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1. DreamGigs: A “Stepping Stone” for Low-resource Job Seekers to Reach Their Ideal Job

   https://doi.org/10.1145/3272973.3274086  

   Lu, Alex; Brill, Jason; Dillahunt, Tawanna R. (January 2018, In Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing)

   Digital employment tools ought to support job seekers in developing viable career paths while preparing them with necessary skills for employment. This is particularly important for job seekers who are not highly educated and lack access to resources such as career counseling. We designed, implemented, and conducted a preliminary evaluation of a prototype -- DreamGigs, a tool to help job seekers understand the career-related skills they would need to obtain to reach their -dream" job or gig. Our preliminary results suggest that DreamGigs is helpful for job seekers in understanding what skills employers need, identifying potential pathways towards their career goals, and accessing opportunities to gain the necessary skills. We contribute the design of this tool, our implementation, and the results of our initial evaluation with low-resource job seekers. 

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2. DreamGigs: Designing a Tool to Empower Low-Resource Job Seekers

   https://doi.org/10.1145/3290605.3300808  

   Dillahunt, Tawanna R.; Lu, Alex (January 2019, Proceedings of CHI Conference on Human Factors in Computing Systems)

   Technology allows us to scale the number of jobs we search for and apply to, train for work, and earn money online. However, these technologies do not benefit all job seekers equally and must be designed to better support the needs of underserved job seekers. Research suggests that underserved job seekers prefer employment technologies that can support them in articulating their skills and experiences and in identifying pathways to achieve their career goals. Therefore, we present the design, implementation, and evaluation of DreamGigs, a tool that identifes the skills job seekers need to reach their dream jobs and presents volunteer and employment opportunities for them to acquire those skills. Our evaluation results show that DreamGigs aids in the process of personal empowerment. We contribute design implications for mitigating aspects of powerlessness that low-resource job seekers experience and discuss ways to promote action-taking in these job seekers. 

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3. LinkedIn(to) Job Opportunities: Experimental Evidence from Job Readiness Training

   https://doi.org/10.1257/app.20200025  

   Wheeler, Laurel; Garlick, Robert; Johnson, Eric; Shaw, Patrick; Gargano, Marissa (April 2022, American Economic Journal: Applied Economics)

   Online professional networking platforms are widely used and may help workers to search for and obtain jobs. We run the first randomized evaluation of training work seekers to join and use one of the largest platforms, LinkedIn. Training increases the end-of-program employment rate by 10 percent (7 percentage points), and this effect persists for at least 12 months. The available employment, platform use, and job search data suggest that employment effects are explained by work seekers using the platform to acquire information about prospective employers and perhaps by work seekers accessing referrals and conveying information to prospective employers on the platform. (JEL J22, J23, J24, J64, M53, O15) 

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4. Self-regulation and Autonomy in the Job Search: Key Factors to Support Job Search Among Swiss Job Seekers

   https://doi.org/10.1093/iwc/iwac008  

   Dillahunt, Tawanna R; Siqueira Rodrigues, Lucas; Chiao-Yin Hsiao, Joey; Cherubini, Mauro (July 2021, Interacting with Computers)

   Abstract Technology integration in the workplace context has led to substantial growth in high- versus low-skilled jobs, and thus, further disparities between workers and those who were already unemployed. Technology use is also being used more frequently in the job search process, which could further lead to disparities, especially for job seekers experiencing marginalization. Thus, we conducted a controlled longitudinal field deployment of two employment-based tools—RevueCV and InterviewApp—among 46 Switzerland-based unemployed job seekers. Using the theory of planned behavior (TPB), we sought to understand how the tools affected job search self-efficacy, subjective norms and job search attitudes—the three factors that influence a job seekers’ job search intention. Although participants appreciated the support the two tools provided, and the inherent study benefits, our interview and survey results showed no substantial changes in their TPB values, primarily because the tools provided overlapping services with the local job placement offices. However, results of our interviews found autonomy, or the lack thereof, to be a key factor contributing to job seeker dissatisfaction. We introduce the concept of self-regulation to the TPB as an explanatory construct and contribute design and theoretical implications to support autonomy among job seekers with less control of their job search. 

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5. “Am I Answering My Job Interview Questions Right?”: A NLP Approach to Predict Degree of Explanation in Job Interview Responses

   https://doi.org/10.18653/v1/2022.nlp4pi-1.14  

   Verrap, Raghu; Nirjhar, Ehsanul; Nenkova, Ani; Chaspari, Theodora (January 2022, Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI), Empirical Methods in Natural Language Processing (EMNLP) Conference)