“Each graduate of the Master of Library and Information Science program is able to... describe the fundamental concepts of information-seeking behaviors.”
Introduction
Learning is at the heart of information seeking, which usually encompasses the idea of search. For information professionals, we not only look for information as part of our life-long learning objectives, but we must understand how humans seek for information if we are to help them with their own learning objectives. The search for information is a process that people engage in with the purpose of changing their own state of knowledge (Marchionini, 1995, chapter 1). There is also a distinction made between information seeking and information retrieval, the former of which is human-centric while the latter can be applied to computers as well as humans. This distinction is important as many of the first computerized information retrieval systems were based on the idea that an information need could be directly mapped to a query which could, in turn, be mapped to set of documents represented by query terms. As many information seeking models attempt to show, humans don’t actually seek information this way. Unless a person already knows the exact query terms she/he needs in order to retrieve the relevant documents, an information seeker will probably spend many iterations trying different query terms until they find the right combination of terms.
While there are many information seeking theories and models, here I cover three important information seeking models including Bates’ Berry Picking model, Dervin’s Sense-making model, and Kuhlthau’s Information Search Process model. In addition, information seeking strategies and tactics are covered, as they are also important aspects of information seeking in general.
Information Seeking Theories
There are several information seeking theories and models that can help us understand how people look for information so we are better able to help them in their search for knowledge. The classic model of information retrieval that was in use for 25 years by the time Marcia Bates published her “Berrypicking” model is one of a “match” between a human-formulated query and a machine or system representation of documents. Figure 1, taken from https://pages.gseis.ucla.edu/faculty/bates/berrypicking.html, shows this matching function.
This made sense in a time when computers, if they were used at all, took up whole rooms and had about as much memory as a 32nd of a FitBit. The cost and lack of computer space meant that mapping information needs of the user to a well formed query made sense. But now that the cost and space constraints have eased up by quite a lot, the opportunity to implement more human friendly systems exists. Understanding these models helps us to design a much more user friendly information retrieval systems based on information seeking behaviors.
Bates BerryPicking Model
“A query is satisfied not by a single final retrieved set, but by a series of selections of individual references and bits of information at each stage of the ever-modifying search. A bit-at-a-time retrieval of this sort is here called berrypicking” (Bates, 1989).
Marcia Bates was probably the first researcher to point out the inadequacies of the information retrieval model as a way to describe how people should seek information. She is also instrumental in shaping the field of information seeking behaviors (Morville, 2005). In contrast to Figure 1, Figure 2 (taken from (Bates, 1989)) doesn’t show a straight-forward linear process for information seeking. Instead what it shows is that the information search actually evolves over time and, instead of the idea that relevant documents would congregate together, they tend to be scattered (like berries). So, for example, when I went to look for original work by Dervin (see below) I was unable to access any of her original work (not covered by King Library subscription to Emerald) so I needed to refine (evolve) my query to include work others did that built upon hers. This required me to look at several other researchers’ descriptions of her work so I could piece together a coherent picture of her original model. She also describes a series of strategies such as footnote chasing, area scanning, searching on citation, subject, and author, which is covered in the section on information seeking strategies below.
Information Search Strategies
An information search strategy is a plan for the entire search (Bates, 1979). Bates defined six different search strategies that information professionals should be aware of in order to provide the appropriate help and tools to support these strategies. The first strategy is called “Footnote chasing” (or backward chaining) in which the searcher uses the footnotes encountered in articles and books to find further information on the topic of interest. This causes the information seeker to move backwards through reference lists. The next strategy is called “Citation searching” (or forward chaining) which involves finding those works that cite the current work and looking at those. “Journal run” is another strategy and in it, the seeker finds the central or most important journal in an area of interest and searches through every issue of that journal from the 1st issue to the most current. If that journal covers the searcher’s interest, then a great deal of good information about the topic can be found using this strategy. Another strategy is called “Area scanning” wherein the information seeker browses materials that are physically co-located in the same area as materials that have already been determined to be of interest. “Subject searches in bibliographies and abstracting and indexing (A&I) services” is another information seeking strategy. This basically means that information seekers use these tools to find information because they are arranged by subject and if a subject can be mapped to the user’s topic, they can search for information using subject descriptions. Finally, “Author searching” is a strategy that is similar to subject search except that it may be more efficient to search on an author known to be an expert on the subject of which the information seeker is interested.
Understanding that information seekers will use these strategies can inform the way we support them as information professionals. For example, we can make searching by author or subject equally easy through systems design. The ability to hyperlink references for digital copies of articles is another example of a tool that would support some search strategies.
Information Search Tactics
An information tactic is the next step in the search strategy or a move that is made to further a search. Information search tactics, as opposed to information seeking behaviors, are designed to help experienced searchers, such as librarians, during the search process. It is important for information professionals to understand these tactics as it helps them to provide more accurate search results for their patrons. Marcia Bates defined 29 such tactics in her seminal paper, “Information Search Tactics” (Bates, 1979). These tactics help for both bibliographic and reference searches that are performed both manually and with on-line systems. These tactics are classified into four different types: Monitoring tactics to help keep the search on track, file structure tactics that help with understanding the information organization’s file structure, search formulation tactics that help with formulating the search, and term tactics that help with determining which terms or revision of terms are needed during a search. As librarians, we should be familiar with the 29 search tactics because whether we are helping patrons to find information or designing systems to support information seeking, implementing these tactics will save time and ultimately frustration on everybody’s part when the information needed is found quickly.
Dervin’s Model
Dr. Brenda Dervin was one of the first researchers to point out that the formal systems people used for getting information frequently failed. She supported what was considered a different way of thinking about and studying information seeking (Case, 2008). Her model or theory of human centered information seeking is generally referred to as Sense-making because it is based on the need for people to make sense of the world. “The bottom-line goal of Sense making from its inception has been to find out what users –audiences, customers, patients, clients, patrons, employees – ”really” think, feel, want, dream.” (Dervin, 1998). Figure 3, taken from Wikipedia, is a graphical representation of the model. Sense making uses the metaphor of humans traveling through space and time. They come out of situations with a history, come to new situations and, when facing gaps, they build bridges across those gaps. They then evaluate outcomes and move on.
Figure3: Dervin Model – Taken from: https://en.wikipedia.org/wiki/Brenda_Dervin#/media/File:P269fig5.jpg
The situation in space-time is the context in which the information seeker finds herself/himself wherein a question or problem needs to be resolved. The gap is the distance between where the person is and where they want to be (Rowley & Hartley, 2008, chapter 4). The ‘gap’ is where the real story in sense making is; where “the creating, seeking, using and rejecting of information and knowledge” occurs (Dervin, 1998). The bridge is how the user gets over the gap and the outcome is result of their “sense-making” journey.
What was revolutionary about Dervin’s ideas was that people’s sense making changes over space and time and that these changes mean that we have to design services in a way that supports the “person-in-situation” and to not assume that all users always seek information in the same ways because they might not seek information in the same way for each instance themselves. In addition, “Sense-making questioning” tries to stay away from the use of nouns and ask questions like: “What happened that brought you here? What question are you trying to answer? What help would you like? If I was able to help, what would you do with it (Dervin, 1998)?”
Kuhlthau’s Model
When people search for information, the search process normally begins with a vague idea of a need. As the process continues, the search for information becomes more narrow and focused (Rubin, 2010, chapter 7). Kuhlthau’s model of six stages, is known as the Information Search Process (ISP). Kuhtthau’s model covers affective (feelings) and cognitive learning and shows us that feelings have an effect on the outcome of information seeking (Grassian and Kaplowitz, 2009, chapter 4). It also gives us a way to break the information seeking process into a series of chunks that can each be targeted by techniques designed to help the learner/seeker in her/his search. In addition, the model covers actions or tasks appropriate to each stage in the model. Table 1 shows each of stages along with the feelings and actions associated with each stage.
Table 1: Information search process (ISP). From Kuhlthau, 1991.
During the “initiation,” stage a person is cognizant of a need for knowledge or understanding and feels uncertain or apprehensive. Thoughts during initiation may be general or vague and centered on thinking about the problem and trying to figure out if the problem can be related to prior experience or knowledge. Associated actions include discussing possible topics and approaches. The task normally seen in this stage is simply to recognize that information is needed. Feelings in the “selection” stage can be optimistic as the task becomes the identification and selection of the general topic that will be examined. When looking at possible topics, thoughts are focused on comparing topics against criteria such as personal interest, assignment requirements, usability of information, and available time. The topic with the most potential for success is chosen. Some of the typical actions that occur during this stage include talking to others, preliminary searches of available information and possibly looking at related topics. If the selection stage takes longer than expected, anxiety may set in.
The “exploration” stage is usually accompanied by feelings of confusion, uncertainty, and doubt. During this stage, information on the general topic is further investigated in order to gain a better understanding. At this point, thoughts are focused on getting well-enough informed on the topic to allow a focus to emerge. The information seeker may not be able to state exactly what information is needed yet and this is part of why the feelings of confusion, uncertainty, and doubt arise. The actions typically seen during this stage include finding information on the general topic, reading to get informed, and integrating new information into what is already known. This is the point where information seekers may become discouraged and give up. The next stage is the ‘Formulation” stage. Feelings of uncertainty, confusion, and doubt decrease and confidence increases and it is possible to build a focus from the information gathered by this point. The thoughts revolve around finding and selecting ideas from the information that help clarify a focused perspective of the topic.
The next stage is the “Collection” stage where the interactions between the information seeker and the information system are the most effective. The task is to get as much information about the focused topic as possible and thoughts may be focused on defining, extending, and supporting that focus. Confidence rises as uncertainty decreases even more and interest in the project deepens. In the last stage, “Presentation” feelings of relief and of satisfaction if the search has gone well or disappointment if it has not, are common. Thoughts focus on finishing the search and being able to merge what was learned into a personal construct of the topic. The task associated with this stage is to complete the search and prepare to use the learned information in some way.
What makes Kuhlthau’s work so impressive is the amount of research she has done with the model. A study done in 1988 helped her to cement her ideas about the model and is actually based on the work of cognitive psychologist George A. Kelly’s theory of personal constructs. The idea is that a construct enables us to predict outcomes, and that, based on our predictions, we will behave in a certain way. If it turns out we didn’t predict correctly, our construct is reconsidered, but if we were correct, the construct is validated. We change our behavior as a direct response to a change in our personal constructs (Kuhlthau, 1988).
The importance of this model is that it allows us, as information professionals to design tools and interventions that may help people during the information seeking process. Through strategies like charting, conversing, composing, we can help make the process easier (Kuhlthau, 1994). Charting lets the person know what to expect during each stage of the process. So, for example, when they reach the exploration stage, they may not give up, knowing that the stage is temporary and will soon be followed by a stage in which they will be much more confident. Conversation allows the information seeker to get the librarian involved. The librarian can listen to the patron as they bounce ideas back and forth and this can help the patron to get a better focus on the topic. Composing is normally thought of as the last aspect of information seeking and typically involves “getting things down on paper” for later use and presentation. Tools, such as journaling, are considered powerful for this aspect of information seeking.
Information Seeking Theories & Models
Models and theories of information seeking are important for us to understand how people try and satisfy their information needs. If we also understand the common strategies and tactics that people employ while actively seeking information, we can more concretely define the types of tools and services needed to support those models. Taken together, these models, strategies, and tactics help us, as information professionals to provide the best service we can because we understand how people look for information. Whether we are at the reference desk, roaming the library, or building systems, we can provide our patrons help in a way that makes sense to them, is comfortable and familiar, and above all, is able to help them integrate what they want to know with what they already know.
Coursework & Work Experience
I have taken 3 courses in the MLIS program that have helped me with this competency: INFO-200, INFO-250, and INFO 287: Seminar in Information Science — Virtual Environments: Immersive Learning for Libraries and Archives. Information needs and seeking behaviors was covered as part of the coursework of INFO-200 and discussion was required as part of the Information Services unit of the course. In INFO-250, we were required to conduct an information needs assessment in which I anticipated the information that would be needed by participants in the learning modules. The information needs assessment constitutes the first of the evidence I will present in order to demonstrate my ability determine what information would be expected by information seekers. For the INFO-287, I looked at the information needs of the people I designed the exhibit for in order to determine the types of information I would include in the exhibit. In addition to the courses I have taken through the MLIS program, I have experience with determining the information behaviors of programmers while trying to find and fix software programming bugs as well as other software-related tasks. As part of this research I was able to recommend tools for use by programmers that specifically addressed their information needs. The evidence I submit here are two publications on this work. One focuses on the information seeking behaviors while the other focuses on the tools needed to help with those information needs.
Evidence
The first piece of evidence is the needs assessment I prepared for my INFO-250 course in the summer of 2013. The evidence can be found on the evidence page and is called LIBR_250-11_Marie_Vans_Learning_Activity_1_Summer_2013.docx. On page 7 of this document under “Needs Assessment” I explain who my learners are and what they can be expected to know before starting the learning module. I am very specific about the types of related experiences they might already have and what they need to know by the end of the module based on the learning objectives of the course. I also specifically state where all the information will come from and how the information can be used by the learners in order to integrate the knowledge into previously acquired knowledge. A needs assessment that anticipates the needs of information seekers helps to speed up the seeking process and alleviate some of the more unpleasant feelings like confusion, frustration, and doubt. While this evidence is not directly related to information seeking in a library situation, it does show I am aware of the need to foresee the needs of patrons based on the types of information for which they might be looking.
The second piece of evidence is a paper I wrote in 1999 after completing my Ph.D. It can be downloaded from the evidence page and is called Program Understanding behavior during.pdf. This paper, was published in the International Journal of Human-Computer Studies (Vans et. al., 1999), and discusses, among other things, the information needs displayed by programmers during observed corrective maintenance (debugging) sessions. Table 13 in the paper shows the type of information four subjects searched for during those sessions. Interestingly, the types of information sought was highly dependent on the expertise and the accumulated domain knowledge of the subjects. I believe this paper demonstrates my ability to study information seeking behaviors.
The final piece of evidence is another paper I wrote much earlier as a Masters student. The evidence is called From Code understanding needs to reverse.pdf and can be found on the evidence page. This article, which appeared in the CASE’93 proceedings (von Mayrhauser and Vans, 1993), not only looked at the information needs of programmers attempting to understand code they did not originally write but also what tools could be used to address those information needs. The software engineers studied for this paper are not the same as those for the previous evidence provided above. Table 4 in the paper shows tasks involved in the information need and what a tool that addresses that need would look like, if it didn’t already exist. So for example when a programmer is trying to get a high—level understanding of the software by determining the most frequently used functions and routines, the information need is for the total number of times each function is called in the program. The tool capability in this case is one that can peruse the code and present the programmer with a list of all functions and the number of times each one is called. This publication shows my ability to take the information seeking behavior all the way to a recommendation on how to support the seeking process with automatic tools.
Conclusions
My knowledge of information seeking behaviors gained through learning in my MLIS course as well as through direct observation during the course of my computer science Master’s and Ph.D. degrees has prepared me for this competency. One area of increasing importance for librarians and other information professionals is in the area of information architecture. A highly connected world through the internet means that we will increasingly be putting information out that will be searchable by anyone in world. We need to be very cognizant of information behaviors if we want that information to be useful as well as findable. As part of the effort to make information available, we need to build our on-line presence in the form of websites, blogs, and other on-line tools with the information seeking models in mind. For example, users who want to both search and browse your site, will need to have a “berry-picking” model supported (Morville and Rosenfeld, 2007). Search strategies should also be supported where it makes sense. As mentioned previously, the ability to forward or backward chain through a series of references is a powerful and efficient method for finding related materials quickly. I believe with the combination of my coursework and other degrees, I am well prepared to help information seekers find the information they need either face-to-face in the same physical location or as a technical designer and implementer of tools created to help with specific information needs.
References
Bates, M. J. (1989). The design of browsing and berrypicking techniques for the online search interface. Online review, 13(5), 407-424.
Bates, M.J. (1979). Information search tactics. Journal of the American Society for information Science, 30(4), 205-214.
Case, D.O. (2008) Information seeking. In The Portable MLIS: Insights from the Experts, Haycock, K. and Sheldon B.E., eds. Libraries Unlimited, Westport CT.
Dervin, B. (1998). Sense-making theory and practice: an overview of user interests in knowledge seeking and use. Journal of knowledge management, 2(2), 36-46.
Grassian E.S. and Kaplowitz, J.R. (2009) Information literacy instruction: Theory and practice, 2nd edition, pp. 35-41. Neal-Schuman Publishers, Inc. New York, NY.
Kuhlthau, C. C. (1994). Impact of the information search process model on library-services. RQ, 34(1), 21-26.
Kuhlthau, C. C. (1991). Inside the search process: Information seeking from the user's perspective. Journal of the American society for information science, 42(5), 361.
Kuhlthau, C. C. (1988). Developing a model of the library search process: Cognitive and affective aspects. RQ, 232-242.
Marchionini, G. (1995). Information seeking in electronics environments. Cambridge University Press, Cambridge, UK.
Morville, P. and Rosenfeld, L.(2007). Information architecture. O’Reilly Media, Inc. Sebastopol, CA.
Morville, P. (2005). Ambient findability. O’Reilly Media, Inc. Sebastopol, CA.
Rowley, J. and Hartley, R. (2008). Organizing knowledge: An introduction to managing access to information. Ashgate Publishing Limited, Hampshire, U.K.
Rubin, R.E. (2010). Foundations of library and information science, 3rd edition. Neal-Schuman Publishers, Inc. New York, NY.
Vans, A. M., von Mayrhauser, A., and Somlo, G. (1999). Program understanding behavior during corrective maintenance of large-scale software. International Journal of Human-Computer Studies, 51(1), 31-70.
von Mayrhauser, A., and Vans, A. M. (1993). From code understanding needs to reverse engineering tool capabilities. In Computer-Aided Software Engineering, 1993. CASE'93., Proceeding of the Sixth International Workshop on (pp. 230-239). IEEE.