skip to main content

Title: Towards an Effective Digital Literacy Intervention to Assist Returning Citizens with Job Search
Returning citizens (formerly incarcerated individuals) face great challenges finding employment, and these are exacerbated by the need for digital literacy in modern job search. Through 23 semi-structured interviews and a pilot digital literacy course with returning citizens in the Greater Detroit area, we explore tactics and needs with respect to job search and digital technology. Returning citizens exhibit great diversity, but overall, we find our participants to have striking gaps in digital literacy upon release, even as they are quickly introduced to smartphones by friends and family. They tend to have employable skills and ability to use offline social networks to find opportunities, but have little understanding of formal job search processes, online or offline. They mostly mirror mainstream use of mobile technology, but they have various reasons to avoid social media. These and other findings lead to recommendations for digital literacy programs for returning citizens.  more » « less
Award ID(s):
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Page Range / eLocation ID:
1 to 12
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. This study aims to investigate the collaboration processes of immigrant families as they search for online information together. Immigrant English-language learning adults of lower socioeconomic status often work collaboratively with their children to search the internet. Family members rely on each other’s language and digital literacy skills in this collaborative process known as online search and brokering (OSB). While previous work has identified ecological factors that impact OSB, research has not yet distilled the specific learning processes behind such collaborations. Design/methodology/approach: For this study, the authors adhere to practices of a case study examination. This study’s participants included parents, grandparents and children aged 10–17 years. Most adults were born in Mexico, did not have a college-degree, worked in service industries and represented a lower-SES population. This study conducted two to three separate in-home family visits per family with interviews and online search tasks. Findings: From a case study analysis of three families, this paper explores the funds of knowledge, resilience, ecological support and challenges that children and parents face, as they engage in collaborative OSB experiences. This study demonstrates how in-home computer-supported collaborative processes are often informal, social, emotional and highly relevant to solving information challenges. Research limitations/implications: An intergenerational OSB process is different from collaborative online information problem-solving that happens between classroom peers or coworkers. This study’s research shows how both parents and children draw on their funds of knowledge, resilience and ecological support systems when they search collaboratively, with and for their family members, to problem solve. This is a case study of three families working in collaboration with each other. This case study informs analytical generalizations and theory-building rather than statistical generalizations about families. Practical implications: Designers need to recognize that children and youth are using the same tools as adults to seek high-level critical information. This study’s model suggests that if parents and children are negotiating information seeking with the same technology tools but different funds of knowledge, experience levels and skills, the presentation of information (e.g. online search results, information visualizations) needs to accommodate different levels of understanding. This study recommends designers work closely with marginalized communities through participatory design methods to better understand how interfaces and visuals can help accommodate youth invisible work. Social implications: The authors have demonstrated in this study that learning and engaging in family online searching is not only vital to the development of individual and digital literacy skills, it is a part of family learning. While community services, libraries and schools have a responsibility to support individual digital and information literacy development, this study’s model highlights the need to recognize funds of knowledge, family resiliency and asset-based learning. Schools and teachers should identify and harness youth invisible work as a form of learning at home. The authors believe educators can do this by highlighting the importance of information problem solving in homes and youth in their families. Libraries and community centers also play a critical role in supporting parents and adults for technical assistance (e.g. WiFi access) and information resources. Originality/value: This study’s work indicates new conditions fostering productive joint media engagement (JME) around OSB. This study contributes a generative understanding that promotes studying and designing for JME, where family responsibility is the focus.

    more » « less
  2. null (Ed.)
    We study allocation of COVID-19 vaccines to individuals based on the structural properties of their underlying social contact network. Even optimistic estimates suggest that most countries will likely take 6 to 24 months to vaccinate their citizens. These time estimates and the emergence of new viral strains urge us to find quick and effective ways to allocate the vaccines and contain the pandemic. While current approaches use combinations of age-based and occupation-based prioritizations, our strategy marks a departure from such largely aggregate vaccine allocation strategies. We propose a novel agent-based modeling approach motivated by recent advances in (i) science of real-world networks that point to efficacy of certain vaccination strategies and (ii) digital technologies that improve our ability to estimate some of these structural properties. Using a realistic representation of a social contact network for the Commonwealth of Virginia, combined with accurate surveillance data on spatio-temporal cases and currently accepted models of within- and between-host disease dynamics, we study how a limited number of vaccine doses can be strategically distributed to individuals to reduce the overall burden of the pandemic. We show that allocation of vaccines based on individuals' degree (number of social contacts) and total social proximity time is signi ficantly more effective than the currently used age-based allocation strategy in terms of number of infections, hospitalizations and deaths. Our results suggest that in just two months, by March 31, 2021, compared to age-based allocation, the proposed degree-based strategy can result in reducing an additional 56{110k infections, 3.2{5.4k hospitalizations, and 700{900 deaths just in the Commonwealth of Virginia. Extrapolating these results for the entire US, this strategy can lead to 3{6 million fewer infections, 181{306k fewer hospitalizations, and 51{62k fewer deaths compared to age-based allocation. The overall strategy is robust even: (i) if the social contacts are not estimated correctly; (ii) if the vaccine efficacy is lower than expected or only a single dose is given; (iii) if there is a delay in vaccine production and deployment; and (iv) whether or not non-pharmaceutical interventions continue as vaccines are deployed. For reasons of implementability, we have used degree, which is a simple structural measure and can be easily estimated using several methods, including the digital technology available today. These results are signi ficant, especially for resource-poor countries, where vaccines are less available, have lower efficacy, and are more slowly distributed. 
    more » « less
  3. null (Ed.)
    Online employment resources are now as important as offline personal and professional networks, which have been pivotal in finding employment. However, it is unclear, which specific online resources are key to employment and how job seekers take advantage of them. Therefore, in an online survey of 768 job seekers, we investigated which online platforms, specific job search phases, behaviors, and job search strategies job seekers used in their job search, and which of these were associated with positive outcomes. We examined whether these results correlated with demographic factors and found differences in online platform use among income, gender, years of education, and race. Our results suggest that higher-income job seekers were more likely to use different strategies and more likely to get callbacks than lower-income job seekers. We raise new questions around demographics and technology and discuss the need for practitioners to design for a wider variety of job seekers. 
    more » « less
  4. Carmo, M. (Ed.)
    To succeed in the 21stcentury, students need to acquire skills that are critical to the workforce such as collaboration, social skills, and technology literacy (World Economic Forum, 2016). Individuals with disabilities (D) must develop the same skills as their peers without disabilities. Unfortunately, college students with disabilities often find computing courses frustrating and are more vulnerable to lower academic self-concept, academic challenges, and disability stigma (Kim & Kutscher, 2021). Although computing disciplines often provide good job opportunities, Students with D who enrolled in computing courses are especially at risk of falling behind and dropping out of introductory programming courses (Richman et al., 2014). To address the problem, we examined the use of pair programming, a collaborative approach to programming, as a pedagogic method to improve students with disabilities’ attitudes toward programming in undergraduate computer courses. There is a need to study effective instructional approaches that can facilitate learning and improve the outcomes of students with D. 
    more » « less
  5. Abstract

    In the face of climate change, climate literacy is becoming increasingly important. With wide access to generative AI tools, such as OpenAI’s ChatGPT, we explore the potential of AI platforms for ordinary citizens asking climate literacy questions. Here, we focus on a global scale and collect responses from ChatGPT (GPT-3.5 and GPT-4) on climate change-related hazard prompts over multiple iterations by utilizing the OpenAI’s API and comparing the results with credible hazard risk indices. We find a general sense of agreement in comparisons and consistency in ChatGPT over the iterations. GPT-4 displayed fewer errors than GPT-3.5. Generative AI tools may be used in climate literacy, a timely topic of importance, but must be scrutinized for potential biases and inaccuracies moving forward and considered in a social context. Future work should identify and disseminate best practices for optimal use across various generative AI tools.

    more » « less