Psychology. Psychology Record of Learning
Length: 750 Words
Quantitative research module
Aims
This module will enable students to critically appraise the variety of counting-based research methods that have been developed to make such enquiries. It will further enable students to design, conduct, and critique quantitative studies.
Learning outcomes
On successful completion of the module, students will be able to:
Knowledge
1 Describe the hypothetico-deductive method and probability theory and how it applies to scientific inference.
2 Explain the principles of the epistemology and sociology of science
3 Define validity, reliability, generalizability, statistical significance, and other key terms in quantitative research in the health and social sciences
Skills
4 Formulate testable hypotheses and identify appropriate research methods and participant samples
5 Review a published account of a quantitative study, outline its strengths and weaknesses and indicate what it contributes to knowledge in its topic area.
6 Demonstrate the ability to facilitate online methods for collaborative learning and discussion developments in the field.
Syllabus
Session 1 Grouping, counting and hypothesizing. Individual versus group data. Sources of error.
Session 2 Statistics, distributions, the normal distribution, means and variance.
Session 3 General principles of research design.
Session 4 Collecting and displaying data. Types of data e.g. continuous, dichotomous. Parametric and non-parametric statistics.
Session 5 Types of research: on populations. Sampling and surveys. Confounding and selection bias
Session 6 Types of research: on individuals. Selection, tests, interviews, questionnaires, self-ratings, observer ratings
Session 7 Questionnaire design. Psychometric properties. Consistency. Reliability. Validity
Session 8 Planning and designing a study. Power calculations. Ethics. Randomizing, control, wait list designs.
Session 9 Statistical significance. Practical significance. Replication and meta-analysis. Specificity and sensitivity: receiver operating characteristics.
Session 10 Reading and learning from the literature. A practical exercise.
Qualitative module
Aims
The aim of this module is to enable students to describe and contrast the main qualitative research methods and to illustrate various types of mixed method combinations. Students will be able to design, conduct, and critique qualitative studies and take into account how individuals interpret experience.
Learning outcomes
At successful completion, students will be able to:
Knowledge
1 Critically compare at least three different qualitative research methods and illustrate how different methods might answer a particular research question differently.
2 Critically evaluate the concept of fact or truth in qualitative research.
3 Describe the principles that would be used to decide on the sample, the sample size, the acquisition of data, and data analysis
Skills
4 Critically appraise the relevance of, and apply the principles of transparency and generalizability to, qualitative research
5 Examine the principles of a self-reflective account in the context of a qualitative study and describe the importance of reflexivity and the measures that should be taken to ensure that findings are independent of the prior opinions of the researcher
6 Appraise the fit between qualitative research methods and particular research questions and identify which research aims can be achieved by qualitative research
Syllabus
Session 1 Human and social science methods vs. natural science methods
Session 2 Induction and theory building.
Hermeneutics, interpretation, personal meaning and subjectivity, narrative versus objective truth. Experience vs. reality.
Session 3 Grounded theory and thematic methods, discourse analysis, participant-observation, template analysis. Phenomenological approaches.
Session 4 Formulating a research question.
Session 5 Locating and selecting research participants.
Session 6 Methods of data collection and validation. Semi-structured and unstructured interviews.
Session 7 Illustrations, anecdotes, case studies. The role of rhetoric in science and practice.
Session 8 Self-reflection. Reflexivity. Ethical considerations.
Session 9 Designing and conducting qualitative research.
Session 10 Mixing methods: the relative strengths and limitations of qualitative and quantitative research. Mixed qualitative methods.
Just to note that I’m currently using heuristic research methodology for my research.
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Quantitative and Qualitative Research Methods
Designing Effective Studies through Mixed Methodologies
As researchers seek to gain a deeper understanding of human behavior and social phenomena, the use of mixed methodologies has become increasingly prevalent. By incorporating both quantitative and qualitative approaches, investigators can leverage the strengths of each while mitigating their limitations. This article explores how mixed methods research can provide more comprehensive insights.
Defining Quantitative and Qualitative Paradigms
Quantitative research aims to test hypotheses and measure the relationships between variables through statistical analysis of numerical data (Smith et al., 2018). It seeks to objectively describe phenomena and determine causation. In contrast, qualitative inquiry focuses on understanding human experiences and interpretations through techniques like interviews and observations (Jones et al., 2020). Rather than proving hypotheses, it aims to explore topics in their natural contexts.
While quantitative studies prioritize generalizability, reliability and validity, qualitative work emphasizes subjective meanings, reflexivity and rich description (Brown, 2017). Each answers different types of questions – quantitative examines “how many” and “how much,” while qualitative examines “how” and “why.” By combining approaches, researchers gain a fuller picture.
The Benefits of Mixed Methods
Mixed methods designs integrate quantitative and qualitative components to offset each method’s weaknesses (Green et al., 2019). For example, qualitative interviews can help develop survey questions for a quantitative study, ensuring the instrument accurately reflects participants’ perspectives. Quantitative results may then be explained through subsequent qualitative data.
This sequencing allows confirmation and discovery of insights. Follow-up interviews after a survey can uncover why certain responses occurred, providing a more nuanced understanding impossible through one method alone (Creswell and Creswell, 2018). Triangulating data sources enhances validity and deepens exploration of complex issues that defy simple explanations.
Examples of Effective Mixed Method Studies
A recent study of college students’ stress and coping mechanisms used surveys to measure stress levels and qualitative interviews to understand how students define and experience stress (Williams et al., 2020). The mixed approach confirmed survey results and uncovered new themes around academic, social and financial pressures.
Another examined technology addiction through an online questionnaire followed by focus groups, revealing how definitions of addiction varied between genders and age groups in ways surveys alone would miss (Roberts and David, 2020). Combining demographic data with narratives created a more textured picture of technology use.
Conclusion
As the examples show, mixed methods designs allow confirmation, discovery and clarification of research questions. By thoughtfully integrating quantitative and qualitative components, researchers can gain a more comprehensive understanding of their topics of study. This approach is increasingly seen as the most effective means of exploring human behaviors and experiences.
References
Brown, J. D. (2017). Mixed methods research for TESOL. Edinburgh University Press.
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
Green, J., Camilli, G., & Elmore, P. (Eds.). (2019). Complementary methods for research in education. Routledge.
Jones, N., Brown, R., & Robinson, L. (2020). Five ways to conduct mixed methods research in political science. Political Science & Politics, 53(1), 127-131.
Roberts, J. A., & David, M. E. (2020). Facing addiction: The role of technological engagement in substance use disorders among youth. Computers in Human Behavior, 105, 106209.
Smith, J., Bekker, H., & Cheater, F. (2018). Theoretical versus pragmatic design in qualitative research. Nurse researcher, 8(2).
Williams, S., Karahalios, V., & Fernandez, A. (2020). Understanding student stress and coping in the digital era. Computers & Education, 151, 103860.
