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Digital Inclusion in Nothern England: Training Women from Underrepresented Communities in Tech: A Data Analytics Case Study

Aduragba, Olanrewaju Tahir and Yu, Jialin and Cristea, Alexandra I. and Hardey, Mariann and Black, Sue (2020) 'Digital Inclusion in Nothern England: Training Women from Underrepresented Communities in Tech: A Data Analytics Case Study.', in 2020 15th International Conference on Computer Science & Education (ICCSE). , pp. 162-168.


The TechUPWomen programme takes 100 women from the Midlands and North of England, particularly from underrepresented communities, with degrees or experience in any subject area, retrains them in technology and upon graduation guarantees an interview with a company. The retraining programme, developed by the Partner Universities in conjunction with the Industrial Partners, has modules at level 6/7 including: Technology: coding, data science, cyber security, machine learning, agile project management; Workplace readiness skills: public speaking, clear communication, working as a team. In this paper, we introduce, for the first time, the TechUPWomen programme, and we analyse its temporal evolution and special features via a data analytics nowcasting approach. Deepening these women’s experience with applied upskilling includes one-to-one mentoring (100-100), strong networking, residentials, close industry connection with two directions (non-technical & technical) and four job-focussed final tracks: business analyst, agile project manager, data scientist, developer. TechUPWomen also has significant representation of traditionally underrepresented communities, with focus on enabling instead of teaching approach. Beside the originality of the unique combination of features of the programme, this is, to the best of our knowledge, the first analysis based on data analytics of a women in tech(nology) retraining programme, based on nowcasting. Results show that the approach is effective; topic analysis shows that frequent topics include joy, BAME, networking, residential, industry, learning.

Item Type:Book chapter
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Publisher statement:© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Date accepted:No date available
Date deposited:03 November 2021
Date of first online publication:22 September 2020
Date first made open access:03 November 2021

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