Please note: This paper was written for a graduate-level course and is not peer-reviewed. My current perspectives, as well as research in the field, may have changed. All errors are my own.
“Damian Huang” is a college student who reached out to me for help revising his résumé. He had uploaded his original résumé to his university’s job board, but he wasn’t getting contacted for positions despite his strong leadership and management experience. After a 1.5-hour interview, Damian and I revised his résumé to match the job listing for an internship at Google. Damian and his mentors felt much more confident with his revised résumé.
- Clarifies language for increased legibility.
- Restructures résumé to show a continued work history.
- Moves education to the bottom to prioritize leadership experience.
“Pablo Fernandez” doesn’t have a college degree, but he’s had jobs across multiple industries. He called me for help applying for a position in the hospitality industry. His skills as a caretaker in his previous hotel job and group home job made him an excellent candidate for the position. He received an offer for the job, which he accepted.
- Removes irrelevant work experience.
- Tightens bulky paragraphs into easy-to-read bullet points.
- Removes “hobbies” section to increase space for skills.
Virtual roleplay and remedial instruction to evaluate students’ retention of Mandarin Chinese after three months’ learning inactivity over summer vacations. Built on the Virtual Chinese platform developed in partnership with Virtual Virginia Online School.
Tasks included developing a curriculum, creating analytics for evaluating students’ language skills, writing and implementing branching conversations, writing remedial lesson content, and creating an utterance library of possible correct and incorrect responses to be evaluated by the ASR system and learning management system (LMS).
June 2014–January 2015.
Virtual roleplay conversations for students of English as a Foreign Language (EFL) built on the Enskill® platform . Tasks included writing and implementing branching conversations about daily activities such as going to the post office and ordering food at a restaurant, as well as iteratively creating a library of possible utterances for the ASR system to parse. Utterances were standardized to be applicable to multiple locales, including Thailand and Brazil.
December 2016–June 2017.
Mandarin Chinese robot-assisted learning development. Tasks included writing and implementing branching conversations and recruiting native speakers of Mandarin to create automatic speech recognition (ASR) models.
June 2014–January 2015.