Implementation of Language Processing Tools for the University Quality System

2021 ◽  
Author(s):  
Yevhenii Shendrikov ◽  
Daria Tabunshchyk ◽  
Sergey Subbotin ◽  
Peter Arras ◽  
Galyna Tabunshchyk
Keyword(s):  
Language Processing ◽  
Quality System ◽  
The University ◽  
University Quality

A Tracer Study of ICT Graduate Students at Mzuzu University, Malawi

Mousaion ◽  
2019 ◽  
Vol 36 (3) ◽  
Author(s):  
Chimango Nyasulu ◽  
Winner Chawinga ◽  
George Chipeta
Keyword(s):  
Language Processing ◽  
Mobile Application ◽  
First Century ◽  
Application Development ◽  
Job Requirements ◽  
Level Of Satisfaction ◽  
Information And Communication ◽  
Quantitative Design ◽  
The Right ◽  
The University

Governments the world over are increasingly challenging universities to produce human resources with the right skills sets and knowledge required to drive their economies in this twenty-first century. It therefore becomes important for universities to produce graduates that bring tangible and meaningful contributions to the economies. Graduate tracer studies are hailed to be one of the ways in which universities can respond and reposition themselves to the actual needs of the industry. It is against this background that this study was conducted to establish the relevance of the Department of Information and Communication Technology at Mzuzu University to the Malawian economy by systematically investigating occupations of its former students after graduating from the University. The study adopted a quantitative design by distributing an online-based questionnaire with predominantly closed-ended questions. The study focused on three key objectives: to identify key employing sectors of ICT graduates, to gauge the relevance of the ICT programme to its former students’ jobs and businesses, and to establish the level of satisfaction of the ICT curriculum from the perspectives of former ICT graduates. The key findings from the study are that the ICT programme is relevant to the industry. However, some respondents were of the view that the curriculum should be strengthened by revising it through an addition of courses such as Mobile Application Development, Machine Learning, Natural Language Processing, Data Mining, and LINUX Administration to keep abreast with the ever-changing ICT trends and job requirements. The study strongly recommends the need for regular reviews of the curriculum so that it is continually responding to and matches the needs of the industry.

Quality System Development at the University of Graz: Lessons Learned from the Case of RCE Graz-Styria

2014 ◽  
pp. 131-152
Author(s):  
Friedrich M. Zimmermann ◽  
Andreas Raggautz ◽  
Kathrin Maier ◽  
Thomas Drage ◽  
Marlene Mader ◽  
...  
Keyword(s):  
System Development ◽  
Quality System ◽  
Lessons Learned ◽  
The University

scholarly journals Levels and Profiles of Functionality as Dimensions of University Quality: An Empirical Study of Universidad Complutense

2007 ◽  
Vol 15 ◽  
pp. 12
Author(s):  
Arturo De la Orden Hoz ◽  
Inmaculada Asensio Muñoz ◽  
Chantal-María Biencinto López ◽  
Coral González Barberá ◽  
José Mafokozi Ndabishibije
Keyword(s):  
Total Sample ◽  
Three Dimensions ◽  
The Core ◽  
Starting Point ◽  
Systemic Model ◽  
Global Vision ◽  
Effectiveness And Efficiency ◽  
The University ◽  
University Quality ◽  
Function Profile

This study comes out as a step forward in a research line focused on validating empirically a systemic model of university quality. The article defines university quality in terms of three dimensions: functionality, effectiveness and efficiency. The focus of the article is on the analysis of the dimension of functionality as a starting point in the process of identifying and validating indicators for the evaluation of university quality. The core of the article integrates the presentation of the level and profile of functionality of the university for the total sample and for three audiences: faculty, students and employers. For each audience the study emphasizes the evaluation of the extent to which the university accomplishes its functions as a whole institution (level) and for each separate function (profile), as well as the differences among different strata of each audience. Finally, the study points out the differences in the profiles of functionality of the university observed by the different audiences, both as a whole institution and for each function. In the conclusions, a global vision of the level of functionality of the university, evaluated by the three audiences, is established.

scholarly journals Fenix: A Semantic Search Engine Based on an Ontology and a Model Trained with Machine Learning to Support Research

2021 ◽  
Author(s):  
Felipe Cujar-Rosero ◽  
David Santiago Pinchao Ortiz ◽  
Silvio Ricardo Timaran Pereira ◽  
Jimmy Mateo Guerrero Restrepo
Keyword(s):  
Machine Learning ◽  
Virtual Environment ◽  
Search Engine ◽  
Language Processing ◽  
Machine Learning Algorithms ◽  
Semantic Search ◽  
Research Projects ◽  
Machine Learning Model ◽  
The University ◽  
Semantic Search Engine

This paper presents the final results of the research project that aimed to build a Semantic Search Engine that uses an Ontology and a model trained with Machine Learning to support the semantic search of research projects of the System of Research from the University of Nariño. For the construction of FENIX, as this Engine is called, it was used a methodology that includes the stages: appropriation of knowledge, installation and configuration of tools, libraries and technologies, collection, extraction and preparation of research projects, design and development of the Semantic Search Engine. The main results of the work were three: a) the complete construction of the Ontology with classes, object properties (predicates), data properties (attributes) and individuals (instances) in Protegé, SPARQL queries with Apache Jena Fuseki and the respective coding with Owlready2 using Jupyter Notebook with Python within the virtual environment of anaconda; b) the successful training of the model for which Machine Learning algorithms and specifically Natural Language Processing algorithms were used such as: SpaCy, NLTK, Word2vec and Doc2vec, this was also done in Jupyter Notebook with Python within the virtual environment of anaconda and with Elasticsearch; and c) the creation of FENIX managing and unifying the queries for the Ontology and for the Machine Learning model. The tests showed that FENIX was successful in all the searches that were carried out because its results were satisfactory.

scholarly journals First Steps to Evaluate an NLP Tool’s Medication Extraction Accuracy from Discharge Letters

2021 ◽  
Author(s):  
Deniz Caliskan ◽  
Jakob Zierk ◽  
Detlef Kraska ◽  
Stefan Schulz ◽  
Philipp Daumke ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Data Warehouse ◽  
Language Processing ◽  
Gold Standard ◽  
Evaluation System ◽  
University Hospital ◽  
Industry Partner ◽  
Standard Medication ◽  
The University ◽  
F Measure

Introduction: The aim of this study is to evaluate the use of a natural language processing (NLP) software to extract medication statements from unstructured medical discharge letters. Methods: Ten randomly selected discharge letters were extracted from the data warehouse of the University Hospital Erlangen (UHE) and manually annotated to create a gold standard. The AHD NLP tool, provided by MIRACUM’s industry partner was used to annotate these discharge letters. Annotations by the NLP tool where then compared to the gold standard on two levels: phrase precision (whether or not the whole medication statement has been identified correctly) and token precision (whether or not the medication name has been identified correctly within correctly discovered medication phrases). Results: The NLP tool detected medication related phrases with an overall F-measure of 0.852. The medication name has been identified correctly with an overall F-measure of 0.936. Discussion: This proof-of-concept study is a first step towards an automated scalable evaluation system for MIRACUM’s industry partner’s NLP tool by using a gold standard. Medication phrases and names have been correctly identified in most cases by the NLP system. Future effort needs to be put into extending and validating the gold standard.

scholarly journals Two-stage topic modelling of scientific publications: A case study of University of Nairobi, Kenya

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0243208
Author(s):  
Leacky Muchene ◽  
Wende Safari
Keyword(s):  
Hierarchical Clustering ◽  
Language Processing ◽  
Latent Dirichlet Allocation ◽  
Topic Modelling ◽  
Two Stage ◽  
Scientific Publications ◽  
Statistical Tool ◽  
Second Stage ◽  
The University ◽  
Dirichlet Allocation

Unsupervised statistical analysis of unstructured data has gained wide acceptance especially in natural language processing and text mining domains. Topic modelling with Latent Dirichlet Allocation is one such statistical tool that has been successfully applied to synthesize collections of legal, biomedical documents and journalistic topics. We applied a novel two-stage topic modelling approach and illustrated the methodology with data from a collection of published abstracts from the University of Nairobi, Kenya. In the first stage, topic modelling with Latent Dirichlet Allocation was applied to derive the per-document topic probabilities. To more succinctly present the topics, in the second stage, hierarchical clustering with Hellinger distance was applied to derive the final clusters of topics. The analysis showed that dominant research themes in the university include: HIV and malaria research, research on agricultural and veterinary services as well as cross-cutting themes in humanities and social sciences. Further, the use of hierarchical clustering in the second stage reduces the discovered latent topics to clusters of homogeneous topics.

Nigerian University Quality - Why the Hero Fails

2016 ◽  
Vol 2 (3) ◽  
pp. 77
Author(s):  
Adeniyi Temitope Adetunji
Keyword(s):  
Systematic Approach ◽  
Critical Realism ◽  
Relevant Literature ◽  
University Education ◽  
Quality Of Education ◽  
Human Thinking ◽  
Nigerian University ◽  
The University ◽  
University Quality

This paper was designed to take an in-depth look into the establishment and practices of university education in Nigeria from 1960 to 2015, to investigate the reality of what caused Nigerian university education to gradually decline. The paper takes a critical realism approach to reviewing the relevant literature in the field, and forming a base from which to answer the question of ‘why the hero fails’. Three major questions are raised, but not answered, in this paper, as three other papers focus solely on answering these questions. They are; where have things gone wrong? Where are things going wrong? and where may things continue to go wrong? This paper is particular about identifying areas where things are happening within the university sector. The findings reveal that not only is the quality of education declining, but human thinking on tasks, involvement/pro-activeness and funding are also declining, a major reason why Nigerians ignorantly give way to corrupt practices, which slip in like wolves and continue to devolve the system. The paper concludes that the best approach to the wider picture of what is going on within the university sector is to understand, and provide answers to, the three major questions above, in detail.  In order to overcome the problems caused, leading to the need to carry out this study, rebuilding is needed using a systematic approach to eradicating waste.

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