methodology semestre 3
DESCRIPTION
by benhacenTRANSCRIPT
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SEMESTRE 3:SEMESTRE 3:RESEARCH RESEARCH METHODOLOGY IN METHODOLOGY IN LINGUISTICSLINGUISTICS
Semestre 3
RESEARCH METHODOLOGY IN
LINGUISTICS
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Four LessonsFour Lessons Four LessonsFour Lessons1. Linguistic research methodology
2. Research methods3. Research tools/ data collection techniques or strategies
4. Data analysis
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Lesson 1Lesson 1Lesson 1Lesson 11. RESEARCH METHODOLOGY IN LINGUISTICS
Origin of Method: is the Greek word “methodos” which consists of two parts: “meta”:“after”, and “hodos”: “road”
Methods = procedures = techniques = approaches = ways
Methodology is to analyse research methods
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WHAT IS RESEARCH ?WHAT IS RESEARCH ?WHAT IS RESEARCH ?WHAT IS RESEARCH ?
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WHAT IS LINGUISTIC WHAT IS LINGUISTIC RESEARCH METHODOLOGY ?RESEARCH METHODOLOGY ?WHAT IS LINGUISTIC WHAT IS LINGUISTIC RESEARCH METHODOLOGY ?RESEARCH METHODOLOGY ?
The analysis of research methods used by linguists to collect data related to a topic in linguistics.
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Writing The Research ProposalWriting The Research ProposalWriting The Research ProposalWriting The Research ProposalINTRODUCTION1. Review of Literature2. Statement of the Problem 3. Aims of the Study 4. Hypothesis5. Research Methodology and Design
5.1 Choice of the Method5.2 Population of the Study5.3 Data Gathering Tools6. Structure of the DissertationCONCLUSIONBIBLIOGRAPHY
INTRODUCTION1. Review of Literature2. Statement of the Problem 3. Aims of the Study 4. Hypothesis5. Research Methodology and Design
5.1 Choice of the Method5.2 Population of the Study5.3 Data Gathering Tools6. Structure of the DissertationCONCLUSIONBIBLIOGRAPHY
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Review of literatureReview of literatureReview of literatureReview of literature
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Population of the Population of the study =study =
Population of the Population of the study =study =
Sample = Sample =
Participants =
Participants =Informants =
Informants =
Subjects = Subjects =
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PopulationPopulationPopulationPopulation
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Bibliography citation Bibliography citation stylesstyles
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Structure of the Structure of the DissertationDissertation
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FiguresFigures
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FiguresFigures
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INTRODUCTIONINTRODUCTIONINTRODUCTIONINTRODUCTION
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THANK YOU FOR LISTENING
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LESSON TWO
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Lesson twoLesson twoLesson twoLesson two2. RESEARCH METHODSQUANTITATIVE
METHODS
QUALITATIVE METHODS
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Hypothesis: Hypothesis: If A happens, B would occur.A: the assumed cause (stimulus)
B: the assumed effect (response)
Cause and effect relationship/ causal relationship.
If A happens, B would occur.A: the assumed cause (stimulus)
B: the assumed effect (response)
Cause and effect relationship/ causal relationship.
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Example of a Example of a hypothesishypothesis
If students use their metacognitive strategies, they would become autonomous learners.
Use of metacognitive strategies: the cause: independent variable. I.V
Autonomy: the effect: dependent variable. D.V
If students use their metacognitive strategies, they would become autonomous learners.
Use of metacognitive strategies: the cause: independent variable. I.V
Autonomy: the effect: dependent variable. D.V
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The null hypothesis: The null hypothesis: HH00
What people believe is true. But the researcher thinks it’s false. Example:
If students work in groups (co-operative learning), their writing proficiency would be high.
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The alternative The alternative hypothesishypothesis H H11
What the researcher believes is true. It is his/her research hypothesis. Eg.
If students work individually, their writing proficiency would increase.
Because s/he thinks that: if students work in groups, their writing proficiency would decrease.
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QUANTITATIVE METHODSQUANTITATIVE METHODS
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QUALITATIVE QUALITATIVE METHODSMETHODS
Descriptive method
Historical method
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CORRELATIONAL METHODCorrelation = the relationship between two variables.
When do we follow this method?
When both variables are countable/ measurable.
Eg. Intelligence and academic achievement.
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DESCRIPTIVE METHODDESCRIPTIVE METHODWhen?1. When one variable is uncountable.
Eg. Attention in the classroom and academic achievement.
2. When the two/both variables are uncountable.
Eg. CALL and motivation.3. When we have one variable: students’ lack of vocabulary.
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EXPERIMENTAL EXPERIMENTAL METHODMETHOD1. When something doesn’t exist.
2. When we can realize it: feasibility/practicability of research.
3. When we cannot count the correlation coefficient. Eg. Cooperative learning and high writing proficiency.
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« r »: coefficient of « r »: coefficient of correlationcorrelation
If r is near +1 or -1 the correlation is high. (0.95; 0.8; -0.7...)
If r = +1 or -1 the correlation is strong/perfect/high.
If r is between “+/- 0.25” and “+/- 0.75” it is a moderate correlation.
If r is near 0 the correlation is weak If r = 0 there is no correlation: no relationship between variables
If r is near +1 or -1 the correlation is high. (0.95; 0.8; -0.7...)
If r = +1 or -1 the correlation is strong/perfect/high.
If r is between “+/- 0.25” and “+/- 0.75” it is a moderate correlation.
If r is near 0 the correlation is weak If r = 0 there is no correlation: no relationship between variables
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If r is positive (marked by +) this means that if “x” increases ,“y” also increases.( linear relationship)
if “r” is negative (marked by -) this indicates that if “x” increases, “y” decreases.
X: 1st variable: causeY: 2nd variable: effect
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MIXEDMIXED METHODSMETHODSThe Experimental-correlational method (two methods)
When? When we can conduct an experiment + we can count correlation coefficient.
E.g. the influence of using collocations on students’ writing proficiency.
Experiment: teaching collocations
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Experimental Experimental designdesign
Experimental Experimental designdesign
At least 2 groups:1.The experimental group
2.The control group
At least 2 groups:1.The experimental group
2.The control group
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1.The experimental group: It receives the experiment = treatment = intervention
Example: If we teach students grammar, their writing proficiency would raise.
Teaching grammar is the experiment.
1.The experimental group: It receives the experiment = treatment = intervention
Example: If we teach students grammar, their writing proficiency would raise.
Teaching grammar is the experiment.
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2.The control group: it doesn’t receive the experiment/treatment. It’s a comparison group (we don’t teach them grammar)
Why do we need this group? to compare the results of the experimental group to those of the control group in order to see whether the experiment was effective. If the writing proficiency of the experimental group has raised.the experiment was effective (successful)
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Sampling Sampling
1. THE PROBABILITY/ RANDOM SAMPLE: generalization is possible
2. THE NON-PROBABILITY/ PURPOSIVE SAMPLE: generalization is impossible
1. THE PROBABILITY/ RANDOM SAMPLE: generalization is possible
2. THE NON-PROBABILITY/ PURPOSIVE SAMPLE: generalization is impossible
Sampling
sample
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1. THE PROBABILITY/ 1. THE PROBABILITY/ RANDOM SAMPLERANDOM SAMPLE
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2. THE NON-PROBABILITY/ 2. THE NON-PROBABILITY/ PURPOSIVE SAMPLEPURPOSIVE SAMPLE
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CSR: CSR: CCase ase SStudy tudy RResearchesearch
CSR DESIGN
a single case: a student, a school
a group of cases/
multiple cases:
st1+st2+st3 or
sc1+sc2+sc3
a single casea group of cases/ multiple cases
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Generalization in case Generalization in case studiesstudiesGeneralization in case Generalization in case studiesstudiesIt depends on:1.The sample: random or not random
2. The method: quantitative, qualitative, qualitative + quantitative
It depends on:1.The sample: random or not random
2. The method: quantitative, qualitative, qualitative + quantitative
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Types of CSR: Robert K. Types of CSR: Robert K. Yin Yin ((Case Study Research: Case Study Research: Design and methods, Design and methods, 19931993))
Types of CSR: Robert K. Types of CSR: Robert K. Yin Yin ((Case Study Research: Case Study Research: Design and methods, Design and methods, 19931993))1.EXPLORATORY: before research2.EXPLANATORY: only the case study, no research after it.3.DESCRIPTIVE: before research, there is a descriptive theory
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Types of CSR: Robert E. Types of CSR: Robert E. Stake (Stake (The Art of Case Study The Art of Case Study Research: Research: 1995)1995)
Types of CSR: Robert E. Types of CSR: Robert E. Stake (Stake (The Art of Case Study The Art of Case Study Research: Research: 1995)1995)
1. INTRINSIC
2.INSTRUMENTAL
3.COLLECTIVE (DESIGN)
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YIN CSR YIN CSR METHODOLOGYMETHODOLOGY
YIN CSR YIN CSR METHODOLOGYMETHODOLOGY
ConclusionRecommendati
onsImplications
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CSR METHODOLOGYCSR METHODOLOGYCSR METHODOLOGYCSR METHODOLOGY
1. research question(s)2. case(s)+ way of data collection and analysis
3. preparation to collect data4. data collection in field5. data analysis6. writing the report
1. research question(s)2. case(s)+ way of data collection and analysis
3. preparation to collect data4. data collection in field5. data analysis6. writing the report
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CSR Sources of CSR Sources of evidenceevidence
1. Documentati
on
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LettersLettersLettersLetters
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MemorandaMemoranda
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AgendasAgendasAgendasAgendas
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ReportsReportsReportsReports
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3. interviews3. interviews3. interviews3. interviews
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2. ARCHIVAL RECHORDS2. ARCHIVAL RECHORDS
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6. Physical artifacts6. Physical artifacts
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THANK YOU FOR PAYING
ATTENTION TO THE LESSON
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Lesson ThreeLesson Three3. Research tools: data collection techniques/ strategies
3. Research tools: data collection techniques/ strategies
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We have many research We have many research tools. We’re going to deal tools. We’re going to deal
with:with:
We have many research We have many research tools. We’re going to deal tools. We’re going to deal
with:with:1. The questionnaire2. The interview3. Observation4. The pretest and the post -test
1. The questionnaire2. The interview3. Observation4. The pretest and the post -test
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1. The 1. The questionnairequestionnaire
To operationalize the questionnaire
= to make it structured as
much as possible
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Structured = there is wording / written form
Example: choice 1: 15 studentsQuestion 1 choice 2: 5 students choice 3: 10 students scoring / coding : numbers
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Structured way of data collectionStructured way of data collection
Unstructured way of data collectionUnstructured way of data collection
There is wording (words)
Written formData type is
quantitative / numerical: there are numbers, scores, measurements,percentages (℅)…
There is wording (words)
Written formData type is
quantitative / numerical: there are numbers, scores, measurements,percentages (℅)…
No wording (words)
No written formData type is
qualitative / word-based / narrative: there are words.
No wording (words)
No written formData type is
qualitative / word-based / narrative: there are words.
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Questionnaire Questionnaire typestypes
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2. The 2. The interviewinterview
2. The 2. The interviewinterview
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Interview types: Interview types: according to according to
structurestructure
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2. The semi-structured 2. The semi-structured interviewinterview2. The semi-structured 2. The semi-structured interviewinterviewNo questions, no wording, just topics
of questions. Example:Question 1: question topic:
definition of motivation.Question 2: question topic: types of
motivation.So, no wording for each question. i.e.
the question is not written: different forms of questions (different wording) for different informants but the same topic.
No questions, no wording, just topics of questions. Example:
Question 1: question topic: definition of motivation.
Question 2: question topic: types of motivation.
So, no wording for each question. i.e. the question is not written: different forms of questions (different wording) for different informants but the same topic.
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Question 1: definition of Question 1: definition of motivationmotivation Question 1: definition of Question 1: definition of motivationmotivationInformant 1: Do u know the definition of motivation?
Informant 2: What is motivation?
Informant 3: How could you define motivation?
Informant 1: Do u know the definition of motivation?
Informant 2: What is motivation?
Informant 3: How could you define motivation?
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Interview types: Interview types: according to the according to the number of number of intervieweesinterviewees
Interview types: Interview types: according to the according to the number of number of intervieweesinterviewees
Two typesTwo types
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1. Individual 1. Individual interviewinterview
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2. Group 2. Group interviewinterview
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Interview designInterview designInterview designInterview design= The nature of the questions:
1. Open and/or closed questions.
2. Direct and/or indirect questions:
Specific and/or non-specific (general) questions
= The nature of the questions:
1. Open and/or closed questions.
2. Direct and/or indirect questions:
Specific and/or non-specific (general) questions
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3. Observation3. Observation
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3. Observation3. Observation3. Observation3. ObservationTo get ‘live’ data from ‘live’ situations.
To get ‘live’ data from ‘live’ situations.
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According to Patton observation is
“to look at what is taking place in situation rather than at second hand” (cited in Cohen, L , Manion, L and Morrison, K. 2000: 305).
According to Patton observation is
“to look at what is taking place in situation rather than at second hand” (cited in Cohen, L , Manion, L and Morrison, K. 2000: 305).
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Observation types: Observation types: according to structureaccording to structure
Observation types: Observation types: according to structureaccording to structure
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1. Structured/standardized observation: topic + hypothesis (hypothesis-testing) numerical data
2. Semi-structured observation: topic but no hypothesis (hypothesis-generating)
3. Unstructured observation: no topic, no hypothesis (hypothesis-generating)
1. Structured/standardized observation: topic + hypothesis (hypothesis-testing) numerical data
2. Semi-structured observation: topic but no hypothesis (hypothesis-generating)
3. Unstructured observation: no topic, no hypothesis (hypothesis-generating)
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Observation chart / Observation chart / schedulescheduleObservation chart / Observation chart / schedulescheduleStructured/standardized observation: topic (students’ interaction in the classroom) + hypothesis (if students’ interact with each other, their oral performence would improve)
Structured/standardized observation: topic (students’ interaction in the classroom) + hypothesis (if students’ interact with each other, their oral performence would improve)
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Degrees of Participant/ Degrees of Participant/ naturalistic observationnaturalistic observationDegrees of Participant/ Degrees of Participant/ naturalistic observationnaturalistic observation
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1. The complete 1. The complete participantparticipant1. The complete 1. The complete participantparticipantcomplete participation in daily activities. He lives within a group like the spy.
covert research: secret.Negative point: s/he could be influenced by the group. So s/he may stop to act a researcher.
complete participation in daily activities. He lives within a group like the spy.
covert research: secret.Negative point: s/he could be influenced by the group. So s/he may stop to act a researcher.
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2. The participant-as-2. The participant-as-observer:observer:2. The participant-as-2. The participant-as-observer:observer:s/he participates in the group but they know s/he is a researcher: overt research
s/he participates in the group but they know s/he is a researcher: overt research
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3. 3. The observer-as-The observer-as-participant participant
3. 3. The observer-as-The observer-as-participant participant
s/he doesn’t participate: marginal observer: overt research (not covert)
s/he doesn’t participate: marginal observer: overt research (not covert)
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4. The complete observer4. The complete observer4. The complete observer4. The complete observer
s/he doesn’t participate. s/he observes secretly. Covert research
Example: a teacher who observes students in the classroom.
s/he doesn’t participate. s/he observes secretly. Covert research
Example: a teacher who observes students in the classroom.
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4. The pretest and the 4. The pretest and the posttestposttest
4. The pretest and the 4. The pretest and the posttestposttest
Testing = measuring . What? an aptitude, an ability, a skill, knowledge..
Examples: -verbal aptitude tests: words
- I.Q. tests. Intelligence Quotient.
(Quotient = ratio).
Testing = measuring . What? an aptitude, an ability, a skill, knowledge..
Examples: -verbal aptitude tests: words
- I.Q. tests. Intelligence Quotient.
(Quotient = ratio).
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I.Q. = MA/CA × 100.
MA: Mental AgeCA: Chronological Age
I.Q. = MA/CA × 100.
MA: Mental AgeCA: Chronological Age
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1. The pretest: before the intervention /experiment/ treatment.
2. The posttest: after the intervention /experiment/ treatment.
1. The pretest: before the intervention /experiment/ treatment.
2. The posttest: after the intervention /experiment/ treatment.
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The pretestThe pretestThe pretestThe pretestTo see if the level of students in the experimental group and the control group is equal
To see if the level of students in the experimental group and the control group is equal
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The same pretest for both groups
The same pretest for both groups
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The posttestThe posttestThe posttestThe posttestTo see if the level of students in the experimental group and the control is not equal: a change in the experimental group due to the experiment/intervention/the treatment.
To see if the level of students in the experimental group and the control is not equal: a change in the experimental group due to the experiment/intervention/the treatment.
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The same posttest for both groups
The same posttest for both groups
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Experiment methodology Experiment methodology (steps)(steps)
Experiment methodology Experiment methodology (steps)(steps)
1. Research problem/question
2. Hypothesis 3. Sample choice (random: experimental/not random: quasi-experimental)
4.Experimental design: two groups: experimental group + control group
1. Research problem/question
2. Hypothesis 3. Sample choice (random: experimental/not random: quasi-experimental)
4.Experimental design: two groups: experimental group + control group
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5. Students’questionnaire and/or teachers’ questionnaire (+ Interview if possible)
6. Pretest + experiment + posttest
7. Data analysis 8.Conclusion: confirming or rejecting the hypothesis
5. Students’questionnaire and/or teachers’ questionnaire (+ Interview if possible)
6. Pretest + experiment + posttest
7. Data analysis 8.Conclusion: confirming or rejecting the hypothesis
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The Solomon four-group The Solomon four-group designdesignThe Solomon four-group The Solomon four-group designdesignRandomiz-ed groups
Pre-test
experiment
Post-test
Group 1
Group 2Group 3Group 4
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The Solomon four-group The Solomon four-group designdesignThe Solomon four-group The Solomon four-group designdesignWe add two control groups. Why?to eliminate the effect of the pretest:
1. on the posttest: group 3: it’ s the experiment that affected the posttest.
2. on the posttest: group 4: and it is not the experiment that affected the posttest.
We add two control groups. Why?to eliminate the effect of the pretest:
1. on the posttest: group 3: it’ s the experiment that affected the posttest.
2. on the posttest: group 4: and it is not the experiment that affected the posttest.
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THANK YOU FOR
LISTENING
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LESSON FOUR
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Lesson 4Lesson 44. Data analysis:4.1 Analysis of Quantitative data
4.2 Analysis of Qualitative data
4. Data analysis:4.1 Analysis of Quantitative data
4.2 Analysis of Qualitative data
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Data-collection strategiesData-collection strategiesData-collection strategiesData-collection strategies
1. Longitudinal strategies: individual change over time. Two samples. Example:
The influence of teaching oral expression on students’ speaking:
two samples: First sample: first year students (2011-2012)
Second sample: second year students (the same students: 2012-2013)
1. Longitudinal strategies: individual change over time. Two samples. Example:
The influence of teaching oral expression on students’ speaking:
two samples: First sample: first year students (2011-2012)
Second sample: second year students (the same students: 2012-2013)
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2. Cross-sectional strategies: differences between groups at one point in time. one sample.
Students’ pronunciation in second year: difference between two groups.
2. Cross-sectional strategies: differences between groups at one point in time. one sample.
Students’ pronunciation in second year: difference between two groups.
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Analysis of quantitative Analysis of quantitative datadata
Analysis of quantitative Analysis of quantitative datadata
Example: Analysis of data driven from students’ questionnaire
A questionnaire has been administered to collect information from first year students of English who have been allocated randomly to two groups: an experimental group that will receive the treatment and a control one which stands as a means of comparison to see whether the treatment has come to any changes. The aim behind this questionnaire is to collect data about students’ level in writing and their knowledge of collocations.
Example: Analysis of data driven from students’ questionnaire
A questionnaire has been administered to collect information from first year students of English who have been allocated randomly to two groups: an experimental group that will receive the treatment and a control one which stands as a means of comparison to see whether the treatment has come to any changes. The aim behind this questionnaire is to collect data about students’ level in writing and their knowledge of collocations.
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Analysis of Results and Findings
The answers collected from students’ questionnaire have been counted and organized in tables in order to quantify the results which are presented below.
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3- Students' choice to study 3- Students' choice to study English at the universityEnglish at the university
3- Students' choice to study 3- Students' choice to study English at the universityEnglish at the university
The experimental
group
The control group
number
percentage
number
percentage
Yes 17 70.83 ℅ 16 66.66℅
No 7 29.16 ℅ 8 33.33℅
Total 24 100℅ 24 100℅
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COUNTING PERCENTAGESCOUNTING PERCENTAGESCOUNTING PERCENTAGESCOUNTING PERCENTAGES
NUMBER × 100 / 24Example: 17 × 100 / 24 = 70.83℅
NUMBER × 100 / 24Example: 17 × 100 / 24 = 70.83℅
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3- Students' choice to study 3- Students' choice to study English at the universityEnglish at the university3- Students' choice to study 3- Students' choice to study English at the universityEnglish at the university
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Thank you a lot for
listening
Thank you a lot for
listening