PAPER
QUANTITATIVE RESEARCH APROACHES AND DESIGN Lecturer : Prof. Dr. Idham Kholid, S.Pd, M.Pd
Arranged by Group 1 : Aliful Azizah (2211040157) Annisa Permata Sari (2211040018) Kanaya Thabita Yunan(2211040056)
Mell Yana (2211040074)
RADEN INTAN STATE ISLAMIC UNIVERSITY TARBIYAH AND
TEACHER FACULTY ENGLISH LANGUAGE
EDUCATION 2024
FOREWORD
Alhamdulillah, praise and thanks be to Allah Ta'ala. for His abundance of grace and grace so that the paper entitled, "Quantitative Research Approach and Design" can be completed properly. We hopes that this paper can increase knowledge and experience for readers about what violations or errors commonly occur in everyday language. Likewise, for the abundance of health and opportunities that Allah SWT has given us so that we can compile this paper through several sources, namely through literature review and through internet media.
On this occasion, we would like to thank all those who have encouraged us and motivation in making this paper assignment. To our parents who have contributed a lot for us, my supervisor, Prof.Dr. Idham Kholid, S.Pd, M.Pd. We hope that the information and material contained in this paper can be useful for readers. There is nothing perfect in the world, but Allah SWT. God is the Most Perfect, therefore we ask for constructive criticism and suggestions for the improvement of my next paper.
If there are errors in writing, or there is a discrepancy in the material we raise in this paper, we apologize. The drafting welcomes the widest possible criticism and suggestions from readers in order to make better paper work on the next occasion.
Bandar Lampung, 29 September 2024
Writer
LIST OF CONTENTS
FOREWORD... ii
LIST OF CONTENTS...iii
CHAPTER 1... 1
INTRODUCTION... 1
A. Background Of The Paper...1
B. Purpose of the Paper...1
C. Problem Formulation... 1
CHAPTER II...2
DISCUSSION...2
A. Definition of Quantitative Research Approach...2
B. Aspects the Quantitative Reasearch Approach...4
C. Quantitative Approach Design and Steps...6
CHAPTER III...11
CLOSING...11
A. Conclusion...11
REFERENCES...12
CHAPTER I
A. Background of the paper
Quantitative research design is a crucial step in ensuring the validity and reliability of research findings. Good design will minimize bias, increase measurement accuracy, and allow more precise interpretation of results. The choice of appropriate research design will depend largely on the research question, the variables studied, and the resources available.
Quantitative research is an approach that is widely used in various fields of science, ranging from social science, education, to health. This method aims to test hypotheses, explain phenomena, and measure certain variables using numerical data. In this context, quantitative research is very important because it can provide a clear and objective picture of a problem, as well as allow generalization of findings to a wider population. In recent years, the development of information and communication technology has brought significant changes in the way data is collected and analyzed.
More sophisticated statistical analysis tools and better data accessibility allow researchers to conduct more in-depth and complex analyses. However, despite the many advantages offered by quantitative methods, there are also challenges that need to be faced, such as issues of data validity and reliability, as well as the influence of external factors that can affect research results.
Therefore, this research aims to explore the use and effectiveness of quantitative methods in addressing a range of contemporary issues, as well as identify the advantages and disadvantages of these approaches. It is hoped that the results of this study can contribute to the development of future research methods and improve understanding of how quantitative data can be optimally utilized in various contexts. Translated with DeepL.com (free version)
B. Purpose of the paper
1. Knowing about quantitative research approach.
2. Knowing about quantitative Research Design and Steps.
C. Problem formulation
1. What is Quantitative research Approach?
2. What kind of Quantitative Research Design and Steps?
CHAPTER II DISCUSSION
A. Definition of Quantitative research approaches
Quantitative research is a systematic method that uses numerical data to test hypotheses and generalize findings to a larger population. This method focuses on objective measurement and statistical analysis to identify patterns, relationships, and differences in the phenomena being studied.Quantitative research is a systematic investigation that primarily focuses on quantifying relationships, behaviors, phenomena, or outcomes. By employing statistical, mathematical, or computational techniques, quantitative research seeks to establish patterns, test theories, and make predictions. This paper will explore various approaches to quantitative research and detail the designs commonly used in these studies.1
Quantitative research basically emphasizes objective and measurement statistical, mathematical or numerical analysis of data collected through polls and surveys.
Quantitative research prioritizes collecting numerical data and attempt to generalize it to several groups of people to explain a specific phenomenon. In the previous section it was explained about making questionnaires, how to collect quantitative data, how carry out the control process over the data and finally how to process the data (Babbie, 2010).
Definition of quantitative research according to severe experts2:
1. Creswell (in Alsa, 2012: 13) says that quantitative research is research that works with numbers, whose data are in the form of numbers (scores or values, ranks or frequencies). Quantitative research carries out its research in a systematic, controlled, empirical and critical manner regarding the hypothesis of assumed relationships between natural phenomena.
2. According to Creswell in Sugiyono (2015: 58) are: A quantitative study, consistent with the quantitative paradigm, is an inquiry into a social or human problem, based on testing a theory composed of variables, measured with numbers, and analyzed with statistical procedures, in order to determine whether the predictive generalizations of the theory hold true. Where the quantitative approach corresponds to the quantitative paradigm (method), which is an investigation of problems that occur in humans or society based on testing a theory composed of several variables measured by numbers and analyzed by statistical means, in addition to determining whether the theory used to predict it is true or not. The quantitative approach is written in the third person. The non- person-specific view removes the authors from the picture and helps create a sense of objectivity and distance between the researcher and the researched.
1 Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications
2 LISTYANISA, A. (2019). ANALISIS DAMPAK PENDAPATAN PT. POS INDONESIA (Persero) JAKARTA UTARA SEBELUM DAN SESUDAH ADANYA KIRIMAN LAZADA (Doctoral dissertation, Sekolah Tinggi Ilmu Ekonomi Indonesia (STEI) Jakarta).
Quantitative research is more likely to focus on various kinds of issues from the shape of the model, size, and sample population to be used.
3. In line with that Neuman still in Sugiyono (2015: 59) explains as follows:
Quantitative researchers are more concerned about issues of design, measurement, and sampling because their deductive approach emphasized detailed planning prior to data collection and analysis ... Quantitative researchers emphasize precisely measuring variables and testing hypotheses that are linked to general causal explanations. So quantitative research is more about method, measurement, and sample issues because the deductive approach emphasizes detailed planning prior to data collection and analysis, quantitative approaches emphasize the measurement of several variables and precise hypothesis testing linked to general causal explanations.
4. Sugiyono (2014: 54), quantitative research, is research by obtaining data in the form of numbers or graded qualitative data, while comparative research is a study that compares. Here the variable is still the same as the independent variable but for more than one sample, or at different times. comparative is a study that compares. Here the variable is still the same as the independent variable but for more than one sample, or at different times.
Quantitative research requires a discourse on the concept of science according to a quantitative view. Ary, Jacobs, and Razavieh define science as a research method that provides opportunities for researchers to test phenomena of interest. Furthermore, Ary, et al. explained two assumptions that underlie the way of scientists. First, a fundamental assumption made by scientists is that the events under investigation are according to a certain law of regularity. According to this assumption, there are no events in this world that occur capriciously. In the quantitative view, all natural phenomena have factors that precede them (antecenfactors).
This assumption refers to universal determinism. This is very different from the qualitative view that in this world many events are anomalous, incompatible or non- commutative with previous events/knowledge, and therefore there needs to be a new paradigm other than normal science. The second assumption is that truth is obtained only through direct observation. Scientists, according to this assumption, do not depend on authority as a source of truth, but depend on empirical evidence. There are several basic assumptions that apply to science, as follows:
a. That all phenomena in the universe are bound by rules or laws (orderly) and are in order (regulary).
b. That humans have the ability to follow all the rules of order of all phenomena in the universe. Every phenomenon (substance, condition, and process) does not occur by chance, but there is a cause and there are consequences for other phenomena. That scientific knowledge is only able to describe something that actually occurs in the universe, if that knowledge is empirical.3
3 Romlah, S. (2021). Penelitian Kualitatif dan Kuantitatif (Pendekatan Penelitian Kualitatif dan Kuantitatif).
Pancawahana: Jurnal Studi Islam, 16(1), 1-13.
Characteristics of Quantitative Research
Characteristics of quantitative research. Anderson and Biddle stated that there are main characteristics possessed by behavioral research (with a quantitative approach).
a. Quantitative research includes experimental research, which is a study that gives different treatments to different groups and non-experimental research, which is research that does not carry out manipulation and control in the sense that subjects are observed as they are then the relationship between variables is tested without making any changes.
b. Quantitative research illustrates objectivity, which is a methodological aspect in science that allows a researcher to test his ideas “outside” the subject under study.
c. In this research, statistical analysis is used, such as averages, frequencies, correlations, different tests and so on. d. In quantitative research, the problems, relationships, and methodology are simple and clear.
Philosophical Assumptions in Quantitative Research
Quantitative research is based on philosophical assumptions that influence how researchers approach research. These assumptions include:4
a. Objective Reality: This assumption states that reality is something objective and can be measured independently of the observer.
b. Determinism: This assumption states that all events have identifiable causes.
c. Theory Verification: This assumption states that the goal of research is to test and verify existing theories.
B. Aspects of the Quantitative approach
1. Methodological Approach Aspects In the quantitative approach, the types of approach fields are experiments, hard data, empirical, positivistic, real facts in society and statistics, experiments, surveys, structured interviews, and so on.
2. Conceptualization Aspects In the quantitative approach, the key conceptual types are variables, validity, reliability, significance, hypothesis, replication, and so on.
3. Aspects of Pioneers In the quantitative approach, positivistic figures such as Emile Durkhein, L. Guttman, Fred Kerlinger, Donald Cambell, and Peter Rossi.
Most of them are experts who believe in exact science with strong quantum formulas.
4. Aspects of Theoretical Orientation In the quantitative approach, the basis of the theory is functional structure, positivism, behaviorism, empirical logic and theoretical systems. They prioritize systematic, clear and definite theories. In the qualitative approach, the theoretical basis is symbolic interactionism, ethnomethodology, phenomenology, culture, and so on.
4 Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications.
5. Aspects of the Type of Science This field is rather blended and changes in nuances (range), meaning that it is difficult to specify (corridor, box) the science an sich. However, there is a tendency for sciences to have an ambivalent approach at the same time. Quantitative tendencies are found in engineering, science and nature, economics, psychology, sociology, computer science, and so on.
6. Objective or Target Aspects In the quantitative approach, the direction and focus of a study is through theoretical tests, building or compiling facts and data, statistical descriptions, clarity of relationships and predictions. This means that each step prioritizes axioms, formulas, and problems to solve and overcome problems directly.
7. Aspects of Correlation with Respondents In the quantitative approach, it is necessary to measure short term or long term, distance from the researched, assess as a full researcher of the researched, dominance of the researcher, and so on.
They confront the researcher person and the researched object with various actions, rules and norms.
8. Aspects of Instruments and Equipment In the quantitative approach, equipment such as questionnaires, inventories, computers, indices, measurements from formulas, and so on. Obviously they apply the application of formula techniques and certainty.
9. Approach to Population In the quantitative approach, rechecking is used in the form of control, validity, reification, obtrusiveness, and so on. They use clear controls with repetition of the process leading to the truth of the research objectives.
10. Design Aspects In the quantitative approach, they want a structured, organized, sequential design, a systematic chart. “Design is a detailed plan of operation”.
11. Field Data Collection In the quantitative approach, data collection is done through quantitative coding, calculation, measurement, and statistics. All of them are applied to a common benchmark and measured against that benchmark, to declare the evidence accepted or rejected.
12. Sampling Aspects In the quantitative approach, the number of samples must be clearly selected, in a randomized, structured manner, which is the experimental group and which is the control group. The sample must represent the population (representative).
13. Aspects of Data Analysis The quantitative approach uses deduction-based data analysis inference, conclusions from a collection of data, finally calculated through statistical calculations. Quantitative data analysis establishes limits that are accepted or rejected by existing theories.
14. Data Validity The quantitative approach uses controls in the form of statistical tools, measurements, and results that are relevant to the applicable formula.
15. Report Writing Aspects The quantitative approach writes reports according to a fixed formal chart, fixed content, complete and is the result of reports and test results with calculations from empirical research fields.5
C. Quantitative research design and Steps
Research design is basically a procedure, which is a planned and systematic way guided by certain scientific methods or rules. A planned and systematic way guided by certain scientific methods or rules in approaching research problems. in approaching research problems. A good research is always preceded by a strong research design.
The explanations below will outline in more detail the steps of developing a research design. More specifically, the research design we developed is aimed at conducting quantitative research on a sensitive topic. In contrast with qualitative research that usually focuses on single case studies, quantitative research usually tries to explain large phenomena with the aim of creating new insights. usually tries to explain large- sized phenomena with the aim of creating generalizations.6
Quantitative research design refers to the framework used to collect and analyze numerical data. This design determines how researchers will collect data, control variables, and analyze the results. Some commonly used quantitative research designs include:
Experimental Design: This design involves manipulating an independent variable to observe its effect on the dependent variable. Experimental design allows researchers to test causal relationships between variables.
Survey Design: This design involves collecting data from a sample population through questionnaires, interviews, or observations. Survey design allows researchers to measure opinions, attitudes, and behaviors of the population.
Correlational Design: This design aims to identify relationships between two or more variables. Correlational design does not test causal relationships, but it indicates the strength of the relationship between variables.
Descriptive Design: This design aims to describe the characteristics of a population or a particular phenomenon. Descriptive design does not test hypotheses, but it provides an overview of the topic being studied
Steps of quantitative research
Below we break down the quantitative research design into a more detailed explanation more detailed explanation. There are six key dimensions of research design which include7
5 Musianto, L. S. (2002). Perbedaan pendekatan kuantitatif dengan pendekatan kualitatif dalam metode penelitian.
Jurnal Manajemen dan kewirausahaan, 4(2), 123-136.
6 Brady, H. E., & Collier, D. (Eds.). (2010). Rethinking social inquiry: Diverse tools, shared standards. Rowman &
Littlefield Publishers.
7 Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications
1. Identification of the problem and research questions
Selection of problems usually always coincides with determining the research topic. Topics are general and can cover anything. Meanwhile, the problem is a bit The issues you want to examine further are more focused and specific in nature. Election The topic does not in itself present a research problem.
And clarity Problems are basically what differentiates research with journalistic reporting. This is because every problem usually contains assumptions and perhaps certain theoretical propositions. Therefore every researcher needs allocate special time to determine interesting research problems.
On the other hand, research questions are a further step after the problem has been formulated. Research questions have a very central position in a study.
This is due to the function of the research question itself as a 'path guide' researcher. Mistakes in asking research questions can have fatal consequences, ie misunderstanding of the phenomenon to be explaine Because its function is to explain phenomena, the basic elements in The research question is the existence of a dependent variable, namely a value or conditions whose existence depends on one or more other variables.
Dependent This variable will later become the researcher's 'proof goal' through written arguments derived from theory and data. In formulating research questions, in addition to suggesting that the questions Research has weight related to issues that are considered important by people academics. King et al (1994) suggest that every researcher places their questions in the context of existing literature. This is to be sure our academic contribution to the literature we choose, while also ensuring that research has a solid academic footing. The research question Unguided literature studies will usually be ignored by the academic community because considered not a serious study.8
2. Theories and hypotheses
If research questions are guiding the way, then theories and hypotheses are the lighting lamp. Theories give us perspective, while hypotheses helps us sort out which information is essential and which is necessary ignored. Understanding theory will be very helpful for researchers faced with piles of data and information. Without the guidance of theories and hypotheses, researchers can get stuck in prolonged descriptions.
In choosing a theory, choose a theory that can be falsified or proven wrong (King et al, 1994). Theories that cannot be falsified violate the basic nature of science which is dialectical. Practical advice from scientists regarding how to falsify done is by asking questions like this: “Case or findings like what can prove my theory wrong?” “Just what I need to prove my theory wrong?” If we can't find an answer on this question, the theory we choose cannot be falsified.
8 Brady, H. E., & Collier, D. (Eds.). (2010). Rethinking social inquiry: Diverse tools, shared standards. Rowman &
Littlefield Publishers.
Apart from that, quite often there are cases where a theory just doesn't work suitable to be applied to the selected context. With the data we collect, for example, we find that a fairly well-established theory turns out to be less relevant with research cases. In cases like this, minor revisions of a theory permitted as long as we can prove it through empirical research data (King et al, 1994).9
3. Operationalization of concepts and explanation of relationships between variables.
Operationalization of concepts is related to specific definitions of the main ideas of research. Concepts must be explained precisely and in a limited manner so that readers understand limitations of a research. Included in this limitation are various things what the researcher wants to explain, what is not included in the scope research, and how and what definitions of concepts are used. In research with sensitive topics, giving definitions, or even selecting definitions from a variety contested concepts can really help researchers get focus on the object research as well as helping sort out relevant data.
Take for example what is the definition of democracy. Scientists such as Joseph Schumpeter and Adam Przeworsksi understands democracy in a 'minimalist' way, namely a mechanism election of leaders through competitive elections. By this definition, if any leaders in a country are elected through non- competitive elections, for example because If a party wins an election through fraud, then that is not included in the category the two authors above. But there are also scientists who define democracy as public and participatory deliberation processes, or those that connect understanding democracy with economic development outcomes. These three definitions have respective literature references. And it's all up to us, what and why we adopt a particular definition and what is the justification. Clarity about The definition of this concept will make readers understand the researcher's explanation
better.
On the other hand, the relationship between variables indicates the process of linkage, association, correlation, even causality between two or more variables.
In the quantitative research tradition, Usually the relationship between these variables can be explained more clearly. This matter due to the quantitative research tendencies that usually explain his research into a model of the relationship between specific variables. Apart from that, the nature of the research is quantitative also always quantify any social phenomenon; how the value changes variable X will influence variations in the value of Y. This research can also explain the average effect of several independent variables on the dependent variable, so researchers can decipher more precisely which variables have the most effect strong against Y. Lastly, quantitative research is also relatively easier
9 Choi, J. W. (2011). Measuring the performance of an anticorruption agency: The case of the KPK in Indonesia.
International Review of Public Administration, 16(3), 45-63.
to carry out hypothesis testing (hypothesis testing). In this way a hypothesis can be derived to in several variables to test whether the hypothesis is accepted or rejected.10
4. Data collection and data collection
Regarding research interests, it is very important for researchers to report how the data was collected. Researchers must explain transparently data collection process. For example, if you are conducting an interview, what must be explained the background of the informants and how many there are. If you do a survey, you must explained who the respondents were, how the sample was drawn, how many there were respondents, and what is the margin of error? If you do clipping news, it must be stated what the source of the newspaper is, the periodization, and what the technique is Issue classification (if any) is carried out.
By reporting in a transparent manner data collection, readers can provide an assessment of the validity of the data we provide have. Apart from that, readers can also find out the shortcomings of the research when researchers are hampered by poor data quality. In this way researchers opens up the possibility of providing input to improve research forward.
The next step in data collection is how to use the data. In qualitative research this relationship between data collection and use sometimes it is reciprocal. But in quantitative research it is usually this relationship rather sequential where the researcher collects data first, conducts it cleaning, then determine how the data will be used. Use Data in this case must be guided by theory and research hypotheses. With this way we make connections between data and theory; whether the data confirms it or not reject the theory/hypothesis. A practical way to do this is to ask; “What type of data do I expect to prove that theory/hypothesis am I right/wrong?” From here researchers will be guided in determining the type and quantity necessary observations.11
5. Descriptive and causal analysis
The analysis section includes the final step of the research. Analysis will not be able to start before researchers have a big picture of how the problem is related, research questions, theories and hypotheses, relationships between variables, and data. In Quantitative research, analysis that is deductive in nature is more common than Qualitative research is more inductive in nature. This is due to research trends Quantitative research designs are more often developed aims to test a particular hypothesis. While the general trend towards Qualitative research is to refute or confirm a theory through findings, or the uniqueness of the case raised. In this paper we distinguish two types of analysis: descriptive analysis and analysis causal. Descriptive analysis means the researcher tries to explain particular things observation to get a general picture of the universe of a
10 Fowler Jr, F. J. (2013). Survey research methods. Sage publications.King, G., Keohane, R. O., & Verba, S. (1994).
Designing social inquiry: Scientific
11 helen, K., & Mahoney, J. (2015). Comparative-historical analysis in contemporary political science. Advances in comparative-historical analysis, 3-36.
phenomenon. Matter most commonly, for example, in public opinion surveys.
From the particular picture researchers get through surveys, researchers then try to understand perceptions population in a country. In qualitative research, the attempt to explain the universals of these particular things can also be found.
Researchers often carry out classifications observations to facilitate analysis. For example, by dividing observations into several typologies based on age, ideology, work background, education, and so on.
Descriptive analysis is also used when researchers want to describe the extent a concept applies or does not apply in the case under review. A concept that written with supporting arguments will help researchers make clarifications. Or conversely, researchers can also start a description of a particular condition which is then connected to a theoretical proposition so that researchers can provide a perspective in looking at a phenomenon. On the other hand, causal analysis is often also called inferential analysis, namely how the researcher explains the cause-and-effect relationship of the phenomenon under study. Connection Causation must not be simply assumed, but must be proven through scientific procedures whose validity can be tested through data, assumptions and theories. If the procedure Inferential analysis has been carried out, the researcher can confidently state a 'causal claim' of the phenomena he studied.
6. Explanation of the implications of the research.
The final step of research design is to write down what the implications of our research are. The implications of research can mean many things; better understanding of references literature, improvements and strengthening of literature, suggestions and future research agenda after evidence is found, and can also explain practical policy implications. Research implications are written at the end and usually begin with restating the research problem and its main findings.
From there, you can see it what is the conclusion of this research.12
12 helen, K., & Mahoney, J. (2015). Comparative-historical analysis in contemporary political science. Advances in comparative-historical analysis, 3-36.
CHAPTER III CLOSING
A. Conclusion
Quantitative research is an effective approach in collecting and analyzing data to understand social and scientific phenomena. Through the systematic use of statistical methods, quantitative research can identify significant patterns, relationships, and trends between the variables under study. The results show that the data obtained are reliable and provide concrete information for decision-making. In addition, the study also highlights the importance of good research design, selection of a representative sample, and the validity and reliability of the instruments used. Despite its advantages, quantitative research also has limitations, such as the lack of depth in understanding the context. Overall, quantitative research is a powerful tool in the world of research, and its results can make a significant contribution to the development of science and practical policy.
REFERENCES
Brady, H. E., & Collier, D. (Eds.). (2010). Rethinking social inquiry: Diverse tools, shared standards. Rowman & Littlefield Publishers.
Choi, J. W. (2011). Measuring the performance of an anticorruption agency: The case of the KPK in Indonesia. International Review of Public Administration, 16(3), 45-63.
Fowler Jr, F. J. (2013). Survey research methods. Sage publications.
King, G., Keohane, R. O., & Verba, S. (1994). Designing social inquiry: Scientific inference in qualitative research.
Princeton university press. Thelen, K., & Mahoney, J. (2015). Comparative-historical analysis in contemporary political science. Advances in comparative-historical analysis, 3-36.
