Blog – Page 10 – The Renegade Coder

As you probably know, I've been working toward a PhD since late 2018. There's been a few bumps along the way, but I'm finally in the middle of data collection, which puts me right near the end of my journey. Today, I wanted to give you a sneak preview into what all that work has come to, specifically through the lens of student advocacy. Using Educational Ethnography to Get at Values Something that I haven't really talked about too much on this site is what I actually do for research as a graduate student. Since passing my candidacy exam, I've gone through a lot of changes in my life—from losing my mother to moving into a house to restoring my parents' deck. As a result, I thought today might be a good day to shift away from the content grind and talk a bit about what my research looks like. To start, I'm doing a form of research known as ethnography. Ethnography is a tool that anthropologists tend to use to study cultures. In short, it typically involves embedding yourself in the community you're interested in studying, and I like to think it shares a lot of overlap with investigative journalism. In my specific context, I'm working with early programming students to learn more about their values. Specifically, I'm interested in their education values and how those compare to their beliefs about the education values of the institution. Ultimately, I care about the alignment between the two, known as values congruence, but just learning what students think the institution cares about tells us a lot about the signals the institution is sending. As folks in power, we can then change our institutions for the better. Following the Developmental Research Sequence The way that I've chosen to go about uncovering student values is through a relatively old framework known as the Developmental Research Sequence (DRS). In short, it's a tool outlined by Spradley to provide some training wheels for folks doing their first ethnography. For me, DRS is an excellent tool for brainstorming both observation and interview questions that I can ask to help map out the cultural landscape of early programming students. For instance, I like to ask open-ended questions about the student experience to get folks talking: "what does a typical day look like for a student?" These types of questions allow me to map out different aspects of student culture, such as kinds of resources that students use or places that students like to study. As I use DRS to build up these lists of terms, I'm able to return to the students and ask about them. For example, once I've gotten a few resources, I might turn around and ask students if there are different kinds of resources. When they can confirm that there are, I'll ask them to share some with me. After doing this a few times, I can put together a deck of cards with all the kinds of resources on them. Students can then let me know if everything makes sense and if there is anything missing. With the packs of cards established, I'm finally able to learn about student values, though students will have almost certainly hinted at their values up to this point. Regardless, I like to take those packs ask the students to pick out the cards that are most important to them. For instance, a student might say the most important resource to them is StackOverflow, a key resource in computing culture. Then, I'll ask the question again but in relation to the most important resources to the institution. As the study progresses, I've been able to uncover more lists of terms that describe the local culture of computing while also digging more into specific topics. Sharing Some Preliminary Findings Part of ethnography that sets itself apart from most qualitative research is that the study design is iterative. In order to get at the research question, you have to constantly return to your data to inform how you'll collect data in the future. Or put another way, you sort of walk in clueless and map out the culture as you go. As a result, while I'm only halfway through collecting data, I already have some preliminary findings. To start, I've built up a few lists of terms that relate to the following topics: kinds of resources, reasons for taking summer classes, ways to study, kinds of exam questions, kinds of students, characteristics of engineering spaces, etc. Many of these lists are growing, but they help you get a feel for different aspects of the local computing culture. For instance, early programming students have a certain set of resources that they lean on as well as certain approaches to studying. While describing the culture is interesting in its own right, I obviously care deeply about student values. As a result, I have to approach these students with some deeper questions about these lists of topics. For example, which places to study do you think students think are most important? How do you think that compares with what the institution might say? Having only had a chance to ask this question once, I've found that students prefer the library and their homes. They seem to agree that the library is somewhere that the institution prefers as well, demonstrating some level of alignment. However, they argue that the institution would prefer they study during office hours rather than at their home. Ultimately, these kind of findings help me figure out what students care about, so I can advocate on their behalf. More specifically, I want to be able to go back to the institution and say "hey, we know you have students' best interests in mind, but these are the signals you're sending." Both should help reform education in important ways. Working Toward That Dissertation Given that I'm quite busy this weekend with Relay for Life and my mom's celebration of life, I'm somewhat inclined to call it a day on this article. That said, research is a pretty massive part of my life at the moment, so you're welcome to share your questions and comments with me at any time. With that said, it's been some time since I've posted about my PhD progress, so count this as the latest installment. Here are some other articles in the journey: I Passed My Qualifying Exam! I Failed My Qualifying Exam Journey to a PhD Otherwise, take care! See you next time.