MULTI-METHODOLOGY DALAM KAJIAN LINGKUNGAN DAN PEMBANGUNAN Bahan kajian MK Interdisciplinary...

MULTI-METHODOLOGY

DALAM KAJIAN LINGKUNGAN DAN PEMBANGUNAN

Bahan kajian MK Interdisciplinary Environmental Studies

Disarikan olehSoemarno, pm-pslp ppsub 2010

Multi-methodology

Multimethodology, mixed methods research, compatibility thesis or pragmatist paradigm IS an

approach to research that combines the collection and analysis of quantitative and qualitative data.

The term 'multimethodology' appears to be more widely used in operations research than in other branches of

social science.

This approach has been gaining in popularity since the 1980s

METODE RISET

Approaches to studying human behavior using the

scientific method (systematic, empirical observation)

The five research methods we’ll be looking at are….

• Naturalistic observation

• Case studies

• Surveys & Interviews

• Quasi-experiment

• Controlled experiments

Defining mixed methods

Combining quantitative and qualitative methods sounds like a good idea.

Using multiple approaches can capitalise on the strengths of each approach and offset their

different weaknesses.

It could also provide more comprehensive answers to research questions, going beyond the

limitations of a single approach.

Classification of combinations of research methods

There are many ways in which different research methods can be combined in social research and we’ll look at these in later units in this module.

But first, let’s try to classify the types of combination, if we can.

In the research literature, a distinction is often made between multi-method and mixed method

studies.

Multi-method studies

Multi-method studies use different methods of data collection and analysis within a single research paradigm.

For example, you might conduct a qualitative study in which you observe as a participant and also interview

people.

Or in a quantitative study you might carry out an attitude survey of students and also collect information from

computer records about the frequency of ‘hits’ in the use of web-based course materials.

In other words, you make use of methods that are broadly compatible within a paradigm or a set of beliefs and

values.

Mixed method studies

Mixed method studies attempt to bring together methods from different paradigms.

In a mixed method study you might conduct a series of semi-structured interviews with a small number of students and also carry out a large-scale survey.

This kind of integration, of qualitative with quantitative methods, is also referred to sometimes as multi-strategy

research.

In this module, we shall use the terms multi-method and mixed method to maintain the distinction described above.However, you will find that there is little consistency in the

use of the terms multiple and mixed methods in the research literature.


At the next level of complexity, the meaning given to ‘mixed methods’ is influenced by how methods

are combined. For instance, you might collect information by using each method concurrently (at the same time), or sequentially if your aim is to use one method to inform another (say, interviewing

before surveying).


These two approaches are different. The first (MULTI) is more like two parallel studies that only come together once the data are being analysed, whereas, in the second (MIXED) , the aim is to use the methods in a more integrated

way.The actual methods used may be the same, but

the ways in which they are sequenced and combined can make a big difference in the process of conducting the study and in the

results.

Multi-method designs

Multi-method designs are generally intended to supplement one information source with another, or ‘triangulate’ on an issue by using

different data sourcesto approach a research problem from different points of view.

There are two types:

A1. Multi-method quantitative studies stay within a quantitative paradigm but use more than one method of data collection. One example might be the use of a survey mailed to distance students used in conjunction with

other data collected from the same students from other sources – perhaps student record data.

This kind of research design might allow you to crosscheck between (for example) students’ opinions of the assessment process and their actual

assessments, or the dates they returned assignments.

Multi-method designs

Multi-method designs are generally intended to supplement one information source with another, or ‘triangulate’ on an

issue by using different data sourcesto approach a research problem from different points of view.

There are two types:

A2. Multi-method qualitative methods might combine student interviews, observations made of email discussions and staff interviews. Again the key

design idea is to cross-check between sources and to supplement one kind of data with another.

Mixed methods designs

Mixed methods designs are conceptually more complex.They may provide a basis for triangulation but, more often, they become the source of different ways of

conceptualising the problem.

They might set out to look at the same things from different points of view, but it often turns out that the

viewpoint implies such different ways of seeing that the lines of sight do not converge.

B1. Mixed method studies might include a survey followed up by detailed individual interviews, or

observations used as the basis for constructing a questionnaire.

Mixed methods designs

B2 The final category ‘mixed model studies’ requires some explanation. In an earlier book

Tashakkori and Teddlie (1998) extend the issue of mixing methods to a set of broader considerations

than the use of different methods per se.They argue that the issues are not narrowly about method, but also involve mixes of methodology

(i.e. the ‘logic of methods’).This might sound abstract but it has significant

implications.

It means looking beyond stitching together methods from different paradigms and instead considering other

aspects of research design, specifically:

1.Overall inquiry purpose – whether the aim is to confirm or refute hypotheses or whether it is

more exploratory

2. Instrument design data collection – whether qualitative or quantitative

3.Data analysis and inference – whether statistical or qualitative.

Case study and mixed methods

Case studies are research and evaluation studies that focus on specifics andgive an account of the

instance in action.

A case study can describe a project, a course, an institution or a particular innovation.

Its value lies in its capacity to provide vicarious experience to the reader – to give you the feeling of ‘being there’ and perhaps to set you thinking about how you might respond to dilemmas and conflicts

as events unfold.

Case study and mixed methods

Generally, case studies are not very good as sources of theory or explanation that goes

beyond the conditions in which they are located.

They are more effective as a source of interpretations and ideas than as a way of

verifying them or providing generalisations that can be confidently applied system-wide.

Case study, measurement and mixed methods

The term case study is often taken to be synonymous with qualitative methods, for to study ‘cases’ seems to imply

looking up close and being drawn into the world of alternative perceptions and different views about common and shared tasks and workplace contexts. But there is no

reason why cases cannot be measurement-based. Accountants might look at a school or a course, a hospital or

a project primarily through a balance sheet and a social statistician or demographer could approach the study of a neighbourhood or a local service through an analysis of

census data.These methods can be used alone or combined with

qualitative methods to investigate cases by mixed method approaches.


In fact many quantitative research approaches are easier to use in a mixed method context now than they used to be, since many databases are accessible, and available for

interrogation on-line.

Indeed such approaches have become much more common as many education systems have accumulated achievement test data on total populations of students (where before they

would have had mostly small patchy samples).So the scene is set for mixing methods.

Databases can be searched for anomalous figures or gaps and contradictions in the numerical data that can be used as

leads to be followed to identify specific case studies.


Notice the methodological shift involved here.

If we use numerical data bases in this way – to identify particular cases for investigation – then, in effect, we are treating the quantitative material in an

exploratory manner (inductively) and using qualitative methods to identify ‘hard’ data that offers

explanations and identifies causes (deductively).

Strengths of Mixed Research

1. Words, pictures, and narrative can be used to add meaning to numbers.

2. Numbers can be used to add precision to words, pictures, and narrative.

3. Can provide quantitative and qualitative research strengths .4. Researcher can generate and test a grounded theory.5. Can answer a broader and more complete range of research

questions because the researcher is not confined to a single method or approach.

6. The specific mixed research designs discussed in this article have specific strengths and weaknesses that should be considered. A researcher can use the strengths of an additional method to overcome the weaknesses in another method by using both in a research study.

7. Can provide stronger evidence for a conclusion through convergence and corroboration of findings.

8. Can add insights and understanding that might be missed when only a single method is used.

9. Can be used to increase the generalizability of the results.10. Qualitative and quantitative research used together produce more

complete knowledge necessary to inform theory and practice.

Weaknesses of Mixed Research

1. Can be difficult for a single researcher to carry out both qualitative and quantitative research, especially if two or more approaches are expected to be used concurrently; it may require a research team.

2. Researcher has to learn about multiple methods and approaches and understand how to mix them appropriately.

3. Methodological purists contend that one should always work within either a qualitative or a quantitative paradigm.

4. More expensive.5. More time consuming.6. Some of the details of mixed research remain to be worked out

fully by research methodologists (e.g., problems of paradigm mixing, how to qualitatively analyze quantitative data, how to interpret conflicting results).

Using a multi-method qualitative approach to examine collaborative relationships

Mixed methods research

There are two broad classes of research studies that are currently being labeled “mixed methods

research”:

single approach designs (SADs) in which additional qualitative and/or quantitative strategies are employed to enhance research quality; and

mixed approach designs (MADs). These definitions require that a distinction be made between

research strategies and research approaches.


A research strategy is a procedure for achieving a particular intermediary research objective—such as sampling, data

collection, or data analysis. We may therefore speak of sampling strategies or data

analysis strategies.

The use of multiple strategies to enhance construct validity (a form of methodological triangulation) is now routinely

advocated by most methodologists.

In short, mixing or integrating research strategies (qualitative and/or quantitative) in any and all research undertaking is now considered a common feature of all good research.

http://en.wikipedia.org/wiki/Triangulation_(social_science)


A research approach refers to an integrated set of research principles and general procedural guidelines.

Approaches are broad, holistic (but general) methodological guides or roadmaps that are associated with particular

research motives or analytic interests.

Two examples of analytic interests are population frequency distributions and prediction.

Examples of research approaches include experiments, surveys, correlational studies, ethnographic research, and

phenomenological inquiry.


Each approach is ideally suited to addressing a particular analytic interest.

For instance, experiments are ideally suited to addressing nomothetic explanations or probably cause;

surveys—population frequency descriptions, correlations studies—predictions;

ethnography—descriptions and interpretations of cultural processes;

and phenomenology—descriptions of the essence of phenomena or lived experiences.


In a single approach design (SAD) only one analytic interest is pursued.

In a mixed approach design (MAD) two or more analytic interests are pursued.

NOTE:

a mixed approach design may include entirely “quantitative” approaches such as combining a survey and an

experiment; or entirely “qualitative” approaches such as combining an ethnographic and a phenomenological

inquiry.


A word of caution about the term “multimethodology”. It has become quite common place to use the terms "method" and "methodology" as synonyms (as is the case with the

above entry). However, there are convincing philosophical reasons for

distinguishing the two.

"Method" connotes a way of doing something — a procedure.

"Methodology" connotes a discourse about methods—i.e., a discourse about the adequacy and appropriateness of

particular combination of research principles and procedures.


The terms methodology and biology share a common suffix "logy." Just as bio-logy is a discourse about life—all kinds of life; so too, methodo-logy is a discourse about methods

—all kinds of methods.

It seems unproductive, therefore, to speak of multi-biologies or of multi-methodologies.

It is very productive, however, to speak of multiple biological perspectives or of multiple methodological perspectives.


Desirability

The case for multimethodology as a strategy for intervention and/or research is based on four observations:

Narrow views of the world are often misleading, so approaching a subject from different perspectives or paradigms may help to gain a holistic

perspective

There are different levels of social research (ie: biological, cognitive, social, etc), and different methodologies may have particular strengths

with respect to one of these levels.

Using more than one should help to get a clearer picture of the social world and make for more adequate explanations

Many existing practices already combine methodologies to solve particular problems, yet they have not been theorised sufficiently

Multimethodology fits well with postmodernism.

http://en.wikipedia.org/wiki/Paradigm


FeasibilityThere are also some hazards to multimethodological

approaches. Some of these problems include:Many paradigms are at odds with each other. However, once

the understanding of the difference is present, it can be an advantage to see many sides, and possible solutions may

present themselves. Cultural issues affect world views and analyzability.

Knowledge of a new paradigm is not enough to overcome potential biases; it must be learned through practice and

experience. People have cognitive abilities that predispose them to particular paradigms. The logical thinker can more easily

understand and use quantitative methodologies. It is easier to move from quantitative to qualitative, and not the

reverse.


Conclusion

Multimethodology is desirable and feasible because it gives a more complete view, and because the requirement during the different phases of the intervention (or research project) make very

specific demands on a general methodology.

While it is demanding, it is more effective to choose the right tool for the job at hand.


Criticism

Multimethodology is criticized by the adherents of incompatibility thesis - particularly post-

structuralist and post-modernists.

Its critics argue that multimethodology is inherently wrong because quantitative and qualitative research paradigms should not be mixed.

Operations research

Operational research, also known as operations research, is an interdisciplinary mathematical science that focuses

on the effective use of technology by organizations. In contrast, many other science & engineering disciplines

focus on technology giving secondary considerations to its use.

Employing techniques from other mathematical sciences --- such as mathematical modeling, statistical analysis, and mathematical optimization --- operations research arrives at optimal or near-optimal solutions to complex decision-

making problems.

Operations research

Because of its emphasis on human-technology interaction and because of its focus on practical applications,

operations research has overlap with other disciplines, notably industrial engineering and management science,

and draws on psychology and organization science.

Operations Research is often concerned with determining the maximum (of profit, performance, or yield) or minimum

(of loss, risk, or cost) of some real-world objective.

Originating in military efforts before World War II, its techniques have grown to concern problems in a variety of

industries

Operational research encompasses a wide range of problem-solving techniques and methods applied in the pursuit of improved

decision-making and efficiency.

Some of the tools used by operational researchers are statistics, optimization, probability theory, queuing theory, game theory, graph

theory, decision analysis, mathematical modeling and simulation. Because of the computational nature of these fields, OR also has

strong ties to computer science.

Operational researchers faced with a new problem must determine which of these techniques are most appropriate given the nature of the system, the goals for improvement, and constraints on time and

computing power.

Work in operational research and management science may be characterized as one of three categories:

1. Fundamental or foundational work takes place in three mathematical disciplines: probability, optimization, and dynamical systems theory.

2. Modeling work is concerned with the construction of models, analyzing them mathematically, implementing them on computers, solving them using software tools, and assessing their effectiveness with data. This level is mainly instrumental, and driven mainly by statistics and econometrics.

3. Application work in operational research, like other engineering and economics' disciplines, attempts to use models to make a practical impact on real-world problems.

The major subdisciplines in modern operational research, as identified by the journal Operations Research, are:

1. Computing and information technologies 2. Decision analysis 3. Environment, energy, and natural resources 4. Financial engineering 5. Manufacturing, service sciences, and supply chain

management 6. Policy modeling and public sector work 7. Revenue management 8. Simulation 9. Stochastic models 10.Transportation.

What position does the mixed researcher take on the compatibility thesis and pragmatist philosophy?

According to the mixed research paradigm, researchers should :

1. Use the pragmatist philosophy (especially in terms of mixing methods is a way that works) and

2. Follow the compatibility thesis (i.e., quantitative and qualitative are compatible and they can be fruitfully

mixed in many ways that can work quite well).

Why is the fundamental principle of mixed research important?

According to the fundamental principle of mixed research, the researcher should use a mixture or combination of

methods that has complementary strengths and nonoverlapping weaknesses:

1. This principle is important because provides researcher with a logic for mixing quantitative and qualitative

research approaches. 2. Mixing quantitative and qualitative approaches in a

haphazard way will produce undesirable results. 3. Mixing should be systematic and well though out by the

researcher when planning and designing a research study.

Give an example of a within-stage mixed model research study.

In within-stage mixed model research, quantitative and qualitative approaches are mixed within one

or more stages of research.

A simple example would be a study where you constructed a questionnaire that is composed of closed-ended items (quantitative approach) and open-ended

items (qualitative approach).

Give an example of an across-stage mixed model research study.

In across-stage mixed model research, quantitative and qualitative approaches are mixed across at least two of

the stages of research.

1. A simple example would be a study where the researcher wishes to explore why people willingly

handle snakes in certain churches (qualitative purpose); the researcher goes to the churches and observes the

services and informally interviews some church members (qualitative data collection); during data

analysis, the researcher enters all of the verbal data into a computer program and then obtains word counts and

calculates the percentages for different responses (quantitative data analysis).

Give an example of an across-stage mixed model research study.

In across-stage mixed model research, quantitative and qualitative approaches are mixed across at least two

of the stages of research.

2. In the above example, the across-stage model mixing took place from the qualitative data collection to the

quantitative data analysis.

3. For additional across-stage mixed model designs, take a look at follow figure. Here it is for your

convenience.

In across-stage mixed model research, quantitative and qualitative approaches are mixed across at least two of the stages of research.

What is the difference between mixed model research and mixed method research?

Here are the definitions:

Mixed model research = The method where quantitative and qualitative approaches are mixed within or across the stages of the research process. This is where you use the within-stage mixing approach or the across-stage mixing

approach.

Mixed method research = The method where a quantitative phase and a qualitative phase are included in the overall research study. This is like having a quantitative and a

qualitative mini-study in the overall research study.

What is the difference between a sequential and a concurrent design feature?

One major dimension on which mixed method designs are differentiated is the time dimension. The time dimension is either sequential or concurrent. A sequential time order means that the qualitative and quantitative phases are conducted one after the other. A concurrent time order means that the quantitative and

qualitative phases occur at approximately the same time—this is like running parallel mini-studies.

Note that a sequential design is important when the results of one phase will be needed to inform the next phase and when the nature of the questions require that a phase occurs after or before another

phase. A concurrent design can be done when both kinds of information are needed, but they can be collected at roughly the

same time without causing any problems (logistically or informational/theoretical).

What are the eight stages of the mixed research process?I’m going to provide Figure 14.4 here, which lists the eight stages.

What is the difference between quantizing and qualitizing, and are these used in mixed method or

mixed model designs?

Quantitizing means that you convert qualitative data into quantitative data.

Qualitizing means that you convert quantitative data into qualitative data.

What kinds of validity might be relevant in a mixed design?All of the types of validity used in quantitative and qualitative research can be

relevant in a mixed research study because you want the quantitative and qualitative parts to be trustworthy and defensible.

On the quantitative side, the primary kinds of validity include:Statistical conclusion validityInternal (causal) validityExternal (generalizing) validityConstruct (measurement) validity On the qualitative side, the primary kinds of validity include:Descriptive validity Interpretative validity Theoretical validity Internal validity (if any cause and effect issues are addressed qualitatively) External validity (if one hopes to make generalizations based on the qualitative data) All of the above forms of validity are discussed in the lecture for Chapter 8. Note that types of validity specifically developed for mixed research are currently being developed.

What are the four potential problems involved in writing and attempting to publish a mixed research report?

1. Quantitative and qualitative research have traditionally

used different styles of writing; therefore, it can be challenging to strike a balance between the two forms of

writing.

2. Your audience might not be well versed in both quantitative and qualitative research; therefore, you must be sure to define all specialized terms that are

used so that either type of reader can clearly understand what you are saying.

What are the four potential problems involved in writing and attempting to publish a mixed research report?

3. Mixed research reports can be lengthy (especially mixed

method studies) because they include qualitative and quantitative parts. This can be a problem when you want to publish your study and journals have page limitations

that you have to deal with.

4. Mixed research is still an emerging field; therefore, some people you deal with (e.g., reviewers and other readers of your report) may not be open to the use of

both qualitative and quantitative approaches.

IJMRAInternational Journal of Multiple Research Approaches

is an international peer-reviewed journal for timely publication of global research, scholarship, educational,

researcher and practitioner perspectives on multiple, hybrid (outcome of unusual blending), synergistic (combined effect), integrated and cultural research approaches (be these Indigenous, institutional, or

community based) including the Asian, Arctic, Pacific, Latin American and African regions, as well as European

and North American.

The journal's primary focus is effectively to combine various theoretical frameworks, methodologies and

methods to address current research questions appropriately.

IJMRAInternational Journal of Multiple Research Approaches covers:

1. Multiple, hybrid, synergistic, integrated, cultural, mixed qualitative and quantitative empirical research approaches

2. Theoretical and conceptual articles on methodological and ethical dilemmas and advances

3. Critical perspectives and proposals for the management of technical issues (eg, software development and data handling)

4. Discussion of the philosophical issues, practical problems and benefits associated with multiple, hybrid, synergistic, integrated and cultural approaches including theoretical frameworks, methodologies, data collection, management and analysis methods and the different forms of transformation and representation

5. Literature reviews - including those from theses - on methodological trends/advances

6. Articles on methodology education, technologies and learning techniques

7. Practitioner perspectives, experiences from the field and case applications of methodologies and results

TERIMA KASIH

SEMOGA BERMANFAAT

Soemarno, pslp-pdklp-ppsub

MULTI-METHODOLOGY DALAM KAJIAN LINGKUNGAN DAN PEMBANGUNAN Bahan kajian MK Interdisciplinary...

Documents

Transcript of MULTI-METHODOLOGY DALAM KAJIAN LINGKUNGAN DAN PEMBANGUNAN Bahan kajian MK Interdisciplinary...