The methodology of this course, based on action research, focuses on observation as a starting point, followed by the planning, implementation and evaluation of practical interventions. Each student will have the opportunity to apply theoretical knowledge in real situations, reflect on her actions and develop critical analysis and problem-solving skills. To this end, collaboration and teamwork are also promoted to enrich learning and obtain different perspectives.

Thus, from a multivariate methodological perspective, the strategies that will be used will include:

• Self-observation and analysis of psycho-pedagogical practice.
• Design, implementation and evaluation of psycho-pedagogical proposals.
• Specialized face-to-face, collective and/or individual tutorials
• Consultation and reading of the recommended bibliography.
• Comments and/or exhibitions of readings.
• Preparation of psycho-pedagogical reports.

Continuous assessment

• The assessment of the course is based on continuous monitoring of the internship/practical training process and on the evaluation of the evidence produced throughout the training period.
• Attendance at in-person sessions and at the placement centre is mandatory. Failure to meet the attendance requirements will result in not passing the course.
• The submission date for the internship report will be during the first week of June 2027.
• Except for tutorials and complementary activities, which may be individual or group-based, all other assessment activities are individual.
• To pass the course, all pieces of evidence must achieve a minimum grade of 5 out of 10.
• According to UAB regulations, plagiarism or copying of any assignment or written test will be penalised with a grade of 0 for that piece of evidence, with no possibility of retake, whether it is an individual or group assignment (in the latter case, all group members will receive a 0).
• A student will be considered “Not Assessable” if they have not submitted evidence representing at least 33% of the total grade.

Single assessment

This course/module does not include a single-assessment system.

Points to consider:

• Feedback, returns, or grades for the assessed tasks will be provided within a period not exceeding 20 working days.
• If the course is not passed, it will be possible to retake the internship report or the failed assessments within the period established by the academic calendar.
• This course is based on the deontological principles of the profession. To pass the course, students must demonstrate attitudes consistent with professional educational practice: responsibility, punctuality, respect, teamwork skills, appropriate communication, and ethical commitment.
• In all assessed tasks, linguistic accuracy, textual coherence, and academic communication skills will be evaluated. An activity may be returned or failed if it does not meet minimum formal quality requirements.
• In this course, the use of Artificial Intelligence (AI) technologies is permitted exclusively as support tools, such as text correction, translation, idea generation, initial content organisation, or preliminary conceptual exploration. These tasks must not replace, under any circumstances, the systematisation or standard handling of data, nor the student’s main responsibilities as the author of the work, such as original writing, management and processing of their own data, critical analysis, or discussion of results.
• The student must clearly identify which parts of the work have been generated using AI technologies, specify the tool used (including version and specific function), and include a critical reflection on how the use of AI has influenced the process and the final outcome of the work. This reflection may be included in the appendix or in the methodological chapter, as appropriate.
• Failure to be transparent about the use of generative AI tools will be considered a lack of academic honesty and may result in partial or total grade penalties for the course, as well as more severe sanctions in serious cases, in accordance with institutional regulations.
• In addition, students must demonstrate that the AI tools used comply with appropriate criteria regarding confidentiality, data security, copyright protection, and content reliability, in line with good editorial practices and research ethics.