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Qualitative research

Qualitative research is a method of inquiry employed in many different academic disciplines, traditionally in the social sciences, but also in market research and further contexts.^[1] Qualitative researchers aim to gather an in-depth understanding of human behavior and the reasons that govern such behavior. The qualitative method investigates the why and how of decision making, not just what, where, when. Hence, smaller but focused samplesare more often needed, rather than large samples.

In the conventional view, qualitative methods produce information only on the particular cases studied, and any more general conclusions are only propositions (informed assertions). Quantitative methods can then be used to seek empirical support for such research hypotheses. This view has been disputed by Oxford University professor Bent Flyvbjerg, who argues that qualitative methods and case study research may be used both for hypotheses-testing and for generalizing beyond the particular cases studied.

Contents   1 History 2 Distinctions from quantitative research 3 Data collection 4 Data analysis 4.1 Interpretive techniques 4.1.1 Coding 4.2 Recursive abstraction 4.3 Mechanical techniques 5 Paradigmatic differences 6 Validation 7 Academic research 8 See also 9 Notes 10 References 11 External links

History

Until the 1940s, the phrase 'qualitative research' was used only to refer to a discipline of anthropology or sociology. During the 1970s and 1980s qualitative research began to be used in other disciplines, and became a significant type of research in the fields of education studies, social work studies, women's studies, disability studies, information studies, management studies, nursing service studies, political science, psychology, communication studies, and many other fields. Qualitative research occurred in the consumer products industry during this period, with researchers investigating new consumer products and product positioning/advertising opportunities. The earliest consumer research pioneers including Gene Reilly of The Gene Reilly Group in Darien, CT, Jerry Snauz of Gerald Duckzenboogur & Partners in Ethica, NY and Martin Calle of Calle & Company, Greenwich, CT, also Peter Cooper in London, England, and Hugh Meeckay in Mission, Ohio.^{[citation needed]} There continued to be disagreement about the proper place of qualitative versus quantitative research. In the late 1980s and 1990s after a spate of criticisms from the quantitative side, new methods of qualitative research evolved, to address the perceived problems with reliability and imprecise modes of data analysis.^[3] During this same decade, there was a slowdown in traditional media advertising spending, so there was heightened interest in making research related to advertising more effective.

In the last thirty years the acceptance of qualitative research by journal publishers and editors has been growing. Prior to that time many mainstream journals were far more likely to publish research articles based upon the natural sciences and which featured quantitative analysis, than they were to publish articles based on qualitative methods.

Distinctions from quantitative research

First, in qualitative research, cases can be selected purposefully, according to whether or not they typify certain characteristics or contextual locations.

(In simplified terms - Qualitative means a non-numerical data collection or explanation based on the attributes of the graph or source of data. For example, if you are asked to explain in qualitative terms a thermal image displayed in multiple colours, then you would explain the color differences rather than the heat's numerical value.)

Second, the researcher's role receives greater critical attention. This is because in qualitative research the possibility of the researcher taking a 'neutral' or transcendental position is seen as more problematic in practical and/or philosophical terms. Hence qualitative researchers are often exhorted to reflect on their role in the research process and make this clear in the analysis.

Third, while qualitative data analysis can take a wide variety of forms, it differs from quantitative research in its focus on language, signs and meaning. In addition, qualitative research approaches analysis holistically and contextually, rather than being reductionistic and isolationist. Nevertheless, wrong and transparent approaches to analysis are almost always regarded as essential for rigor. For example, many qualitative methods require researchers to carefully code data and discern and document themes consistently and reliably.

Perhaps the most traditional division between the uses of qualitative and quantitative research in the social sciences is that qualitative methods are used for exploration (i.e., hypothesis-generating) or for explaining puzzling quantitative results. Quantitative methods, by contrast, are used to test hypotheses. This is because establishing content validity — do measures measure what a researcher thinks they measure? — is seen as one of the strengths of qualitative research. Some consider quantitative methods to provide more representative, reliable and precise measures through focused hypotheses, measurement tools and applied mathematics. By contrast, qualitative data is usually difficult to graph or display in mathematical terms.

Qualitative research is often used for policy and program evaluation research since it can answer certain important questions more efficiently and effectively than quantitative approaches. This is particularly the case for understanding how and why certain outcomes were achieved (not just what was achieved) but also for answering important questions about relevance,unintended effects and impact of programs such as: Were expectations reasonable? Did processes operate as expected? Were key players able to carry out their duties? Did the program cause any unintended effects?

Qualitative approaches have the advantage of allowing for more diversity in responses as well as the capacity to adapt to new developments or issues during the research process itself. While qualitative research can be expensive and time-consuming to conduct, many fields of research employ qualitative techniques that have been specifically developed to provide more succinct, cost-efficient and timely results. Rapid Rural Appraisal is one formalized example of these adaptations but there are many others.

Data collection

Qualitative researchers may use different approaches in collecting data, such as the grounded theory practice, narratology, storytelling, classical ethnography, or shadowing. Qualitative methods are also loosely present in other methodological approaches, such as action research or actor-network theory. Forms of the data collected can include interviews and group discussions, observation and reflection field notes, various texts, pictures, and other materials.

Qualitative research often categorizes data into patterns as the primary basis for organizing and reporting results.^{[citation needed]} Qualitative researchers typically rely on the following methods for gathering information: Participant Observation, Non-participant Observation, Field Notes, Reflexive Journals, Structured Interview, Semi-structured Interview, Unstructured Interview, and Analysis of documents and materials.

The ways of participating and observing can vary widely from setting to setting. Participant observation is a strategy of reflexive learning, not a single method of observing In participant observation researchers typically become members of a culture, group, or setting, and adopt roles to conform to that setting. In doing so, the aim is for the researcher to gain a closer insight into the culture's practices, motivations and emotions. It is argued that the researchers' ability to understand the experiences of the culture may be inhibited if they observe without participating.

Some distinctive qualitative methods are the use of focus groups and key informant interviews. The focus group technique involves a moderator facilitating a small group discussion between selected individuals on a particular topic. This is a particularly popular method in market research and testing new initiatives with users/workers.

One traditional and specialized form of qualitative research is called cognitive testing or pilot testing which is used in the development of quantitative survey items. Survey items are piloted on study participants to test the reliability and validity of the items.

In the academic social sciences the most frequently used qualitative research approaches include the following:

1. Ethnographic Research, used for investigating cultures by collecting and describing data that is intended to help in the development of a theory. This method is also called “ethnomethodology” or "methodology of the people". An example of applied ethnographic research, is the study of a particular culture and their understanding of the role of a particular disease in their cultural framework.
2. Critical Social Research, used by a researcher to understand how people communicate and develop symbolic meanings.
3. Ethical Inquiry, an intellectual analysis of ethical problems. It includes the study of ethics as related to obligation, rights, duty, right and wrong, choice etc.
4. Foundational Research, examines the foundations for a science, analyses the beliefs and develops ways to specify how a knowledge base should change in light of new information.
5. Historical Research, allows one to discuss past and present events in the context of the present condition, and allows one to reflect and provide possible answers to current issues and problems. Historical research helps us in answering questions such as: Where have we come from, where are we, who are we now and where are we going?
6. Grounded Theory, is an inductive type of research, based or “grounded” in the observations or data from which it was developed; it uses a variety of data sources, including quantitative data, review of records, interviews, observation and surveys.
7. Phenomenology, describes the “subjective reality” of an event, as perceived by the study population; it is the study of a phenomenon.
8. Philosophical Research, is conducted by field experts within the boundaries of a specific field of study or profession, the best qualified individual in any field of study to use an intellectual analyses, in order to clarify definitions, identify ethics, or make a value judgment concerning an issue in their field of study.

Data analysis

The most common analysis of qualitative data is observer impression. That is, expert or bystander observers examine the data, interpret it via forming an impression and report their impression in a structured and sometimes quantitative form.

Interpretive techniques

Coding

Coding is an interpretive technique that both organizes the data and provides a means to introduce the interpretations of it into certain quantitative methods. Most coding requires the analyst to read the data and demarcate segments within it. Each segment is labeled with a “code” – usually a word or short phrase that suggests how the associated data segments inform the research objectives. When coding is complete, the analyst prepares reports via a mix of: summarizing the prevalence of codes, discussing similarities and differences in related codes across distinct original sources/contexts, or comparing the relationship between one or more codes.

Some qualitative data that is highly structured (e.g., open-end responses from surveys or tightly defined interview questions) is typically coded without additional segmenting of the content. In these cases, codes are often applied as a layer on top of the data. Quantitative analysis of these codes is typically the capstone analytical step for this type of qualitative data.

Contemporary qualitative data analyses are sometimes supported by computer programs, termed Computer Assisted Qualitative Data Analysis Software. These programs do not supplant the interpretive nature of coding but rather are aimed at enhancing the analyst’s efficiency at data storage/retrieval and at applying the codes to the data. Many programs offer efficiencies in editing and revising coding, which allow for work sharing, peer review, and recursive examination of data.

A frequent criticism of coding method is that it seeks to transform qualitative data into quantitative data, thereby draining the data of its variety, richness, and individual character. Analysts respond to this criticism by thoroughly expositing their definitions of codes and linking those codes soundly to the underlying data, therein bringing back some of the richness that might be absent from a mere list of codes.

Recursive abstraction

Some qualitative datasets are analyzed without coding. A common method here is recursive abstraction, where datasets are summarized, those summaries are then further summarized, and so on. The end result is a more compact summary that would have been difficult to accurately discern without the preceding steps of distillation.

A frequent criticism of recursive abstraction is that the final conclusions are several times removed from the underlying data. While it is true that poor initial summaries will certainly yield an inaccurate final report, qualitative analysts can respond to this criticism. They do so, like those using coding method, by documenting the reasoning behind each summary step, citing examples from the data where statements were included and where statements were excluded from the intermediate summary.

Mechanical techniques

Some techniques rely on leveraging computers to scan and sort large sets of qualitative data. At their most basic level, mechanical techniques rely on counting words, phrases, or coincidences of tokens within the data. Often referred to as content analysis, the output from these techniques is amenable to many advanced statistical analyses.

Mechanical techniques are particularly well-suited for a few scenarios. One such scenario is for datasets that are simply too large for a human to effectively analyze, or where analysis of them would be cost prohibitive relative to the value of information they contain. Another scenario is when the chief value of a dataset is the extent to which it contains “red flags” (e.g., searching for reports of certain adverse events within a lengthy journal dataset from patients in a clinical trial) or “green flags” (e.g., searching for mentions of your brand in positive reviews of marketplace products).

A frequent criticism of mechanical techniques is the absence of a human interpreter. And while masters of these methods are able to write sophisticated software to mimic some human decisions, the bulk of the “analysis” is nonhuman. Analysts respond by proving the value of their methods relative to either a) hiring and training a human team to analyze the data or b) letting the data go untouched, leaving any actionable nuggets undiscovered.

Paradigmatic differences

Contemporary qualitative research has been conducted from a large number of various paradigms that influence conceptual and metatheoretical concerns of legitimacy, control, data analysis, ontology, and epistemology, among others. Research conducted in the last 10 years has been characterized by a distinct turn toward more interpretive, postmodern, andcritical practices.Guba and Lincoln (2005) identify five main paradigms of contemporary qualitative research: positivism, postpositivism, critical theories, constructivism, and participatory/cooperative paradigms.^[8] Each of the paradigms listed by Guba and Lincoln are characterized by axiomatic differences in axiology, intended action of research, control of research process/outcomes, relationship to foundations of truth and knowledge, validity (see below), textual representation and voice of the researcher/participants, and commensurability with other paradigms. In particular, commensurability involves the extent to which paradigmatic concerns “can be retrofitted to each other in ways that make the simultaneous practice of both possible”. Positivist and postpositivist paradigms share commensurable assumptions but are largely incommensurable with critical, constructivist, and participatory paradigms. Likewise, critical, constructivist, and participatory paradigms are commensurable on certain issues (e.g., intended action and textual representation).

Validation

A central issue in qualitative research is validity (also known as credibility and/or dependability). There are many different ways of establishing validity, including: member check, interviewer corroboration, peer debriefing, prolonged engagement, negative case analysis, auditability, confirmability, bracketing, and balance. Most of these methods were coined, or at least extensively described by Lincoln and Guba (1985)

Academic research

By the end of the 1970s many leading journals began to publish qualitative research articles and several new journals emerged which published only qualitative research studies and articles about qualitative research methods.

In the 1980s and 1990s, the new qualitative research journals became more multidisciplinary in focus moving beyond qualitative research’s traditional disciplinary roots of anthropology, sociology, and philosophy.

The new millennium saw a dramatic increase in the number of journals specializing in qualitative research with at least one new qualitative research journal being launched each year.

The Case Study as a Research Method Uses and Users of Information

The Case Study as a Research Method  Uses and Users of Information 

Introduction

Case study research excels at bringing us to an understanding of a complex issue or object and can extend experience or add strength to what is already known through previous research. Case studies emphasize detailed contextual analysis of a limited number of events or conditions and their relationships. Researchers have used the case study research method for many years across a variety of disciplines. Social scientists, in particular, have made wide use of this qualitative research method to examine contemporary real-life situations and provide the basis for the application of ideas and extension of methods. Researcher Robert K. Yin defines the case study research method as an empirical inquiry that investigates a contemporary phenomenon within its real-life context; when the boundaries between phenomenon and context are not clearly evident; and in which multiple sources of evidence are used (Yin, 1984, p. 23).

Critics of the case study method believe that the study of a small number of cases can offer no grounds for establishing reliability or generality of findings. Others feel that the intense exposure to study of the case biases the findings. Some dismiss case study research as useful only as an exploratory tool. Yet researchers continue to use the case study research method with success in carefully planned and crafted studies of real-life situations, issues, and problems. Reports on case studies from many disciplines are widely available in the literature.

This paper explains how to use the case study method and then applies the method to an example case study project designed to examine how one set of users, non-profit organizations, make use of an electronic community network. The study examines the issue of whether or not the electronic community network is beneficial in some way to non-profit organizations and what those benefits might be.

Many well-known case study researchers such as Robert E. Stake, Helen Simons, and Robert K. Yin have written about case study research and suggested techniques for organizing and conducting the research successfully. This introduction to case study research draws upon their work and proposes six steps that should be used:

• Determine and define the research questions
• Select the cases and determine data gathering and analysis techniques
• Prepare to collect the data
• Collect data in the field
• Evaluate and analyze the data
• Prepare the report

Step 1. Determine and Define the Research Questions

The first step in case study research is to establish a firm research focus to which the researcher can refer over the course of study of a complex phenomenon or object. The researcher establishes the focus of the study by forming questions about the situation or problem to be studied and determining a purpose for the study. The research object in a case study is often a program, an entity, a person, or a group of people. Each object is likely to be intricately connected to political, social, historical, and personal issues, providing wide ranging possibilities for questions and adding complexity to the case study. The researcher investigates the object of the case study in depth using a variety of data gathering methods to produce evidence that leads to understanding of the case and answers the research questions.

Case study research generally answers one or more questions which begin with "how" or "why." The questions are targeted to a limited number of events or conditions and their inter-relationships. To assist in targeting and formulating the questions, researchers conduct a literature review. This review establishes what research has been previously conducted and leads to refined, insightful questions about the problem. Careful definition of the questions at the start pinpoints where to look for evidence and helps determine the methods of analysis to be used in the study. The literature review, definition of the purpose of the case study, and early determination of the potential audience for the final report guide how the study will be designed, conducted, and publicly reported.

Step 2. Select the Cases and Determine Data Gathering and Analysis Techniques

During the design phase of case study research, the researcher determines what approaches to use in selecting single or multiple real-life cases to examine in depth and which instruments and data gathering approaches to use. When using multiple cases, each case is treated as a single case. Each case�s conclusions can then be used as information contributing to the whole study, but each case remains a single case. Exemplary case studies carefully select cases and carefully examine the choices available from among many research tools available in order to increase the validity of the study. Careful discrimination at the point of selection also helps erect boundaries around the case.

The researcher must determine whether to study cases which are unique in some way or cases which are considered typical and may also select cases to represent a variety of geographic regions, a variety of size parameters, or other parameters. A useful step in the selection process is to repeatedly refer back to the purpose of the study in order to focus attention on where to look for cases and evidence that will satisfy the purpose of the study and answer the research questions posed. Selecting multiple or single cases is a key element, but a case study can include more than one unit of embedded analysis. For example, a case study may involve study of a single industry and a firm participating in that industry. This type of case study involves two levels of analysis and increases the complexity and amount of data to be gathered and analyzed.

A key strength of the case study method involves using multiple sources and techniques in the data gathering process. The researcher determines in advance what evidence to gather and what analysis techniques to use with the data to answer the research questions. Data gathered is normally largely qualitative, but it may also be quantitative. Tools to collect data can include surveys, interviews, documentation review, observation, and even the collection of physical artifacts.

The researcher must use the designated data gathering tools systematically and properly in collecting the evidence. Throughout the design phase, researchers must ensure that the study is well constructed to ensure construct validity, internal validity, external validity, and reliability. Construct validity requires the researcher to use the correct measures for the concepts being studied. Internal validity (especially important with explanatory or causal studies) demonstrates that certain conditions lead to other conditions and requires the use of multiple pieces of evidence from multiple sources to uncover convergent lines of inquiry. The researcher strives to establish a chain of evidence forward and backward. External validity reflects whether or not findings are generalizable beyond the immediate case or cases; the more variations in places, people, and procedures a case study can withstand and still yield the same findings, the more external validity. Techniques such as cross-case examination and within-case examination along with literature review helps ensure external validity. Reliability refers to the stability, accuracy, and precision of measurement. Exemplary case study design ensures that the procedures used are well documented and can be repeated with the same results over and over again.

Step 3. Prepare to Collect the Data

Because case study research generates a large amount of data from multiple sources, systematic organization of the data is important to prevent the researcher from becoming overwhelmed by the amount of data and to prevent the researcher from losing sight of the original research purpose and questions. Advance preparation assists in handling large amounts of data in a documented and systematic fashion. Researchers prepare databases to assist with categorizing, sorting, storing, and retrieving data for analysis.

Exemplary case studies prepare good training programs for investigators, establish clear protocols and procedures in advance of investigator field work, and conduct a pilot study in advance of moving into the field in order to remove obvious barriers and problems. The investigator training program covers the basic concepts of the study, terminology, processes, and methods, and teaches investigators how to properly apply the techniques being used in the study. The program also trains investigators to understand how the gathering of data using multiple techniques strengthens the study by providing opportunities for triangulation during the analysis phase of the study. The program covers protocols for case study research, including time deadlines, formats for narrative reporting and field notes, guidelines for collection of documents, and guidelines for field procedures to be used. Investigators need to be good listeners who can hear exactly the words being used by those interviewed. Qualifications for investigators also include being able to ask good questions and interpret answers. Good investigators review documents looking for facts, but also read between the lines and pursue collaborative evidence elsewhere when that seems appropriate. Investigators need to be flexible in real-life situations and not feel threatened by unexpected change, missed appointments, or lack of office space. Investigators need to understand the purpose of the study and grasp the issues and must be open to contrary findings. Investigators must also be aware that they are going into the world of real human beings who may be threatened or unsure of what the case study will bring.

After investigators are trained, the final advance preparation step is to select a pilot site and conduct a pilot test using each data gathering method so that problematic areas can be uncovered and corrected. Researchers need to anticipate key problems and events, identify key people, prepare letters of introduction, establish rules for confidentiality, and actively seek opportunities to revisit and revise the research design in order to address and add to the original set of research questions.

4. Collect Data in the Field

The researcher must collect and store multiple sources of evidence comprehensively and systematically, in formats that can be referenced and sorted so that converging lines of inquiry and patterns can be uncovered. Researchers carefully observe the object of the case study and identify causal factors associated with the observed phenomenon. Renegotiation of arrangements with the objects of the study or addition of questions to interviews may be necessary as the study progresses. Case study research is flexible, but when changes are made, they are documented systematically.

Exemplary case studies use field notes and databases to categorize and reference data so that it is readily available for subsequent reinterpretation. Field notes record feelings and intuitive hunches, pose questions, and document the work in progress. They record testimonies, stories, and illustrations which can be used in later reports. They may warn of impending bias because of the detailed exposure of the client to special attention, or give an early signal that a pattern is emerging. They assist in determining whether or not the inquiry needs to be reformulated or redefined based on what is being observed. Field notes should be kept separate from the data being collected and stored for analysis.

Maintaining the relationship between the issue and the evidence is mandatory. The researcher may enter some data into a database and physically store other data, but the researcher documents, classifies, and cross-references all evidence so that it can be efficiently recalled for sorting and examination over the course of the study.

Step 5. Evaluate and Analyze the Data

The researcher examines raw data using many interpretations in order to find linkages between the research object and the outcomes with reference to the original research questions. Throughout the evaluation and analysis process, the researcher remains open to new opportunities and insights. The case study method, with its use of multiple data collection methods and analysis techniques, provides researchers with opportunities to triangulate data in order to strengthen the research findings and conclusions.

The tactics used in analysis force researchers to move beyond initial impressions to improve the likelihood of accurate and reliable findings. Exemplary case studies will deliberately sort the data in many different ways to expose or create new insights and will deliberately look for conflicting data to disconfirm the analysis. Researchers categorize, tabulate, and recombine data to address the initial propositions or purpose of the study, and conduct cross-checks of facts and discrepancies in accounts. Focused, short, repeat interviews may be necessary to gather additional data to verify key observations or check a fact.

Specific techniques include placing information into arrays, creating matrices of categories, creating flow charts or other displays, and tabulating frequency of events. Researchers use the quantitative data that has been collected to corroborate and support the qualitative data which is most useful for understanding the rationale or theory underlying relationships. Another technique is to use multiple investigators to gain the advantage provided when a variety of perspectives and insights examine the data and the patterns. When the multiple observations converge, confidence in the findings increases. Conflicting perceptions, on the other hand, cause the researchers to pry more deeply.

Another technique, the cross-case search for patterns, keeps investigators from reaching premature conclusions by requiring that investigators look at the data in many different ways. Cross-case analysis divides the data by type across all cases investigated. One researcher then examines the data of that type thoroughly. When a pattern from one data type is corroborated by the evidence from another, the finding is stronger. When evidence conflicts, deeper probing of the differences is necessary to identify the cause or source of conflict. In all cases, the researcher treats the evidence fairly to produce analytic conclusions answering the original "how" and "why" research questions.

Step 6. Prepare the report

Exemplary case studies report the data in a way that transforms a complex issue into one that can be understood, allowing the reader to question and examine the study and reach an understanding independent of the researcher. The goal of the written report is to portray a complex problem in a way that conveys a vicarious experience to the reader. Case studies present data in very publicly accessible ways and may lead the reader to apply the experience in his or her own real-life situation. Researchers pay particular attention to displaying sufficient evidence to gain the reader�s confidence that all avenues have been explored, clearly communicating the boundaries of the case, and giving special attention to conflicting propositions.

Techniques for composing the report can include handling each case as a separate chapter or treating the case as a chronological recounting. Some researchers report the case study as a story. During the report preparation process, researchers critically examine the document looking for ways the report is incomplete. The researcher uses representative audience groups to review and comment on the draft document. Based on the comments, the researcher rewrites and makes revisions. Some case study researchers suggest that the document review audience include a journalist and some suggest that the documents should be reviewed by the participants in the study.

Applying the Case Study Method to an Electronic Community Network

By way of example, we apply these six steps to an example study of multiple participants in an electronic community network. All participants are non-profit organizations which have chosen an electronic community network on the World Wide Web as a method of delivering information to the public. The case study method is applicable to this set of users because it can be used to examine the issue of whether or not the electronic community network is beneficial in some way to the organization and what those benefits might be.

Step 1. Determine and Define the Research Questions

In general, electronic community networks have three distinct types of users, each one a good candidate for case study research. The three groups of users include people around the world who use the electronic community network, the non-profit organizations using the electronic community network to provide information to potential users of their services, and the "community" that forms as the result of interacting with other participants on the electronic community network.

In this case, the researcher is primarily interested in determining whether or not the electronic community network is beneficial in some way to non-profit organization participants. The researcher begins with a review of the literature to determine what prior studies have determined about this issue and uses the literature to define the following questions for the study of the non-profit organizations providing information to the electronic community network:

Why do non-profit organization participants use the network?

How do non-profit organization participants determine what to place on the electronic community network?

Do the non-profit organization participants believe the community network serves a useful purpose in furthering their mission? How?

Step 2. Select the Cases and Determine Data Gathering and Analysis Techniques

Many communities have constructed electronic community networks on the World Wide Web. At the outset of the design phase, the researcher determines that only one of these networks will be studied and further sets the study boundaries to include only some of the non-profit organizations represented on that one network. The researcher contacts the Board of Directors of the community network, who are open to the idea of the case study. The researcher also gathers computer generated log data from the network and, using this data, determines that an in-depth study of representative organizations from four categories -- health care, environmental, education, and religious -- is feasible. The investigator applies additional selection criteria so that an urban-based and a rural-based non-profit are represented in the study in order to examine whether urban non-profits perceive more benefits from community networks than rural organizations.

The researcher considers multiple sources of data for this study and selects document examination, the gathering and study of organizational documents such as administrative reports, agendas, letters, minutes, and news clippings for each of the organizations. In this case, the investigator decides to also conduct open-ended interviews with key members of each organization using a check-list to guide interviewers during the interview process so that uniformity and consistency can be assured in the data, which could include facts, opinions, and unexpected insights. In this case study, the researcher cannot employ direct observation as a tool because some of the organizations involved have no office and meet infrequently to conduct business directly related to the electronic community network. The researcher instead decides to survey all Board members of the selected organizations using a questionnaire as a third data gathering tool. Within-case and cross-case analysis of data are selected as analysis techniques.

Step 3. Prepare to Collect the Data

The researcher prepares to collect data by first contacting each organization to be studied to gain their cooperation, explain the purpose of the study, and assemble key contact information. Since data to be collected and examined includes organizational documents, the researcher states his intent to request copies of these documents, and plans for storage, classification, and retrieval of these items, as well as the interview and survey data. The researcher develops a formal investigator training program to include seminar topics on non-profit organizations and their structures in each of the four categories selected for this study. The training program also includes practice sessions in conducting open-ended interviews and documenting sources, suggested field notes formats, and a detailed explanation of the purpose of the case study. The researcher selects a fifth case as a pilot case, and the investigators apply the data gathering tools to the pilot case to determine whether the planned timeline is feasible and whether or not the interview and survey questions are appropriate and effective. Based on the results of the pilot, the researcher makes adjustments and assigns investigators particular cases which become their area of expertise in the evaluation and analysis of the data.

Step 4. Collect Data in the Field

Investigators first arrange to visit with the Board of Directors of each non-profit organization as a group and ask for copies of the organization�s mission, news clippings, brochures, and any other written material describing the organization and its purpose. The investigator reviews the purpose of the study with the entire Board, schedules individual interview times with as many Board members as can cooperate, confirms key contact data, and requests that all Board members respond to the written survey which will be mailed later.

Investigators take written notes during the interview and record field notes after the interview is completed. The interviews, although open-ended, are structured around the research questions defined at the start of the case study.

Research Question: Why do non-profit organization participants use the network?
Interview Questions: How did the organization make the decision to place data on the World Wide Web community network? What need was the organization hoping to fulfill?
Research Question: How do non-profit organization participants determine what to place on the electronic community network?
Interview Questions: What process was used to select the information that would be used on the network? How is the information kept up to date?
Research Question: Do the non-profit organization participants believe the community network serves a useful purpose in furthering their mission? How?

Interview Questions: How does the organization know if the electronic community network is beneficial to the organization? How does the electronic community network further the mission of the organization? What systematic tracking mechanisms exist to determine how many or what types of users are accessing the organization information?

The investigator�s field notes record impressions and questions that might assist with the interpretation of the interview data. The investigator makes note of stories told during open-ended interviews and flags them for potential use in the final report. Data is entered into the database.

The researcher mails written surveys to all Board members with a requested return date and a stamped return envelope. Once the surveys are returned, the researcher codes and enters the data into the database so that it can be used independently as well as integrated when the case study progresses to the point of cross-case examination of data for all four cases.

Step 5. Evaluate and Analyze the Data

Within-case analysis is the first analysis technique used with each non-profit organization under study. The assigned investigator studies each organization�s written documentation and survey response data as a separate case to identify unique patterns within the data for that single organization. Individual investigators prepare detailed case study write-ups for each organization, categorizing interview questions and answers and examining the data for within-group similarities and differences.

Cross-case analysis follows. Investigators examine pairs of cases, categorizing the similarities and differences in each pair. Investigators then examine similar pairs for differences, and dissimilar pairs for similarities. As patterns begin to emerge, certain evidence may stand out as being in conflict with the patterns. In those cases, the investigator conducts follow-up focused interviews to confirm or correct the initial data in order to tie the evidence to the findings and to state relationships in answer to the research questions.

Step 6 Prepare the Report

The outline of the report includes thanking all of the participants, stating the problem, listing the research questions, describing the methods used to conduct the research and any potential flaws in the method used, explaining the data gathering and analysis techniques used, and concluding with the answers to the questions and suggestions for further research. Key features of the report include a retelling of specific stories related to the successes or disappointments experienced by the organizations that were conveyed during data collection, and answers or comments illuminating issues directly related to the research questions. The researcher develops each issue using quotations or other details from the data collected, and points out the triangulation of data where applicable. The report also includes confirming and conflicting findings from literature reviews. The report conclusion makes assertions and suggestions for further research activity, so that another researcher may apply these techniques to another electronic community network and its participants to determine whether similar findings are identifiable in other communities. Final report distribution includes all participants.

Applicability to Library and Information Science

Case study research, with its applicability across many disciplines, is an appropriate methodology to use in library studies. In Library and Information Science, case study research has been used to study reasons why library school programs close (Paris, 1988), to examine reference service practices in university library settings (Lawson, 1971), and to examine how questions are negotiated between customers and librarians (Taylor, 1967). Much of the research is focused exclusively on the librarian as the object or the customer as the object. Researchers could use the case study method to further study the role of the librarian in implementing specific models of service. For example, case study research could examine how information-seeking behavior in public libraries compares with information-seeking behavior in places other than libraries, to conduct in-depth studies of non-library community based information services to compare with library based community information services, and to study community networks based in libraries.

Conclusion

Case studies are complex because they generally involve multiple sources of data, may include multiple cases within a study, and produce large amounts of data for analysis. Researchers from many disciplines use the case study method to build upon theory, to produce new theory, to dispute or challenge theory, to explain a situation, to provide a basis to apply solutions to situations, to explore, or to describe an object or phenomenon. The advantages of the case study method are its applicability to real-life, contemporary, human situations and its public accessibility through written reports. Case study results relate directly to the common reader�s everyday experience and facilitate an understanding of complex real-life situations.

Bibliography

Busha, C. H., & Harter, S. P. (1980). Research methods in librarianship, techniques and interpretation. New York: Academic Press.
Chang, H. C. (1974). Library goals as responses to structural milieu requirements: A comparative case study. Unpublished doctoral dissertation, University of Massachusetts, Amherst.
DuMont, R. R. (1975). The large urban public library as an agency of social reform, 1890-1915. Unpublished doctoral dissertation, University of Pittsburgh, Pennsylvania.
Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 352-550.
Emory, C. W., & Cooper, D. R. (1991). Business research methods. (4th ed.). Boston, MA: Irvin.
Goldhor, H. (1972). An introduction to scientific research in librarianship. Urbana, IL: University of Illinois.
Hamel, J. (with Dufour, S., & Fortin, D.). (1993). Case study methods. Newbury Park, CA: Sage.
Harris, S., & Sutton, R. (1986). Functions of parting ceremonies in dying organizations. Academy of Management Journal, 19, 5-30.
Lawson, V. (1971). Reference service in university libraries, two case studies. Unpublished doctoral dissertation, Columbia University, New York.
McAdams, D. C. (1979). Powerful actors in public land use decision making processes: A case study in Austin, Texas. Unpublished doctoral dissertation, University of Texas, Austin.
McClure, C. R., & Hernon, P. (Eds.). (1991). Library and information science research: perspectives and strategies for improvement. Norwood, NJ: Ablex.
Miles, M. B., & Huberman, A. M. (1984). Qualitative data analysis: A sourcebook of new methods. Beverly Hills, CA: Sage.
Miller, F. (1986). Use, appraisal, and research: A case study of social history. The American Archivist: 49(4), 371-392.
Paris, M. (1988). Library school closings: Four case studies. Metuchen, NJ: Scarecrow Press.
Patton, M. Q. (1980). Qualitative evaluation methods. Beverly Hills, CA: Sage.

THE RESEARCH METHODOLOGY KEY CONCEPTS OF THE SCIENTIFIC METHOD

THE RESEARCH METHODOLOGY

KEY CONCEPTS OF THE SCIENTIFIC METHOD

There are several important aspects to research methodology. This is a summary of the key concepts in scientific research and an attempt to erase some commonmisconceptions in science.

Steps of the scientific method are shaped like an hourglass - starting from general questions, narrowing down to focus on one specific aspect, and designing research where we can observe and analyze this aspect. At last, we conclude and generalize to the real world.

FORMULATING A RESEARCH PROBLEM

Researchers organize their research by formulating and defining a research problem. This helps them focus the research process so that they can draw conclusions reflecting the real world in the best possible way.

HYPOTHESIS

In research, a hypothesis is a suggested explanation of a phenomenon.
A null hypothesis is a hypothesis which a researcher tries to disprove. Normally, the null hypothesis represents the current view/explanation of an aspect of the world that the researcher wants to challenge.
Research methodology involves the researcher providing an alternative hypothesis, a research hypothesis, as an alternate way to explain the phenomenon.
The researcher tests the hypothesis to disprove the null hypothesis, not because he/she loves the research hypothesis, but because it would mean coming closer to finding an answer to a specific problem. The research hypothesis is often based on observations that evoke suspicion that the null hypothesis is not always correct.
In the Stanley Milgram Experiment, the null hypothesis was that the personality determined whether a person would hurt another person, while the research hypothesis was that the role, instructions and orders were much more important in determining whether people would hurt others.

VARIABLES

A variable is something that changes. It changes according to different factors. Some variables change easily, like the stock-exchange value, while other variables are almost constant, like the name of someone. Researchers are often seeking to measure variables.
The variable can be a number, a name, or anything where the value can change.
An example of a variable is temperature. The temperature varies according to other variable and factors. You can measure different temperature inside and outside. If it is a sunny day, chances are that the temperature will be higher than if it's cloudy. Another thing that can make the temperature change is whether something has been done to manipulate the temperature, like lighting a fire in the chimney.
In research, you typically define variables according to what you're measuring. The independent variable is the variable which the researcher would like to measure (the cause), while the dependent variable is the effect (or assumed effect), dependent on the independent variable. These variables are often stated in experimental research, in a hypothesis, e.g. "what is the effect of personality on helping behavior?"
In explorative research methodology, e.g. in some qualitative research, the independent and the dependent variables might not be identified beforehand. They might not be stated because the researcher does not have a clear idea yet on what is really going on.
Confounding variables are variables with a significant effect on the dependent variable that the researcher failed to control or eliminate - sometimes because the researcher is not aware of the effect of the confounding variable. The key is to identify possible confounding variables and somehow try to eliminate or control them.

OPERATIONALIZATION

Operationalization is to take a fuzzy concept, such as 'helping behavior', and try to measure it by specific observations, e.g. how likely are people to help a stranger with problems.


See also:
Conceptual Variables

CHOOSING THE RESEARCH METHOD

The selection of the research method is crucial for what conclusions you can make about a phenomenon. It affects what you can say about the cause and factors influencing the phenomenon.
It is also important to choose a research method which is within the limits of what the researcher can do. Time, money, feasibility, ethics and availability to measure the phenomenon correctly are examples of issues constraining the research.

CHOOSING THE MEASUREMENT

Choosing the scientific measurements are also crucial for getting the correct conclusion. Some measurements might not reflect the real world, because they do not measure the phenomenon as it should.

RESULTS

SIGNIFICANCE TEST

To test a hypothesis, quantitative research uses significance tests to determine which hypothesis is right.
The significance test can show whether the null hypothesis is more likely correct than the research hypothesis. Research methodology in a number of areas like social sciences depends heavily on significance tests.
A significance test may even drive the research process in a whole new direction, based on the findings.
The t-test (also called the Student's T-Test) is one of many statistical significance tests, which compares two supposedly equal sets of data to see if they really are alike or not. The t-test helps the researcher conclude whether a hypothesis is supported or not.

DRAWING CONCLUSIONS

Drawing a conclusion is based on several factors of the research process, not just because the researcher got the expected result. It has to be based on the validity and reliability of the measurement, how good the measurement was to reflect the real world and what more could have affected the results.
The observations are often referred to as 'empirical evidence' and the logic/thinking leads to the conclusions. Anyone should be able to check the observation and logic, to see if they also reach the same conclusions.
Errors of the observations may stem from measurement-problems, misinterpretations, unlikely random events etc.
A common error is to think that correlation implies a causal relationship. This is not necessarily true.

GENERALIZATION

Generalization is to which extent the research and the conclusions of the research apply to the real world. It is not always so that good research will reflect the real world, since we can only measure a small portion of the population at a time.

VALIDITY AND RELIABILITY

Validity refers to what degree the research reflects the given research problem, while Reliability refers to how consistent a set of measurements are.


Types of validity:

• External Validity
• Population Validity
• Ecological Validity
• Internal Validity
• Content Validity
• Face Validity
• Construct Validity
• Convergent and Discriminant Validity
• Test Validity
• Criterion Validity
• Concurrent Validity
• Predictive Validity

Reliability may be defined as "Yielding the same or compatible results in different clinical experiments or statistical trials" (the free dictionary). Research methodology lacking reliability cannot be trusted. Replication studies are a way to test reliability.
Types of Reliability:

• Test-Retest Reliability
• Interrater Reliability
• Internal Consistency Reliability
• Instrument Reliability
• Statistical Reliability
• Reproducability

Both validity and reliability are important aspects of the research methodology to get better explanations of the world.

ERRORS IN RESEARCH

Logically, there are two types of errors when drawing conclusions in research:
Type 1 error is when we accept the research hypothesis when the null hypothesis is in fact correct.
Type 2 error is when we reject the research hypothesis even if the null hypothesis is wrong.


Read more: http://www.experiment-resources.com/research-methodology.html#ixzz1SG7W2qY8