Registry
Module Specifications
Archived Version 2022 - 2023
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Description This year long module will provide students with an understanding of advanced qualitative and quantitative research methodologies, designs and analytical techniques in Psychology. A strong emphasis will be placed on developing and supporting statistical reasoning skills, including analytic competence, through laboratory experiments and computer-based practical sessions. Modules Aims: • To introduce students to statistical tests such as univariate and factorial ANOVA, regression analysis, and multi-variate analysis, their appropriate usage, how to compute them using SPSS statistical software, how to interpret them and how to report them in a manner consistent with standard reporting. • To introduce students to qualitative analytical techniques such as content and thematic analysis, their appropriate use, interpretation and reporting. • To equip students with the skills necessary to critically evaluate journal articles and other forms of research literature. • To increase students’ ability to identify and evaluate ethical issues in undertaking psychological research. | |||||||||||||||||||||||||||||||||||||
Learning Outcomes 1. Critically discuss the principal research designs and methods used in psychological research and assess their strengths and limitations. 2. Demonstrate a systematic understanding of the principles of univariate and factorial ANOVA, regression analysis and multivariate analysis, and the ability to accurately carry out such analyses using SPSS and report statistical results in a manner consistent with standard report writing and which is appropriate to NFQ Level 9 standard. 3. Show a critical awareness of the importance of power and effect size when carrying out any statistical analysis. 4. Critically evaluate the relative merits of different qualitative methodologies and demonstrate an understanding of key issues in qualitative approaches used in psychological research. 5. Demonstrate the ability to conduct qualitative research in an appropriate manner and analyse, interpret and report data gathered using qualitative means in a manner consistent with standard report writing and which is appropriate to NFQ Level 9 standard. 6. Demonstrate the ability to communicate psychological research in a clear, concise and scholarly manner, in practical reports that outline the research rationale, method, analysis, interpretation of findings and subsequent conclusions. 7. Demonstrate an advanced ability to critically analyse and synthesise research literature. 8. Demonstrate advanced literature searching skills and an enhanced ability to use the library and online psychology resources effectively. 9. Demonstrate the ability to effectively manage quantitative and qualitative data sets in a manner which is appropriate to NFQ Level 9 standard. 10. Recognise and critically discuss the ethical, methodological and professional issues in undertaking psychological research at NFQ Level 9. | |||||||||||||||||||||||||||||||||||||
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
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Indicative Content and
Learning Activities Advanced information literacy skills(accessing and effectively using library and online resources in psychology)Systematic reviews and meta-analysesResearch methods and design(quantitative, qualitative, mixed methods; design issues such as replication & reproduction)Qualitative Methods(e.g. grounded theory, phenomenology, ethnography, case study)Approaches to qualitative data collection(e.g. interview, focus groups, print and visual media)Approaches to qualitative analysis(including introduction to NVIVO computer software)Conducting advanced qualitative research(including content analysis, thematic analysis, interpretative phenomenological analysis)Experimental and correlational designDescriptive statistical techniques(central tendency, dispersion, exploring data using graphs, introduction to SPSS)Distributions, confidence intervals and hypothesis testingUnivariate techniques(e.g. Within- and between-group t-tests and ANOVA, non-parametric equivalents of each, factorial ANOVA)Bivariate techniques(e.g. correlation and simple regression analysis)Preparing for multivariate analysis(e.g. examining your data, missing data analysis, outliers, assumptions, data transformation)Dependence techniques(e.g. multiple regression analysis, logistic regression, multivariate analysis of variance)Interdependence techniques(e.g. factor analysis)Ethical and professional issuesData handling(e.g. missing data, transforming data, data cleansing, GDPR-related issues) | |||||||||||||||||||||||||||||||||||||
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Indicative Reading List
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Other Resources None | |||||||||||||||||||||||||||||||||||||
Programme or List of Programmes | |||||||||||||||||||||||||||||||||||||
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