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Research in neurolinguistics examines how language is organized and processed in the human brain. The findings from neurolinguistic studies on language can inform our understanding of the basic ingredients of language and the operations they undergo. In the domain of the lexicon, a major debate concerns whether and to what extent the morpheme serves as a basic unit of linguistic representation, and in turn whether and under what circumstances the processing of morphologically complex words involves operations that identify, activate, and combine morpheme-level representations during lexical processing. Alternative models positing some role for morphemes argue that complex words are processed via morphological decomposition and composition in the general case (full-decomposition models), or only under certain circumstances (dual-route models), while other models do not posit a role for morphemes (non-morphological models), instead arguing that complex words are related to their constituents not via morphological identity, but either via associations among whole-word representations or via similarity in formal and/or semantic features. Two main approaches to investigating the role of morphemes from a neurolinguistic perspective are neuropsychology, in which complex word processing is typically investigated in cases of brain insult or neurodegenerative disease, and brain imaging, which makes it possible to examine the temporal dynamics and neuroanatomy of complex word processing as it occurs in the brain. Neurolinguistic studies on morphology have examined whether the processing of complex words involves brain mechanisms that rapidly segment the input into potential morpheme constituents, how and under what circumstances morpheme representations are accessed from the lexicon, and how morphemes are combined to form complex morphosyntactic and morpho-semantic representations. Findings from this literature broadly converge in suggesting a role for morphemes in complex word processing, although questions remain regarding the precise time course by which morphemes are activated, the extent to which morpheme access is constrained by semantic or form properties, as well as regarding the brain mechanisms by which morphemes are ultimately combined into complex representations.

Emotions are an important part of how audiences connect with health and risk messages. Feelings such as fear, anger, joy, or empathy are not just byproducts of information processing, but they can interact with an individual’s perception and processing of the message. For example, emotions can attract attention to the message, they can motivate careful processing of the message, and they can foster changes in attitudes and behavior. Sometimes emotions can also have counterproductive effects, such as when message recipients feel pressured and react with anger, counterarguments, or defiance. Thus, emotion and cognition are closely intertwined in individuals’ responses to health messages. Recent research has begun to explore the flow and interaction of different types of emotions in health communication. In particular, positive feelings such as joy and hope have been found to counteract avoidant and defensive responses associated with negative emotions such as fear and anger. In this context, research on health communication has begun to explore complex emotions, such as a combination of fear and hope, which can highlight both the severity of the threat, and individuals’ self-efficacy in addressing it. Empathy, which is characterized by a combination of affection and sadness for the suffering of others, is another example of a complex emotion that can mitigate defensive responses, such as anger and reactance, and can encourage insight and prosocial responses.

Dyslexia, or a reading disability, occurs when an individual has great difficulty at the level of word reading and decoding. Comprehension of text, writing, and spelling are also affected. The diagnosis of dyslexia involves the use of reading tests, but the continuum of reading performance means that any cutoff point is arbitrary. The IQ score does not play a role in the diagnosis of dyslexia. Dyslexia is a language-based learning disability. The cognitive difficulties of dyslexics include problems with recognizing and manipulating the basic sounds in a language, language memory, and learning the sounds of letters. Dyslexia is a neurological condition with a genetic basis. There are abnormalities in the brains of dyslexic individuals. There are also differences in the electrophysiological and structural characteristics of the brains of dyslexics. Hope for dyslexia involves early detection and intervention and evidence-based instruction.

Psychology’s attention to mental events took root in the middle of the 19th century and grew through studies of learning, forgetting, and problem solving. Following several decades during which behaviorism dominated the field, cognitive studies of learning rapidly expanded after the mid-1960s. Foci for research concerned how learners acquire different kinds information, particularly declarative knowledge, procedural knowledge, and schemas, and identifying cognitive operations learners can apply to transform experience into knowledge. What learners know significantly shapes what they learn. Prior knowledge often benefits learning, but inaccurate knowledge, called misconceptions, and skills applied indiscriminately can impede it. Effort to learn, called cognitive load, is not a unary concept. Designing learning tasks to focus cognition in ways germane to content is one key to effective instruction. Learners can think about their cognition and its properties. This is metacognition. Examples include judgments of whether and what is learned, planning shaped by the relative success in tasks and affective experiences, and decisions to abandon risky or unproductive tasks. Measures of metacognition, predominantly learners’ reports as opposed to direct indicators, correlate modestly with achievement, but this may reflect that students are not often educated in study tactics and learning strategies. Metacognition is a key factor in learners’ decisions about which study tactics and learning strategies they use, and a challenge learners face is overcoming overconfidence about what they know. The metacognitive decision-making event is modeled as an If–Then production. Metacognitive control of how learners choose to go about learning is conditional on metacognitive monitoring of conditions the learner believes will influence learning processes and outcomes. When learners experiment with approaches to learning, they engage in self-regulated learning (SRL). SRL is a very energetic area of research that spans investigations into learners’ metacognition about conditions for learning, operations on information, products resulting from those operations, and evaluations of products in terms of standards the learner holds; the COPES model. Like its foundation in metacognition, SRL also correlates modestly with achievement and is similarly challenged by relying on learners’ self-reports about SRL. However, learners can be taught how to better apply SRL which may realize benefits to achievement.

The theoretical outlook of usage-based linguistics is a position that views language as a dynamic, evolving system and that recognizes the importance of usage frequency and frequency effects in language, as well as the foundational role of domain-general sociocognitive processes. Methodologically, usage-based studies draw on corpus-linguistic methods, experimentation, and computational modeling, often in ways that combine different methods and triangulate the results. Given the availability of corpus resources and the availability of experimental participants, there is a rich literature of usage-based studies focusing on Germanic languages, which at the same time has greatly benefited from usage-based research into other language families. This research has uncovered frequency effects based on measurements of token frequency, type frequency, collocational strength, and dispersion. These frequency effects result from the repeated experience of linguistic units such as words, collocations, morphological patterns, and syntactic constructions, which impact language production, language processing, and language change. Usage-based linguistics further investigates how the properties of linguistic structures can be explained in terms of cognitive and social processes that are not in themselves linguistic. Domain-general sociocognitive processes such as categorization, joint attention, pattern recognition, and intention reading manifest themselves in language processing and production, as well as in the structure of linguistic units. In addition to research that addresses the form and meaning of such linguistic units at different levels of linguistic organization, domains of inquiry that are in the current focus of usage-based studies include linguistic variation, first and second-language acquisition, bilingualism, and language change.

A brain-based approach can provide a framework for intelligence, for integration of biology and cognitive processes that have direct implications for education and brain plasticity. Intelligence is reframed here as a selective cluster of different cognitive processes often localized in broad divisions of the brain. Theories and systems that have guided investigation into the brain mechanisms for cognitive processes are reviewed. The focus is on education and cultural disadvantage, delineating changes in the brain due to learning and its dysfunction. Selected programs for enhancement of neurocognitive abilities are presented. Neuronal changes appear to occur as a consequence of learning throughout life. A brain-based approach not only relates to how intelligence works, but also opens the door to understanding the mind and hence consciousness. One may say that the mind is not an eclectic collection of intellectual functions of the brain. Rather, the ultimate goal of intelligence is to form a better view of self that gives meaning to an individual’s existence.

Cognitive psychology highlights the constraints that prevent individuals from acting as utility-maximizing, fully rational decision-makers. These constraints lead people to rely on a regularly occurring set of cognitive mechanisms to simplify the decision-making process. Scholars of foreign policy have drawn from several prominent areas of cognitive psychology to inform their research. One such area looks at the beliefs and belief systems that are the building blocks for most judgments. Researchers have also examined how actors use cognitive biases and heuristics to cope with uncertainty, which is abundant in foreign policy settings. An important set of cognitive mechanisms examined in foreign policy analysis (FPA) relates to judgments about policy risks and costs. In order to make inferences and predictions about behavior concerning voting decision, certain key public influences must be considered. These influences include the role of emotions, political socialization, political sophistication, tolerance of diversity of political views, and the media. The effect of these influences on voting behavior is best understood through theories on the formation of attitudes, beliefs, schema, knowledge structures, and the practice of information processing. The degree to which voting decision is affected by internal processing systems of political information alters the quality of making truly democratic decisions.

Online processing, and the models arising from it, starts with an optimistic view of the American voter, in which it is supposed that the seeming ignorance of voters does not prevent them from expressing rational attitudes about the very political objects they do not know much about. This means that the seeming ignorance of voters is not necessarily a threat to electoral democracy, but the cognitive structures needed for this sort of rationality also lead to necessary, and sometimes extreme, biases in political information processing. Since information stored in long-term memory is linked, both semantically and affectively (that is, based on the perceived positive or negative valence of the information), affect—understood here as a simple positive or negative valence—colors all steps of information processing. For instance, individuals are likely to avoid, or counter-argue, or simply reject information that is at odds with their existing views. As a result, individuals of different political persuasions may have difficulty coming to agreement on the correct interpretation of relevant facts, or even the facts themselves. Alternative memory-based models, which propose that evaluations are constructed on the spot when a question is asked, may help to explain response instability, but fail to serve as complete replacements for the online processing approach. The bias caused by affect-infused cognition seems to present challenges for electoral democracy just as much as the seeming ignorance it accounts for, but it is argued that such biases are mostly limited to individuals who already hold fairly strong existing attitudes, a group which is unlikely to include most voters. Moreover, some degree of intransigence is likely a good thing, as the alternative is views that shift rapidly with new information.

Information processing is a cognitive learning theory that helps explain how individuals acquire, process, store, and retrieve information from memory. The cognitive architecture that facilitates the processing of information consists of three components: memory stores, cognitive processes, and metacognition. The memory stores are sensory memory, a virtually unlimited store that briefly holds stimuli from the environment in an unprocessed form until processing begins; working memory, the conscious component of our information processing system, limited in both capacity and duration, where knowledge is organized and constructed in a form that makes sense to the individual; and long-term memory, a vast and durable store that holds an individual’s lifetime of acquired information. Information is moved from sensory memory to working memory using the cognitive processes attention, selectively focusing on a single stimulus, and perception, the process of attaching meaning to stimuli. After information is organized in working memory so it makes sense to the individual, it is represented in long-term memory through the process of encoding, where it can later be retrieved and connected to new information from the environment. Metacognition is a regulatory mechanism that facilitates the use of strategies, such as chunking, automaticity, and distributed processing, that help accommodate the limitations of working memory, and schema activation, organization, elaboration, and imagery that promote the efficient encoding of information into long-term memory. Information processing theory has implications for our daily living ranging from tasks as simple as shopping at a supermarket to those as sophisticated as solving complex problems.

The messages spoken in everyday conversation are influenced by participants’ goals. Interpersonal scholars have distinguished two types of goals thought to influence the wording of a message: instrumental goals (primary goals) and secondary goals. An instrumental goal is related to a speaker’s primary reason for designing the message. Instrumental goals would include goals such as to ask for a favor, seek information, apologize, give advice, or change the other person’s opinion. Secondary goals pertain to more general concerns. They include goals such as to manage one’s impression, avoid offending the hearer, and act consistently with one’s values. The ability to design a message that pursues an instrumental goal effectively while also addressing (or at least not conflicting with) relevant secondary goals is associated with greater communication competence. Considerable research has sought to explain differences in the ability to design messages that effectively address multiple goals. One such factor appears to be the extent to which a speaker can adapt the language of a message to the communication-relevant features of a specific situation or hearer. If a speaker’s primary goal is to seek a favor, relevant situation features may include the speaker’s right to ask, expected resistance, and qualities of the speaker–hearer relationship. A second behavior associated with the ability to produce multiple-goal messages is suggested by research on cognitive editing. The latter research indicates that the likelihood of producing a message that addresses relevant secondary goals will sometimes depend upon whether a speaker becomes aware, prior to speaking, that a planned message could have an unwanted outcome (e.g., the message may offend the hearer). When such outcomes are anticipated in advance, the message may be left unspoken or edited prior to speaking. The ability to produce a message that achieves a speaker’s goals may also depend on the type of planning that precedes the design of a message. The plan-based theory of strategic communication views plans as hierarchical structures that specify goals and actions at different levels of specificity. The theory holds that a person pursuing a goal first tries to retrieve from memory a preexisting plan that could be modified for the current situation. When that is not possible, speakers must formulate a novel plan. Research employing indicants of fluency suggests that formulating a novel plan (which requires changes at a higher, more abstract level of a plan) makes heavier demands on limited capacity than does modifying an existing plan at a lower level of the hierarchy (e.g., speaking more slowly). Insight into how persons plan what to say has also come from research on imagined interactions, conflict management, anticipating obstacles to compliance, and verbal disagreement tasks. In an effort to better understand the design of messages in interpersonal settings, a number of scholars have proposed models of the cognitive processes and structures thought to be involved in designing, editing, and producing such messages. Action models of this sort, which generate testable hypotheses, draw from work in artificial intelligence, cognitive models of language production, and research on social cognition. Three such models are action assembly theory, the cognitive rules model, and the implicit rules model.

Age-related hearing loss is heterogeneous. Multiple causes can damage the auditory system from periphery to cortex. There can be changes in thresholds for detecting sound and/or in the perception of supra-threshold sounds. Influenced by trends in neuroscience and gerontology, research has shifted from a relatively narrow modality-specific focus to a broader interest in how auditory aging interacts with other domains of aging. The importance of the connection between sensory and cognitive aging was reported based on findings from the Berlin Aging Study in the mid-1990s. Of the age-related sensory and motor declines that become more prevalent with age, hearing loss is the most common, and it is the most promising as an early marker for risk of cognitive decline and as a potentially modifiable mid-life risk factor for dementia. Hearing loss affects more than half of the population by 70 years of age and about 80% of people over 80 years of age. It is more prevalent in people with dementia than in peers with normal cognition. People with hearing loss can be up to five times more likely to develop dementia compared to those with normal hearing. Evidence from cross-sectional studies has confirmed significant correlations between hearing loss and cognitive decline in older adults. Longitudinal studies have demonstrated that hearing loss is associated with incident cognitive decline and dementia. Various biological, psychological, and social mechanisms have been hypothesized to account for these associations, but the causes remain unproven. Nevertheless, it is widely believed that there is a meaningful interface among sensory, motor, and cognitive dysfunctions in aging, with implications for issues spanning brain plasticity to quality of life. Experimental research investigating sensory-motor-cognitive interactions provides insights into how age-related declines in these domains may be exacerbated or compensated. Ongoing research on auditory aging and how it interfaces with cognitive aging is expected to increase knowledge of the neuroscience of aging, provide insights into how to optimize the everyday functioning of older adults, and inspire innovations in clinical practice and social policy.

A growing body of research uses computational models to study political decision making and behavior such as voter turnout, vote choice, party competition, social networks, and cooperation in social dilemmas. Advances in the computational modeling of political decision making are closely related to the idea of bounded rationality. In effect, models of full rationality can usually be analyzed by hand, but models of bounded rationality are complex and require computer-assisted analysis. Most computational models used in the literature are agent based, that is, they specify how decisions are made by autonomous, interacting computational objects called “agents.” However, an important distinction can be made between two classes of models based on the approaches they take: behavioral and information processing. Behavioral models specify relatively simple behavioral rules to relax the standard rationality assumption and investigate the system-level consequences of these rules in conjunction with deductive, game-theoretic analysis. In contrast, information-processing models specify the underlying information processes of decision making—the way political actors receive, store, retrieve, and use information to make judgment and choice—within the structural constraints on human cognition, and examine whether and how these processes produce the observed behavior in question at the individual or aggregate level. Compared to behavioral models, information-processing computational models are relatively rare, new to political scientists, and underexplored. However, focusing on the underlying mental processes of decision making that must occur within the structural constraints on human cognition, they have the potential to provide a more general, psychologically realistic account for political decision making and behavior.

Cognitive regulation refers to the self-directed regulation of cognitions (thoughts, beliefs, affects) toward the attainment of goals. Cognitive regulation can occur before individuals engage in tasks, while they are working on them, and during pauses or when tasks are completed where individuals reflect on their performances. Researchers have addressed which cognitive regulation processes are used during various phases of task engagement, how these processes differ among individuals due to ability and achievement levels and due to development, how cognitive regulation processes operate during task engagement, and which interventions can effectively help persons become better cognitive regulators. The implications of the research findings are that teachers and others can help learners improve their cognitive regulation skills. Some important processes are goal setting, strategy use and adaptation, monitoring of cognition and performance, motivation (e.g., self-efficacy), and self-evaluation. Effective interventions expose students to models displaying these skills and provide for practice with feedback. There are six limitations of the present research that should be addressed. This can be accomplished by conducting more intervention studies, examining fine-grained changes in cognitive regulation, conducting research in non-traditional contexts, integrating the educational and developmental literatures, exploring cognitive regulation across cultures, and investigating cognitive regulation during learning with technology.

Hindsight bias describes the tendency of persons—after the outcome of an event is known—to overestimate their foresight. For example, following a political election, persons tend to retrospectively adjust their predictions to the actual outcome. These judgment distortions are very robust and have been observed in a variety of domains and tasks. About 50 years of research on hindsight bias have meanwhile brought a wealth of findings and insights. Core research questions are (1) how to explain hindsight bias in terms of underlying processes, (2) whether there are individual differences in susceptibility, (3) how the bias possibly impedes decision-making in applied contexts, such as political decision-making, and (4) how possibly to overcome it. Theoretical approaches suggest that there are distinct components of hindsight bias, and that several, mainly cognitive, mechanisms are responsible for them. Using stochastic models of hindsight bias allows us to estimate the relative proportions of these mechanisms. Depending on the task, motivational factors may also exert their influence. In addition, the strength of hindsight bias appears to be related to some personality traits and also to age. For example, some authors found that hindsight bias tends to increase with the tendency toward favorable self-presentation and to decrease with intelligence. Moreover, lifespan studies have shown that children and older adults show larger hindsight bias than young adults. Hindsight bias has been found in political decision-making (as well as in other applied domains). Surprisingly, attempts to overcome hindsight bias have mainly failed, whereas only a few debiasing techniques show promising results. In sum, one important conclusion is to be continuously aware of the potentially distorting influence of outcome knowledge on the evaluation of our own (or other’s) prior knowledge state.

Throughout the 20th century, structuralist and generative linguists have argued that the study of the language system (langue, competence) must be separated from the study of language use (parole, performance), but this view of language has been called into question by usage-based linguists who have argued that the structure and organization of a speaker’s linguistic knowledge is the product of language use or performance. On this account, language is seen as a dynamic system of fluid categories and flexible constraints that are constantly restructured and reorganized under the pressure of domain-general cognitive processes that are not only involved in the use of language but also in other cognitive phenomena such as vision and (joint) attention. The general goal of usage-based linguistics is to develop a framework for the analysis of the emergence of linguistic structure and meaning. In order to understand the dynamics of the language system, usage-based linguists study how languages evolve, both in history and language acquisition. One aspect that plays an important role in this approach is frequency of occurrence. As frequency strengthens the representation of linguistic elements in memory, it facilitates the activation and processing of words, categories, and constructions, which in turn can have long-lasting effects on the development and organization of the linguistic system. A second aspect that has been very prominent in the usage-based study of grammar concerns the relationship between lexical and structural knowledge. Since abstract representations of linguistic structure are derived from language users’ experience with concrete linguistic tokens, grammatical patterns are generally associated with particular lexical expressions.

Rather than being a slow, deliberative, and fully conscious process, political thinking is steeped in automaticity: that is, it is fast, relatively effortless, and often unconscious. Political and social psychologists have made great strides in measuring different components of this automaticity while pinpointing its influence on different types of citizens under a variety of social and political circumstances. There are manifold ways through which automaticity seeps into political cognition by focusing on various important domains of political decision-making, including intergroup relations, identity and information processing, and candidate evaluation. Multiple research frontiers in political science exist where automaticity can help break new conceptual and theoretical ground as it relates to people’s thinking, judgment, and evaluation of politics.

Milton Friedman and Herbert Simon introduced two opposing “schools” of thought in decision-making: the “rational actor” approach and the “cognitive approach,” respectively. Friedman argued that theories should be judged based on the validity of their predictions (“outcome validity”), whereas Simon countered that more emphasis must be placed on “process validity.” Seeking to bridge the gap between the cognitive and rational approaches, in the early 1990s Alex Mintz and colleagues developed poliheuristic theory. The theory is based on five main processing characteristics of decision-making: nonholistic search, dimension-based processing, noncompensatory decision rules, satisficing behavior, and order-sensitive search. A key premise of poliheuristic theory is its reference to the political aspects of decision making in a foreign policy context. Poliheuristic theory is related to Applied Decision Analysis (ADA), an analytic procedure which can be applied to all levels of analysis in foreign policy decision-making: the leader, the group and the coalition. As a bridge between rational and cognitive decision models, poliheuristic theory is uniquely positioned to contribute to progress in the study of world politics. Indeed, despite being relatively new to the discipline of foreign policy analysis, it has enriched our understanding of both the process of decision-making and the outcome of decisions, for example, or the diversionary use of force, international bargaining and negotiation, coalition formation, and terrorists’ decisions. A number of avenues deserve attention in future research on poliheuristic theory, in particularl the use of a more decision-theoretic dataset for investigating its basic proposition as well as more large-N methodological studies.

An extensive literature has accumulated during the past three quarters of a century on the topic of intuition in management. The beginnings of management intuition scholarship are to be found in Chester Barnard’s insightful speculations on the role and significance of logical and non-logical processes in managerial work. Barnard’s thinking impacted profoundly Herbert Simon’s foundational concept of bounded rationality, which shed much needed light on how managerial decision-making is accomplished in real-world settings by using intuition as well as analysis. In parallel, management researchers in common with scholars in a wide range of applied fields also drew on Daniel Kahneman, Amos Tversky, and colleagues’ seminal behavioral decision research and its focus on the systematic errors and biases that accrue in managers’ intuitive judgments as the result of the use of heuristics (e.g., representativeness, availability, anchoring and adjustment, and affect heuristics). In recent years management researchers have drawn on further insights from Klein and colleagues’ work in naturalistic decision-making (NDM) (e.g., the “recognition primed decision-making model,” RPD) to conceptualize managerial work as expert performance and in understanding expert-versus-novice differences using the “skill acquisition model” (SAM). In recent years managerial intuition research has alighted on the dual-process theories of Epstein, Evans, Stanovich, and others as a conceptual foundation for further theorizing and research in terms of System 1 (also referred to as Type 1) and System 2 (Type 2) processing. More recently still, research in neurology (e.g., the “somatic marker hypothesis”) and social cognitive neuroscience (e.g., the specification of complementary “reflexive (X)” and “reflective (C)” systems) has mapped the physiological and neural correlates of intuitive processing and begun to inform not only intuition research but decision research more widely in management and organization studies. These various developments have shed light on how intuitive decision-making is accomplished in managerial work across diverse management subfields including entrepreneurship, business ethics, human resources, and strategic management. More recently, scholars are turning to paradox theory and process philosophy as alternative ways of viewing the phenomenon of intuition in organizations.

The democratization of university access made possible the arrival of new university students from different backgrounds. At this time access was opened to all individuals coming from all different backgrounds. The new student population had a strong impact on the university life. Some university professors complained that although some students were talented, they could not communicate in complex scenarios. The article will focus on the theoretical principles that inspired the democratic curriculum and the psychological approach that allowed new individual cognitive perspectives and a new vision of the university population. At this time the education principles by Freire and Dewey generated an impulse for democratic education. From this framework the article will analyze the research and educational principles that inspired the Writing Across Curriculums (WAC) movement and the supplementary Writing in the Disciplines (WID). Both programs were very successful and led to the establishment of the Writing Academic Centers that since then and until now guarantee a democratic university education. These centers have fostered WAC, which developed into WID. The need to address global classrooms has inspired Writing Across the Communities, which considers race and social justice within language programs. The university scientific approach is aligned with the international organization’s objectives for the 20th century.