Definition
A procedure used to collect both qualitative and quantitative data.
This is done due to the fact that it is believed that both types of studies will provided a clearer understanding of what is being studied.
“It consists of merging ,integrating ,linking ,or embedding the two “strands””(Ceswell,2012).
this presentation file is all about the mixed method design for the research study and for those researchers who actually want to mixed two kinds of methods at a time. i hope it will help you and for your research.
this presentation file is all about the mixed method design for the research study and for those researchers who actually want to mixed two kinds of methods at a time. i hope it will help you and for your research.
A presentation about the added value of combining qualitative and quantitative methods. It begins with a brief discussion of qualitative research and how it is distinct from yet shares basic principles with quantitative research, followed by a discussion of four important ways mixed methods -- integrating qualitative and quantitative -- adds value to our research efforts, and then a discussion of mixed methods research -- what it is, typologies, alternatives to typologies, and the use of diagrams.
Triangulation research is all about the integration of data, method, investigators, and settings. there is a description of various types of triangulation and their impact on the validity of the results. there is a slight introduction to meta-analysis and systematic review.
A presentation about the added value of combining qualitative and quantitative methods. It begins with a brief discussion of qualitative research and how it is distinct from yet shares basic principles with quantitative research, followed by a discussion of four important ways mixed methods -- integrating qualitative and quantitative -- adds value to our research efforts, and then a discussion of mixed methods research -- what it is, typologies, alternatives to typologies, and the use of diagrams.
Triangulation research is all about the integration of data, method, investigators, and settings. there is a description of various types of triangulation and their impact on the validity of the results. there is a slight introduction to meta-analysis and systematic review.
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This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
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Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
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• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
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Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
1. Mixed Methods Designs
Definition
A procedure used to collect both qualitative
and quantitative data.
This is done due to the fact that it is believed
that both types of studies will provided a
clearer understanding of what is being
studied.
“It consists of merging ,integrating ,linking ,or
embedding the two “strands””(Ceswell,2012).
2. Understanding the Difference in
Quantitative and Qualitative Data
• Quantitative Data
Objective
Deductive
Numbers
• Qualitative Data
Subjective
Inductive
Words
3. When to Use it
• “You conduct a mixed methods study when
you have both quantitative and qualitative
data and both types of data ,together ,
provide a better understanding of your
research problem than either type by itself.
• Mixed methods research is a good design
to use if you seek to build on the strengths of
both quantitative and qualitative
data.”(Creswell,2012).
4. How it Developed
• Mixing forms of Quantitative data(1950’s)
• Combing Quantitative Data and Qualitative
Data(1970’s)
• Questioning the Integration of world views and
methods(late 1980’s and early 1990’s)
• Developing Procedures for Mixed Methods
Studies(late 1990’s)
• Advocating for Distinct Design(early 2000’s)
• Reflexive Period(mid.2000’s-last5-7years)
5. Key Characteristics
• Provide a rational for the design
• Include collecting quantitative and
qualitative data
• Consider Sequence
• Match the data analysis to a design
• Diagram the Procedures
6. Key Characteristics
Provide Rational for
the design
• Important to know
why you using Mixed
Methods,
• Include justification
for the use of both
types of data
Include a collecting
quantitative and
qualitative data
• “Clearly indicate that
you are collecting
both qualitative and
quantitative
data”(Creswell,2012)
7. Key Characteristics
Consider Priority
• Priority in mixed
methods design is when
” the research places
more emphasis on one
type than on the other
types of data in the
research and the
written
report”(Creswell,2012)
Consider Sequence
• “Mixed methods
researchers ” advance
the sequence of data
collecting using
concurrent or
sequential approaches
or some
combination”(Creswell,
2012)
8. Key Characteristics
Match Data Analysis to a
design
• The data analysis needs
to match the research
design
Diagram the Procedures
• Visualization or diagram
of the design showing
the procedures
• Label the data
• Indicating the sequence
• Emphasizing the priority
9. Types of Designs
• The Convergent Parallel Design
• The Explanatory Sequential Design
• The Exploratory Sequential Design
• The Embedded Design
• The Transformative design
• The Multiphase Design
10. Types of Designs
Convergent Parallel
• Collect both number
and text data at the
same time
• Merge the data
• Rational : one of the
data collection designs
strengths will offset the
other’s weakness
Explanatory sequential
• Two-phase
• Collects number data then
collects narrative data to
explain number data
• Rational : number data
provides a general picture
and the narrative data
helps explain the general
picture
11. Convergent
• Quantitative and
Qualitative results
are compared
Data Collection Data collection
Data Analysis Data Analysis
Qualitative
findings
Quantitative
findings
12. Explanatory Sequential
Quantitative results
are further explained
by Qualitative data
and results
Data Collection Data collection
Data Analysis Data Analysis
Qualitative
findings
Quantitative
Results
Interpretations
13. Exploratory Sequential
• Two-phase
• Start with narrative
data then collects
number data to
explain relationship
Embedded
• Collect data at the
same time or
sequentially but one
will be more
supportive of the
other
14. Exploratory Sequential
Data Collection Data collection
Data Analysis Data Analysis
Qualitative
findings
Quantitative
Results
Interpretations
Qualitative exploration
leading to a quantitative
test
15. Transformative
• Complex
• Intent is to address a
social issue
• Common issues are
racial , ethnic , and
disability
Multiphase
• Complex
• Series of phases or
separate studies
16. Adding a framework Advanced Mixed
Methods Designs
Basic Design
+
Convergent
Explanatory Seq.
Exploratory Seq.
Added framework
(Such as )
Experiment Case
Study
=
Basic Design
Advanced Design
17. Ethical Issues
There have not been a lot of discussions
rearing the ethical issues that arise in
mixed methods research . One major
concern is the design of grouping all
participants together in a general
category that may stereotype them .
Also, you need to look at the ethical
considerations of the two types of data.
18. Steps in Conducting Research
Step1 .determine if a mixed methods study is
feasible.
Step2. Identify rational for mixing methods.
Step3. Identify a data collection strategy.
Step4 .Develop Quantitative ,Qualitative, and
mixed methods questions.
Step5. Collect Quantitative and Qualitative data.
Step6. Analyze data separately, concurrently or
both.
Step7. Write the report as a one-or-two-phase
study or a multiple-phase study.
19. Evaluation of the Quality of these
research designs
AS a form of qualitative and quantitative
research ,”mixed methods needs to be
consistent in it's criteria for a good
qualitative and quantitative study”.
20. Summary of Mixed Methods Research
1. Collecting and analyzing qualitative and
quantitative data (open-and closed-ended) in
response to research questions.
2. Using rigorous qualitative and
quantitative methods.
3. Combining or integrating quantitative
and qualitative data using a specific type of
mixed methods design.
4. Framing the mixed methods design
within a broader framework(e g; experiment
,theory , or philosophy).