Learning Targets and Cognitive Science: How much Knowledge Do Low-income Children Catch in their Memory Nets?

By Helen Abadzi, College of Education, University of Texas at Arlington.

Around 1973, a young Indian woman fell ill and went into a coma. When she emerged, she reportedly found in her memory the personal recollections of a Bengali woman who had died about 150 years earlier. Furthermore she reportedly spoke and wrote Bengali with ease. She is perhaps the most spectacular case of skills and knowledge acquired through “reincarnation”.

This phenomenon of recalling information that belonged to deceased individuals has been extensively researched and some claim it to be real, although the physics and neuroscience responsible for it are currently inexplicable. In a database of about 2700 people compiled at the University of Virginia, 2-3 cases involved ability to read without prior instruction.

We do not normally find reading skills implanted in our memories! Someone must teach us. But in poor countries schools teach very little, and many students remain (functionally) illiterate. A knowledgeable visitor to a classroom can quickly spot the signs and give actionable advice. However, donor staff usually lack the training.  They may intuitively believe that students will somehow learn, just like middle-class kids. Or that teachers will magically adjust their instruction when they see test results.

The primary victims of this ignorance are the beneficiaries; billions of dollars in taxpayer money and 25 years of efforts have produced in some countries a generation of schooled illiterates. In the post-2015 education dialogue, donors have much to say about learning targets, but much less about the process for attaining them.

So what should you know about learning in order to help students learn better? Here is an outline.

Memory evolved not for schooling but for survival. Neuronal circuits in our brain have some minimum requirements for creating proteins to store information. These are set in our DNA, so we all encode, retrieve, and forget information on this basis. There are individual and cultural variations, but the general memory rules apply to all.

Our memories are laid in intricate networks, with items linked in complex configurations. Most operations involve unconscious procedures.  School curricula largely involve information that must be learned consciously.

Imagine a fishing net of multiple dimensions.  Some people have nets dense with knowledge; their nets have many knots and many ties to each knot. A denser net catches more information.  Even a trivial item will be fished from the sea of information coming at us and will be attached somewhere on the net. Other people know very little about certain topics. Then their nets have few knots and few links to other knots, therefore good-sized chunks will pass through and escape.  Very smart people may need fewer tries to catch the fish.

Looser net, less and less connected knowledge

Looser net, less and less connected knowledge

To get ensnared in the net and encoded in long-term memory, new information travels a perilous road.  It must pass through our senses, cross the fast-shutting gates of attention and crawl through the narrow tunnels of visual perception and working memory.  It must prevail over other information items that travel the same road.

Dense net, more and better connected knowledge

Dense net, more and better connected knowledge

Surviving this obstacle course is not enough. Networks are built bit by bit.  If a concept is too complex or too fuzzy to fit in an existing knowledge scheme, the fish will escape; the item will be forgotten.  An item must find a suitable place in the network of relevant knowledge to hook itself. Even still, long-term survival is not guaranteed. Items that are recalled often and used in solving problems are linked to many nodes and may be stored permanently. Items used rarely or are hooked to just a few nodes may be forgotten.

Consciously learned, “declarative” information enters first through the senses. If we pay attention to it, it arrives into working memory. There it must be caught in the knowledge net in milliseconds or it gets lost forever.  The networks keep the knowledge classified in long-term memory. When we need the information, we search our networks, locate the right items, and bring them back into working memory.

Consciously learned, “declarative” information enters first through the senses. If we pay attention to it, it arrives into working memory. There it must be caught in the knowledge net in milliseconds or it gets lost forever. The networks keep the knowledge classified in long-term memory. When we need the information, we search our networks, locate the right items, and bring them back into working memory.

 

 

 

 

 

 

 

These events take place in milliseconds, outside our consciousness.  To understand them, psychologists have been conducting memory experiments since about 1875, and 21st century neuroscience has largely validated the findings of the earlier decades.

This “standard model” of human memory is called information processing theory.  Faculties of education rarely teach it. In higher-income countries, teachers may intuitively figure out what to do, so the memory basics and human commonalities may seem boring or banal. Individual differences of learners, philosophy, culture and sociology of education seem more relevant.

But when students and teachers have very limited knowledge and resources, even the biggest fish escape the knowledge nets.  Tests are given, stakeholders are shocked at the results, but they do not know how to improve them.

Learning failures have resulted in intense debates on how best to teach the very poor. Advisors with glamorous credentials give radically different recommendations. Some believe in active learning, transformative pedagogies, constructivism, and community involvement. Some put a premium on innovation, regardless of its effects; they may prescribe complex games and continuous evaluations, writing long descriptions in dense teacher guides.  As a result, in some countries, teachers who may have the equivalent of 3rd grade education and who read perhaps 80 words per minute are expected to read volumes and intuitively convert instructions to activities. Government officials are often confused by the conflicting advice and may take no action at all.

A common language and a generally accepted road map are necessary in order to converse on learning methods and results. Information processing is that roadmap. It can reasonably predict what students may learn from various classroom activities.  The science can lead the fishing boats to schools of fish swimming far below the surface. The guidance will make learning easier and cheaper. And fewer students will fail.

So what does the information processing model tell us about learning basic skills efficiently?

To learn just about everything, we must start with small chunks of information and practice them to automaticity while gradually adding more chunks to form longer skills chains. To progress, feedback is required.   Detailed instruction in letters and numbers or practice activities may seem boring or “rote memorization” to educated adults, but they are a necessary stage.  Analysis, critical thinking, and creativity depend on big chunks of automatized prior knowledge.

Those component chunks should be formed first.  And they should rush into our working memory in milliseconds. We have only a few seconds to contemplate all data together and make decisions!

So, whenever you hear of a great-sounding teaching idea, or whenever you visit a classroom, please ask yourself:  How much of the information may get ensnared in the nets and become consolidated?

  • Will the weaker students learn to execute various items fast enough? Will answers be choked in the bottleneck of working memory?  When will the students get sufficient practice? And who will give them at least a modicum of corrective feedback?
  • Will the teachers remember in class to do all that trainers told them? Can they read fast enough to go through complex teacher manuals?  Will they make the mental effort to interact with everyone or just deal with the best students and neglect everyone else?

Perhaps the most learner-centered and innovative strategy is to tailor teaching to the features of human memory. We have no way of negotiating with our DNA. Either its learning requirements are fulfilled or learning targets are not met.  They will not be met by 2015 or thereafter.

To expect that normal students will learn complex skills in classrooms that lack the information processing prerequisites, is to dally with the only other alternative:  The exceedingly rare and mysteriously produced “reincarnation” memories.

 

Helen Abadzi is a cognitive psychologist at the College of Education, University of Texas at Arlington. Dr Abadzi examines international education issues from the perspective of information-processing research. Email: habadzi@gmail.com

 

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NORRAG (Network for International Policies and Cooperation in Education and Training) is an internationally recognised, multi-stakeholder network which has been seeking to inform, challenge and influence international education and training policies and cooperation for almost 30 years. NORRAG has more than 4,200 registered members worldwide and is free to join. Not a member? Join free here.

 

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