Developing Research Plan - Quantitative by Dr. Daniel Churchill

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

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

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

Revision--Overview of Approaches to ER

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.

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

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

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.

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…

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.

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.

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

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

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

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

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

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

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.)

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

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

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.

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

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

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

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

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

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: http://www.hku.hk/rss/HREC.htm (include in your research plan)

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.

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

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