Prior Knowledge in Cognitive Perception Discussion and Design Review March 24, 2015
Introduction to Prior Knowledge Prior knowledge plays an integral role in the process of top down cognitive perception. Prior Knowledge enters the perceptual process after the signal has been detected, and grouped by preattentive “bottom up” elements. As Sohoglu noted, “A striking feature of human perception is that our subjective experience depends not only on sensory information from the environment but also on our prior knowledge or expectations” (Sohoglu, Peelle, Carlyon, & Davis, 2012) In cognitive perception, prior knowledge is integrated with information about stimuli coming in from the environment in order to understand, and effectively respond to a stimuli. The more prior knowledge that has been collected about the stimuli or situation, the less processing is required, and the quicker the response will be executed. (Gregory, 1997) There are several propositional vehicles in which the mind harnesses prior knowledge in order to process stimuli. These vehicles include: semantic networks, which leverage knowledge structures that connect related stimuli based on similar or related qualities; schema, or action sequences, or “knowledge building blocks” that store the appropriate response to a stimuli; mental models, which unify traits to create predictive and explanatory sets of information about situations and stimuli, and metaphors, which serve as analogical comparisons that map one experience against another in order to facilitate comprehension. Three common characteristics are pervasive throughout these vehicles, and serve as identifying traits of the mind; highly structured, constantly modified, and intricately connected. In the following writing these vehicles will be explored with a special focus on these three qualities. Semantic Networks A semantic network is the proposed notion of a knowledge structure comprised of a group of nodes that are discriminatingly linked to one another by connections labeled by the relationship or connecting feature shared between each pair of linked nodes. (Trehub, 1994) These links, also known as relationships between nodes, can be comprised of diverse commonalities including; category membership or a part to while property for example. “A trout is a fish, and a trout has gills”, substances stimuli are made of, and relative weight between subjects. (Trehub, 1994) Quillian’s seminal theory on activation first proposed the idea of the semantic network and the relationship between nodes and links as a means of storing information, “The network is composed of links between two sorts of nodes: type nodes, which represent concepts, and token nodes, which represent instances of concepts by virtue of the links to their respective type nodes. The amount of information in a network is potentially so vast that Quillian assumed that facts are stored explicitly only if they cannot be generated from the network. Hence, general information need be represented only at a superordinate level without being attached to all the subordinate nodes to which it applies.” (Chaffin, Herrmann, & Johnson-Laird, 1984)This propositional network is comprised of categories, that are stored in a hierarchical fashion. (Collins & Quillian, Retrieval Time from Semantic Memory , 1969) Broad categories are divided into smaller subcategories, and “Information stored at one level of the hierarchy is not repeated at other levels. A fact is stored at the highest level to which it applies.” (Collins & Loftus, A Spreading-Activation Theory of Semantic Processing, 1975)
Throughout the years, multiple researchers have explored the concept of semantic networks and built on the original Quillian’s work. In 1973, Andersen and Bower developed the Human Associate Memory model, which resulted in a computer model of long term memory. (Anderson & Bower, 1974)They built on Quillian’s findings that “both linguistic and perceptual information is stored in the form of abstract prepositional representations (i.e., structures in a network).” (Chaffin, Herrmann, & Johnson-Laird, 1984) In 1974, Glass and Holyoak proposed a revision to Quillian’s model that suggested that semantic markers, “form a structure that underlies the intentional relations between words. Each noun is mentally associated with a defining marker, which is supposed to represent an abstract concept roughly equivalent to possessing the essential properties of X, where X is the noun in question…the links between markers represent relations between concepts.” (Chaffin, Herrmann, & Johnson-Laird, 1984) Glass and Holyoak also postulated “that a network need not be strictly hierarchical (as did Quillian and others). There may be, for example, a direct link from canary to animate (not just canary to bird). As they recognized, however, the introduction of this sort of possibility releases the network from any formal constraints on its configurations” (Chaffin, Herrmann, & JohnsonLaird, 1984). In 1994, Jonassen developed the concept of semantic networks as concept maps or cognitive maps, and defined them as “spatial representations of concepts and their interrelationships that are intended to represent the knowledge structures that humans store in their minds” (Jonassen & Marra, 1994) Schema According to Bartlett’s definition, schema is “the active organization of past reactions, or past experience" (Bartlett 1932) Bartlett’s research proposed that humans do not receive every diminutive detail when presented with a stimuli, but rather perceive the stimuli as a whole and “on the basis of this construct the probable detail. Very little of his construction is literally observed…but it is the sort of construction which serves to justify his general impression” (Bartlett 1932) In the 1950s, Jean Piaget defined schema as “a cohesive, repeatable action sequence possessing component actions that are tightly interconnected and governed by a core meaning.” (Piaget, 1954) These action sequences can be considered instructions of knowledge, each action storing information on what the appropriate reaction to a stimuli would be. “When Piaget talked about the development of a person's mental processes, he was referring to increases in the number and complexity of the schemata that a person had learned.” (Macleod, 2012) In 2004, bulding on Piaget’s theory, Wadsworth referred to these instructions as “index cards” filed away in the brain. (Macleod, 2012) There several common types of schema. One example of schema is script, also known as cognitive scripts, which are processes for the way humans approach behaviorally oriented routine tasks and problems. (Sims & Lorenzi, 1992)Person Schema includes “attributes skills, competencies, values of a particular individual. This often takes the form the personality we attribute to that person.” Role schema contains “instructions for role expectations, that is, how we expect an individual occupying a certain role to behavior.” (Sims & Lorenzi, 1992) Piaget believed that cognitive development occurred as a result of adaption to the environment. According to Piaget, this occurred one of two ways,
through assimilation, where existing schema are used to map a new object or situation in the mind, or accommodation, where existing schema are modified in order to understand a new concept. (Piaget, 1954) (Macleod, 2012) “Acquisition of new material by the learner by connecting or assimilating some aspect of the existing cognitive structure and the product of learning of the newly organized cognitive structure which integrates old and new knowledge and in turn may serve as assimilative schema for subsequent learning.” (Mayer R. , 1977) In the 1970s, Richard Mayer introduced the concept of Multimedia Learning, which described Schemas as a function of working memory, where information is actively processed to produce mental structures. (Mayer R. , 70(6), 880-886.) Mental Models Mental Models are defined by Gentner as “Internal representations of reality that people use to understand specific phenomena.” (Gentner D. , 2002) Mental models offer a “predictive and explanatory understanding interactions with the world around us.” (Shute & Zapata-Riveria, 2008) Johnson-Laird, described the integral function that mental models serve in cognition, “mental models play a central and unifying role in representing objects, states of affairs, sequences of events, the way the world is, and the social psychological actions of daily life.” (Johnson-Laird, 1983) Johnson and Laird also documented traits that characterize mental models, “Mental Models are complete and constantly evolving, may contain errors, misconceptions, and contradictions, they may provide simplified explanations of complex phenomena and they often contain implicit measure of uncertainty about their validity that allow them to be used even if incorrect.” (Johnson-Laird, 1983) Mental models pose the risk of generating several biases due to their subjective nature, and the degree to which misconception and errors may be propagated. These include selective omission, and conformational bias. Selective omission is a bias that occurs in collective memory, where a group of information is forgotten in order to overcome traumatic experiences. (Paez & Rime, 1997) A conformational bias is the tendency to search for or elucidate information in such a manner that conforms to preconceived notions or beliefs. (Nickerson, 1998) Metaphors Metaphors are defined by Vosniadou and Ortony as “analogies which allow us to map one experience in the terminology of another experience and thus to acquire an understanding of complex topics or new situations” (Vosniadou & Ortony, 1989) Metaphors in cognition enable humans to leverage past prior knowledge and existing schemas in order to readily understand and comprehend a new phenomenon. (Roediger, 1980) Metaphors work by projecting one schema, (the source domain of the metaphor) onto another schema (the target domain of the metaphor), in order to perceive the relation between the two subjects. (Lakoff, 1992 ) “Metaphors not only enable the reflection and communication of complex topics and the anticipation of new situations, the use of different metaphor models also affects further perception, interpretation of experiences and possibly also subsequent actions” (Gentner D. , 2010) Due to their dependence on prior knowledge and analogical processing, metaphors are greatly influenced by cultural and social percepts. Metaphors are extremely useful in the design of systems, especially in relation to novice users “Interface metaphors enable users to map
knowledge from a familiar source domain to an unfamiliar target domain, allowing them to use prior experience to comprehend and navigate in novel situations� (Green, Kaber, & Segall, 2007) Highly Structured, Constantly Modified, Intricately Connected The semantic network exemplifies a highly structured quality through theories of an incredibly organized hieratical structure of categories, nodes methodically connected based on similarity, and through its essence as systematic knowledge structure. Schema displays this trait through its development of consistent, repeatable action sequences. The nature of schema are highly organized by grouping together like elements that historically result in a similar outcome. The processes of assimilation and accommodation are also reflect the exceptional structure of the mind. Mental Models represent a strong structure by organizing internal representations of reality used to understand specific phenomena. Metaphors also imbue this trait by mapping experience with one another, which would be impossible without a solid reference point and organized structure within the mind. Constantly modified is the next defining characteristic of the cognitive process. Schema represents this quality through its ability to increase in number and complexity as a result of adaptation to the environment. Also assimilation and accommodation represent the mapping of novel stimuli to old conventions, and the development of new conventions which displays a constantly evolving process of comprehension. Mental models display this trait as they are by definition. Metaphors also embody constant modification due to their dependence on cultural and social percepts. The third trait is intricately connected. The semantic network exemplifies this trait by way of it’s group of nodes that are discriminatingly linked to one another by connections labeled by the relationship or connecting feature shared between each pair of linked nodes. Also, its spatial representations of concepts and their interrelationships illustrate strong interconnected qualities. Schema possess component actions that are tightly interconnected and governed by a core meaning. Assimilation also connects incoming stimuli with prior knowledge in order to process information. Mental Models typify interconnect qualities by unifying objects, states of affairs, sequences of events, the way the world is, and the social psychological actions of daily life, while metaphors work by perceiving the relation between two subjects. Example Design Case: Bovada Casino: http://casino.bovada.lv/lobby Bovada Casino is an excellent representation of how a target user’s prior knowledge can be leveraged in order to create a satisfying digital experience. Lobby Using a casino as a metaphor for the services delivered on the site instantly communicates to the target user what type of activities they can engage in on the website. The domain name,
along with the name of the landing page “lobby” leverages the mental model of the target user that a lobby is the common entry point when entering a physical casino. Blackjack When a user enters the blackjack page, the interface resembles a blackjack table. This leverages the user’s prior knowledge about the customary practices of blackjack within a real life casino in order to deliver an experience that they are familiar with. It contains components that are common at blackjack tables including the color of the table, the placement of the cards and chips, and even the orientation, as if the user is sitting at the edge of a round table.
Chips The chips one again employ the user’s prior knowledge of blackjack experiences to facilitate the action of placing a bet on the website. The chips symbolize the bet, on the site and are depicted in different colors which maps the process of what occurs in real life. Different colors are worth different values, matching the characteristics of black jack in a realistic casino.
Action Buttons The actions use terminology that is common to casinos, and the experience of practiced blackjack players, once again mapping to previously stored information. The symbols within these buttons are also exemplary of motions common to the game of black jack for example, the “hit” button depicts an index finger pointed at the cards which is common hand gesture used in blackjack associated with the action of receiving more cards. The shape of the buttons could also be reminiscent of the chip shape, or possibly buttons for automated blackjack games that one might find at an automated casino such as Twin River. Once again, the orientation and placement of the buttons on an arc is meant to duplicate the experience of a user sitting on the edge of a round blackjack table, mimicking the real life experience, and playing to the user’s prior knowledge of what blackjack experience has been or should be.
Layout and Changes The layout as the user plays the game is structured to map directly the real life set up blackjack as the game progresses. As the user bets more chips, the stack of chips rises. Cards are moved in accordance to the action buttons selected by the user, and appear in the exact areas where they would, should the game be unfolding in real life. Once again, this displays a close match to the mental model of target users and a close match to the prior knowledge of users who have played blackjack previously. Conclusion By understanding the prior knowledge and experience of the users of website, UX professionals can design digital experiences and products that align with this knowledge to increase the usability, and learnability of the site. Mapping the structure and actions of a product to match this prior knowledge and mental models increases the ease of use of a product because it requires less cognitive processing.
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