Anomalous State of Knowledge

2 Anomalous State of Knowledge Nicholas J. Belkin School of Communication, Information and Libraryr Studies Rutgers University, USA nick@belkin.rutgers.edu The concept of the anomalous state of knowledge (ASK) was proposed by Belkin (1977), within an explicitly communicative analysis of the fundamental problem of information science as "the effective communicationof desired information between human generator and human user" (Belkin, 1977, p.22). following Paisley and Parker (1965), Belkin understood that in the context of information science, this communication system is recipient-instigated and recipient-controlled. There exists a universe of texts that have been generated by a large number of human beings, and the actual communication begins when some person (the recipient) engages with one or more texts, thereby completing the communication systems, and terminates it when some goal has been achieved. This is termed the linguistic level of communication, at which generators produce texts that users read. At the cognitive level, the texts are understood as being representations of the conceptual states of knowledge of their generators, as modified by their purposes, value and intentional and belief structures, and knowledge of potential recipients states of knowledge. Belkin suggested that this underlying structure be considered the information associated with the next. He further proposed that the reason for initiating this communication system could be best understood at the cognitive level, as the recipient's recognition of a conceptual state of knowledge that is anomalous with respect to some goal, and the desire to resolve the anomaly. The two levels of the system are represented in Figure 2.1. By anomaly, Belkin means that the user's state of knowledge with respect to a topic is in some way inadequate with respect to the person's ability to achieve some goal (later generalized as the ability to resolve a problematic situation) (Belkin, Seeger, & Wersig, 1983). Anomaly was used explicitly to indicate that this state of inadequacy could be due not only to lack of knowledge, but many other problems, such as uncertainty as to which of several potentially relevant concepts holds in some situation. ASK has obvious relationships to other proposals in information science, such as Taylor's (1968) "unconscious need," Wersig's (1971) "problematic situation," and Dervin's (1983) "gaps," but Belkin's ASK hypothesis differs from these other proposals in that  It is an explicitly cognitive explanation of the general phenomenon.  It suggests that anomalous states could be of different types.  Some consequences of an operationalization of the concept have been tested in an empirical experiment (Belkin, 1977).  Specific means to take it into account have been proposed and tested in the understanding and design of information retrieval systems (Belkin, 1980b; Belkin, Oddy, & Brooks, 1982; Belkin & Kwasnik, 1986). Figure 2.1 The communication system of interest to information science. Note : Following "Anomalous states of knowledge as a basis for information retrieval," by N.J. Belkin,1980, Canadian Journal of Information Science,5,133-143. The general idea behind the ASK hypothesis is what was known as the cognitive viewpoint. This was succinctly explained by de Mey (1977, p.xvii): " The central point the cognitive view is that any processing of information, whether perceptual or symbolic, is mediated by a system of categories or concepts which, for the information-processing device, are a model of this world." Figure 2.1 indicates how the ASK hypothesis fits into the cognitive viewpoint. There, one can see that the communication systems is understood as interactions between different states of knowledge, in particular between the ASK and the information, the modified ASK and the general conceptual state of knowledge with respect to the topic or goal, and the problematic situation. This communication system is dynamic, in that any such interaction, by virtue of its possibility of modifying the user's image, leads to a different ASK, perhaps one closer to resolution of the problematic situation. Belkin (1980a) pointed out that under the ASK hypothesis and its implications, for information retrieval (IR) purposes, it is inappropriate to ask a person to specify that which is required to resolve an ASK. The ASK should be represented in ways that are appropriate for representing that which a person doesn't know; and therefore, the normal IR retrieval model of ranking according to best match of query to document representation should be replaced by other techniques dependent upon type of ASK. Belkin (1980b) elaborated on these ideas, laying out the general ASK hypothesis and suggesting how it could be implemented in IR systems. Combining the ASK hypothesis with Oddy's (1977) concept of IR without query formulation, Belkin, Oddy, and Brooks (1982) presented a general system design for an ASK-based IR system, and a method for eliciting and representing ASKs. The representation technique was based on ideas of associative memory and its representation from cognitive psychology, in particular those of Deese (1965), Kintsch (1974), and Kiss (1975). In brief, the technique elicited so-called "problem statements" from users, and used a distance-sensitive co-occurrence analysis of this text to generate conceptual graphs, which were understood to be ASK representations. The same technique was used on document texts, the results of which were understood to be representations of the information associated with those texts. Later, Belkin and Kwasnik (1986) used this basic representational technique to develop methods for classifying ASKs according to their structural characteristics, in such a way as to suggest different retrieval techniques according to the different structures. The ASK hypothesis has a clear relationship to information behavior in that it proposes a specific reason explaining why people engage in information-seeking behavior, and how that reason can be responded to through a person's interaction with information. Furthermore, it has been used to indicate how such interaction might best be supported through IR system design. The ASK hypothesis has also been a key element of the so-called cognitive viewpoint in information science, a turn in information science from system orientation to user orientation, which began in the mid-to late 1970s. Belkin (1990) and Ingwersen (2001) each provide evidence of the effect of this turn, and to some extent of the ASK hypothesis on theory and research in information science in general, and on information retrieval, and in the integration of information retrieval research with information behavior research in particular. Belkin,N.J.(1977).A concept of information for information science. Unpublished doctoral dissertation, University College, University of London. Belkin,N.J.(1980a). The problem of 'matching' in information retrieval. In O. Harbo & L. Kajberg (Eds), Theory and application of information research. Proceedings of the second international research forum on information science. (pp.187-197).London:Mansell. Belkin,N.J.(1980b).Anomalous states of knowledge as a basis for information retrieval.Canadian Journal of Information Science,5,133-143. Belkin,N.J.(1990). The cognitive viewpoint in information science. Journal of Information Science,16, 11-15. Belkin,N.J., & Kwasnik,B.H.(1986). Using structural representations of anomalous states of knowledge for choosing document retrieval strategies. In f. rabitti (Ed).1986-ACM conference on research and development in information retrieval. (pp.11-22).Pisa : IEI. Belkin,N.J., Oddy,R.N., & Brooks,H.M.(1982). ASK for information retrieval. Parts 1 and 2. Journal of Documentation. 38(2),61-71 ; 145-164. Belkin,N.J., Seeger,T., & Wersig,G. (1983). Distributed expert problem treatment as a model for information system analysis and design. Journal of Information Science, 5, 153-167.

Affective Load

1 Affective Load Diane Nahl Information and Computer Sciences Departement Library and Information Science Program University of Hawaii, USA nahl@hawaii.edu Information-seeking research and theory is focusing increasingly on the role of affect in information behavior (IB) and how it influences cognitive operations. Diane Nahl's research draws on the field of psychology. Following the work of soial-learning theorists such as Albert Bandura (1986), who contributed to the behavioral approach in cognitive psychology, and Erving Goffman (1974), who contributed to the behavioral approach in sociolinguistics, as well as Martin Seligman (1992) (positive psychology), Harold Garfinkle (1968) (ethnomethodology), and John Searle (1969) (speech act theory). Nahl's research on the role of effect in information behavior relates to the work of Nicholas Belkin (1980,2000), Brenda Dervin (1992), Carol Khulthau (1993), T.D. Wilson (1984, 1999, 2000), Amanda Spink (2000), Sanda Erdelez (1997), and Rosalind Picard (1997), among others. Affective load theory (ALT) is a social-behavioral perspective on the thoughtsand feelings of individuals while engaged in information behavior (IB). ALT provides empirical methods for identifying affective states of users that disrupt ongoing cognitive operations (James & Nahl, 1986). Once a disruptive affective state is identified, coping assistance services (CAS) can be provided to encourage users to mitigate discruptive states to achieve task success. ALT identifies underlying habits of thinking and feeling while engaging in information behavior, and clarifies the details of information retrieval from a user perspective. There are three essential ideas in applying social-behavioral psychology to IB : 1). The mental activity of information users, both cognitive and affective, is defined as behavior (Martin & Briggs, 1986). For instance, "thinking of a search word" or "feeling motivated to finish a task" are behaviors. Global control of the affective over the cognitive operates at general and specific levels. At the general level of control people possess motivational states such as optimism or pessimism prior to a search. At the specific level of control we experience micro-behaviors that involve search strategy such as inspecting a list, thinking of a synonym, or recalling an item that has been seen before. A search task or session involves hundreds of individual cognitive micro-behaviors, each one connected to an affective state that maintains or interrupts it (Nahl, 1997). Affective states are organized in a top-down hierarchy and can be reliably measured through concurrent self-reports about expectations, satisfactions, and acceptance during continuous cognitive activity. 2). Affective behavior initiates, maintains, and terminates cognitive behavior (Isen, Doubman & Gorgolione, 1987; Carver & Scheier, 2001). For instance, when searches lose the motivation to continue a task, they begin thinking about something else. Or, if they unexpectedly find some new information they want, they switch activity midstream. The new affective behavior interrupts and takes over the ongoing activity and continues in a new direction with new cognitive activity. This managerial or directive function of affective behavior over cognitive, makes it desirable in information environments to employ self-monitoring techniques to keep track of the affective behavior of users (Nahl, 1996, 1998). 3). Affective behavior operates within a binary-value system : on/off or positive/negative. Cognitive behavior operates through a multivalue logic. Therefore, affective behavior is measured with multiple-choice, matching or fill-in items. Content analysis and protocol analysis of concurrent verbal reports are used identify affective and cognitive behavior patterns during search tasks (Nahl, 2001). The behavioral approach to information use is attracting increasing interest among information scientists. However, sufficient attention is not given to the three essential elements outlined above. The focus has been on cognitive behavior and more recently, on how affective behavior is also important to consider. Nahl's social-behavioral theory of affective load makes explicit the need to create a methodological connection between each cognitive behavior and its affective support or control state. Affective load theory was developed by analyzing concurrent self-reports of searchers and learners in conjuction with quantitative ratings filled out by searchers while engaged in searching and problem-solving. To achieve high reliability, it is critical to obtain concurrent rather than recollected data. Nahl's ALT theory is emerging from a 20-year research program. One area of application has been to identify affective dimensions like self-efficacy and optimism that help searchers perform better. Currently ALT research focuses on how diverse affective behaviors interact to produce ab effective coping style when searchers feel challenged by uncertainty. ALT proposes that all information behavior involves affective states that provide specific goal-directionality and motivation to support cognitive activity. Affective load (AL) is operationally defined as uncertainty (U) multiplied by felt time pressure (TP). Uncertainty is defined as the combined degrees of irritation, frusration, anxiety, and rage (Nahl, 2004). AL = U (irritation + frustration + anxiety + ragel) x TP Affective load is high when people operate with ineffective cognitive behaviors. For example, cognitive ambiguity, uncertainty, or information overload attract affective behaviors that are negative and counter-productive to the searcher's goal. For instance, a search that appears to yield no relevant results after some attempts is cognitively disorienting, as represented by such thoughts as, " I'm no good at this " or " This is so frustrating! " At other times, searchers are able to engage affective coping strategies when faced with cognitive load and uncertainty. For instance, " I'll just keep going untill find something " or " I'm positive I can find what I need in another database." These verbal expressions are standard and recurrent within a population of searchers, and because they are learned cultural habits, can be termed " learned affective norms" (LANs). Negative LANs disrupt cognitive strategies, interrupt the search, and often terminate it prematurely, while positive LANs provide persistence and integration to cognitive strategies. In general, negative LANs increase AL and appear in the form of uncertainty, anxiety, frustration, low expectations, pessimism, low self-effecacy, low task completion motivation, low satisfaction, low system acceptance, and other disruptive symptoms that interfere with a positive outcome. On the other hand, positive LANs decrease AL because they provide better coping strategies to manage ambiguity and cognitive load. Support and counseling interventions can be triggered when affective load rises above a specified level. Knowledge about the affective environment of searchers will also helpful in search instruction. More research is needed on how the affective information environment of searchers impinges on their cognitive activity to strengthen information systems services and design.

SWOT Analysis

SWOT analysis : this is a strategic planning method used to evaluate the Strengths, Weakneses, Opportunities, and Threats involved in a project or in a business venture. It involves specifying the objective of the business venture or project and identifying the internal and external factors that are favorable and unfavorable to achieve that objective. SWOT analysis usually starts with defining a desired end state or objective and incorporated into the strategic planning model. SWOT and SCAN analysis, is accredited strategy for research subject, these initials usually means: 1. Strengths: attributes of the person or company that is helpful to achieving the objective(s). 2. Weaknesses: attributes of the person or company that is harmful to achieving the objective(s). 3. Opportunities: external conditions that is helpful to achieving the objective(s). 4. Threats: external conditions which could do damage to the objective(s).