1. Developing Research Plan - Quantitative
by Dr. Daniel Churchill

2. Admin Matters
Classes originally scheduled for 1st and 8th August will move to 4th and 11th of July.

3. Let’s Check on your Group Blogs…
Let’s have your presentations and some discussion about reviews

4. Content of this lesson is largely based on Chapters 2, 3 and 4 from the recommended book for the module:
Gay, L. R., Mills, G. E., & Airasian, P. (2006). Educational Research: Competencies for Analysis and Applications. Upper Saddle River, N.J. : Pearson/Merrill Prentice Hall Some slides are from the presentations by the book authors

5. Revision--Overview of Approaches to ER

6. Selecting Quantitative Methodology
A quantitative research question includes variables of interest to the researcher, relationship between the variables and type of subjects involved, e.g.,
The relationship between intelligence (var a) and computer use (var b) in a secondary school science class.

7. General components of a research plan
A justification for the hypotheses or exploration of the research problem
A detailed presentation of the steps to be followed in conducting the study
Purposes of a written research plan
Forces the researcher to think through every aspect of the study
Facilitates the evaluation of the proposed study
Provides detailed procedures to guide the conduct of the study
Obj. A.1

8. Quantitative Research Plans
Four major components
Introduction = Abstract
Method = Procedure
Data analysis
Timeline and budget
Obj. 3.1

9. Quantitative Research Plans
Introduction -- three sections
Statement of the topic
The topic is identified with a discussion of the background and rationale = why it is important in this topic.
Review of the literature
Provides an overview of the topic and positions the study in the context of what is known, and, more importantly, what is not known about the topic. (Don’t have too many literatures)
Statement of the hypotheses (prove the hypothesis)
A formal statement specifying the hypothesis, support for expected relationships between variables, and operational definitions of all variables.

10. The research aims to test a hypothesis. Example:
Defining Hypotheses
A hypothesis is a researcher’s preliminary prediction of the results of the research.
The research aims to test a hypothesis.
Example:
Secondary 1 mathematics students whose teachers use visual representations as a part of their instructional technique will exhibit significantly higher understanding of algebra than the students…

11. Selecting Method
From a question you can identify a kind of quantitative research based on the following formulas:
[variable X], [variable Y], and [variable Z] among [type of subjects]  descriptive research.
The relationship between [variable X] and [variable Y] among [type of subjects]  correlational research.
The effect of [independent variable not under experimenter's control] on [dependent variable] for [type of subjects]  causal-comparative research.
The effect of [independent variable X under experimenter's control] on [dependent variable Y] for [type of subjects]  experimental research.

12. Types of Quantitative Hypotheses
Research hypotheses state the expected relationship between two variables
Non-directional – no relationship or difference exists between the variables
Directional – there is expected direction of the relationship or difference between variables
Null – a statistical statement that no statistically significant relationship or difference exists between variables
Let’s change our example into different types of hypotheses:
Secondary 1 mathematics students whose teachers use visual representations as a part of their instructional technique will exhibit significantly higher understanding of algebra.

13. Stating Hypotheses Formats for quantitative experimental studies
P who get X do better on Y than P who do not get X
P represents the participant
X represents the treatment
Y represents the outcome
Testing hypotheses
Statistical analysis of data
Importance of the results regardless of the outcome
Results support or fail to support hypotheses, but they never prove or disprove hypotheses
Obj. 5.7 & 5.9

14. Quantitative Research Plans
Method -- five major sections
Participants
Instruments
Design
Procedures = how to going to do the analysis?
Data analyses
Obj. 3.3

15. Method
Participants
Characteristics of the population and sample as well as the sampling technique used.
Quantitative studies typically use large samples and probability sampling techniques.
Obj. 3.3

16. Quantitative Sampling
Identify participants for the study
Nature of the sample
Size of the sample
Method of selecting the sample
Terminology
Population: all members of a specified group
Target population – the population to which the researcher ideally wants to generalize
Accessible population – the population to which the researcher has access
Sample: a subset of a population
Subject: a specific individual participating in a study
Sampling technique: the specific method used to select a sample from a population

17. Quantitative Sampling
Terminology
Representation – the extent to which the sample is representative of the population.
Demographic characteristics/characteristics population you want to representation of your research.
Personal characteristics/characteristics population you want to representation of your research.
Specific traits
Generalization – the extent to which the results of the study can be reasonably extended from the sample to the population.
Sampling error – when randomly selected sample is not representative of the population.
Sampling bias, e.g.,: Use data returned from only 25% of those sent a questionnaire.
Obj. 1.4

18. Quantitative Sampling
Three fundamental steps
Identify a population
Define the sample size
Select the sample
Obj. 1.5

19. Quantitative Sampling
General rules for sample size
As many subjects as possible
Thirty (30) subjects per group for correlational, causal-comparative, and true experimental designs
Ten (10) to twenty (20) percent of the population for descriptive designs
For population of less than 100, use the entire population
If the population is about 500, sample 50%
If the population is about 1,500, sample 20%
If the population is larger than 5,000, sample 400
(large population will have less sample.)

20. Random Samples or Probability Sampling
Selecting subjects so that all members of a population have an equal and independent chance of being selected
Stratified random
Selecting subjects so that relevant subgroups in the population (i.e., strata) are guaranteed representation
Cluster
Selecting subjects by using groups that have similar characteristics and in which subjects can be found Neighborhoods (e.g.,School districts, Schools, Classrooms)
Systematic
Selecting every Kth subject from a list of the members of the population
Obj. 1.7

21. Random Samples Proportional and non-proportional (i.e., equal size)
Proportional – same proportion of subgroups in the sample as in the population
If a population has 45% females and 55% males, the sample should have 45% females and 55% males
Non-proportional – different, often equal, proportions of subgroups
Selecting the same number of children from each of the five grades in a school even though there are different numbers of children in each grade
Obj. 3.4

22. Known as non-probability sampling.
Non-Random Samples
Known as non-probability sampling.
Use of methods that do not have random sampling at any stage.
Useful when the population cannot be described.
Three techniques
Convenience – Volunteers, Pre-existing groups.
Purposive Selection -- based on the researcher’s experience and knowledge of the individuals being sampled.
Quota -- based on the exact characteristics and quotas of subjects in the sample when it is impossible to list all members of the population.

23. Method
Instruments
Descriptions of the specific measures of each variable, the technical characteristics of the instruments, and the administration and scoring techniques
Quantitative studies typically use non-interactive instruments (Tests, Questionnaires and Surveys)
Obj. 3.3

24. Method Design Procedures
Descriptions of the basic structure of the study and the specific research design chosen
Procedures
Detailed descriptions of all the steps that will be followed in conducting the study, assumptions, and limitations
Gaining entry to the site
How subjects will be selected
The ways data will be collected and analyzed
Assumptions – any important “fact” presumed to be true but not verified
Limitations – some aspect of the study that could have a negative effect upon the results
Size of the sample
Length of the study
Obj. 3.3

25. Method
Data analysis
Descriptions of the techniques used to analyze the data
Descriptive statistics – statistics that summarize data in terms of central tendency (e.g., means), variation (e.g., standard deviations), relative position (e.g., standard scores), or relationships (e.g., correlations)
Inferential statistics – procedures used to infer the likelihood of the results happening in the population rather than just the sample
Obj. 3.3 & 3.4

26. Quantitative Research Plans
Timeline
Description of the major activities and corresponding anticipated completion dates
Help assess the feasibility of conducting the study
The resulting structure helps avoid procrastination
A general strategy is to allow more time than you initially think you will need!!!
Budget
Descriptions of anticipated costs that are likely to be incurred
Optional in many plans
Obj. 3.5 & 3.6

27. Ask participants to acceptance to participant in the study
Ethical issues
Ask participants to acceptance to participant in the study
Provide the participant with Plain Language Statement containing;
Information about the objectives of the study;
Data collection methods;
Right to withdraw from the study;
Access preliminary data, analysis and report ;
Explanations of the participants’ role and responsibilities will be;
That the participant’s identity will not be disclosed and acronyms will be used for his/her name, and
Inform the participant that data will be used for the purpose of the study and possible journal publications

28. Ethical issues
Inform the participant when collecting data
When writing report the researcher will ensure that the audience will be able to distinguish between data and interpretations.
The researcher will remain unbiased in respect to collected data and will acknowledge if any biases cannot be controlled.
Let’s check this site: (include in your research plan)

29. Validity and reliability issues
Concept of Validity and reliability is different for Qualitative and Quantitative studies
In Quantitative Research:
The concept of reliability has to do with how well have you carried out your research project. Have you carried it out in such a way that, if another researcher were to look into the same questions in the same setting, they would come up with essentially the same results (though not necessarily an identical interpretation). If so, then your work might be judged reliable.
Validity has to do with whether your methods, approaches and techniques relate to, or measure, the issues you have been exploring.

30. Evaluation of a Research Plan
Informal assessment
Critiques by the researcher, advisors, peers and colleagues, etc.
Critiques by experienced researchers
Formal assessment
Field tests
Pilot studies
Modifications based on the results of both informal and formal evaluations
Obj. 5.1 & 5.2

31. Task
Identify and evaluate one computer tool that can be used to facilitate research.
Atlas.ti
SPSS
HyerRESEARCHER
Nudist
EndNote
MS Project