Teaching methodology based mainly on master classes with ICT support and seminars on the analysis and application of topics worked on in the subject, with specific practical work for each topic and analysis and debate on the specific practical contribution of the psychologist in Health Psychology.

In the link https://www.uab.cat/doc/DOC_PautesAvaluacio_2026 you will find the evaluation guidelines of the Faculty

Two partial exams will be undertaken, each worth 35% of the final grade. The grades obtained in two blocks of activity reports related to the seminars are added, each of them will count 15% of the final grade (30% together).

To pass the subject, the average of marks of the two partial exams (assessments 2 and 4) must be equal or superior to 5 (on a scale from 0 to 10). That is, a minimum of 3.5 points must be obtained in the sum of assessments 2 and 4.

In total, the students are offered 4 assessments, which are worth 10 points:

Assessment 1: Written report (individual or group) of activities related to seminars 1, 2 and 3: 1.5 points. Way of presentation, through a specific section in the Moodle classroom of the subject.

Assessment 2: Written test on areas 1, 2 and 3 of the programme: 3.5 points (individual)

Assessment 3: Written report (individual or group) of activities related to seminars 4, 5 and 6: 1,5 points. Way of presentation, through a specific section in the Moodle classroom of the subject.

Assessment 4: Written test on areas 4, 5 and 6 of the programme: 3.5 points (individual)

RETURN:

Evidence 1: Set of reports from seminars 1, 2 and 3. The return consists of a grade between 0 and 1.5 points, throughout week 7, in the Moodle classroom of the subject.

Evidence 2: In person exam on the first three topics of the subject. It is carried out in week 7 and the grade is reported the day after the test.

Evidence 3. Set of reports from seminars 4, 5 and 6. The return consists of a grade between 0 and 1.5 points, throughout week 19, in the Moodle classroom of the subject.

Evidence 4: In person exam on the last three topics of the subject. It is carried out in week 19 and the grade is reported the day after the test.

Regarding evidence 1 and 3, students who request it will be able to receive detailed information on the elements that have led to a certain grade, in face-to-face tutorials and/or by TEAMS

The final grade is the sum of the four evidences. No additional tests are undertaken to improve the grades obtained in the four evidences.

The subject is deemed to be passed if 5 or more points are obtained in the sum of the 4 assessments, as long as 4 points or more have been in each evaluation tests that have a contribution equal to or greater than 20% of the grade of this continuous evaluation, that is, in evidences 2 and 4. Not meeting these criteriameans that a maximum grade of 4.5 marks (range 0-10) can be recorded on the student’s academic transcript.

A student who has submitted assessments with a weighting equal to or greater than 4 points (40%) will obtain a grade. A student with lower assessment grades will be \"not evaluable\".

Re-assessment

All the following criteria must be met in order to go to re-assessment:

a) Having obtained between 3.5 and less than 5 points in the continuous assessment.

b) The weight of the assessments which the student has submitted during the course must be 66.7% or more.

Characteristics of the resit test:

It will consist in re-taking Ev2 or Ev4 assessments, with the same characteristics and correction criteria as in the first time. Assessments EV1 and EV3 cannot be re-assessed, because it is not possible to repeat the seminars (so, the same grades will be added to the final grade).

Re-assessment will take place in the period allocated for resits, the day and time being determined by the Faculty.

No unique final synthesis test for students who enroll for the second time or more is anticipated.

This subject does not consider single assessment

Us of Artificial Intelligence (AI):

Model 2 - Restricted use: For this subject, the use of Artificial Intelligence (AI) technologies is allowed exclusively in support tasks, such as bibliographic or information search, text correction or translations.The student will have to clearly identify which parts have been generated with this technology, specify the tools used and include a critical reflection on how they have influenced the process and the final result of the activity. The non-transparency of the use of AI in this assessable activity will be considered a lack of academic honesty and may lead to a partial or total penalty in the grade of the activity, or greater sanctions in cases of severity.