Measuring and analysing

Academic year: 2009-2010 Course code module 1MSOCW-016 Semester: 2nd semester Credits: 6 Study load (hours) 168 Theory (hours): 45,00 Practice/Exercises(hours): Other (hours): Part-time program: 1 Instructor(s) Dimokritos Kavadias Language of instruction: Dutch Semester exam information: exam in the 2nd semester Contract restriction information: exam contract not possible 1. Prerequisites *Algemene competenties The students have an understanding of a scientific approach of social problems. They are able to elaborate a research design in order to study a descriptive or explanatory  problem.  To this end they use the theoretical tools from the courses “Quantitative Research Methods”, “Statistics 1” and “Statistics 2”. *Sequentiality None 2. Objectives (expected learning outcomes) The main objective of this course is to teach students how to perform quantitative research. As a consequence students should be able to assess social research correctly. The students should know how to design of a quantitative study in a concrete setting, using the most appropriate measurement instruments. The students should be able to analyse the gathered data using the most appropriate method / model of analysis. More specifically: - The students can find relevant social scientific sources on a social problem in a library. - The students are able to translate the social problem into a general scientific research question. - The students are able to translate the research question into  more concrete questions. - The students can elaborate a theoretical framework in function of the research question. - The students are able to operationalize the concepts. The can look up or develop relevant measurement instruments in order to map the research question. - The students are aware of the relevant administrative data-resources as possible alternatives in order to measure a concept. - The students have an understanding of the construction of measurement scales; they are able to test the internal consistency of scales and test them on dimensionality. - The students are able to formulate hypotheses on the basis of their theoretical framework. - The students are able to choose the most appropriate research format in order to test the formulated hypotheses (tabular analyses; analysis of variance/ co-variance; linear and/ or logistic regression) and can apply this format in SPSS. - The students can draw correct conclusions from their analysis. 3. Course content The students are familiarized with the most used quantitative research methods in the social sciences, through 10 contact moments. The final aim of the course is to write a paper. In the writing of this paper, they will journey through the different phases of the social-scientific empirical cycle: the description of a social problem (concept), using existing indicators (indices, measurement scales); the formulation of a scientific research problem; getting some insights in the possible causes (elaboration of a theoretical framework); operationalizing the concepts (develop and assess the measurement instruments); formulating the hypothesis (develop a framework of analyses) and testing the hypothesis in SPSS on existing data; interpret the results of the analysis in the light of existing theory. 4. Teaching method Direct contact: Lectures Exercise sessions Seminars (possible question and answer sessions) Personal work: Exercises Assignments - individual Paper - in group Supervised self-study 5. Assessment method Exam: Practical exam Continuous assessment: Assignments Written assignment: With oral presentation 6. Compulsory reading – study material - Bryman, A. (2004) Social Research Methods. Oxford, Oxford University Press. - De Maeyer, S. & D. Kavadias. (2007). Openleerpakket Beschrijvende statistiek. Principes en toepassingen met SPSS en rekenbladen. Gent: Academia Press. - Mortelmans, D. & Dehertogh, B. (2006). Kennismaken met SPSS en SAS. Leuven: ACCO. - Mortelmans, D. & Dehertogh, B. (2006). Databeheer met SPSS en SAS. Leuven: ACCO. 7. Recommended reading - study material - Dancey, Christine P. & John Reidy. (2004). Statistics without maths for Psychology. Using spss for windows. London: Prentice Hall. - Salkind, Neil J. (2005). Exploring Research. London: Prentice Hall. - Salkind, Neil J. (2002) Statistics for people who (think they) hate statistics, Thousand Oaks: Sage. - Spiegel, Murray R. & Larry J. Stephens (1999). Schaum's outline of theory and problems of statistics, New York: McGraw Hill. 8. Tutoring Tutoring is foreseen during the contact moments. Next of the possibility to ask questions concerning the content of the course, students get each session an assignment pertaining an aspect of “measuring” or “analysing”. This assignment is given posted on the electronic learning platform of the university for this course (Blackboard). The students need to post their assignment within a given term (most of the time one or two weeks) through Blackboard. The students are assessed on completeness and not on the correctness of the answers. In the following contact moment students get feed back on these so-called “self-study assignments”. This course also tries to stimulate electronic tutoring and peer-tutoring (through Blackboard and e-mail). laatste aanpassing: last update: 07/12/2008 22:50 dimokritos.kavadias