Research Study Quantitative

Question # 1

Purposes and benefits of sections of Independent study

My independent study is related to quantitative research model. Purpose of the quantitative research is to do numerical summaries, generalizations across populations and comparisons between populations. It includes few variables (Delay time, work order, number of different products) and many cases (Five sets of data with each set consisting of 500 products). These quantitative research methods use experimental designs. The various experimental methodologies are:

• Quasi Experimental Designs

• RCT: Randomized Controlled Trials

• Baseline Data

• Posttest Only Design

• Longitudinal Design

Out of these experimental methodologies, my study falls under randomized controlled trails, where I generate a random data of five sets each set consisting of 500 different kinds of products.

• Introduction

Purpose: The purpose of my study introduction is to provide background information for the readers for the research reported in the study. It establishes a framework for the research, so that readers can understand how it is related to other research (Creswell, 2003 p.73). It also establishes the issue or concern leading to the research by conveying information about a research problem (Creswell, 2003 p.74). In this, the problem is best addressed by understanding the factors or variables which are the process time, product order that influence an outcome – delay time (Creswell, 2003 p.75). It provides the understanding of the problem that explains or relates to an outcome – delay time and helps the researcher best understand and explain the problem why the delay time is to be minimized (Creswell, 2003 p. 76).

• The research problem in the study

• Guiding research questions

• Reviewed studies addressing the problem

• Deficiencies in past literature and limitations

• Importance of a study for an audience

Benefits: By writing an effective introduction chapter, a reader can figure out the problem leading to the study i.e., how the delay time is optimized by arranging the production work order, reviewing the literature about the problem to find whether there are any related theories that is done by other investigators, identifying deficiencies in the literature about the problem, targeting audiences and notifying the significance of the problem for this audience (Creswell, 2003 p.73).

• Literature Review

Purpose: The purpose of the literature review is to share with the reader the results of other studies that are closely related to the study being reported (Creswell, 2003 p.29). It relates a study to the larger ongoing dialogue in the literature about a topic, filling in gaps and extending prior studies (Cooper, 1984; Marshall & Rossman, 1999). It provides a framework for establishing the importance of the study as well as a benchmark for comparing the results of a study with other findings. All or some of these reasons may be the foundation for writing the scholarly literature into a study (Miller, 1991).

Benefits: The literature review helps to substantiate the problem and also suggests possible questions or hypotheses that need to be addressed (Creswell, 2003 p.46).

• Methodology

Purpose: The purpose of methodology chapter is to bring focus on survey and experimental modes of inquiry. You will also explain the methodology you are using, why you chose that methodology and why you chose not to use other methods. The method that was used to collect data is explained in detail like how did I generated random data of five sets with each set consisting of 500 products using Microsoft Excel ad procedure I followed to find the real-time delay time. The reader will exactly know what was done with the collected data, to the point that he or she can replicate the study to get similar results.

Benefits: With the help of methodology chapter, audiences can recognize the variation that exists in the qualitative, quantitative and mixed method studies, why I chose a quantitative study for the research problem I defined then it advances general guideline for procedures of the study. These guidelines include a discussion about the general characteristics of the study if the audiences are not familiar with the approach to research.

(Source: Classroom material by Dr. Lynda Kenney)

• Results

Purpose: The purpose of results chapter is to make a well-organized and objective presentation of the results by examining the collected data and application of either the descriptive or inferential statistical methods. Then the tables, graphs and figures of the analyzed data are also presented for sufficient support description to permit the reader to interpret them quickly and accurately (Leedy & Ormrod, 2005).

Benefits: The benefits of the results chapter is for readers to quickly interpret the conclusions and significance with the help of the tables, graphs, charts and figures obtained from the interpretation and analysis of the data.

• Flow Chart

Purpose: The purpose of the flow chart is to explain the process of optimization of the production work order in a step-by-step process that is described in the study.

Benefits: It makes the readers understand easily at a glance what has done in the entire study. It also helps the researcher to make and follow the created flow chart while analyzing the data.

• Discussion

Purpose: The purpose of the discussion chapter is to highlight the main theories and conclusion used in the research study so that a reader can easily figure out what theories the researcher used in implementing and analyzing the data. Each major conclusion is clearly explained and compared with the results of the similar work by other investigators. Then, the researcher continually connects her findings with the theoretical frameworks. Any new or unusual results are also explained(Leedy & Ormrod, 2005). If the researcher is not sure about the significance of the results or could not understand the phenomenon of the data, it is sometimes worthwhile to present a speculative discussion outlining several possible outcomes by alerting the readers that such a discussion is speculative.

Benefits: The benefits of the discussion chapter are to make grand conclusions which support the subsequent paragraphs. Here, the entire conclusions, implications or the effects due to each conclusion including the minor and major effects are presented. The discussion also includes the method of computation or derivation of the study. Such situation arises when one figure is derived from preceding figures. If the application or method is involved, then a complete example with the method is to be explained for complete understanding to the reader. Finally, explained the significance and outcomes of the study.

• Conclusions

Purpose: The purpose of the conclusions chapter is to make a summary of the conclusions that are presented in previous chapter. The researcher also points out both what are found and what are not found. It is also the section examined by the prospective reader with limited available time (Leedy & Ormrod, 2005).

Benefits: Although the researcher has previously presented each of the conclusions, conclusions chapter tell us the reader the ultimate effect or the benefit of the study. In my study, I have explained how the delay time is minimized or optimized by arranging the production work order so that it is quite helpful to readers, who might easily lose track of some important conclusions as they read earlier portions of a study(Leedy & Ormrod, 2005). In addition to this, a prospective reader will able to quickly examine the research in limited time. I explained the benefits of my study that findings of this research will aid industries, retails stores by demonstrating how the algorithm is currently used, and how retail stores can assist customers to implement universal algorithm. Industries may benefit from models of evaluating arrangement of parts of a product on an assembly line.

Question # 2

Framework Elements of Research:

For every research proposal, a definite framework exists to follow a certain pattern. Creswell (2003) suggested that from lots of different types and terms in the literature, he focused on three approaches: quantitative, qualitative, and mixed methods approach. The first two has been available for decades, and the last is new and still developing in form and substance. To understand them, we need to consider three framework elements: philosophical assumption about what constitute knowledge claims, general procedures of research called strategies of inquiry, and detailed procedure of data collection, analysis and writing, called methods.

For that Creswell (2003) proposed (which was developed by Crotty) three questions to the design of research:

• What knowledge claims are being made by the researcher?

• What strategies of inquiry will inform the procedures?

• What methods of data collection and analysis will be used?

Framework Elements of Quantitative Research

Knowledge claims:

Stating a knowledge claim means that researcher start with a project with certain assumptions about how we will learn and what we will learn during their inquiry. These are called as paradigms. Philosophically, researchers make claims about what is knowledge (ontology), how we know it (epistemology), what values go into it (axiology), how we write about it (rhetoric), and the process for studying it (methodology). There are four schools for knowledge claims as what follow. Those are post positive knowledge claims, socially constructed knowledge claims, advocacy or participatory knowledge claims and finally pragmatic knowledge claims.

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For quantitative research, the knowledge claims are post positivism which includes determination, reductionism, empirical observation and measurement, and theory verification. Post positivism refers the thinking after positivism; challenging the absolute truth and recognizing that we can not be “positive” about claims of knowledge when studying the behaviors and action of human. Traditionally, the post positivist assumptions have cited claims about what evidences knowledge. Post positivism reflects in determining the effects or outcomes, examining the causes that reflect the outcomes by doing experiments, reducing the ideas into a small, set of ideas to test such as variables that constitute hypothesis and research questions, developing numeric measures of observations and studying the behavior of individuals. The problem studied by post positivist reflects a need to examine causes that influence outcomes. It is also reductionism; testing selected variables that constitute hypothesis and research questions, so it is based on careful observation and measurement of the objective reality in the world. Researching is for test or refining the existing laws or theories.

Strategies of inquiry:

A stage of inquiry in quantitative research includes numerical summaries, generalizations across populations and comparisons between populations.

Strategies of inquiry provide specific designs for procedures in the research design. Like knowledge claims, strategies have multiplied over the years as the computer technology has pushed forward data analysis and the ability to analyze complex models. Strategies associated with quantitative research were those that invoked the post positivist perspectives. These include true experiments and less vigorous experiments called quasi-experiments and correlational studies (Campbell & Stanley, 1963), and specific single-subject experiments (Cooper, heron, & Heward, 1987). But, these days, quantitative research strategies involved complex experiments with many variables and treatments like factorial designs and repeated measure designs. Strategies associated with quantitative approach are:

Experiment: It is about random assignment of subject to treatment conditions and includes quasi-experiment with nonrandomized design. My study used experimental strategy for generating the randomized data and analyzing the data with Microsoft office tools.

Non-experimental designs, such as Surveys: it is studying by using questionnaires or structured interviews with the intent of generalizing from sample to a population. These include cross-sectional and longitudinal studies using questionnaires or structured interviews for data collection, with the intent of generalizing from a sample to a population (Babbie, 1990)

Research methods:

The third major element that goes into a research approach is the specific methods of data collection and analysis. For quantitative research, the research methods I used are predetermined instrument based questions such as performance data, attitude data, observational data and census statistical data using Microsoft Excel. I considered full range of possibilities for data collection in the study by organizing these research methods with the use of closed-ended versus pen-ended questions and their focus on numeric versus non-numeric data analysis.

Question # 5

Validity and generalizability aspects of quantitative, qualitative and mixed methods research:

Qualitative research – validity

The degree to which the interpretations of the data accurately describe the phenomenon under investigation is known as validity. Validity is seen as a strength of the qualitative study which is used in determining whether the findings are accurate from the standpoint of the researcher, the participant, or the readers (Creswell & Miller, 2000).In addition to validity, the terms used are trustworthiness, authenticity, and credibility. There are eight primary strategies, organized from most frequently used and easy to implement to those occasionally used to and difficult to implement. Various qualitative procedures should be used to make a research validate. Some of the procedures are qualitative research paradigm and ethnographic research design.

Methods for establishing the validity are:

• Negative case analysis – Presenting the negative or discrepant information that runs counter to the themes

• Audit trail – Clarifying the bias the researcher brings to the study

• Prolonged field experience – Spending prolonged time in the field to develop an in-depth understanding of the phenomenon under study

• Data triangulation – triangulate different data sources of information by examining evidence from the sources and using it to build a coherent justification

• Member checking – to determine the accuracy of the qualitative findings

• Rich, thick description

Quantitative research – validity

The degree to which the evidence supports that the interpretations of the data are correct and that the manner in which the interpretations are used is appropriate.

Threats to validity: There are several threats to the validity that raise the potential issues about the researcher ability to conclude the intervention affects of an outcome. They are internal threats, external threats, statistical conclusion threats, and construct validity threats.

• Internal validity threats are experimental procedures, treatments, or experiences of the participants that threaten the researcher’s ability to draw correct inferences from the data in an experiment. These involve due to inadequate procedures like changing the instrument or a tool during an experiment, changing the control group participants under study etc.

• External validity threats arise when the researcher draws incorrect inferences from the sample data to other persons, other settings, and past or future situations.

• Statistical conclusion validity arises when experimenters draw inaccurate inferences from the data because of inadequate statistical power or the violation of the assumptions.

• Construct validity threat arises when investigators use inadequate definitions and measure of variables.

Methods of establishing validity

• Experiment review

• Data triangulation

• Participant feedback

• Regression analysis

• Statistical analysis

Types of validity evidence

• Content

• Construct

• Criterion

• Consequential

Procedure:

A researcher need to describe in detain the procedure for conducting the experiments ad the reader should be able to see the design being used, the observation, the treatment, and the timeliness of activities. Typical steps used for the procedure are follows.

• Administering the measures of the dependent variable or a variable that closely correlated with the dependent variable to the research participants.

• Assign participants to the matched pairs on the basis of their scores

• Randomization. Randomly assign one member of each pair to the experimental group and other member to the control group

• Expose experimental group to experimental treatment and alternative treatment to control group.

• Administer measures of the dependent variables to the experimental and control groups

• Compare the performance of the experimental and control groups.

Statistical analysis:

A reader should be able to identify clearly the statistical analyses that are used in the experiment. Various statistical analyses that can be performed during the study are:

• Descriptive analysis – reporting the means, standard deviations and ranges.

• Inferential analysis- performing the hypothesis tests using ‘t’ tests, analysis of variance, analysis of covariance, or multivariate analysis of variance. A researcher can also use the factorial designs, both interaction and main effects of ANOVA.

Mixed methods research:

• Examine potential sources of error and ask:

Chance: Random error in sampling from a population.

1. Type I (alpha) error: The probability of falsely saying that there is a difference between two populations.

2. Type II (beta) error: The probability of falsely saying that there is no difference between two populations.

• How (in what direction) would the threats to validity affect the findings?

  Bias: Systematic distortion

1. Selection bias

– Systematic slant in how subjects are assembled or retained for study

2. Information bias

– Systematic distortion from inaccuracy in measurement or classification of study variables

• Were potential sources of error adequately controlled in the design and analysis?

  Confounding: Misattribution of cause and effect

• How do validity concerns affect your interpretation or application of the data?

  In the Design

• Study design appropriate for the question B,C

• Adequate power A

• Complete accounting of eligible patients B1

• Verification of information and Blinding B2

• Multiple control groups B,C

• Randomization, Restriction and matching C

In the Analysis

• Best case / worst case scenario and Sensitivity analysis B,C

• Adjustment B1,C

• Mathematical modeling C

A Reduces the role of chance; B1 Reduces selection bias ; B2 Reduces information bias; C Reduces confounding

References

Creswell, J. W. 2003. Research Design: Quantitative, Qualitative, and Mixed Methods Approaches. SAGE. Thousand Oaks. USA.

Leedy, P. D., & Ormrod, J. E., (2005). Practical Research: Planning and Design. PEARSON. Columbus. Ohio.

Olds, B., Moskal, B. & Miller, R. “Assessment in Engineering Education”, Journal of Engineering Education , to appear Jan. 2005.

Moskal, B., Leydens, J. & Pavelich, M. “Validity, reliability and the assessment of engineering education”. Journal of Engineering Education , Vol. 91, No. 3, 351-354, 2002.