Redefining Geek: Bias and the Five Hidden Habits of Tech-Savvy Teens
Autor Cassidy Pucketten Limba Engleză Paperback – 19 apr 2022
Picture a typical computer geek. Likely white, male, and someone you’d say has a “natural instinct” for technology. Yet, after six years teaching technology classes to first-generation, low-income middle school students in Oakland, California, Cassidy Puckett has seen firsthand that being good with technology is not something people are born with—it’s something they learn. In Redefining Geek, she overturns the stereotypes around the digitally savvy and identifies the habits that can help everyone cultivate their inner geek.
Drawing on observations and interviews with a diverse group of students around the country, Puckett zeroes in on five technology learning habits that enable tech-savvy teens to learn new technologies: a willingness to try and fail, management of frustration and boredom, use of models, and the abilities to use design logic and identify efficiencies. In Redefining Geek, she shows how to measure and build these habits, and she demonstrates how many teens historically marginalized in STEM are already using these habits and would benefit from recognition for their talent, access to further learning opportunities, and support in career pathways. She argues that if we can develop, recognize, and reward these technological learning habits in all kids—especially girls and historically marginalized racial and ethnic groups—we can address many educational inequities and disparities in STEM.
Revealing how being good with technology is not about natural ability but habit and persistence, Redefining Geek speaks to the ongoing conversation on equity in technology education and argues for a more inclusive technology learning experience for all students.
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Specificații
ISBN-13: 9780226732695
ISBN-10: 022673269X
Pagini: 320
Ilustrații: 18 halftones, 10 tables
Dimensiuni: 152 x 229 x 23 mm
Greutate: 0.43 kg
Ediția:First Edition
Editura: University of Chicago Press
Colecția University of Chicago Press
ISBN-10: 022673269X
Pagini: 320
Ilustrații: 18 halftones, 10 tables
Dimensiuni: 152 x 229 x 23 mm
Greutate: 0.43 kg
Ediția:First Edition
Editura: University of Chicago Press
Colecția University of Chicago Press
Notă biografică
Cassidy Puckett is assistant professor of sociology at Emory University.
Extras
It’s May 2004 and I’m standing next to a whiteboard at the front of a technology class in a small public middle school called Urban Promise Academy (UPA, or “ooo-pah”). The school is located in the predominantly low-income Latinx Fruitvale neighborhood of Oakland, California. Walking to UPA from the Fruitvale Bay Area Rapid Transit (BART) station, I pass clusters of men in dusty work boots—day workers—waiting for the trucks that pick them up and women selling tamales from red coolers on the corner. Vibrant colors adorn most buildings, street signs, and even the trash cans on the street. Music calls out from busy pupuserias and panaderías, the delicious scent of Salvadoran stuffed corn cakes and Mexican sweet breads filling the air, and families smile and wave as they notice neighbors across International Boulevard.
It’s the second of the six years I will teach technology classes (web design and robotics) at UPA, and I’m close to completing a master’s degree from Stanford’s Learning Design and Technology program. I’m standing at the whiteboard, chattering away at a breakneck pace, scribbling hypertext markup language (HTML) tags on the board to explain how to format pages of a yearlong web project celebrating the school’s first graduating class. We’ve collected photos and quotes from each eighth grader about their experiences at UPA and are now formatting the individual student pages and populating the website with content. We are close to completing the project, my students are almost ready to move on to high school, and I am just about to graduate as well. It’s an exciting moment.
Around me, the class munches on snacks. I explain how to hand code to structure each page, including where to add <table> tags. I say, “First you need the opening <table> and closing </table> tags, then you add code for the row, and each cell within that row like this...” I scribble on the board with dry-erase marker:
<table>
<tr>
<td></td>
<td></td>
<td></td>
</tr>
</table>
“That’s a table with one row with three cells. Get it? Anyone have any questions?” I look around the room and turn to Amairani, a quiet Latinx student with bright observant eyes, to whom I had just demonstrated the same task using a web design program called Dreamweaver. I opened the explanation up to the entire class, using hand code and drawing on the board rather than having the software create tags for them. I ask Amairani if this approach is more confusing than using the software and she says no —in fact, it’s simpler than figuring out the extra tags automatically added by Dreamweaver. With that, the class sets to work in pairs—one hand codes and types while the other reads off content to add into the tables.
I look around the room. Given the demographics of science, technology, engineering, and mathematics (STEM) education and occupational fields, everyone here could be viewed as an unlikely participant. This disparity is particularly true in computer science, where sexist, racist, and classist assumptions about “natural” differences in technological competence and “ambient” cues about who belongs in these spaces shape participation. Although not by design, we are all female. We are all from low-income backgrounds, my students much more so. Almost all of my students are first- or second-generation immigrants and come from homes where their first language is something other than English, primarily Spanish. The school and neighborhood have limited resources—which isn’t to say it isn’t a lively, thriving place. But based on the gender, racial, and socioeconomic makeup of my class, the school, and the neighborhood, we should (supposedly) not be engaged in what we are doing—playing with computers and coding—given that research shows we are the least likely people to be included in these aspects of STEM.
Still, here we are—contrary to the statistics and what stereotypes might suggest—and here I am, a new teacher in a relatively new field, trying my best to lead my students toward an ill-defined end goal: technological competence. With so much potential around the room—the kind that I later come to understand as systematically unseen and undervalued—I want them to be able to pursue any form of technology learning to get them to wherever they want to go. But I don’t know how to support them. I need to know: What does it mean to be good with technology, how can I help my students achieve it, and how can I ensure that others recognize their potential?
This book offers an answer to these questions, based on what became a decade long journey to understand what successful technology learners do, including a way of completely rethinking what it means to be good with technology. The project started out as a way to better understand and support my students and other students like them. That remains a goal: to provide tools for parents and educators to help students learn. But I also want to shake up our broader cultural assumptions about “natural” technological ability—assumptions that devalue the talent of low-income, minoritized, and female students and push them out of STEM. We do that by redefining technological competence as something that can be learned. Tech skills and literacies are not natural gifts. Instead, there are learning habits that help skills and literacies grow. These habits are especially important as technologies and the skills and literacies needed to use them change. So, what it really means to be good with technology is to develop skills, literacies, and technology learning habits…
When we reinterpret technological “instinct” as a set of learning habits and systematically describe these habits, we can then peer into what science and technology scholars call the “black box” of scientific and technical work. Black boxing hides what scientists and technologists actually do and makes it seem as though being tech savvy involves no learning at all but is instead the lucky ability of the talented few. When we are unclear about what it means to be good with technology, popular opinion, public policy, and even many scientists default to the cultural myth that being good with technology is natural or instinctual. This idea of natural ability is easily linked to other things considered natural or biological, such as age, race, and gender. In the tech world at this historical moment, assumptions about good “instinct” are often attached to young, white or Asian, and male bodies—an idea that disadvantages women and other racial and ethnic groups. These assumptions make it harder for us to see what real technological ability is, they make it harder to teach, and they make it harder to fight against inequities in tech.
In this book, I use an interdisciplinary approach building on research in the learning sciences, communication, social psychology, and sociology to explain what being good with technology really is. And I counter assumptions about natural ability with in-depth descriptions of the five habits that help people learn new technologies, highlighting in particular the habits of low-income, Black, Latinx, Native American, and female teens. I also show how to measure and build these habits—and demonstrate that many teens historically marginalized in tech already use the habits. In other words, they may be more ready for advanced technological skill development than assumptions about instinct might suggest, building on a growing body of research demonstrating the many missed opportunities for socioeconomic, gender, and racial equity. Unpacking “instinct” in this way is essential not only for the reconceptualization of the goals of STEM education to better support students’ readiness to respond to technological change but also to contest ideas about natural technological ability to combat inequities in STEM.
It’s the second of the six years I will teach technology classes (web design and robotics) at UPA, and I’m close to completing a master’s degree from Stanford’s Learning Design and Technology program. I’m standing at the whiteboard, chattering away at a breakneck pace, scribbling hypertext markup language (HTML) tags on the board to explain how to format pages of a yearlong web project celebrating the school’s first graduating class. We’ve collected photos and quotes from each eighth grader about their experiences at UPA and are now formatting the individual student pages and populating the website with content. We are close to completing the project, my students are almost ready to move on to high school, and I am just about to graduate as well. It’s an exciting moment.
Around me, the class munches on snacks. I explain how to hand code to structure each page, including where to add <table> tags. I say, “First you need the opening <table> and closing </table> tags, then you add code for the row, and each cell within that row like this...” I scribble on the board with dry-erase marker:
<table>
<tr>
<td></td>
<td></td>
<td></td>
</tr>
</table>
“That’s a table with one row with three cells. Get it? Anyone have any questions?” I look around the room and turn to Amairani, a quiet Latinx student with bright observant eyes, to whom I had just demonstrated the same task using a web design program called Dreamweaver. I opened the explanation up to the entire class, using hand code and drawing on the board rather than having the software create tags for them. I ask Amairani if this approach is more confusing than using the software and she says no —in fact, it’s simpler than figuring out the extra tags automatically added by Dreamweaver. With that, the class sets to work in pairs—one hand codes and types while the other reads off content to add into the tables.
I look around the room. Given the demographics of science, technology, engineering, and mathematics (STEM) education and occupational fields, everyone here could be viewed as an unlikely participant. This disparity is particularly true in computer science, where sexist, racist, and classist assumptions about “natural” differences in technological competence and “ambient” cues about who belongs in these spaces shape participation. Although not by design, we are all female. We are all from low-income backgrounds, my students much more so. Almost all of my students are first- or second-generation immigrants and come from homes where their first language is something other than English, primarily Spanish. The school and neighborhood have limited resources—which isn’t to say it isn’t a lively, thriving place. But based on the gender, racial, and socioeconomic makeup of my class, the school, and the neighborhood, we should (supposedly) not be engaged in what we are doing—playing with computers and coding—given that research shows we are the least likely people to be included in these aspects of STEM.
Still, here we are—contrary to the statistics and what stereotypes might suggest—and here I am, a new teacher in a relatively new field, trying my best to lead my students toward an ill-defined end goal: technological competence. With so much potential around the room—the kind that I later come to understand as systematically unseen and undervalued—I want them to be able to pursue any form of technology learning to get them to wherever they want to go. But I don’t know how to support them. I need to know: What does it mean to be good with technology, how can I help my students achieve it, and how can I ensure that others recognize their potential?
This book offers an answer to these questions, based on what became a decade long journey to understand what successful technology learners do, including a way of completely rethinking what it means to be good with technology. The project started out as a way to better understand and support my students and other students like them. That remains a goal: to provide tools for parents and educators to help students learn. But I also want to shake up our broader cultural assumptions about “natural” technological ability—assumptions that devalue the talent of low-income, minoritized, and female students and push them out of STEM. We do that by redefining technological competence as something that can be learned. Tech skills and literacies are not natural gifts. Instead, there are learning habits that help skills and literacies grow. These habits are especially important as technologies and the skills and literacies needed to use them change. So, what it really means to be good with technology is to develop skills, literacies, and technology learning habits…
When we reinterpret technological “instinct” as a set of learning habits and systematically describe these habits, we can then peer into what science and technology scholars call the “black box” of scientific and technical work. Black boxing hides what scientists and technologists actually do and makes it seem as though being tech savvy involves no learning at all but is instead the lucky ability of the talented few. When we are unclear about what it means to be good with technology, popular opinion, public policy, and even many scientists default to the cultural myth that being good with technology is natural or instinctual. This idea of natural ability is easily linked to other things considered natural or biological, such as age, race, and gender. In the tech world at this historical moment, assumptions about good “instinct” are often attached to young, white or Asian, and male bodies—an idea that disadvantages women and other racial and ethnic groups. These assumptions make it harder for us to see what real technological ability is, they make it harder to teach, and they make it harder to fight against inequities in tech.
In this book, I use an interdisciplinary approach building on research in the learning sciences, communication, social psychology, and sociology to explain what being good with technology really is. And I counter assumptions about natural ability with in-depth descriptions of the five habits that help people learn new technologies, highlighting in particular the habits of low-income, Black, Latinx, Native American, and female teens. I also show how to measure and build these habits—and demonstrate that many teens historically marginalized in tech already use the habits. In other words, they may be more ready for advanced technological skill development than assumptions about instinct might suggest, building on a growing body of research demonstrating the many missed opportunities for socioeconomic, gender, and racial equity. Unpacking “instinct” in this way is essential not only for the reconceptualization of the goals of STEM education to better support students’ readiness to respond to technological change but also to contest ideas about natural technological ability to combat inequities in STEM.
Cuprins
Introduction: Why Are Some People So Good with Technology?
Chapter 1. Why Does Digital Inequality Persist?
Chapter 2. What Helps People Learn: Three General Technology Learning Habits
Chapter 3. Techie Tricks: The Two Technology-Specific Habits
Chapter 4. Recognizing the Five Habits: The Digital Adaptability Scale
Chapter 5. The Five Habits, Teens’ Futures, and Digital Inequality
Chapter 6. Tackling Digital Inequality: Gatekeepers
Conclusion: Envisioning an Equitable Future
Acknowledgments
Appendix: A Reflection on Mixed-Methods Research
Notes
Index
Chapter 1. Why Does Digital Inequality Persist?
Chapter 2. What Helps People Learn: Three General Technology Learning Habits
Chapter 3. Techie Tricks: The Two Technology-Specific Habits
Chapter 4. Recognizing the Five Habits: The Digital Adaptability Scale
Chapter 5. The Five Habits, Teens’ Futures, and Digital Inequality
Chapter 6. Tackling Digital Inequality: Gatekeepers
Conclusion: Envisioning an Equitable Future
Acknowledgments
Appendix: A Reflection on Mixed-Methods Research
Notes
Index
Recenzii
"Through extensive interviews, fieldwork, and surveys, [Puckett] uncovers what it takes for teenagers to learn new technologies . . . Overall, this is a thoroughly researched book that nonetheless presents a set of easy-to-understand and actionable conclusions. It should have broad appeal both among sociologists interested in inequality as well as among educators, policy makers, and parents."
"Redefining Geek will serve as an essential guide for a generation of educators who are grappling with how best to teach and lead in this technological age. Puckett draws on a deep data set to redefine what it means to be competent with technology, bust a pile of myths much in need of busting, and offer clear steps for helping students develop the habits they need to succeed in life, work, and play. This book will guide how we tackle digital inequality and support the learning process of young people of all races, ethnicities, and genders for years to come."
"Puckett is a terrific writer with a broad, precise, empathetic, and thoroughly researched account of technology education and where it falls short. In Redefining Geek, Puckett carefully dispels myths about natural technological ability and grit that perpetuate existing inequalities. She offers practical and innovative ideas to make STEM more inclusive. Providing fresh analysis with new stories and actionable examples, Redefining Geek is a smart, engaging look at what needs to change about education in order to bring about technology that benefits us all."
"Redefining Geek is essential reading for educators. Using evidence from extensive fieldwork with students and teachers in STEM programs across the US, Puckett deftly dismantles popular assumptions about the origins of technological ability. Through poignant quotes and engaging stories, Puckett reveals that neither 'natural' talent nor 'grit' can explain why some students are able to navigate the changing technological landscape and learn new technology tools and platforms. Instead, and building on prior research in the science of teaching and learning, Puckett shows that technological competence is the product of five key habits. These include: 1) being willing to try and fail, 2) knowing how to manage frustration and boredom, 3) using models to think through difficult problems, 4) asking why things work the way they do (design-based thinking), and 5) asking how things can be done more quickly or more easily (efficiency-based thinking). By uncovering the habit-based origins of technological competence, and by revealing how successful programs cultivate these habits in students (including in low-income students, Black, Latinx, and Native American students, and girls of all backgrounds), Redefining Geek offers a new way forward for those interested in tackling longstanding inequalities in STEM."
"Through her solid research and her experiences with working with diverse student learners, Puckett does an exemplary job in helping readers understand and rethink what it means to be technologically competent. This is especially important considering our world is more reliant on technology due to the COVID-19 pandemic and having tech skills is essential. This knowledge and her guidance—coupled with a thorough examination of how our biases can further exacerbate the digital divide—is beneficial in designing tech educational curriculums and programs that are more inclusive and supportive to the diverse communities that they are serving. A must-read for any professional seeking to improve and advance technology education."
"Cassidy Puckett understands that the learning disposition--how students feel about learning—as well as their perceptions of their ability to learn--a sense of efficacy—are critical to learning outcomes. In Redefining Geek, Puckett introduces a set of learning habits to help students develop a growth mindset in STEM learning. Through sound research and sharp insights, Puckett makes a convincing case that it’s not only important that students learn how to use the technology available to them today but that they develop the habits and mindset that will support their ability to use and design with the technologies of the future."