All UDC centers have a Internal Quality Assurance System (IQAS), verified by the Agency to Calidade do Sistema Universitario de Galicia (ACSUG) and ANECA in FIDES programs and AUDIT, respectively, and in accordance with the standards and Guidelines for Quality Assurance in the EHEA. Within IQAS centers integrate all their degrees and masters. IQAS procedures established who and how to follow up and monitoring of the results and the student's learning process in the titration, establishing coordinating bodies and mechanisms, evaluation and continuous improvement of the studies, which are the academic comittee and the quality assurance commision of center.
The IQAS establish how UDC centers measure and analyze the learning outcomes. To do the IQAS uses rates and global indicators for assessing the quality of training provided. Included among the results, in addition to the fees included in the title verification reports (efficiency rates, graduation and dropout), assessment rates, success and performance. We compare the results obtained in the title with the center's results for each indicator.
To ensure that the title is developed in accordance with the verification report presented the center conducts an annual monitoring report in accordance with the procedures of the center IQAS and results. This report is reviewed by the ACSUG, external evaluation agency.
The outcome of this analysis will emerge corrective actions and improvement proposals that achieve the intended objectives and the improvement of the degree.
In order to ensure proper standards and quality at UDC, an academic management committee and a quality assurance committee are appointed for each faculty/school. In addition to, each faculty/school will be able to establish a specific academic management committee of the study.
|Total enrolled credits||2018/2019||1,833|
|Credits on 1st enrollment||2018/2019||1,779|
|Credits on 2nd enrollment||2018/2019||54|
|Credits on 3rd enrollment and above||2018/2019||0|
|% credits repeated||2018/2019||2.95|
|Average credits by student||2018/2019||45.83|
|Total enrolled credits||2018/2019||72,990|
|Credits on 1st enrollment||2018/2019||53,620|
|Credits on 2nd enrollment||2018/2019||11,800|
|Credits on 3rd enrollment and above||2018/2019||7,572|
|% credits repeated||2018/2019||26.54|
|Average credits by student||2018/2019||51.08|
|Total enrolled credits||2017/2018||1,515|
|Credits on 1st enrollment||2017/2018||1,509|
|Credits on 2nd enrollment||2017/2018||6|
|Credits on 3rd enrollment and above||2017/2018||0|
|% credits repeated||2017/2018||0.4|
|Average credits by student||2017/2018||47.34|
|Total enrolled credits||2017/2018||69,150|
|Credits on 1st enrollment||2017/2018||49,970|
|Credits on 2nd enrollment||2017/2018||11,560|
|Credits on 3rd enrollment and above||2017/2018||7,624|
|% credits repeated||2017/2018||27.74|
|Average credits by student||2017/2018||52.27|
|Total enrolled credits||2016/2017||768|
|Credits on 1st enrollment||2016/2017||768|
|Credits on 2nd enrollment||2016/2017||0|
|Credits on 3rd enrollment and above||2016/2017||0|
|% credits repeated||2016/2017||0|
|Average credits by student||2016/2017||59.08|
|Total enrolled credits||2016/2017||66,390|
|Credits on 1st enrollment||2016/2017||47,070|
|Credits on 2nd enrollment||2016/2017||11,460|
|Credits on 3rd enrollment and above||2016/2017||7,860|
|% credits repeated||2016/2017||29.1|
|Average credits by student||2016/2017||53.24|
Success Not success Not presented
Success Not success Not presented
These are the master thesis works that have been read in recent academic years.
Epileptic outbreak detection and analysis tool on the EEG in a pharmacological model
Metagenome annotation using nr NCBI database and diversity studies
System for Assessment of Alzheimer's Disease Diagnosis Based on Deep Learning Techniques
The role of prefrontal cortex in working memory
Acceleration of a feature selection method for biological datasets on CPU clusters
Aceleration of a method for gene set enrichment analysis on CPU clusters
Assembly and annotation of decapodite larvae of prawn Palaemon serratus
Automation of acquisition systems of data by quantified self
Design and implementation of an application to calculate new mRNA secondary structure descriptors and prediction of mRNA expression using Artificial Intelligence technologies
Development of a parallel tool to accelerate the detection third-level epistasis on distributed memory systems
Development of a visual stimulation software for electrophysiologic studies on awake primates
Extraction and visualization of the cornea-lens relation in AS-OCT images
HMusket: k-mer spectrum corrector based on Hadoop
PSYR: Platform to support the monitoring and rehabilitation of patients.
Sistema de interpretación clínica de resultados farmacogenéticos
Offer available places last year and, for degree studies, you can also check the cut notes of those admitted by PAAU.
|academic year 2018/2019|