First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Psychology
PSYCHOLOGICAL SCIENCES AND TECHNIQUES
Course unit
PSYCHOMETRICS
PSP4068036, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course First cycle degree in
PSYCHOLOGICAL SCIENCES AND TECHNIQUES
PS1842, Degree course structure A.Y. 2011/12, A.Y. 2018/19
N0
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Number of ECTS credits allocated
Type of assessment Mark
Course unit English denomination PSYCHOMETRICS
Department of reference Department of Developmental Psychology and Socialisation
Mandatory attendance No
Language of instruction Italian
Branch PADOVA
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge LIVIO FINOS M-PSI/03

Modules of the integrated course unit
Course unit code Course unit name Teacher in charge
PSP4068037 PSYCHOMETRICS MOD. A LIVIO FINOS
PSP4068038 PSYCHOMETRICS MOD. B EGIDIO ROBUSTO

Course unit organization
Period  
Year  
Teaching method distance e-learning

Calendar
Start of activities 25/02/2019
End of activities 14/06/2019
Show course schedule 2019/20 Reg.2011 course timetable

Examination board
Board From To Members of the board
4 2018 01/10/2018 30/09/2019 FINOS LIVIO (Presidente)
ALTOE' GIANMARCO (Membro Effettivo)
ROBUSTO EGIDIO (Membro Effettivo)

Syllabus
Prerequisites: Equations and inequalities of the first and second degree; equation of line, of the parabola and of the circle in the plan, trigonometry: key relationships and functions; properties of powers and logarithms; elements of set theory, the concept of relation, function and properties; knowledge of elementary functions; basic geometry concepts.
Target skills and knowledge: This course covers statistical concepts and methods that can be applied in psychological research. The course is intended to provide a conceptual understanding of basic statistical procedures for exploring and understanding data in applied research. It also helps students develop the computational skills needed to carry out statistical procedures in practical settings.
Examination methods: written exam
Assessment criteria: The evaluation of the performance of the student will be based on the comprehension of the statistical methodologies and the ability to apply them autonomously in a research context.

Innovative teaching methods: Teaching and learning strategies
  • Case study
  • Peer feedback
  • Peer assessment
  • Auto correcting quizzes or tests for periodic feedback or exams
  • Video shooting made by the teacher/the students
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • Kaltura (desktop video shooting, file loading on MyMedia Unipd)
  • Camtasia (video editing)
  • Latex
  • R