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Quantitative Methods Topic 1 Research Design.

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1 Quantitative Methods Topic 1 Research Design

2 Subject Aims Data analysis methods appropriate for investigating issues across a range of topics in education. Conceptual understanding of statistics rather than formal mathematical derivations Univariate and bivariate statistics. Skills in questionnaire design

3 Assessments There will be 10 exercises (30%), and 1 project (4000 words) (70%)

4 SPSS is required SPSS (Statistical Package for the Social Sciences)

5 Accessing materials online

6 Reading materials for Topic 1
Module1.pdf: Educational research: some basic concepts and terminology T. Neville Postlethwaite

7 Topic 1 outline Types of educational research
Planning educational research Research questions

8 Issues/headlines in Education
Australian students lag in maths, science Funding splurge fails to improve student results Best assessment practice Boys lag behind girls Accountability policies Use technology in the classrooms Decide if quantitative and/or qualitative methods may be used to investigate each of the issues.

9 Types of Research Questions addressed by quantitative methods
Descriptive Association/Correlational Causal/Explanatory

10 Descriptive Problems - 1
Which subject fields are more frequently chosen by Australian Year 11 and 12 students? Do girls choose different subject fields compared with boys? If so, what are the subjects preferred by girls? Are there differences in subject choice according to differences in social status and ethnic family backgrounds? What are the areas that Professional Development Program for teachers should cover? Are all primary school teachers qualified to teach? What are the status of school building in a country?

11 Descriptive Problems - 2
May not be as straightforward as the computation of frequencies and averages. Break-in On the radio, an advertisement for an insurance company ran as follows: “Every 10 minutes, a car is stolen in Zedland. Every 21 minutes, a house is broken into. Take up an insurance policy today.” Using only the information given in the advertisement, can you conclude anything about the chance a car will be stolen in Zedland? that it is more likely to have a car theft than a house break-in? Give reasons to support your answer.

12 Association - 1 Are there any relationships between students’ reading achievement and their mathematics achievement? Is there an association between reading achievement and the number of books in the home ? Association does not always lead to causal.

13 Association - 2 In a town in Europe, the number of storks is positively correlated with the number of babies born. Crime rate is positively correlated with ice cream sales.

14 Causal relationships - 1
Does smaller class size increase student performance? Do students’ performance improve if more homework is assigned? Does parental attitude have an impact on student achievement?

15 Causal relationships - 2
Causal relationship is very difficult to identify. Number of books at home is positively correlated with student achievement. Can student achievement be improved by placing more books in a home? Mediating variables High parental expectations of achievement is correlated with both number of books at home and student performance.

16 Causal relationships - 3
Study design to establish casual relationships needs to be “confirmatory” than “exploratory”. Confirmatory approach E.g., we hypothesise that increasing homework can increase student performance. Carry out a study where some students are assigned more homework and some are not. Exploratory approach Obtain student performance data and other information including homework, school administration, hours of teaching, etc. Find correlations between student performance and other variables.

17 Research Stages Stage 1: Research aims Stage 2: Literature
Stage 3: Research design Stage 4: Instrumentation Stage 5: Piloting Stage 6: Data collection Stage 7: Data cleaning and Data analysis Stage 8: Research report

18 Research aim(s) Example: To identify factors influencing student withdrawal from school and explore the extent to which each factor contributes to student withdrawal from school This example will take you through the process of: 1-operationalising a research aim into research questions. 2-how literatures were reviewed and the proportions established 3- hypotheses 4-resech design 5-developping instruments

19 Literature Review Review the related literature
What have been done in the field? What are controversial debates? School of thought? What are the “gaps”? (knowledge and methods) What are the findings? Develop a theoretical framework

20 Research questions What are the factors that influence students’ academic achievement? Which method of instruction is most effective in teaching young children to read?

21 Propositions Gender, ethnicity, family economic status, parents’ education and occupation, parents’ and students’ attitudes, were important factors relating to students' academic achievement. School effectiveness has an impact on student achievement Teacher qualification has an impact on student achievement Propositions were established as a result of literature review . Propositions formed the research theoretical framework for your project.

22 Research design At this stage the following should be identified:
Source of information Who is appropriate to provide the necessary information Characteristics of the target population Data collection methods

23 Data collection methods
Cross-sectional vs longitudinal If longitudinal, how many times? Sample vs cohort If sample, how many? Questionnaire, test, interview, published statistics How many questions?

24 Establishing the link between information needed, source of information and methods of data collection Information needed/variables to be measured Source of information Methods of data collection The table that presents a link between information needed, and from whom and whore information can be obtained, and how to obtain this information (structured interview or mail questionnaire…)

25 Link between the information needed, sources and methods
Data collection Student gender Students Questionnaire Family characteristics parents Parent attitudes Parents Student attitudes Student achievement tests School characteristics School/Principal Questionnaire/interview

26 Questionnaires Needed
  Student questionnaire   Parent questionnaire   School questionnaire

27 Instrumentation Develop/validate and pilot instruments (test or questionnaires) Once the research design was completed. The next step is to design the instruments and pipot the instruments.

28 Variables included in the Parent Questionnaire
Family social status/wealth Mother Education Father Education Mother Occupation Father Occupation Family size Parent attitudes It is important to identify the variables to be coved in the questionaries.

29 Variables included in the Student Questionnaire
Student gender Ethnicity Student attitudes Student academic achievement Student behaviour

30 Data collection and data management
Field work supervision Entering the data into data file Cleaning the data

31 Data Analysis Descriptive Correlational Causal
Note that statistics can only provide correlational information. Any causal interpretation is made by people.

32 Writing up the reports and discussions
Technical report Policy report General public

33 A few examples to contemplate
Margins of error in test scores For Year 5 numeracy, each child is tested on just 40 questions each year in a national test. If David obtained 25 out of 40 on the 2009 test, how much would we expect David’s scores to vary if tests similar to the 2009 test are administered? For a 40-question test, David’s scores might vary by as much as 5 score points. In percentage terms, if a student’s score is 70% on a test, we expect the range of this student’s scores on similar tests to be between 58% and 82%.

34 Simpson’s paradox Men Women Arts Sci total
5 men and 5 women apply for university places (http://en.wikipedia.org/wiki/Simpson%27s_paradox) Men Women Arts 3 out of 4 (75%) 1 out of 1 (100%) Sci 0 out of 1 (0%) 1 out of 4 (25%) total

35 False positives Prevalence rate for a disease in a population is 1%.
Test for this disease -ve/-ve 95% +ve/-ve 5% (5% of those who do not have the disease show a +ve result) +ve/+ve 95% -ve/+ve 5% (5% of those who have the disease show a -ve result) Is this a good test? Suppose 10,000 people were tested. 600 had +ve result. What is the proportion of the people with +ve result who actually have the disease?


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