Sabtu, 28 November 2015

What Is Descriptive Research?

Descriptive research does not fit neatly into the definition of either quantitative or qualitative research methodologies, but instead it can utilize elements of both, often within the same study. The term descriptive research refers to the type of research question, design, and data analysis that will be applied to a given topic. Descriptive statistics tell what is, while inferential statistics try to determine cause and effect.
The type of question asked by the researcher will ultimately determine the type of approach necessary to complete an accurate assessment of the topic at hand. Descriptive studies, primarily concerned with finding out "what is," might be applied to investigate the following questions: Do teachers hold favorable attitudes toward using computers in schools? What kinds of activities that involve technology occur in sixth-grade classrooms and how frequently do they occur? What have been the reactions of school administrators to technological innovations in teaching the social sciences? How have high school computing courses changed over the last 10 years? How do the new multimediated textbooks compare to the print-based textbooks? How are decisions being made about using Channel One in schools, and for those schools that choose to use it, how is Channel One being implemented? What is the best way to provide access to computer equipment in schools? How should instructional designers improve software design to make the software more appealing to students? To what degree are special-education teachers well versed concerning assistive technology? Is there a relationship between experience with multimedia computers and problem-solving skills? How successful is a certain satellite-delivered Spanish course in terms of motivational value and academic achievement? Do teachers actually implement technology in the way they perceive? How many people use the AECT gopher server, and what do they use if for?

Descriptive research can be either quantitative or qualitative. It can involve collections of quantitative information that can be tabulated along a continuum in numerical form, such as scores on a test or the number of times a person chooses to use a-certain feature of a multimedia program, or it can describe categories of information such as gender or patterns of interaction when using technology in a group situation. Descriptive research involves gathering data that describe events and then organizes, tabulates, depicts, and describes the data collection (Glass & Hopkins, 1984). It often uses visual aids such as graphs and charts to aid the reader in understanding the data distribution. Because the human mind cannot extract the full import of a large mass of raw data, descriptive statistics are very important in reducing the data to manageable form. When in-depth, narrative descriptions of small numbers of cases are involved, the research uses description as a tool to organize data into patterns that emerge during analysis. Those patterns aid the mind in comprehending a qualitative study and its implications.

Most quantitative research falls into two areas: studies that describe events and studies aimed at discovering inferences or causal relationships. Descriptive studies are aimed at finding out "what is," so observational and survey methods are frequently used to collect descriptive data (Borg & Gall, 1989). Studies of this type might describe the current state of multimedia usage in schools or patterns of activity resulting from group work at the computer. An example of this is Cochenour, Hakes, and Neal's (1994) study of trends in compressed video applications with education and the private sector.

Descriptive studies report summary data such as measures of central tendency including the mean, median, mode, deviance from the mean, variation, percentage, and correlation between variables. Survey research commonly includes that type of measurement, but often goes beyond the descriptive statistics in order to draw inferences. See, for example, Signer's (1991) survey of computer-assisted instruction and at-risk students, or Nolan, McKinnon, and Soler's (1992) research on achieving equitable access to school computers. Thick, rich descriptions of phenomena can also emerge from qualitative studies, case studies, observational studies, interviews, and portfolio assessments. Robinson's (1994) case study of a televised news program in classrooms and Lee's (1994) case study about identifying values concerning school restructuring are excellent examples of case studies.

Descriptive research is unique in the number of variables employed. Like other types of research, descriptive research can include multiple variables for analysis, yet unlike other methods, it requires only one variable (Borg & Gall, 1989). For example, a descriptive study might employ methods of analyzing correlations between multiple variables by using tests such as Pearson's Product Moment correlation, regression, or multiple regression analysis. Good examples of this are the Knupfer and Hayes (1994) study about the effects of the Channel One broadcast on knowledge of current events, Manaev's (1991) study about mass media effectiveness, McKenna's (1993) study of the relationship between attributes of a radio program and it's appeal to listeners, Orey and Nelson's (1994) examination of learner interactions with hypermedia environments, and Shapiro's (1991) study of memory and decision processes.

On the other hand, descriptive research might simply report the percentage summary on a single variable. Examples of this are the tally of reference citations in selected instructional design and technology journals by Anglin and Towers (1992); Barry's (1994) investigation of the controversy surrounding advertising and Channel One; Lu, Morlan, Lerchlorlarn, Lee, and Dike's (1993) investigation of the international utilization of media in education (1993); and Pettersson, Metallinos, Muffoletto, Shaw, and Takakuwa's (1993) analysis of the use of verbo-visual information in teaching geography in various countries.

Descriptive statistics utilize data collection and analysis techniques that yield reports concerning the measures of central tendency, variation, and correlation. The combination of its characteristic summary and correlational statistics, along with its focus on specific types of research questions, methods, and outcomes is what distinguishes descriptive research from other research types.

Three main purposes of research are to describe, explain, and validate findings. Description emerges following creative exploration, and serves to organize the findings in order to fit them with explanations, and then test or validate those explanations (Krathwohl, 1993). Many research studies call for the description of natural or man-made phenomena such as their form, structure, activity, change over time, relation to other phenomena, and so on. The description often illuminates knowledge that we might not otherwise notice or even encounter. Several important scientific discoveries as well as anthropological information about events outside of our common experiences have resulted from making such descriptions. For example, astronomers use their telescopes to develop descriptions of different parts of the universe, anthropologists describe life events of socially atypical situations or cultures uniquely different from our own, and educational researchers describe activities within classrooms concerning the implementation of technology. This process sometimes results in the discovery of stars and stellar events, new knowledge about value systems or practices of other cultures, or even the reality of classroom life as new technologies are implemented within schools.

Educational researchers might use observational, survey, and interview techniques to collect data about group dynamics during computer-based activities. These data could then be used to recommend specific strategies for implementing computers or improving teaching strategies. Two excellent studies concerning the role of collaborative groups were conducted by Webb (1982), and Rysavy and Sales (1991). Noreen Webb's landmark study used descriptive research techniques to investigate collaborative groups as they worked within classrooms. Rysavy and Sales also apply a descriptive approach to study the role of group collaboration for working at computers. The Rysavy and Sales approach did not observe students in classrooms, but reported certain common findings that emerged through a literature search.

Descriptive studies have an important role in educational research. They have greatly increased our knowledge about what happens in schools. Some of the important books in education have reported studies of this type: Life in Classrooms, by Philip Jackson; The Good High School, by Sara Lawrence Lightfoot; Teachers and Machines: The Classroom Use of Technology Since 1920, by Larry Cuban; A Place Called School, by John Goodlad; Visual Literacy: A Spectrum of Learning, by D. M. Moore and Dwyer; Computers in Education: Social, Political, and Historical Perspectives, by Muffoletto and Knupfer; and Contemporary Issues in American Distance Education, by M. G. Moore.

Henry J. Becker's (1986) series of survey reports concerning the implementation of computers into schools across the United States as well as Nancy Nelson Knupfer's (1988) reports about teacher's opinions and patterns of computer usage also fit partially within the realm of descriptive research. Both studies describe categories of data and use statistical analysis to examine correlations between specific variables. Both also go beyond the bounds of descriptive research and conduct further statistical procedures appropriate to their research questions, thus enabling them to make further recommendations about implementing computing technology in ways to support grassroots change and equitable practices within the schools. Finally, Knupfer's study extended the analysis and conclusions in order to yield suggestions for instructional designers involved with educational computing.

41.1.1 The Nature of Descriptive Research

The descriptive function of research is heavily dependent on instrumentation for measurement and observation (Borg & Gall, 1989). Researchers may work for many years to perfect such instrumentation so that the resulting measurement will be accurate, reliable, and generalizable. Instruments such as the electron microscope, standardized tests for various purposes, the United States census, Michael Simonson's questionnaires about computer usage, and scores of thoroughly validated questionnaires are examples of some instruments that yield valuable descriptive data. Once the instruments are developed, they can be used to describe phenomena of interest to the researchers.

The intent of some descriptive research is to produce statistical information about aspects of education that interests policy makers and educators. The National Center for Education Statistics specializes in this kind of research. Many of its findings are published in an annual volume
called Digest of Educational Statistics. The center also administers the National Assessment of Educational Progress (NAEP), which collects descriptive information about how well the nation's youth are doing in various subject areas. A typical NAEP publication is The Reading Report Card, which provides descriptive information about the reading achievement of junior high and high school students during the past 2 decades.

On a larger scale, the International Association for the Evaluation of Education Achievement (IEA) has done major descriptive studies comparing the academic achievement levels of students in many different nations, including the United States (Borg & Gall, 1989). Within the United States, huge amounts of information are being gathered continuously by the Office of Technology Assessment, which influences policy concerning technology in education. As a way of offering guidance about the potential of technologies for distance education, that office has published a book called Linking for Learning: A New Course for Education, which offers descriptions of distance education and its potential.

There has been an ongoing debate among researchers about the value of quantitative (see 40.1.2) versus qualitative research, and certain remarks have targeted descriptive research as being less pure than traditional experimental, quantitative designs. Rumors abound that young researchers must conduct quantitative research in order to get published in Educational Technology Research and Development and other prestigious journals in the field. One camp argues the benefits of a scientific approach to educational research, thus preferring the experimental, quantitative approach, while the other camp posits the need to recognize the unique human side of educational research questions and thus prefers to use qualitative research methodology. Because descriptive research spans both quantitative and qualitative methodologies, it brings the ability to describe events in greater or less depth as needed, to focus on various elements of different research techniques, and to engage quantitative statistics to organize information in meaningful ways. The citations within this chapter provide ample evidence that descriptive research can indeed be published in prestigious journals.

Descriptive studies can yield rich data that lead to important recommendations. For example, Galloway (1992) bases recommendations for teaching with computer analogies on descriptive data, and Wehrs (1992) draws reasonable conclusions about using expert systems to support academic advising. On the other hand, descriptive research can be misused by those who do not understand its purpose and limitations. For example, one cannot try to draw conclusions that show cause and effect, because that is beyond the bounds of the statistics employed.

Borg and Gall (1989) classify the outcomes of educational research into the four categories of description, prediction, improvement, and explanation. They say that descriptive research describes natural or man-made educational phenomena that is of interest to policy makers and educators. Predictions of educational phenomenon seek to determine whether certain students are at risk and if teachers should use different techniques to instruct them. Research about improvement asks whether a certain technique does something to help students learn better and whether certain interventions can improve student learning by applying causal-comparative, correlational, and experimental methods. The final category of explanation posits that research is able to explain a set of phenomena that leads to our ability to describe, predict, and control the phenomena with a high level of certainty and accuracy. This usually takes the form of theories.


The methods of collecting data for descriptive research can be employed singly or in various combinations, depending on the research questions at hand. Descriptive research often calls upon quasi-experimental research design (Campbell & Stanley, 1963). Some of the common data collection methods applied to questions within the realm of descriptive research include surveys, interviews, observations, and portfolios.

Types of quantitative research question

Dissertations that are based on a quantitative research design attempt to answer at least one quantitative research question. In some cases, these quantitative research questions will be followed by either research hypotheses or null hypotheses. However, this article focuses solely on quantitative research questions. Furthermore, since there is more than one type of quantitative research question that you can attempt to answer in a dissertation (i.e., descriptive research questions, comparative research questions and relationship-based research questions), we discuss each of these in this article. If you do not know much about quantitative research and quantitative research questions at this stage, we would recommend that you first read the article, Quantitative research questions: What do I have to think about, as well as an overview article on types of variables, which will help to familiarise you with terms such as dependent and independent variable, as well as categorical and continuous variables [see the article: Types of variables]. The purpose of this article is to introduce you to the three different types of quantitative research question (i.e., descriptive, comparative and relationship-based research questions) so that you can understand what type(s) of quantitative research question you want to create in your dissertation. Each of these types of quantitative research question is discussed in turn:

Descriptive research questions

Descriptive research questions simply aim to describe the variables you are measuring. When we use the word describe, we mean that these research questions aim to quantify the variables you are interested in. Think of research questions that start with words such as "How much?", "How often?", "What percentage?", and "What proportion?", but also sometimes questions starting "What is?" and "What are?". Often, descriptive research questions focus on only one variable and one group, but they can include multiple variables and groups. We provide some examples below:
Question: How many calories do Americans consume per day?
Variable: Daily calorific intake
Group: Americans

Question: How many calories do American men and women consume per day?
Variable: Daily calorific intake
Group: 1. American men
2. American women

Question: How often do British university students use Facebook each week?
Variable: Weekly Facebook usage
Group: British university students

Question: How often do male and female British university students upload photos
and comment on other users' photos on Facebook each week?
Variable: 1. Weekly photo uploads on Facebook
2. Weekly comments on other users? photos on Facebook
Group: 1. Male, British university students
2. Female, British university students

Question: What are the most important factors that influence the career choices of Australian university students?
Variable: Factors influencing career choices
Group: Australian university students
In each of these example descriptive research questions, we are quantifying the variables we are interested in. However, the units that we used to quantify these variables will differ depending on what is being measured. For example, in the questions above, we are interested in frequencies (also known as counts), such as the number of calories, photos uploaded, or comments on other users? photos. In the case of the final question, What are the most important factors that influence the career choices of Australian university students?, we are interested in the number of times each factor (e.g., salary and benefits, career prospects, physical working conditions, etc.) was ranked on a scale of 1 to 10 (with 1 = least important and 10 = most important). We may then choose to examine this data by presenting the frequencies, as well as using a measure of central tendency and a measure of spread [see the section on Data Analysis to learn more about these and other statistical tests].
However, it is also common when using descriptive research questions to measure percentages and proportions, so we have included some example descriptive research questions below that illustrate this.
Question: What percentage of American men and women exceed their daily calorific allowance?
Variable: Daily calorific intake
Group: 1. American men
2. American women

Question: What proportion of British male and female university students use the top 5 social networks?
Variable: Use of top 5 social networks (i.e. Facebook, MySpace, Twitter, LinkedIn, and Classmates)
Group: 1. Male, British university students
2. Female, British university students
In terms of the first descriptive research question about daily calorific intake, we are not necessarily interested in frequencies, or using a measure of central tendency or measure of spread, but instead want understand what percentage of American men and women exceed their daily calorific allowance. In this respect, this descriptive research question differs from the earlier question that asked: How many calories do American men and women consume per day? Whilst this question simply wants to measure the total number of calories (i.e., the How many calories part that starts the question); in this case, the question aims to measure excess; that is, what percentage of these two groups (i.e., American men and American women) exceed their daily calorific allowance, which is different for males (around 2500 calories per day) and females (around 2000 calories per day).
If you are performing a piece of descriptive, quantitative research for your dissertation, you are likely to need to set quite a number of descriptive research questions. However, if you are using an experimental or quasi-experimental research design, or a more involved relationship-based research design, you are more likely to use just one or two descriptive research questions as a means to providing background to the topic you are studying, helping to give additional context for comparative research questions and/or relationship-based research questions that follow.

Comparative research questions

Comparative research questions aim to examine the differences between two or more groups on one or more dependent variables (although often just a single dependent variable). Such questions typically start by asking "What is the difference in?" a particular dependent variable (e.g., daily calorific intake) between two or more groups (e.g., American men and American women). Examples of comparative research questions include:
Question: What is the difference in the daily calorific intake of American men and women?
Dependent variable: Daily calorific intake
Groups: 1. American men
2. American women

Question: What is the difference in the weekly photo uploads on Facebook between British male
and female university students?
Dependent variable: Weekly photo uploads on Facebook
Groups: 1. Male, British university students
2. Female, British university students

Question: What are the differences in usage behaviour on Facebook between British male
and female university students?
Dependent variable: Usage behaviour on Facebook (e.g. logins, weekly photo uploads, status changes, commenting
on other users' photos, app usage, etc.)
Group: 1. Male, British university students
2. Female, British university students

Question: What are the differences in perceptions towards Internet banking security between
adolescents and pensioners?
Dependent variable: Perceptions towards Internet banking security
Groups: 1. Adolescents
2. Pensioners

Question: What are the differences in attitudes towards music piracy when pirated music is freely
distributed or purchased?
Dependent variable: Attitudes towards music piracy
Groups: 1. Freely distributed pirated music
2. Purchased pirated music
Groups reflect different categories of the independent variable you are measuring (e.g., American men and women = "gender"; Australian undergraduate and graduate students = "educational level"; pirated music that is freely distributed and pirated music that is purchased = "method of illegal music acquisition").
Comparative research questions also differ in terms of their relative complexity, by which we are referring to how many items/measures make up the dependent variable or how many dependent variables are investigated. Indeed, the examples highlight the difference between very simple comparative research questions where the dependent variable involves just a single measure/item (e.g., daily calorific intake) and potentially more complex questions where the dependent variable is made up of multiple items (e.g., Facebook usage behaviour including a wide range of items, such as logins, weekly photo uploads, status changes, etc.); or where each of these items should be written out as dependent variables.
Overall, whilst the dependent variable(s) highlight what you are interested in studying (e.g., attitudes towards music piracy, perceptions towards Internet banking security), comparative research questions are particularly appropriate if your dissertation aims to examine the differences between two or more groups (e.g., men and women, adolescents and pensioners, managers and non-managers, etc.).

Relationship research questions

Whilst we refer to this type of quantitative research question as a relationship-based research question, the word relationship should be treated simply as a useful way of describing the fact that these types of quantitative research question are interested in the causal relationships, associations, trends and/or interactions amongst two or more variables on one or more groups. We have to be careful when using the word relationship because in statistics, it refers to a particular type of research design, namely experimental research designs where it is possible to measure the cause and effect between two or more variables; that is, it is possible to say that variable A (e.g., study time) was responsible for an increase in variable B (e.g., exam scores). However, at the undergraduate and even master's level, dissertations rarely involve experimental research designs, but rather quasi-experimental and relationship-based research designs [see the section on Quantitative research designs]. This means that you cannot often find causal relationships between variables, but only associations or trends.
However, when we write a relationship-based research question, we do not have to make this distinction between causal relationships, associations, trends and interactions (i.e., it is just something that you should keep in the back of your mind). Instead, we typically start a relationship-based quantitative research question, "What is the relationship?", usually followed by the words, "between or amongst", then list the independent variables (e.g., gender) and dependent variables (e.g., attitudes towards music piracy), "amongst or between" the group(s) you are focusing on. Examples of relationship-based research questions are:
Question: What is the relationship between gender and attitudes towards music piracy amongst adolescents?
Dependent variable: Attitudes towards music piracy
Independent variable: Gender
Group: Adolescents

Question: What is the relationship between study time and exam scores amongst university students?
Dependent variable: Exam scores
Independent variable: Study time
Group: University students

Question: What is the relationship amongst career prospects, salary and benefits, and physical working conditions on job satisfaction between managers and non-managers?
Dependent variable: Job satisfaction
Independent variable: 1. Career prospects
2. Salary and benefits
3. Physical working conditions
Group: 1. Managers
2. Non-managers
As the examples above highlight, relationship-based research questions are appropriate to set when we are interested in the relationship, association, trend, or interaction between one or more dependent (e.g., exam scores) and independent (e.g., study time) variables, whether on one or more groups (e.g., university students).
The quantitative research design that we select subsequently determines whether we look for relationships, associations, trends or interactions. To learn how to structure (i.e., write out) each of these three types of quantitative research question (i.e., descriptive, comparative, relationship-based research questions), see the article: How to structure quantitative research questions.
What are the main types of quantitative approaches to research?
It is easier to understand the different types of quantitative research designs if you consider how the researcher designs for control of the variables in the investigation. 
If the researcher views quantitative design as a continuum, one end of the range represents a design where the variables are not controlled at all and only observed.  Connections amongst variable are only described.  At the other end of the spectrum, however, are designs which include a very close control of variables, and relationships amongst those variables are clearly established. In the middle, with experiment design moving from one type to the other, is a range which blends those two extremes together.
There are four main types of Quantitative research:  Descriptive, Correlational, Causal-Comparative/Quasi-Experimental, and Experimental Research.
Types of Quantitative Design
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Descriptive research seeks to describe the current status of an identified variable. These research projects are designed to provide systematic information about a phenomenon.  The researcher does not usually begin with an hypothesis, but is likely to develop one after collecting data.  The analysis and synthesis of the data provide the test of the hypothesis.  Systematic collection of information requires careful selection of the units studied and careful measurement of each variable.
Examples of Descriptive Research:
  • A description of how second-grade students spend their time during summer vacation
  • A description of the tobacco use habits of teenagers  
  • A description of how parents feel about the twelve-month school year
  • A description of the attitudes of scientists regarding global warming 
  • A description of the kinds of physical activities that typically occur in nursing homes, and how frequently each occurs
  • A description of the extent to which elementary teachers use math manipulatives
Correlational research attempts to determine the extent of a relationship between two or more variables using statistical data.  In this type of design, relationships between and among a number of facts are sought and interpreted. This type of research will recognize trends and patterns in data, but it does not go so far in its analysis to prove causes for these observed patterns. Cause and effect is not the basis of this type of observational research. The data, relationships, and distributions of variables are studied only. Variables are not manipulated; they are only identified and are studied as they occur in a natural setting. 
*Sometimes correlational research is considered a type of descriptive research, and not as its own type of research, as no variables are manipulated in the study
Examples of Correlational Research:
  • The relationship between intelligence and self-esteem 
  • The relationship between diet and anxiety 
  • The relationship between an aptitude test and success in an algebra course 
  • The relationship between ACT scores and the freshman grades 
  • The relationships between the types of activities used in math classrooms and student achievement 
  • The covariance of smoking and lung disease
Causal-comparative/quasi-experimental research attempts to establish cause-effect relationships among the variables.  These types of design are very similar to true experiments, but with some key differences.  An independent variable is identified but not manipulated by the experimenter, and effects of the independent variable on the dependent variable are measured. The researcher does not randomly assign groups and must use ones that are naturally formed or pre-existing groups. Identified control groups exposed to the treatment variable are studied and compared to groups who are not. 
When analyses and conclusions are made, determining causes must be done carefully, as other variables, both known and unknown, could still affect the outcome.   A causal-comparative designed study, described in a New York Times article, "The Case for $320,00 Kindergarten Teachers,"  illustrates how causation must be thoroughly assessed before firm relationships amongst variables can be made.
Examples of Correlational Research:
  • The effect of preschool attendance on social maturity at the end of the first grade
  • The effect of taking multivitamins on a students’ school absenteeism
  • The effect of gender on algebra achievement
  • The effect of part-time employment on the achievement of high school students
  • The effect of magnet school participation on student attitude
  • The effect of age on lung capacity 
Experimental research, often called true experimentation, uses the scientific method to establish the cause-effect relationship among a group of variables that make up a study.  The true experiment is often thought of as a laboratory study, but this is not always the case; a laboratory setting has nothing to do with it.  A true experiment is any study where an effort is made to identify and impose control over all other variables except one.  An independent variable is manipulated to determine the effects on the dependent variables.  Subjects are randomly assigned to experimental treatments rather than identified in naturally occurring groups
Examples of Experimental Research: 
  • The effect of a new treatment plan on breast cancer
  • The effect of positive reinforcement on attitude toward school
  • The effect of teaching with a cooperative group strategy or a traditional lecture approach on students’ achievement
  • The effect of a systematic preparation and support system on children who were scheduled for surgery on the amount of psychological upset and cooperation
  • A comparison of the effect of personalized instruction vs. traditional instruction on computational skill 
What is the basic methodology for a quantitative research design?
The overall structure for a quantitative design is based in the scientific method.  It uses deductive reasoning, where the researcher forms an hypothesis, collects data in an investigation of the problem, and then uses the data from the investigation, after analysis is made and conclusions are shared, to prove the hypotheses not false or false.  The basic procedure of a quantitative design is:
  1. Make your observations about something that is unknown, unexplained, or new.  Investigate current theory surrounding your problem or issue. 
  1. Hypothesize an explanation for those observations.
  1. Make a prediction of outcomes based on your hypotheses. Formulate a plan to test your prediction.
  1. Collect and process your data. If your prediction was correct, go to step 5. If not, the hypothesis has been proven false. Return to step 2 to form a new hypothesis based on your new knowledge.

  2. Verify your findings.  Make your final conclusions.  Present your findings in an appropriate form for your audience.
REFLECTION:  Copy and paste the Worksheet chart and questions into your Reflection Journal.  Then complete the chart and answer the reflection questions in the digital worksheet.