Good computer and video games like System Shock 2, Deus Ex, Pikmin, Rise of Nations, Neverwinter Nights, and Xenosaga: Episode 1 are learning machines. They get themselves learned and learned well, so that they get played long and hard by a great many people. This is how they and their designers survive and perpetuate themselves. If a game cannot be learned and even mastered at a certain level, it won't get played by enough people, and the company that makes it will go broke. Good learning in games is a capitalist-driven Darwinian process of selection of the fittest. Of course, game designers could have solved their learning problems by making games shorter and easier, by dumbing them down, so to speak. But most gamers don't want short and easy games. Thus, designers face and largely solve an intriguing educational dilemma, one also faced by schools and workplaces: how to get people, often young people, to learn and master something that is long and challenging--and enjoy it, to boot.

/pdf/what-video-games-have-to-teach-us-about-learning-and-4ye8hcmm33.pdf

What Video Games Have to Teach Us About Learning and Literacy

Miller (1956) summarized evidence that people can remember about seven chunks in short-term memory (STM) tasks. How- ever, that number was meant more as a rough estimate and a rhetorical device than as a real capacity limit. Others have since suggested that there is a more precise capacity limit, but that it is only three to five chunks. The present target article brings together a wide vari- ety of data on capacity limits suggesting that the smaller capacity limit is real. Capacity limits will be useful in analyses of information processing only if the boundary conditions for observing them can be carefully described. Four basic conditions in which chunks can be identified and capacity limits can accordingly be observed are: (1) when information overload limits chunks to individual stimulus items, (2) when other steps are taken specifically to block the recoding of stimulus items into larger chunks, (3) in performance discontinuities caused by the capacity limit, and (4) in various indirect effects of the capacity limit. Under these conditions, rehearsal and long-term memory cannot be used to combine stimulus items into chunks of an unknown size; nor can storage mechanisms that are not capacity- limited, such as sensory memory, allow the capacity-limited storage mechanism to be refilled during recall. A single, central capacity limit averaging about four chunks is implicated along with other, noncapacity-limited sources. The pure STM capacity limit expressed in chunks is distinguished from compound STM limits obtained when the number of separately held chunks is unclear. Reasons why pure capacity estimates fall within a narrow range are discussed and a capacity limit for the focus of attention is proposed.

/pdf/the-magical-number-4-in-short-term-memory-a-reconsideration-3704b9phuz.pdf

The magical number 4 in short-term memory: a reconsideration of mental storage capacity.

Confirmation bias, as the term is typically used in the psychological literature, connotes the seeking or interpreting of evidence in ways that are partial to existing beliefs, expectations, or a h...

/pdf/confirmation-bias-a-ubiquitous-phenomenon-in-many-guises-18m0fi8wck.pdf

Confirmation Bias: A Ubiquitous Phenomenon in Many Guises:

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components - not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored.

/pdf/perceptual-symbol-systems-4spsk97r61.pdf

Perceptual symbol systems.

Psychology of Learning and Motivation publishes empirical and theoretical contributions in cognitive and experimental psychology, ranging from classical and instrumental conditioning to complex learning and problem solving. Each chapter thoughtfully integrates the writings of leading contributors, who present and discuss significant bodies of research relevant to their discipline. Volume 62 includes chapters on such varied topics as automatic logic and effortful beliefs, complex learning and development, bias detection and heuristics thinking, perceiving scale in real and virtual environments, using multidimensional encoding and retrieval contexts to enhance our understanding of source memory, causes and consequences of forgetting in thinking and remembering and people as contexts in conversation. * Volume 62 of the highly regarded Psychology of Learning and Motivation series* An essential reference for researchers and academics in cognitive science* Relevant to both applied concerns and basic research

The Psychology of Learning and Motivation: Advances in Research and Theory

We report a new phenomenon associated with language comprehension: theaction—sentence compatibility effect (ACE). Participants judged whether sentences were sensible by making a response that required moving toward or away from their bodies. When a sentence implied action in one direction (e.g., “Close the drawer” implies action away from the body), the participants had difficulty making a sensibility judgment requiring a response in the opposite direction. The ACE was demonstrated for three sentences types: imperative sentences, sentences describing the transfer of concrete objects, and sentences describing the transfer of abstract entities, such as “Liz told you the story.” These data are inconsistent with theories of language comprehension in which meaning is represented as a set of relations among nodes. Instead, the data support an embodied theory of meaning that relates the meaning of sentences to human action.

/pdf/grounding-language-in-action-4xzy2msagf.pdf

Grounding language in action

Let's start from scratch in thinking about what memory is for, and consequently, how it works. Suppose that memory and conceptualization work in the service of perception and action. In this case, conceptualization is the encoding of patterns of possible physical interaction with a three-dimensional world. These patterns are constrained by the structure of the environment, the structure of our bodies, and memory. Thus, how we perceive and conceive of the environment is determined by the types of bodies we have. Such a memory would not have associations. Instead, how concepts become related (and what it means to be related) is determined by how separate patterns of actions can be combined given the constraints of our bodies. I call this combination "mesh." To avoid hallucination, conceptualization would normally be driven by the environment, and patterns of action from memory would play a supporting, but automatic, role. A significant human skill is learning to suppress the overriding contribution of the environment to conceptualization, thereby allowing memory to guide conceptualization. The effort used in suppressing input from the environment pays off by allowing prediction, recollective memory, and language comprehension. I review theoretical work in cognitive science and empirical work in memory and language comprehension that suggest that it may be possible to investigate connections between topics as disparate as infantile amnesia and mental-model theory.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0140525X97000010

What memory is for.

https://psychology.illinoisstate.edu/jccutti/psych480_24/readings/glenberg2000.pdf

Symbol Grounding and Meaning: A Comparison of High-Dimensional and Embodied Theories of Meaning

Five experiments examined the effects of environmental context on recall and recognition. In Experiment 1, variability of input environments produced higher free recall performance than unchanged input environments. Experiment 2 showed improvements in cued recall when storage and test contexts matched, using a paradigm that unconfounded the variables of context mismatching and context change. In Experiment 3, recall of categories and recall of words within a category were better for same-context than different-context recall. In Experiment 4, subjects given identical input conditions showed strong effects of environmental context when given a free recall test, yet showed no main effects of context on a recognition test. The absence of an environmental context effect on recognition was replicated in Experiment 5, using a cued recognition task to control the semantic encodings of test words. In the discussion of these experiments, environmental context is compared with other types of context, and an attempt is made to identify the memory processes influenced by environmental context.

https://link.springer.com/content/pdf/10.3758%2FBF03197465.pdf

Environmental context and human memory

Mental models contribute to foregrounding during text comprehension

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