TBDS 2015 - Workshop “Teaching Big Data Science”
Topics/Call fo Papers
Through increasing digitalization of today’s business world, enormous amounts of data are available for decision making. As a consequence, companies are currently seeking for skilled analysts and managers to have more insight on their big data sets. Thus, the ability of analyzing huge amounts of data, spotting patterns, and extracting useful information are becoming key competitive advantages.
Big data analytics requires multiple skills that span a variety of disciplines, methods and techniques from both business and technical perspectives. However, still there is a gap between companies’ expectations and academic curricula. Conventional academic programs are not corresponding with labour market requirements towards graduates’ skills and knowledge. Therefore, academia is facing a new challenge of combining big data aspects with the existing degree programs or develop entirely new offerings that focus on big data topics.
The main goal of this Workshop is to bring together academics to share their thoughts and experience in teaching big data and smart economy topics at different universities (business and technical). The area of interest covers theories, current and novel methods, learning concepts and pedagogical aspects useful for teaching big data, as well as review and critical analysis of existing approaches and implementation reports (lessons learnt). The main question still to be answered is: “How can or should big data topics be integrated into academic curricula?”.
Topics of interest
Designing big data curricula
Developing multiple analytical skills (approaches towards teaching analytical techniques / data mining / process mining)
Technical architectures and technological infrastructure for teaching big data topics
Key resources (tools and software) for teaching big data
Novel teaching methodologies/ formats / materials
Learning concepts to develop analytical skills and capabilities
Pedagogical aspects of teaching big data topics
Teaching statistical inference for big data
E-learning supporting big data analytics
Use of new media in teaching big data topics
Use of linked data for teaching big data analytics
Trends and issues
Big data analytics requires multiple skills that span a variety of disciplines, methods and techniques from both business and technical perspectives. However, still there is a gap between companies’ expectations and academic curricula. Conventional academic programs are not corresponding with labour market requirements towards graduates’ skills and knowledge. Therefore, academia is facing a new challenge of combining big data aspects with the existing degree programs or develop entirely new offerings that focus on big data topics.
The main goal of this Workshop is to bring together academics to share their thoughts and experience in teaching big data and smart economy topics at different universities (business and technical). The area of interest covers theories, current and novel methods, learning concepts and pedagogical aspects useful for teaching big data, as well as review and critical analysis of existing approaches and implementation reports (lessons learnt). The main question still to be answered is: “How can or should big data topics be integrated into academic curricula?”.
Topics of interest
Designing big data curricula
Developing multiple analytical skills (approaches towards teaching analytical techniques / data mining / process mining)
Technical architectures and technological infrastructure for teaching big data topics
Key resources (tools and software) for teaching big data
Novel teaching methodologies/ formats / materials
Learning concepts to develop analytical skills and capabilities
Pedagogical aspects of teaching big data topics
Teaching statistical inference for big data
E-learning supporting big data analytics
Use of new media in teaching big data topics
Use of linked data for teaching big data analytics
Trends and issues
Other CFPs
- 3rd Workshop on Formal Semantics for the Future Enterprise (FSFE 2015)
- 3rd Workshop on Digital Currencies (DC 2015)
- 6th Workshop on Business and IT Alignment (BITA 2015)
- 7th Workshop on Applications of Knowledge-Based Technologies in Business (AKTB 2015)
- 2015 Workshop on Privacy by Transparency in Data-Centric Services
Last modified: 2015-01-26 23:17:42