Design of a data warehouse model for decision support at higher education

Aljawarneh, Isam Mashhour

doi:10.1177/0266666915621105

Cited by 8 publications

(3 citation statements)

References 22 publications

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“…However, traditional analytics in learning quality assurance are unable to handle the load of such massive and diverse data nowadays [17]. An examination of previous research proves that data warehousing is widely implemented in the education industry to support decisionmaking as well as analytical activities in terms of didactics, research, and management [18]. Ref.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Multi-Dimensional Analysis Approach to Teaching and Learning Analytics in Higher Education

Li¹,

Duffy²,

Zhang³

2022

Systems

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E-learning platforms are being used in higher education to liberate teaching and learning from the constraints of time, pace, and space. These platforms provide rich media content, collaborative assessment, and analytics tools and support learning through a variety of online possibilities. However, the focus of most of this research is on learning analytics inside e-learning platforms and does not cover other related institutional surveys and educator professional development activities. This paper outlines a novel conceptual approach for the creation of a teaching and learning data warehouse analytics system that utilizes a Multi-Dimensional Analysis approach to teaching and learning analytics across these e-learning platforms in combination with other institutional data sources, such as various institutional surveys, tracking of professional development activities, and analysis of the use of the learning management system. The novel teaching and learning data warehouse analytics system (TLDWAS) is being developed at Lingnan University, a leading liberal arts university in Hong Kong. The genesis of this project is analyzing large volumes of teaching and learning data and presenting a big picture for senior management to gain insight from massive amounts of student courses and teacher evaluation data, fill the research gaps mentioned above, and help educators identify problems and solutions more effectively. The TLDWAS provides a visual interface for identifying some indicators and storing, classifying, and analyzing teaching and learning data in various forms to generate statistics, analyze models, and identify meaningful patterns in the data in order to improve teaching and learning. The TLDWAS not only provides more evidence-based decision-making for senior management but is also capable of being applied to identify patterns and relations pertaining to students’ academic performance, usage of e-learning systems, and associated staff development activities.

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Section: Literature Reviewmentioning

confidence: 99%

A Novel Multi-Dimensional Analysis Approach to Teaching and Learning Analytics in Higher Education

Li¹,

Duffy²,

Zhang³

2022

Systems

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“…Setiap perguruan tinggi memiliki data akademik yang merupakan hasil dari transaksi administrasi. Perluasan institusi pendidikan tinggi dan peningkatan penekanan pada perencanaan strategis telah meningkatkan pemintaan sistem informasi terintegrasi yang dapat mendukung analisis strategis [4]. Data akademik di perguruan tinggi adalah aset yang terus berkembang dan membutuhkan manajemen khusus baik dalam hal pemanfaatan maupun penyimpanan [5].…”

Section: Pendahuluanunclassified

Rancangan Data Warehouse Akademik Politeknik Pariwisata Bali Berbasis Linux Opensuse

et al. 2021

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This study aims to design an academic data warehouse at Politeknik Pariwisata Bali because there are several information systems that require a system capable of handling databases of several existing information system applications and perform analysis. A data warehouse is the right solution for handling databases of several information systems that are not yet integrated. The research method begins with literature study, identification of problems, determining research objectives, designing solutions, namely designing an academic data warehouse, determining the hardware and software specifications needed, and ending with discussions and drawing conclusions. The result of this research is an academic data warehouse design that can be implemented properly. Besides, the results of this study are also accompanied by specifications for open-source hardware and software to save costs. The data warehouse design produced in this study uses a database of 3 information systems which is the main business process of a college, namely: Academic Information System, Information System for New Student Admissions, Research Information System. The three databases of the information system are internal data sources using the MySQL DBMS. The resulting academic data warehouse design uses open source software, namely: openSUSE, Pentaho Data Integration, MySQL DBMS.

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“…En los últimos años, las grandes empresas, así como las medianas han estado produciendo una gran cantidad de información sin límites. lo que hace difícil manejar estas informaciones en las empresas, a su vez resulta en bloqueo en la entrega de estas informaciones (Aljawarneh, 2016).…”

Section: Introductionunclassified

COMPILACIÓN DE RESULTADOS DE INVESTIGACIÓN. Vol 1 Num 2

2022

Libros De Ciencias Sociales Y Educación

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Design of a data warehouse model for decision support at higher education

Cited by 8 publications

References 22 publications

A Novel Multi-Dimensional Analysis Approach to Teaching and Learning Analytics in Higher Education

A Novel Multi-Dimensional Analysis Approach to Teaching and Learning Analytics in Higher Education

Rancangan Data Warehouse Akademik Politeknik Pariwisata Bali Berbasis Linux Opensuse

COMPILACIÓN DE RESULTADOS DE INVESTIGACIÓN. Vol 1 Num 2

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