08829 - Social Research Methodology

Learning outcomes

At the end of the course, students will be able: - to describe the social characteristics of administrative territories (regions, provinces, municipalities) using official statistics; - to detect and evaluate the social hardship by carrying out a basic research; - to critically analyse, from a methodological point of view, a research report ; - to carry out empirical research using the survey method; - to carry out empirical research analysing the official statistic.

Course contents

In social work, planning is necessarily associated with a research perspective. The data collection, data reading, data analysis and research activities form the basis for the definition of interventions, their monitoring and evaluation.

The course will deal with the techniques and methods of data collection and analysis, which are fundamental for both social planning and the preparation of the thesis in its empirical part.

After introducing how a research project is set up, we will focus on the traditional distinction between quantitative and qualitative techniques.

In the case of the former, the sample survey, statistical sources, some basic elements of descriptive statistics will be presented.

With regard to qualitative techniques, reference will be made to participant observation, in-depth interview and the use of documents.

Readings/Bibliography

For all (attending and not):

Corbetta P., Metodologia e tecniche della ricerca sociale, Bologna, Il Mulino, 2014.

Chap. 1, chap. 2, chap. 3, chap. 5, chap. 6 , chap. 8, chap. 10, chap. 11, chap. 12, chap.13 (all except sections 7.1, 7.2, 7.3, 7.4, 9.1, 9.2, 11.1), chap. 14 (all except sections 3, 4, 4.1, 4.2, 4.3, 5, 6.1, 6.2, 6.3, 7.2, 7.3, 7.4).

The book is available on Pandoracampus where individual chapters can also be accessed for a fee.

https://www.pandoracampus.it/store/details/10.978.8815/359292

Teaching methods

Lecturers and, only for attending students, practical exercises (e.g., active listening, interview analysis, introduction to univariate and bivariate data analysis).

Assessment methods

Non-attending students
The exam will be written and will consist of two open questions (with limited answer length) and an analysis exercise (chap. 13 and 14), 60 minutes. Examples of exercises can be found in Virtual.

It is possible to use the calculator (not the one on the smartphone).

Attending students (80% attendance of lectures and at least 4 exercises)
The exam will be written and will consist of one open question (with limited length of answer), 30 minutes. The exercises carried out in the lectures will also be assessed and will contribute to the final grade for a maximum of 3 points out of 30.

The dates of the exercises will be published in Virtual in October 2026. To be considered as having attended, you must complete at least four of the five scheduled exercises. Exercises 4 (analysis of an interview) and 5 (introduction to univariate and bivariate data analysis) are compulsory. The exercises will be discussed in the classroom.

A limited, declared, and non-substantial use of AI is permitted for support activities ONLY in carrying out Exercise 2.

 

 

To take the exam, students must register in Alma Esami (https://almaesami.unibo.it/almaesami/welcome.htm). Please note that for written exam registrations close one week before the exam date.

 

The exam result is communicated to the student by Almaesami; students can accept or refuse the score within the terms provided by the University Didactic Regulations. Once the deadline has passed, the lecturer will record the grades (tacit acceptance procedure).

 

Students with learning disabilities (LD) or temporary or permanent disabilities: please contact the responsible University office promptly (https://site.unibo.it/studenti-con-disabilita-e-dsa/en). They will be responsible for suggesting any accommodations to the students concerned. These accommodations must, however, be submitted to the lecturer for approval 15 days in advance.

 

 

Teaching tools

Slides and resources available on Virtuale (https://virtuale.unibo.it/)

Office hours

See the website of Marco Trentini