Describing oneself as a maker — regardless of what one actually or mostly does — is a way to accrue the gendered capitalist benefits of being a person who makes products.
Debbie Chachra, “Beyond Making,” in Making Things and Drawing Boundaries: Experiments in the Digital Humanities, ed. Jentry Sayers, Debates in the Digital Humanities (University of Minnesota Press, 2017).
This passage caught my attention because it critiques the prioritization of “making” in technology and education, challenging the narrow value systems that overlook essential, less visible labor like caregiving, teaching, and analysis. The quote highlights how societal recognition often hinges on visible outputs, overshadowing equally valuable but less tangible contributions. This perspective resonates deeply with my own learning experiences in computer science and mathematics, where the focus on problem-solving and artifact creation often eclipses the processes of learning, collaboration, and fostering understanding.
Reflecting on my past experiences, I recall moments in computer science and mathematics where the “making” of projects or solutions was celebrated as the ultimate achievement, while the effort to build foundational understanding was undervalued. For instance, in computer science, the immediate satisfaction of writing a functioning program was always rewarding. However, what truly shaped my growth and understanding was the often-overlooked process: debugging tirelessly, collaborating with teammates to exchange ideas, and asking professors questions that delved deeper than “what works” into “why it works.” These experiences taught me the importance of persistence, curiosity, and mutual support in learning.
Similarly, in mathematics, the joy of solving complex equations often overshadowed the foundational steps that made such achievements possible. Exploring abstract concepts, carefully writing out proofs step by step, and engaging professors in discussions about unfamiliar principles were not only essential but also profoundly rewarding. These moments reminded me that the real value of coding and mathematics lies not just in the products but in the process of learning, teaching, and connecting with others.
Under the broad umbrella of Digital (Arts &) Humanities, I am eager to pursue areas that combine technical skills with my passion for analysis and storytelling. Data visualization and computational text analysis are particularly exciting to me because they offer the opportunity to uncover patterns, draw meaningful insights, and tell compelling stories with data, bridging technical expertise and humanistic inquiry.
