Group items tagged

We are becoming symbiotic with our computer tools

"It seems that when we are faced with a gap in our knowledge, we are primed to turn to the computer to rectify the situation."

"when people expect to have future access to information, they have lower rates of recall of the information itself and enhanced recall instead for where to access it."

we seem to have trained our brains to immediately think of using a computer when we're called on to answer a question or otherwise provide some bit of knowledge.

people who believed the information would be stored in the computer had a weaker memory of the information than those who assumed that the information would not be available in the computer

believing that one won’t have access to the information in the future enhances memory for the information itself, whereas believing the information was saved externally enhances memory for the fact that the information could be accessed, at least in general.

when people expect information to remain continuously available (such as we expect with Internet access), we are more likely to remember where to find it than we are to remember the details of the item.

Erasmus, in his 1512 textbook De Copia, stressed the connection between memory and reading. He urged students to annotate their books

He also suggested that every student and teacher keep a notebook, organized by subject, “so that whenever he lights on anything worth noting down, he may write it in the appropriate section.”

kinds of flowers

To him, memorizing was far more than a means of storage

Far from being a mechanical, mindless process, Erasmus’s brand of memorization engaged the mind fully

“We should imitate bees,” Seneca wrote, “and we should keep in separate compartments whatever we have collected from our diverse reading, for things conserved separately keep better. Then, diligently applying all the resources of our native talent, we should mingle all the various nectars we have tasted, and then turn them into a single sweet substance, in such a way that, even if it is apparent where it originated, it appears quite different from what it was in its original state.”

Memory, for Seneca as for Erasmus, was as much a crucible as a container.

“commonplace books,”

Francis Bacon

“a gentleman’s commonplace book” served “both as a vehicle for and a chronicle of his intellectual development.”

The arrival of the limitless and easily searchable data banks of the Internet brought a further shift, not just in the way we view memorization but in the way we view memory itself.

Clive Thompson, the Wired writer, refers to the Net as an “outboard brain”

David Brooks

“I had thought that the magic of the information age was that it allowed us to know more,” he writes, “but then I realized the magic of the information age is that it allows us to know less. It provides us with external cognitive servants—silicon memory systems, collaborative online filters, consumer preference algorithms and networked knowledge. We can burden these servants and liberate ourselves.”

Peter Suderman

“it’s no longer terribly efficient to use our brains to store information.”

“Why memorize the content of a single book when you could be using your brain to hold a quick guide to an entire library? Rather than memorize information, we now store it digitally and just remember what we stored.”

Don Tapscott, the technology writer, puts it more bluntly. Now that we can look up anything “with a click on Google,” he says, “memorizing long passages or historical facts” is obsolete.

When, in an 1892 lecture before a group of teachers, William James declared that “the art of remembering is the art of thinking,” he was stating the obvious.

Dehaene and colleagues proposed that skilled reading involves an adaptation of general object-identification processes in ventral occipitotemporal brain areas to the specific characteristics of printed words

according to the dominant theories of reading, orthographic processing is still primarily considered to be an extension of already established linguistic skills in the domain of spoken language processing

We challenged the hypothesis that learning an orthographic code depends on preexisting linguistic knowledge by investigating whether nonhuman primates can learn this skill.

the word versus nonword discrimination could be made implicitly on the basis of statistical dependencies between letters.

More detailed analyses revealed that baboons were not simply memorizing the word stimuli but had learned to discriminate words from nonwords on the basis of differences in the frequency of letter combinations in the two categories of stimuli (i.e., statistical learning).

words that were seen for the first time triggered significantly fewer “nonword” responses than did the nonword stimuli

Even more striking is the strong linear relation, shown in Fig. 4, between accuracy in response to nonword stimuli and their orthographic similarity to words that the baboons had already learned. The more similar a nonword was to a known word, the more false positive responses it produced.

Our findings have two important theoretical implications. First, they suggest that statistical learning is a powerful universal (i.e., cross-species) mechanism that might well be the basis for learning higher-order (linguistic) categories that facilitate the evolution of natural language (18, 19). Second, our results suggest that orthographic processing may, at least partly, be constrained by general principles of visual object processing shared by monkeys and humans.

Our study may therefore help explain the success of the human cultural choice of visually representing words using combinations of aligned, spatially compact, ordered sequences of symbols. The primate brain might therefore be better prepared than previously thought to process printed words, hence facilitating the initial steps toward mastering one of the most complex of human skills: reading.

Our results indicate that baboons were coding the word and nonword stimuli as a set of letter identities arranged in a particular order. Baboons had learned to discriminate different letters from each other (letter identity) and to associate those letter identities with positional information. Their coding of the statistical dependencies between position-coded letters is reflected in (i) their ability to discriminate novel words from nonwords (i.e., generalization), (ii) the significant correlation between bigram frequency and the accuracy of responses to words, and (iii) the increase in errors in response to nonword stimuli that were orthographically more similar to known words.

today's students think and process information fundamentally differently from their predecessors.

it is very likely that our students’ brains have physically changed - and are different from ours - as a result of how they grew up.  But whether or not this is literally true, we can say with certainty that their thinking patterns have changed.

our Digital Immigrant instructors, who speak an outdated language (that of the pre-digital age), are struggling to teach a population that speaks an entirely new language.  

Digital Natives are used to receiving information really fast.  They like to parallel process and multi-task.  They prefer their graphics before their text rather than the opposite. They prefer random access (like hypertext). They function best when networked.  They thrive on instant gratification and frequent rewards.  They prefer games to "serious" work. 

They have little patience for lectures, step-by-step logic, and "tell-test" instruction. 

Often from the Natives' point of view their Digital Immigrant instructors make their education not worth paying attention to compared to everything else they experience - and then they blame them for not paying attention! 

Smart adult immigrants accept that they don’t know about their new world and take advantage of their kids to help them learn and integrate.  Not-so-smart (or not-so-flexible) immigrants spend most of their time grousing about how good things were in the "old country."

As educators, we need to be thinking about how to teach both Legacy and Future content in the language of the Digital Natives.  The first involves a major translation and change of methodology; the second involves all that PLUS new content and thinking.  It's not actually clear to me which is harder - "learning new stuff" or "learning new ways to do old stuff."  I suspect it's the latter.  

My own preference for teaching Digital Natives is to invent computer games to do the job, even for the most serious content.