Are Universities Ready to Deliver Digital Skills and Competences? A Text Mining Driven Case Study on Marketing Courses in Italy

This chapter takes up several important theoretical problems and complexities introduced by text mining and datafication to historiography and historical research in order to think about the problems and promises of a digital historicism. The chapter argues for an approach that takes the historicity of the digitized archive seriously without reducing the use of computational methods to either those framed strictly by the terms and language of the present or to a form of rigid historicism that would require enclosing the archive in synchronically constructed interpretive framework. Many of the approaches used within text mining deploy secondary archives—dictionaries, thesauruses, and other forms of human-constructed schemata—that have tended to capture categories used in the present. The chapter concludes by examining the methods and practice of extracting and analyzing emotional or affective content in texts through what is called sentiment mining. Functioning as a case study, sentiment mining demonstrates the need for quantitative and computational humanists to give more attention to the historical dimensions of both text and affect, to both primary and secondary digital sources.

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Text Mining Indicators of Affect and Interaction: A Case Study of Students’ Postings in a Blended-Learning Course of English for Specific Purposes

Advances in Intelligent Systems and Computing - Advances in Information Systems and Technologies ◽

10.1007/978-3-642-36981-0_80 ◽

2013 ◽

pp. 861-872

Author(s):

Helvia P. P. Bastos ◽

Magda Bercht ◽

Leandro K. Wives ◽

Júlia Kambara-Silva ◽

Yasmmin Martins

Keyword(s):

Text Mining ◽

Blended Learning ◽

English For Specific Purposes

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Exploiting Digital Skills in Higher Education

Advances in Educational Technologies and Instructional Design - IT and the Development of Digital Skills and Competences in Education ◽

10.4018/978-1-7998-4972-8.ch001 ◽

2021 ◽

pp. 1-20

Author(s):

Domitilla Magni ◽

Beatrice Orlando ◽

Manlio Del Giudice

Keyword(s):

Higher Education ◽

Large Scale ◽

Digital Transformation ◽

Strong Impact ◽

Business And Society ◽

Case Study Analysis ◽

Benefit Corporation ◽

The World ◽

Digital Skills

Thus far, digital transformation had a strong impact on business and society. The large-scale adoption of digital technologies changed social relationships and opened up to new opportunities for higher education. Currently, the interplay between innovation and digitalization become are among the most important assets for the educational system. In this light, this chapter aims to explore how digital skills and competencies modify the issue of co-creation in higher education. The authors use the case study analysis to explore such theme. The Little Genius International case is presented and discussed: an international alternative school in English for digital natives recognized as the best benefit corporation for the world. The main contribution of the chapter is that it outlines what are the new digital skills and competencies enabling a better understanding of the concept of students' co-creation in HEIs.

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The Effects of the State of Union Address of USA Presidents to Their Performance Ratings

International Journal of Software Innovation ◽

10.4018/ijsi.2015040101 ◽

2015 ◽

Vol 3 (2) ◽

pp. 1-12

Author(s):

Carl Lee

Keyword(s):

Text Mining ◽

Performance Ratings ◽

Presidential Approval ◽

Approval Ratings ◽

Mining Technique ◽

State Of The Union ◽

Speech Patterns ◽

Modeling Techniques ◽

Presidential Approval Ratings

In this article, the authors conduct a case study using text mining technique to analyze the patterns of the president's State of the Union Address in USA, and investigate the effects of these speech patterns on their performance rating in the following year. The speeches analyzed include the recent four USA presidents, Bush (1989 – 1992), Clinton (1993 - 2000), G.W. Bush (2001 – 2008), and Obama (2009 – 2011). The patterns found are further integrated and merged with over 4000 surveys on the presidents' performance ratings from 1989 to 2010. Two text mining methodology are applied to study the text patterns. Two predictive modeling techniques are applied to study the effects of these found patterns to their presidential approval ratings. The results indicate that the speech patterns found are highly associated with their approval rates.

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