Factors Affecting Attrition among First Year Computer Science Students: the Case of University of Latvia

<p class="R-AbstractKeywords"><span lang="EN-GB">The purpose of our study was to identify reasons for high dropout of students enrolled in the first year of the computer science study program to make it possible to determine students, who are potentially in risk. Several factors that could affect attrition, as it was originally assumed, were studied: high school grades (admission score), compensative course in high school mathematics, intermediate grades for core courses, prior knowledge of programming. However, the results of our study indicate that none of the studied factors is determinant to identify those students, who are going to abandon their studies, with great precisio…

UNIVERSITY IS ARCHITECTURE FOR THE RESEARCH EVALUATION SUPPORT

The measuring of research results can be used in different ways e.g. for assignment of research grants and afterwards for evaluation of project’s results. It can be used also for recruiting or promoting research institutions’ staff. Because of a wide usage of such measurement, the selection of appropriate measures is important. At the same time there does not exist a common view which metrics should be used in this field, moreover many existing metrics that are widely used are often misleading due to different reasons, e.g. computed from incomplete or faulty data, the metric’s computation formula may be invalid or the computation results can be interpreted wrongly. To produce a good framewo…

Towards a Data Warehouse Architecture for Managing Big Data Evolution

Towards Introducing User Preferences in OLAP Reporting Tool

This paper presents an OLAP reporting tool and an approach for determining and processing user OLAP preferences, which are useful for generating recommendations on potentially interesting reports. We discuss the metadata layers of the reporting tool including our proposed OLAP preferences metamodel, which supports various scenarios of formulating preferences of two different types: schema-specific and report-specific. The process of semantic metadata usage at the stage of formulating user preferences is also considered. The methods for processing schema-specific and report-specific OLAP preferences are outlined.

Evolution-Oriented User-Centric Data Warehouse

Data warehouses tend to evolve, because of changes in data sources and business requirements of users. All these kinds of changes must be properly handled, therefore, data warehouse development is never-ending process. In this paper we propose the evolution-oriented user-centric data warehouse design, which on the one hand allows to manage data warehouse evolution automatically or semi-automatically, and on the other hand it provides users with the understandable, easy and transparent data analysis possibilities. The proposed approach supports versions of data warehouse schemata and data semantics.

Metadata to Support Data Warehouse Evolution

The focus of this chapter is metadata necessary to support data warehouse evolution. We present the data warehouse framework that is able to track evolution process and adapt data warehouse schemata and data extraction, transformation, and loading (ETL) processes. We discuss the significant part of the framework, the metadata repository that stores information about the data warehouse, logical and physical schemata and their versions. We propose the physical implementation of multiversion data warehouse in a relational DBMS. For each modification of a data warehouse schema, we outline the changes that need to be made to the repository metadata and in the database.

Publication Data Integration as a Tool for Excellence-Based Research Analysis at the University of Latvia

The evaluation of research results can be carried out with different purposes aligned with strategic goals of an institution, for example, to decide upon distribution of research funding or to recruit or promote employees of an institution involved in research. Whereas quantitative measures such as number of scientific papers or number of scientific staff are commonly used for such evaluation, the strategy of the institution can be set to achieve ambitious scientific goals. Therefore, a question arises as to how more quality oriented aspects of the research outcomes should be measured. To supply an appropriate dataset for evaluation of both types of metrics, a suitable framework should be p…

Handling Evolving Data Warehouse Requirements

A data warehouse is a dynamic environment and its business requirements tend to evolve over time, therefore, it is necessary not only to handle changes in data warehouse data, but also to adjust a data warehouse schema in accordance with changes in requirements. In this paper, we propose an approach to propagate modified data warehouse requirements in data warehouse schemata. The approach supports versions of data warehouse schemata and employs the requirements formalization metamodel and multiversion data warehouse metamodel to identify necessary changes in a data warehouse.

Computer Programming Aptitude Test as a Tool for Reducing Student Attrition

Submitted to the VTR conference to be held in Rezekne, June 2015

Change Discovery in Heterogeneous Data Sources of a Data Warehouse

Data warehouses have been used to analyze data stored in relational databases for several decades. However, over time, data that are employed in the decision-making process have become so enormous and heterogeneous that traditional data warehousing solutions have become unusable. Therefore, new big data technologies have emerged to deal with large volumes of data. The problem of structural evolution of integrated heterogeneous data sources has become extremely topical due to dynamic and diverse nature of big data. In this paper, we propose an approach to change discovery in data sources of a data warehouse utilized to analyze big data. Our solution incorporates an architecture that allows t…

Architecture Enabling Adaptation of Data Integration Processes for a Research Information System

Abstract Today, many efforts have been made to implement information systems for supporting research evaluation activities. To produce a good framework for research evaluation, the selection of appropriate measures is important. Quality aspects of the systems’ implementation should also not be overlooked. Incomplete or faulty data should not be used and metric computation formulas should be discussed and valid. Correctly integrated data from different information sources provide a complete picture of the scientific activity of an institution. Knowledge from the data integration field can be adapted in research information management. In this paper, we propose a research information system f…

Can SQ and EQ Values and Their Difference Indicate Programming Aptitude to Reduce Dropout Rate?

A crucial problem that we are currently facing at the Faculty of Computing of the University of Latvia is that during the first study semester on average 30% of the first-year students drop out, whereas after the first year of studies the number of dropouts increases up to nearly 50%. Thus, our overall goal is to determine in advance applicants that most likely will not finish the first study year successfully. A hypothesis formulated in another research study was that programming aptitude could be predicted based on the results of two personality self-report questionnaires − Systemizing Quotient (SQ) and Empathy Quotient (EQ) − taken by students. The difference between the SQ and EQ scores…

Towards a System to Monitor the Virus’s Aerosol-Type Spreading

Recent scientific studies indicate that attention should be paid to the indoor spread of the Covid-19 virus. It is recommended to reduce the number of visitors to the premises and to provide frequent ventilation of the premises. The problem is that it is not known what the risk of infection is in a particular room at a specific time, when and what actions should be taken to reduce the risk. We offer a system that helps monitor the conditions in the premises with the help of sensors, calculate the risk of infection and provide information to reduce the infection risk. We give an insight into the created prototype with data collection from public spaces and data visualization according to use…

On Metadata Support for Integrating Evolving Heterogeneous Data Sources

With the emergence of big data technologies, the problem of structure evolution of integrated heterogeneous data sources has become extremely topical due to dynamic and diverse nature of big data. To solve the big data evolution problem, we propose an architecture that allows to store and process structured and unstructured data at different levels of detail, analyze them using OLAP capabilities and semi-automatically manage changes in requirements and data expansion. In this paper, we concentrate on the metadata essential for the operation of the proposed architecture. We propose a metadata model to describe schemata and supplementary properties of data sets extracted from sources and tran…

Strategies to Reduce Attrition among First Year Computer Science Students

The observed trend to lose from one-third to half of students in the first year of computing studies at the University of Latvia served as the motivation to explore the causes of dropout and to find methods, how to determine potential dropouts in advance. The study investigates students enrolled in the year 2013 using integrated data from surveys, management information system and e-learning environment. Several factors that could affect attrition were studied: admission score, compensative course in high school mathematics, intermediate grades for core courses, prior knowledge in programming. The research revealed that the trend of non-beginning studies might indicate the wrong choice of t…

Managing Evolution of Heterogeneous Data Sources of a Data Warehouse

Query-Driven Method for Improvement of Data Warehouse Conceptual Model

We propose a query-driven method that elicits the information requirements from existing queries on data sources and their usage statistics. Our method presumes that the queries against the source database reflect the analysis needs of users. We use this method to recommend changes to the existing data warehouse schemata. In our method, we take advantage of the schema versioning approach to reflect all changes that occur in the analysed process, and we analyse the activity of users in the source system, rather than changes in physical data structure, to infer the necessary improvements to the data warehouse schema.