This course is designed to equip doctoral students with the essential knowledge and skills required to effectively design and conduct empirical research, specifically in the context of analyzing quantitative data. Throughout the course, students will explore in depth a range of key concepts and methodologies critical to empirical research design and implementation. This includes a thorough examination of the tools and techniques needed to structure research questions, collect data, and analyze findings in a meaningful and rigorous way.
Students will also gain hands-on experience with quantitative research procedures that are particularly useful for analyzing multivariate, correlational, and causal relationships. These methods are vital for understanding complex data patterns and drawing valid conclusions from them. By mastering these techniques, students will develop a strong foundation in handling large datasets, applying statistical software, and interpreting quantitative results with confidence and accuracy. They will gain proficiency in using the Jamovi software, which is an open-access alternative to well-known commercial data analysis software.
By successfully completing this course, students will be well-prepared to apply quantitative-driven empirical research methods in their future professional careers. Moreover, they will have the ability to contribute meaningfully to the advancement of knowledge in their chosen discipline, using data-driven approaches to address real-world challenges.
This online, synchronous course is designed to equip students with the essential knowledge and skills required to effectively design and conduct empirical research, specifically in the context of analyzing quantitative data.
A key focus is on developing transversal skills, such as critical thinking, problem-solving, and collaboration. These skills are cultivated through practical assignments, group work, and peer feedback, fostering a learning environment that prepares students to adapt to diverse professional and academic contexts.
This course equips students with a comprehensive understanding of multivariate statistical procedures, which are central to advanced quantitative research.The curriculum includes the exploration of factor analysis and consistency testing methods, which are essential for assessing the reliability and validity of measurement scales. These tools are particularly useful in social sciences research, where understanding latent variables and their consistency is critical.
Additionally, the course covers other key multivariate techniques, which are vital for comparing group differences and relationships between categorical and continuous variables. Moreover, advanced topics such as correlation and various forms of regression analysis will be taught, providing students with the ability to model complex relationships between variables.
To conclude the course, students will participate in an end-of-year wrap-up meeting and present their research findings. This final presentation serves as an opportunity to apply the research-based skills acquired throughout the course, demonstrating their ability to conduct empirical research, analyze data, and communicate results effectively.
To further enhance learners’ understanding, we’ve created a video summarizing key statistical analysis procedures, serving as a useful reference for student revision:https://shorturl.at/tv3sM
Capability (Skills)
Research Design and Implementation: Students will be able to design, implement, and evaluate empirical research projects, applying quantitative methods to analyze multivariate, correlational, and causal relationships.
Data Analysis Using Technology: Students will develop proficiency in using Jamovi software, an open-access tool for data analysis, enhancing their technical skills in quantitative research and fostering adaptability to new technologies.
Critical Thinking and Problem-Solving: Through hands-on practice, students will refine their ability to critically analyze data, interpret statistical results-
Knowledge
Quantitative Research Methods: Students will gain in-depth knowledge of quantitative research procedures, including data collection, multivariate analysis, and statistical interpretation, equipping them with the theoretical understanding necessary for evidence-based research.
Empirical Research Foundations: They will deepen their understanding of key empirical research principles, including hypothesis testing, research design, and the application of statistical methods in the social sciences and sustainability.
Source Evaluation and Utilization: Students will learn how to discover, evaluate, and integrate academic and industry sources relevant to their research, enabling them to conduct thorough literature reviews and support their findings with credible evidence.
Attitude
Ethical Research Conduct: Students will develop a responsible and ethical approach to data handling, analysis, and reporting, fostering a commitment to integrity and transparency in their research.
Collaborative Engagement: Students will build teamwork and collaboration skills, applying technology-enhanced tools to engage with peers, share research, and contribute to collective problem-solving in academic and professional contexts.
There are no specific prerequisites for this course, as it begins with foundational concepts and gradually introduces key quantitative research methods. It is designed for learners at all levels, including those with no prior experience in empirical research
Babbie, E. R. (2014). The practice of social research. Cengage learning.
Bryman, A. (2016). Social research methods. Oxford university press.
Moore, D. S., McCabe, G. P., & Craig, B. A. (2021). Introduction to the practice of statistics (10th ed.). W.H. Freeman and Company.
May, T., & Perry, B. (2022). Social research: Issues, methods and process. McGraw-Hill Education
Neuman, W. L. (2014). Social research methods: Qualitative and quantitative approaches (7th ed.). Pearson.
Navarro, D., & Foxcroft, D. (2019). Learning statistics with jamovi: A tutorial for psychology students and other beginners (Version 0.70). Tillgänglig online: http://learnstatswithjamovi. com
Emphasizing student-centered learning, transversal skills, transdisciplinary, research-based competencies, and technology-enhanced educational principles, this course is designed to provide doctoral students with a comprehensive and practical understanding of empirical research methods.
Students will engage in interactive lectures, discussions, and group activities that encourage active participation and critical thinking in the course of the entire course. Furthermore, regular feedback sessions will be conducted to address individual learning needs and progress, ensuring that each student receives personalized guidance.
To develop students’ research skills, the course will focus on an in-depth exploration of key concepts and methodologies critical to empirical research design and implementation. This includes hands-on experience with quantitative research procedures, such as multivariate, correlational, and causal analysis.
To improve students’ transversal skills, emphasis will be placed on developing skills to critically evaluate research methodologies and data by engaging students in rigorous analysis exercises, case studies, and interactive discussions that challenge their analytical thinking and problem-solving abilities.
Additionally, group projects and peer reviews will foster teamwork and collaborative problem-solving skills. A peer review system will be implemented where students evaluate each other’s work from different disciplinary perspectives. This approach encourages critical evaluation and constructive feedback from diverse viewpoints, thereby improving the quality of research and deepening students’ understanding of interdisciplinary approaches.
To enrich technology-enhanced learning experiences, digital tools and resources will be used, including online databases, statistical software, and virtual collaboration platforms. Additionally, supplementary video materials will be provided to reinforce key concepts and allow for self-paced learning.
Transcript of records
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