (2001, October). Digital natives, digital immigrants. On the Horizon 9(5). Retrieved November 25, 2005, from the Marc Prensky Web site: http://www.marcprensky.com/writing/Prensky%20-%20Digital%20Natives,%20Digital%20Immigrants%20-%20Part1.pdf

Prensky, M. (2001, December). Do they really think differently? On the Horizon 9(6). Retrieved November 25, 2005, from the Marc Presnsky Web site: http://www.marcprensky.com/writing/Prensky%20-%20Digital%20Natives,%20Digital%20Immigrants%20-%20Part2.pdf

Smith, F. (2004). Understanding reading: A psycholinguistic analysis of reading and learning to read (6th ed.). Mahwah, NJ: Lawrence Erlbaum Associates.

Thorsen, C. (2006). TechTactics: Technology for teachers second edition. Boston, MA: Pearson Education, Inc.