Degree | Type | Year | Semester |
---|---|---|---|
4315497 Communication and Language Disorders | OB | 0 | 2 |
There are no specific prerequisites.
The general objective of this course is to offer students the necessary knowledge and skills to carry out the data analysis of empirical research in the field of communication disorders, as well as to develop or adapt measurement tools in this filed.
The student learns to adequately define research objectives and hypotheses. Skills related to the management, analysis and interpretation of data are developed, as well as those related to design and adaptation of measuring instruments.
Finally, the student learn to identify and discuss the practical, methodological and technical implications of the research, as well as its repercussions on the health care services and on the progress of scientific knowledge.
Traditional teaching techniques are combined with other resources aimed at encouraging meaningful learning.
N.B. The proposed teaching and assessment methodologies may experience some modifications as a result of the restrictions on face-to-face learning imposed by the health authorities. The teaching staff will use the Moodle classroom or the usual communication channel to specify whether the different directed and assessment activities are to be carried out on site or online, as instructed by the Faculty.
The teachers will allocate a time of 15 minutes during one of the class sessions for the students to answer the evaluation surveys of the teaching performance and the evaluation of the module.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Computerized practices | 14 | 0.56 | 1, 3, 4 |
Theoretical presentation | 17.5 | 0.7 | 1, 3, 5, 4, 2 |
Type: Supervised | |||
Review of integrated problems | 15.5 | 0.62 | 1, 3, 4 |
Tutoring | 6 | 0.24 | 1, 3, 4 |
Type: Autonomous | |||
Comprehensive reading of the materials proposed by the teachers | 40 | 1.6 | 1, 3, 5, 4, 2 |
Realization of schemes, conceptual maps and summaries | 5 | 0.2 | 5, 4, 2 |
Training in computer programs based on guides and tutorials | 45 | 1.8 | 1, 3, 5, 4, 2 |
In this course the assessment is intended to fulfil a pedagogical function and not just accreditation, and all the evidences are programmed so that they can achieve the corresponding formative return.
Below are the learning evidences that the student will have to contribute, their type and weight in the final qualification:
- Evidence 1 (week 4). Individual classroom examination. Content: Data analysis. Up to 5 points.
- Evidence 2 (week 6). Individual examination (moodle). Content: Textual analysis. Up to 1 point.
- Evidence 3 (week 9). Individual classroom examination. Content: Creation and adaptation of tests and questionnaires. Up to 4 points.
Assessable students: a student is considered assessable when they have presented evidences of learning with a weight greater than or equal to 4 points; otherwise it will appear in final grade sheets as Not Assessable (NA).
Course passed: students have passed the course when they have obtained a minimum score of 5 points and at least 2 points come from EV1 and 2 points from EV3.
Resit examination: may choose to resit the evidences not passed those students who have not achieved the established criteria to pass the course and who, in addition, have previously been assessed on a set of activities whose weight equals a minimum of 2/3 of the total score of the course.
Note: No unique final synthesis test for students who enroll for the second time or more is anticipated.
In this link you can check the evaluation guidelines of the Faculty:
https://www.uab.cat/web/estudiar/graus/graus/avaluacions-1345722525858.html
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
EV1 - Data analysis (semana 4) | 5 points | 3 | 0.12 | 3, 2 |
EV2 - Textual analysis (semana 6) | 1 point | 2 | 0.08 | 3, 5, 2 |
EV3 - Measuring instruments (semana 9) | 4 points | 2 | 0.08 | 1, 4 |
Basic bibliography
Students will have access through moodle to the documents in pdf format that constitute the basic bibliography of the course.
Complementary bibliography
Abad, F.J., Olea, J., Ponsoda, V. y García, C. (2011). Medición en ciencias sociales y de la salud. Madrid: Síntesis.
Ato, M., Losilla, J.M., Navarro, B., Palmer, A., y Rodrigo, M.F. (2005). Modelo Lineal Generalizado. Girona: Documenta Universitaria - EAP.
Botella, J. y Sánchez Meca, J. (2015). Meta-análisis en ciencias sociales y de la salud. Madrid: Síntesis.
Losilla, J.M., Navarro, B., Palmer, A., Rodrigo, M.F. y Ato, M. (2005). Del Contraste de Hipótesis al Modelado Estadístico. Girona: Documenta Universitaria - EAP.
Losilla, J.M. y Vives, J. (2007). L’Ordinador en Psicologia. Barcelona: Universitat Autònoma de Barcelona. Servei de Publicacions.
Martínez Arias, M.R., Hernández, M.J. y Hernández, M.V. (2006). Psicometría. Madrid: Alianza Editorial, S.A.
Pardo, A., Ruiz, M.A.. y San Martín, R. (2009). Análisis de datos en ciencias sociales y de la salud I. Madrid: Síntesis.
Pardo, A.,y Ruiz, M.A.. (2012). Análisis de datos en ciencias sociales y de la salud III. Madrid: Síntesis.
Pardo, A. y San Martín, R. (2010). Análisis de datos en ciencias sociales y de la salud II. Madrid: Síntesis.
Solanas, A., Salafranca, L., Fauquet,J. i Núñez, M.I. (2005). Estadística descriptiva en Ciencias del Comportamiento. Madrid: Thomson.
The free access software jamovi (https://www.jamovi.org/) will be used to perform statistical and psychometric analyses presented in the course.