We may earn an affiliate commission when you visit our partners.
Jennifer Bachner, PhD
This is the final course in the Data Literacy Specialization. In this capstone course, you'll apply the skills and knowledge you have acquired in the specialization to the critical evaluation of an original quantitative analysis. The project will first require you to identify and read a piece of high-quality, original, quantitative research on a topic of your choosing. You’ll then interpret and evaluate the findings as well as the methodological approach. As part of the project, you’ll also review other students’ submissions. By the end of the project, you should be empowered to be a critical consumer and user of quantitative research.
Register for this course and see more details by visiting:
OpenCourser.com/course/jnsl88/data
What's inside
Syllabus
Capstone Project Overview
Welcome to the Capstone Course for the Data Literacy Specialization! The capstone project will allow you to apply the knowledge and skills you've acquired throughout the specialization to the evaluation of a published piece of scholarly work. In this first module, I'll present an overview of the project's purpose and components.
Read more
Syllabus
Capstone Project Overview
Welcome to the Capstone Course for the Data Literacy Specialization! The capstone project will allow you to apply the knowledge and skills you've acquired throughout the specialization to the evaluation of a published piece of scholarly work. In this first module, I'll present an overview of the project's purpose and components.
Read more
Locating Quality Scholarship
In this module, I'll present information that will help you identify an article or report that you'll evaluate for the capstone project. We'll explore sources that frequently publish high-quality, original, quantitative research. We'll also discuss the difference between primary and secondary research.
Final Paper Submission
Welcome to the final module in the Data Literacy Specialization. In this module, you'll complete and submit your capstone project via the peer review system. You'll also review three submissions from other students in the specialization. I hope this specialization has given you a set of tools and skills that empower you to be a critical consumer and user of quantitative research.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Students will be able to evaluate the findings of a piece of high-quality quantitative research on a topic of their choice
Students will be able to apply the skills and knowledge acquired throughout the specialization to the evaluation of published scholarly work
Students will be able to identify an article or report that they'll evaluate for the capstone project with the help of resources that frequently publish original, quantitative research
Students will be able to differentiate between primary and secondary research
Students will be able to complete and submit capstone projects and review submissions from other students as part of peer review system
Save this course
Save Data Literacy Capstone – Evaluating Research to your list so you can find it easily later:
Save
Save
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Data Literacy Capstone – Evaluating Research with these
activities:
Review Introduction to Quantitative Research
Show steps
Refresh your knowledge of the key principles and methods of quantitative research to build a solid foundation for the course.
Browse courses on
Quantitative Research
Show steps
-
Read introductory articles or textbook chapters on quantitative research methods
-
Review online tutorials or videos on basic quantitative research concepts
-
Complete practice questions or exercises on quantitative research techniques
Explore Peer-Reviewed Quantitative Research
Show steps
Gain hands-on experience in finding and evaluating high-quality quantitative research articles to apply in your capstone project.
Browse courses on
Quantitative Research
Show steps
-
Identify reputable journals and databases for quantitative research
-
Use search terms and filters to locate relevant articles
-
Review abstracts and introductions to assess article quality
-
Read selected articles in detail and evaluate their methodology, findings, and conclusions
Develop a Research Question and Hypothesis
Show steps
Solidify your understanding of how to formulate a clear and testable research question and hypothesis for your capstone project.
Browse courses on
Research Question
Show steps
-
Review course materials on research question and hypothesis development
-
Identify a research topic of interest and explore related literature
-
Brainstorm potential research questions and refine them for clarity and specificity
-
Develop a hypothesis that is testable and supported by evidence
Four other activities
Expand to see all activities and additional details
Show all seven activities
Collaborate on Capstone Project Evaluation
Show steps
Enhance your critical thinking and evaluation skills by reviewing and providing feedback on other students' capstone projects.
Browse courses on
Capstone Project
Show steps
-
Read and evaluate assigned capstone project submissions
-
Provide constructive feedback on the methodology, findings, and conclusions
-
Engage in discussions with peers to exchange perspectives and deepen understanding
Support Peer Learning
Show steps
Contribute to a positive learning environment by assisting fellow students on discussion boards or in study groups.
Show steps
-
Participate in online forums or discussion boards
-
Provide helpful answers and explanations to student questions
-
Help clarify concepts or provide additional examples to aid understanding
Implement a Data Literacy Project
Show steps
Apply your acquired knowledge and skills to a practical project that demonstrates your proficiency in data literacy.
Browse courses on
Data Literacy
Show steps
-
Choose a data-driven problem or issue to address
-
Collect and analyze relevant data using appropriate techniques
-
Develop and implement a data-driven solution or intervention
-
Document and share your project findings and outcomes
Connect with Experts
Show steps
Seek guidance and support from experienced practitioners or researchers to enhance your learning and professional development.
Show steps
-
Identify potential mentors in your field of interest
-
Reach out to potential mentors and request mentorship opportunities
-
Establish regular communication and seek advice on your research, career, or other professional goals
Review Introduction to Quantitative Research
Show steps
Refresh your knowledge of the key principles and methods of quantitative research to build a solid foundation for the course.
Browse courses on
Quantitative Research
Show steps
Show steps
Show steps
- Read introductory articles or textbook chapters on quantitative research methods
- Review online tutorials or videos on basic quantitative research concepts
- Complete practice questions or exercises on quantitative research techniques
Explore Peer-Reviewed Quantitative Research
Show steps
Gain hands-on experience in finding and evaluating high-quality quantitative research articles to apply in your capstone project.
Browse courses on
Quantitative Research
Show steps
Show steps
Show steps
- Identify reputable journals and databases for quantitative research
- Use search terms and filters to locate relevant articles
- Review abstracts and introductions to assess article quality
- Read selected articles in detail and evaluate their methodology, findings, and conclusions
Develop a Research Question and Hypothesis
Show steps
Solidify your understanding of how to formulate a clear and testable research question and hypothesis for your capstone project.
Browse courses on
Research Question
Show steps
Show steps
Show steps
- Review course materials on research question and hypothesis development
- Identify a research topic of interest and explore related literature
- Brainstorm potential research questions and refine them for clarity and specificity
- Develop a hypothesis that is testable and supported by evidence
Four other activities
Expand to see all activities and additional details
Show all seven activities
Collaborate on Capstone Project Evaluation
Show steps
Enhance your critical thinking and evaluation skills by reviewing and providing feedback on other students' capstone projects.
Browse courses on
Capstone Project
Show steps
Show steps
Show steps
- Read and evaluate assigned capstone project submissions
- Provide constructive feedback on the methodology, findings, and conclusions
- Engage in discussions with peers to exchange perspectives and deepen understanding
Support Peer Learning
Show steps
Contribute to a positive learning environment by assisting fellow students on discussion boards or in study groups.
Show steps
Show steps
Show steps
- Participate in online forums or discussion boards
- Provide helpful answers and explanations to student questions
- Help clarify concepts or provide additional examples to aid understanding
Implement a Data Literacy Project
Show steps
Apply your acquired knowledge and skills to a practical project that demonstrates your proficiency in data literacy.
Browse courses on
Data Literacy
Show steps
Show steps
Show steps
- Choose a data-driven problem or issue to address
- Collect and analyze relevant data using appropriate techniques
- Develop and implement a data-driven solution or intervention
- Document and share your project findings and outcomes
Connect with Experts
Show steps
Seek guidance and support from experienced practitioners or researchers to enhance your learning and professional development.
Show steps
Show steps
Show steps
- Identify potential mentors in your field of interest
- Reach out to potential mentors and request mentorship opportunities
- Establish regular communication and seek advice on your research, career, or other professional goals
Career center
Learners who complete Data Literacy Capstone – Evaluating Research will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use scientific methods to extract knowledge from data. They use their findings to develop new products and services. The skills learned in this course, such as evaluating research and using data to solve problems, would be very helpful in this role, which typically requires a master's or PhD degree.
Data Analyst
Data Analyst
Data Analysts examine large amounts of data to uncover patterns and trends. They use their findings to help businesses make better decisions. The evaluation and interpretation skills developed in this course would be very helpful in this role, which often requires a master's degree.
Quantitative Researcher
Quantitative Researcher
Quantitative Researchers use statistical methods to analyze data. They use their findings to test hypotheses and draw conclusions. The skills learned in this course, such as evaluating research and understanding statistical methods, would be very helpful in this role, which typically requires a master's degree or PhD.
Research Analyst
Research Analyst
Research Analysts gather and analyze data on a specific topic. They use their findings to write reports and make recommendations. The skills learned in this course, such as searching for rigorous research and critically evaluating research, would be very helpful in this role, which often requires a master's degree.
Statistician
Statistician
Statisticians use data to solve problems. They use their findings to develop new methods and improve existing ones. The skills learned in this course, such as evaluating research and understanding statistical methods, would be very helpful in this role, which typically requires a master's or PhD degree.
Epidemiologist
Epidemiologist
Epidemiologists use data to study the causes of disease. They use their findings to develop new prevention and treatment strategies. The skills learned in this course, such as evaluating research and understanding data, would be very helpful in this role, which typically requires a master's or PhD degree.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to help businesses understand their customers. They use their findings to develop new marketing campaigns and improve customer service. The skills learned in this course, such as evaluating research and understanding data, would be very helpful in this role.
Business Analyst
Business Analyst
Business Analysts use data to help businesses make better decisions. They use their findings to develop new strategies and improve operations. The skills learned in this course, such as evaluating research and using data to solve problems, would be very helpful in this role, which typically requires a master's degree.
Health Economist
Health Economist
Health Economists use data to study the cost and effectiveness of health care. They use their findings to develop new policies and improve the efficiency of the health care system. The skills learned in this course, such as evaluating research and understanding data, would be very helpful in this role, which typically requires a master's or PhD degree.
Data Librarian
Data Librarian
Data Librarians are responsible for managing and organizing data. They use their skills to help researchers and other users find and access the data they need. The skills learned in this course, such as evaluating research and managing data, would be helpful in this role.
Financial Analyst
Financial Analyst
Financial Analysts use data to help businesses make investment decisions. They use their findings to develop financial models and make recommendations. The skills learned in this course, such as evaluating research and understanding data, would be helpful in this role.
Product Manager
Product Manager
Product Managers are responsible for the development and marketing of new products. They use data to understand customer needs and develop products that meet those needs. The skills learned in this course, such as evaluating research and using data, would be very helpful in this role, which typically requires a bachelor's degree.
Data Journalist
Data Journalist
Data Journalists use data to tell stories. They use their findings to inform the public about important issues. The skills learned in this course, such as evaluating research and understanding data, would be very helpful in this role.
Management Consultant
Management Consultant
Management Consultants use data to help businesses improve their operations. They use their findings to develop new strategies and improve processes. The skills learned in this course, such as evaluating research and using data to solve problems, would be very helpful in this role, which typically requires a bachelor's degree.
Market Researcher
Market Researcher
Market Researchers use data to understand customer behavior. They use their findings to develop new products and services. The skills learned in this course, such as evaluating research and understanding data, would be helpful in this role, which may require a bachelor's degree or higher.
For more career information including salaries, visit:
OpenCourser.com/course/jnsl88/data
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Data Literacy Capstone – Evaluating Research.
This comprehensive handbook covers a broad range of quantitative research methods used in psychology. It serves as a reference tool for advanced researchers.
This widely used textbook for social science research methods. It offers a comprehensive introduction to statistical concepts and methods used in social science research.
Provides a detailed and comprehensive guide to using SPSS for data analysis, step by step. It assumes no prior knowledge of SPSS.
Provides a comprehensive introduction to multivariate data analysis techniques. It covers a wide range of techniques and is written for students and researchers in various disciplines.
Comprehensive and up-to-date guide to regression analysis. It covers both the theoretical and practical aspects of regression analysis.
Comprehensive introduction to the Python programming language for data analysis. It covers the basics of Python and provides practical examples of using Python for data analysis and visualization.
Save
Comprehensive introduction to the R programming language for data science. It covers the basics of R and provides practical examples of using R for data analysis and visualization.
This advanced textbook covers research methods used in psychology. It discusses research design, data collection, and data analysis in quantitative psychology research.
Classic guide to social research methods, covering both qualitative and quantitative methods. It provides a good overview of the research process, from problem formulation to data analysis and interpretation.
Gentle introduction to machine learning for beginners. It covers the basics of machine learning and provides practical examples of using machine learning for data analysis and prediction.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/jnsl88/data
Share
Similar courses
Here are nine courses similar to
Data Literacy Capstone – Evaluating Research.
Fundamentals of Quantitative Modeling
OpenCourser.com/course/db3zya/fundamentals
Fundamentals of Quantitative Modeling
Measuring Total Data Quality
OpenCourser.com/course/8r5za3/measuring
Measuring Total Data Quality
Qualitative Research
OpenCourser.com/course/8pcvxx/qualitative
Qualitative Research
Quantitative Research
OpenCourser.com/course/42paf3/quantitative
Quantitative Research
Design Strategies for Maximizing Total Data Quality
OpenCourser.com/course/hgya76/design
Design Strategies for Maximizing Total Data Quality
The Total Data Quality Framework
OpenCourser.com/course/y27dvq/the
The Total Data Quality Framework
Modeling Risk and Realities
OpenCourser.com/course/2n0jtr/modeling
Modeling Risk and Realities
Quantitative Marketing Research
OpenCourser.com/course/8zyhd8/quantitative
Quantitative Marketing Research
Gender Analytics Capstone Project
OpenCourser.com/course/2kpdql/gender
Gender Analytics Capstone Project
Effort
3 weeks of study, 2-4 hours per week
Level
Intermediate
Via
Coursera
Institution
Johns Hopkins University
Instructor
Jennifer Bachner, PhD
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
हिंदी
Nederlands
Svenska
Pусский
Türkçe
Polski
Ελληνικά
українська мова
Bahasa Indonesia
ไทย
қазақша
This course belongs to a
collection
called
Data Literacy. It's comprised of five courses:
- Measurement – Turning Concepts into Data
- What are the Chances? Probability and Uncertainty in Statistics
- Quantifying Relationships with Regression Models
- Data Literacy Capstone – Evaluating Research (viewing)
- Data – What It Is, What We Can Do With It
Good to know
Students will be able to evaluate the findings of a piece of high-quality quantitative research on a topic of their choice
Students will be able to apply the skills and knowledge acquired throughout the specialization to the evaluation of published scholarly work
Students will be able to identify an article or report that they'll evaluate for the capstone project with the help of resources that frequently publish original, quantitative research
Students will be able to differentiate between primary and secondary research
Students will be able to complete and submit capstone projects and review submissions from other students as part of peer review system
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser