BUILDING AND COMMUNICATING THE DATA
COSTRUIRE E COMUNICARE IL DATO
A.Y. | Credits |
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2023/2024 | 6 |
Lecturer | Office hours for students | |
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Francesco Sacchetti | For one hour at the end of lessons |
Teaching in foreign languages |
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Course with optional materials in a foreign language
English
This course is entirely taught in Italian. Study materials can be provided in the foreign language and the final exam can be taken in the foreign language. |
Assigned to the Degree Course
Date | Time | Classroom / Location |
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Date | Time | Classroom / Location |
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Learning Objectives
The course provides students with a broad introduction to the methodology and logic of social science research. In particular, the quantitative approach will be explored, providing the tools to understand the logic and procedures of data construction and analysis. In addition, the aim is to provide students with the necessary knowledge to represent data as a source of information in the communication phase of research work.
Program
The programme will cover the following main themes
from reality to its representation
data matrix
operationalisation of concepts
indicators and index
monovariate analysis
bivariate analysis
graphical representations
sampling
argumentation and presentation of results
Bridging Courses
none
Learning Achievements (Dublin Descriptors)
Students must achieve:
1. Knowledge and understanding
Students should possess
- basic theoretical knowledge for understanding data construction processes in research with a quantitative approach.
- basic conceptual tools for the analysis of data and their interpretation.
Students acquire this knowledge through attendance of lectures, participation in classroom discussions on the topics addressed in the lectures, activities involving the use of data analysis software guided by the lecturer and through the study of texts.
2. Applied knowledge and understanding
The knowledge acquired during the course will be applied to the analysis of concrete research situations. They should be able to construct and recognise different categories of variables, know the main characteristic values, know how to read and construct mono and bivariate analyses, know how to graph data.
Students acquire this knowledge by attending lectures, participating in classroom discussions on the topics addressed in the lectures, and through problem solving, small group work, use of data analysis software, and through the study of texts.
3. Judgment
Students should be able to make informed and autonomous judgements on different concrete situations of reading and constructing data based on the knowledge acquired during the course.
Students acquire these skills through discussion in the classroom with the lecturer and colleagues, during exercises and lectures, and through individual study.
4. Communication skills
Students are expected to have expressive and communicative skills in written and oral Italian, as well as basic competences in the specialised language of the discipline and data representation skills.
Students acquire these skills by interacting in the classroom through questions to the lecturer, responding to the lecturer's requests on the topics dealt with in the lessons, exchanging ideas with fellow students, making short presentations in public while reporting to colleagues and the lecturer on the results of the classroom exercises, writing short texts during the classroom exercises.
5. Learning skills
Students are expected to acquire learning skills for further study.
Students acquire these skills through classroom discussion, argumentation of answers to the lecturer's questions, discussion with fellow students during lectures and classroom exercises and individual study.
Teaching Material
The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it
Supporting Activities
No supporting teaching activities are planned.
Teaching, Attendance, Course Books and Assessment
- Teaching
In addition to lectures, students will be asked to work in groups to operationalise variables and find solutions for the construction of matrices, representation of data series, etc. Concrete examples will be given using the (free) programme PSPP. Concrete examples of construction using the (free) PSPP programme will be presented in the classroom.
- Innovative teaching methods
Flipped learnign; Problem solving
- Attendance
Attendance at least 50% of the lesson hours
- Course books
Marradi, A., Pavsic, R., & Pitrone, M. C. (2007). Metodologia delle scienze sociali. Il mulino.
For foreign students
Bhattacherjee, Anol, "Social Science Research: Principles, Methods, and Practices" (2012). USF Tampa Bay Open Access Textbooks Collection. Book 3.
- Assessment
The expected learning outcomes will be assessed by means of a written test.
The assessment criteria are: the level of mastery of knowledge, the degree of articulation of the answer, the level of mastery in the application of knowledge to concrete cases or referring to examples and experiences of the course.The mark for the written test is expressed in thirtieths.
Positive assessments will be given to: the student's possession of good critical and in-depth study skills; the ability to link together the main themes addressed in the course; the use of appropriate language with respect to the specific nature of the discipline.
Negative evaluations will be given: difficulty in the student's orientation in relation to the themes dealt with in the examination texts; gaps in training; use of inappropriate language.
- Disability and Specific Learning Disorders (SLD)
Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.
To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.
Additional Information for Non-Attending Students
- Teaching
Blended learning, the study of the indicated texts.
- Course books
The set texts for part-time students – who are able to take the exam as non-attending
students – are:Marradi, A., Pavsic, R., & Pitrone, M. C. (2007). Metodologia delle scienze sociali. Il mulino.
Additional material proposed by the teacher on the platform
For foreign students
Bhattacherjee, Anol, "Social Science Research: Principles, Methods, and Practices" (2012). USF Tampa Bay Open Access Textbooks Collection. Book 3.
- Assessment
Students who do not attend classes are invited to consult the teaching materials uploaded on Moodle (slides discussed in class, any additional materials) through which they will be able to study in greater depth the volumes indicated in the "Study texts" section.
through which it will be possible to study in greater depth the volumes indicated in the "Study texts" section.The expected learning outcomes will be assessed by means of a written test.
The assessment criteria are: the level of mastery of knowledge, the degree of articulation of the answer, the level of mastery of the answer, the level of mastery of the answer.
The assessment criteria are: the level of mastery of knowledge, the degree of articulation of the answer, the level of mastery in the application of knowledge to concrete cases.
The mark in the written test is expressed in thirtieths.Positive assessments will be given to: the student's possession of good critical and in-depth skills; the ability to link together the main themes addressed in the course; the use of language appropriate to the specific nature of the discipline.
Negative evaluations will be given: difficulty in orienting the student with respect to the themes dealt with in the examination texts; gaps in training; use of inappropriate language.
- Disability and Specific Learning Disorders (SLD)
Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.
To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.
Notes
Attendance is obligatory for a minimum of 50% of the lessons. It is not possible to take the exam as a non-attending student, with the only exception of those students who are studying part-time.
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