Types of research methods and disciplines A dissertation is an extended piece of writing based on comprehensive reading and research, written by an academic scholar at an undergraduate, masters or post graduate level. In some cases, a dissertation is referred to an academic research document written at PhD level, while a Thesis may be one which is written by an academic at Masters or Undergraduate level. However the opposite is also true in other cases. Etymology[edit] The word ‘dissertation’ was derived from the Latin word dissertātiō which means ‘discourse’ or ‘path. Types of Research[edit] There are two types of research which can be done to develop a thesis or dissertation: Practical Research: The practical approach consists of the empirical study of the topic under research and chiefly consists of hands on approach. Types of Research Method[edit] Descriptive/Qualitative[edit] This type of research methods involve describing in details specific situation using research tools like interviews, surveys, and observations.[3] [edit]
Conformity Conformity is the act of matching attitudes, beliefs, and behaviors to group norms.[1] Norms are implicit, unsaid rules, shared by a group of individuals, that guide their interactions with others. This tendency to conform occurs in small groups and/or society as a whole, and may result from subtle unconscious influences, or direct and overt social pressure. Conformity can occur in the presence of others, or when an individual is alone. For example, people tend to follow social norms when eating or watching television, even when alone. People often conform from a desire for security within a group—typically a group of a similar age, culture, religion, or educational status. Although peer pressure may manifest negatively, conformity can have good or bad effects depending on the situation. As conformity is a group phenomenon, factors such as group size, unanimity, cohesion, status, prior commitment, and public opinion help determine the level of conformity an individual displays. Age[edit]
Meta-analysis In statistics, meta-analysis comprises statistical methods for contrasting and combining results from different studies, in the hope of identifying patterns among study results, sources of disagreement among those results, or other interesting relationships that may come to light in the context of multiple studies.[1] Meta-analysis can be thought of as "conducting research about previous research." In its simplest form, meta-analysis is done by identifying a common statistical measure that is shared between studies, such as effect size or p-value, and calculating a weighted average of that common measure. This weighting is usually related to the sample sizes of the individual studies, although it can also include other factors, such as study quality. The motivation of a meta-analysis is to aggregate information in order to achieve a higher statistical power for the measure of interest, as opposed to a less precise measure derived from a single study. History[edit] Advantages[edit] [edit]
Group polarization Overview[edit] Group polarization is the phenomenon that when placed in group situations, people will make decisions and form opinions to more of an extreme than when they are in individual situations. The phenomenon has shown that after participating in a discussion group, members tend to advocate more extreme positions and call for riskier courses of action than individuals who did not participate in any such discussion.[3] This phenomenon was originally coined risky shift but was found to apply to more than risk, so the replacement term choice shift has been suggested.[4] The importance of group polarization is significant as it helps explain group behavior in a variety of real-life situations. Examples of these situations include public policy, terrorism, college life, and violence. History and origins[edit] In early studies, the risky-shift phenomenon was measured using a scale known as the Choice-Dilemmas Questionnaire. “Mr. ____Place a check here if you think Mr. Controversy[edit]
Scientometrics Scientometrics is the study of measuring and analysing science research. In practice, scientometrics is often done using bibliometrics which is a measurement of the impact of (scientific) publications. Modern scientometrics is mostly based on the work of Derek J. de Solla Price and Eugene Garfield. See also[edit] Further reading[edit] Derek J. de Solla Price, Little Science, Big Science (New York, 1963)G. External links[edit]
Social comparison theory Social comparison theory was initially proposed by social psychologist Leon Festinger in 1954.[1] Social comparison theory is centered on the belief that there is a drive within individuals to gain accurate self-evaluations. The theory explains how individuals evaluate their own opinions and abilities by comparing themselves to others in order to reduce uncertainty in these domains, and learn how to define the self. Following the initial theory, research began to focus on social comparison as a way of self-enhancement,[2][3] introducing the concepts of downward and upward comparisons and expanding the motivations of social comparisons.[4] Initial framework[edit] In the initial theory, Festinger provided nine main hypotheses. Theoretical advances[edit] Since its inception, the initial framework has undergone several advances. Self-evaluation and self-enhancement[edit] Upward and downward social comparisons[edit] Competitiveness[edit] Social status[edit] Proximity to a standard[edit]
Domain analysis In software engineering, domain analysis, or product line analysis, is the process of analyzing related software systems in a domain to find their common and variable parts. It is a model of wider business context for the system. The term was coined in the early 1980s by James Neighbors.[1][2] Domain analysis is the first phase of domain engineering. Domain analysis produces domain models using methodologies such as domain specific languages, feature tables, facet tables, facet templates, and generic architectures, which describe all of the systems in a domain. The products, or "artifacts", of a domain analysis are sometimes object-oriented models (e.g. represented with the Unified Modeling Language (UML)) or data models represented with entity-relationship diagrams (ERD). In information science, the term "domain analysis" was suggested in 1995 by Birger Hjørland and H. Domain analysis techniques[edit] References[edit] Jump up ^ Neighbors, J.M. See also[edit]
Hidden profiles History[edit] In 1981 two researchers, Garold Stasser and William Titus, set out to challenge strongly-held beliefs about group decision making. The researchers attempted to use a number of formal models to identify what would happen when people are not fully informed.[1]:304 One of these was the persuasive argument theory (PAT). The theory, in this case, would state that polarization of judgments is due to culturally pooled arguments. Causes[edit] Hidden profiles occur when some information is shared among group members and other pieces of information remain unshared. One issue with hidden profiles is the time dedicated to discussion. See also[edit] Further reading[edit] Stasser, G. (1988). References[edit] ^ Jump up to: a b c Stasser, G.; Titus, W. (2003). Co-citation Figure visualizing co-citation on the left and a refinement of co-citation, Co-citation Proximity Analysis (CPA) on the right. Co-citation, like Bibliographic Coupling, is a semantic similarity measure for documents that makes use of citation relationships. Co-citation is defined as the frequency with which two documents are cited together by other documents.[1] If at least one other document cites two documents in common these documents are said to be co-cited. The more co-citations two documents receive, the higher their co-citation strength, and the more likely they are semantically related.[1] The figure to the right illustrates the concept of co-citation and a more recent variation of co-citation which accounts for the placement of citations in the full text of documents. The figure's right image shows a citing document which cites the Documents 1, 2 and 3. Over the decades, researchers proposed variants or enhancements to the original co-citation concept. Considerations[edit]
Content analysis Content analysis is "a wide and heterogeneous set of manual or computer-assisted techniques for contextualized interpretations of documents produced by communication processes in the strict sense of that phrase (any kind of text, written, iconic, multimedia, etc.) or signification processes (traces and artifacts), having as ultimate goal the production of valid and trustworthy inferences."[1] On the other side, Content Analysis can also study traces (documents from past times) and artifacts (non-linguistic documents), which come from communication processes in a broad sense of that phrase - commonly referred to as "signification" in Semiotics (in the absence of an intentional sender, semiosis is developed by abduction).[1] Over the years, content analysis has been applied to a variety of scopes. In recent times, particularly with the advent of mass communication, content analysis has known an increasing use to deeply analyse and understand media content and media logic. Description[edit]