Despertando o Interesse de Mulheres para os Cursos em STEM

• URL: http://arxiv.org/abs/2305.18600v1
• Date: Mon, 29 May 2023 20:34:31 GMT
• Title: Despertando o Interesse de Mulheres para os Cursos em STEM
• Authors: Tainara Silva Novaes, Kathleen Danielly Souza Lins, Adolfo Gustavo S. Seca Neto, Mariangela de Oliveira G. Setti, Maria Claudia F. Pereira Emer
• Abstract summary: Em'ilias - Armaccao em Bits Project organizes workshops in schools. A podcast has been created to foster interaction between young people and professionals in the field of computing. According to Spotify, the podcast's audience consists of 53% females, 44% males, and 3% unspecified.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This article presents initiatives aimed at promoting female participation in STEM fields, with the goal of encouraging more women to pursue careers in these areas. One of these initiatives is the Em\'ilias - Arma\c{c}\~ao em Bits Project, which organizes workshops in schools. Additionally, a podcast has been created to foster interaction between young people and professionals in the field of computing, while also contributing to the establishment of female role models in the industry. The results of these initiatives have been promising, as 70.6% of the students who participated in the workshops expressed an interest in computing. Furthermore, according to Spotify, the podcast's audience consists of 53% females, 44% males, and 3% unspecified, indicating that it has successfully reached a female demographic. Resumo. Este artigo apresenta iniciativas que t\^em como objetivo promover a participa\c{c}\~ao das mulheres nas \'areas de STEM, buscando encorajar mais mulheres a seguirem carreiras nesses campos. O Projeto Em\'ilias - Arma\c{c}\~ao em Bits desenvolve oficinas nas escolas e tamb\'em um podcast, promovendo a intera\c{c}\~ao entre jovens e profissionais da \'area de computa\c{c}\~ao, al\'em de contribuir para a forma\c{c}\~ao de modelos femininos nesse campo. Os resultados demonstraram que 70,6% das estudantes demonstraram interesse pela computa\c{c}\~ao ap\'os participarem das oficinas. Em rela\c{c}\~ao aos ouvintes do podcast, dados do Spotify indicaram que 53% do p\'ublico se identifica como feminino, 44% como masculino, e 3% n\~ao especificaram o g\^enero, o que mostra que o podcast tem alcan\c{c}ado um p\'ublico feminino.

Related papers

• BabyLM Turns 3: Call for papers for the 2025 BabyLM workshop [77.62533643491747]
  BabyLM aims to dissolve the boundaries between cognitive modeling and language modeling. We call for both workshop papers and for researchers to join the 3rd BabyLM competition.
  arXiv  Detail & Related papers  (2025-02-15T02:46:43Z)
• Gender Bias in Text-to-Video Generation Models: A case study of Sora [63.064204206220936]
  This study investigates the presence of gender bias in OpenAI's Sora, a text-to-video generation model. We uncover significant evidence of bias by analyzing the generated videos from a diverse set of gender-neutral and stereotypical prompts.
  arXiv  Detail & Related papers  (2024-12-30T18:08:13Z)
• Inspiring Women in Technology: Educational Pathways and Impact [0.0]
  The Meninas++ Project coordinates activities at both the high school and higher education levels. Our study demonstrated the significant impact of these activities on inspiring, empowering, and retaining female students in computing.
  arXiv  Detail & Related papers  (2024-12-23T20:17:38Z)
• Emílias Podcast -- Mulheres na Computação: Ampliando Horizontes e Inspirando Carreiras em STEM [0.42970700836450487]
  "Em'ilias Podcast -- Women in Computing" celebrates its 5th anniversary on October 3, 2024. The podcast aims to provide a space for women in computing and related fields to share their experiences. The results revealed that 100% of interviewees would recommend "Em'ilia's Podcast," reflecting a high level of satisfaction with the project.
  arXiv  Detail & Related papers  (2024-10-06T12:59:48Z)
• FemQuest -- An Interactive Multiplayer Game to Engage Girls in Programming [0.9383920721490117]
  We present a multiplayer game that is used in a workshop setting to motivate girls to program through a 3D game environment. The study involved 235 girls and 50 coaches for the workshop evaluation and a subset of 20 participants for an in-game analysis.
  arXiv  Detail & Related papers  (2024-07-04T08:42:22Z)
• Breaking Barriers: Investigating the Sense of Belonging Among Women and Non-Binary Students in Software Engineering [1.9075820340282934]
  Women are far less likely to pursue a career in the software engineering industry. Reasons for women and other underrepresented minorities to leave the industry are a lack of opportunities for growth and advancement. This research explores how the potential to cultivate or uphold an industry unfavourable to women and non-binary individuals in software engineering education.
  arXiv  Detail & Related papers  (2024-05-06T20:07:45Z)
• "STILL AROUND": Experiences and Survival Strategies of Veteran Women Software Developers [53.5211430148752]
  We conducted 14 interviews to examine the experiences of people at the intersection of ageism and sexism. We identified 283 codes, which fell into three main categories: Strategies, Experiences, and Perception. Several strategies we identified, such as (Deliberately) Not Trying to Look Younger, were not previously described in the software engineering literature.
  arXiv  Detail & Related papers  (2023-02-07T19:26:15Z)
• Towards Understanding Gender-Seniority Compound Bias in Natural Language Generation [64.65911758042914]
  We investigate how seniority impacts the degree of gender bias exhibited in pretrained neural generation models. Our results show that GPT-2 amplifies bias by considering women as junior and men as senior more often than the ground truth in both domains. These results suggest that NLP applications built using GPT-2 may harm women in professional capacities.
  arXiv  Detail & Related papers  (2022-05-19T20:05:02Z)
• Increasing Gender Balance Across Academic Staffing in Computer Science -- case study [0.0]
  Technological University Dublin is the top university in Ireland in terms of gender balance of female academic staff in computer science schools. In an academic team of approximately 55 full-time equivalents, 36% of our academic staff are female. 75% of our School Executive are female.
  arXiv  Detail & Related papers  (2021-10-12T15:43:35Z)
• Gender bias in magazines oriented to men and women: a computational approach [58.720142291102135]
  We compare the content of a women-oriented magazine with that of a men-oriented one, both produced by the same editorial group over a decade. With Topic Modelling techniques we identify the main themes discussed in the magazines and quantify how much the presence of these topics differs between magazines over time. Our results show that the frequency of appearance of the topics Family, Business and Women as sex objects, present an initial bias that tends to disappear over time.
  arXiv  Detail & Related papers  (2020-11-24T14:02:49Z)
• #MeToo on Campus: Studying College Sexual Assault at Scale Using Data Reported on Social Media [71.74529365205053]
  We analyze the influence of the # trend on a pool of college followers. The results show that the majority of topics embedded in those # tweets detail sexual harassment stories. There exists a significant correlation between the prevalence of this trend and official reports on several major geographical regions.
  arXiv  Detail & Related papers  (2020-01-16T18:05:46Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.