Posts that are olin-ish

Curricular principle: being as well as knowing

This is the first post of a series on Olin’s curricular culture principles (draft versions!) which is my attempt to bring transparency into the work I’m doing with Tess Edmonds (‘11) and others. The short backstory is that Olin gets a lot of visitors from other institutions — mostly faculty — who want to learn how to do “what we do.” This requires us to articulate “how we do things around here” — in other words, allergist our curricular culture — to talk about not just the surface-level features of our practice (“students work on teams!”) but the underlying principles that manifest in those surface-level formats. You can find all the posts in this series here.

A note before beginning: I’m writing this for an audience of fellow Oliners, and while I’ve tried to unpack acronyms and terms, I may be missing some. Let me know in the comments if there are things I need to unpack more, and I’ll edit accordingly.

The first principle I’m going to unpack is: learning is about being a practitioner, not just knowing about practice. As Rick Miller has said, Olin students learn to become engineers rather than learning about engineering.

This might seem obvious, but it isn’t. In the engineering education research world, we talk a lot about engineering epistemologies[1], which is the fancy word for “the study of engineering knowledge.” What is engineering knowledge, who decides what this knowledge is, how do we help people obtain it, and so forth? Similarly, when engineering faculty sit down to teach a course, they often talk about what students need to know, what they already know, how to help them acquire this new knowledge; it’s focused on the things students will learn about.

Without this principle, we end up talking a lot about the things students know, but not a lot about the people students are, except perhaps in a diversity-and-inclusion context. Even then, it’s usually in the context of how who they are affects the way they come to know — comments like “well, students from low-income communities tend to come in with less exposure to programming” or “how can we help women become more confident while learning how to use the machine shop?” However, we can’t separate knowledge and being/reality — it’s impossible to know something without there being a reality to know, and without being someone in that reality who can know[2].

This principle of “being as well as knowing” is not well developed throughout most of the engineering education world — including Olin (we don’t always do this perfectly). A lot of engineering educators focus on assessing and developing what students know about engineering. In order to adopt this principle, we also need to pay attention to how students are engineers — what it means for each of them to be their own particular kind of engineer.

To take two Olin faculty members as examples: by “their own particular kind of engineer,” I don’t just mean that Aaron is a MechE and Alisha is a BioE. I also mean that the ways in which Aaron and Alisha are engineers — the ways they embody engineering, the things it means for them specifically to be an engineer — include the things they know about engineering, but also include so much more than that. It’s important that Alisha is deeply invested in the design process and bringing it into non-engineering contexts and spent last semester working at a hospital; it’s important that Aaron has a minimalist aesthetic and works on transforming campus architecture and likes bikes. They know about things, and they also are many things (designers, bikers, people interested in medical work, etc). When Olin practices this principle well, it acknowledges and values these aspects of being (and more), and values how these aspects of being are expressed and developed — and crucially, sees this development and expression as part of engineering, not something separate from it.

This sentiment of also valuing the being of a person as an engineer similarly extends to the context of course design. Here, this looks like Olin faculty talking about what students should know, but also aspects of being they want students to have. For instance, QEA (Quantitative Engineering Analysis) faculty talk about how they want students to be engineers who enjoy doing quantitative analysis — which is related to, but separate from, their knowledge of quantitative techniques and their ability to apply them.

This aspect of Olin’s curricular culture affects the ways Olin community members work to help each other and ourselves grow as individuals[3]. Whether we’re students, faculty, staff, or alumni, we don’t just focus on developing what Oliners know; we focus on developing who they are.

Remember, these principles are drafts — I’m putting them out here for more commentary, feedback, etc. I’d love stories from Oliners (and non-Oliners) about their Olin experiences and how they do/don’t match this principle, and how this resonates with you, and especially how it does not (because that’s how I’ll learn to edit it). Post in the comments or contact me via whatever other means you have, and we’ll talk. And stay tuned for the next post, which I think will probably be on attention ownership (we’ll see!)

[1] Engineering epistemology (what engineering knowledge is and what it means to know about engineering) is one of the 5 key areas of engineering education research set forth in the 2006 paper that is still used to classify a lot of work in the field — see National Engineering Education Research Colloquies. (2006). The Research Agenda for the New Discipline of Engineering Education. Journal of Engineering Education, 95(4), 259–261. There is no mention of engineering ontology (or what it means to be an engineer) in that document, or in later iterations of an engineering education research taxonomy (current version at I’m… working on that.

[2] The philosophical terminology for this is ontology (the study of being/reality) and epistemology (the study of knowledge). Engineering education has a well-developed practice of talking about epistemology, but we are not used to discussing ontology. (Reality is just… real, right? And things just are. What’s there to talk about? Turns out there’s a lot.)

[3] The phenomenon of other fields looking at the ontologies of their disciplines and education practices is very recent, and is known as the “ontological turn” that is sweeping across the disciplines. Engineering education hasn’t quite entered it yet, but part of my work is attempting to bring it there. For an example of the ontological turn from medical education, see Dall’Alba, G. (2009). Learning to be professionals. Dordrecht ; New York: Springer.

Comic: Products and Practitioners: how a visibility of developmental processes aids in practitioner formation

The one-page comic below was created as a quick reference for faculty and students at Olin College, doctor where learners can see the development of both products and processes in the domain they are learning in (whether that’s engineering, education, or something else).

The text after the comic is also in the Scribd document description and functions as an accessible image description of the one-page comic.

Products and Processes: how a visibility of developmental processes aids in practitioner formation by Mel Chua on Scribd

Another theory comic: image description follows. (Heavily influenced by Community of Practice, Situated Cognition, and Cognitive Apprenticeship theories.)

Text at the top of the page: When learners are engaged in an authentic, situated, & communal practice context, they see the development of two kinds of things over and over again in their environment:

Title text: Products & Practitioners (of their practice).

The middle of the page is divided into two columns. The left column is under the portion of the title that says “Products,” and shows three people getting clay from a big lump labeled “raw materials.” Below that, the same three people are shown starting to form pots from the clay; one person drops their pot and cries “oh, no!” Below that, the same three people are shown continuing to work on their pots; the middle person is now saying “oh, cool!” as they piece the pottery shards back together, and one of the other potters looks at them and thinks “I see how you adapted that!” Below that are drawings of the three final pots, all different; one is a squat, short pot with squiggly decorations, another is the broken pot pieced artistically back together, and the third is a tall vase made out of coils. All together, the left column shows the development process of a variety of pottery “products” from start to finish.

The right column is under the portion of the title that says “practitioners.” At the top is a group of three small children labeled “novices,” in the middle is a group of three teens labeled “juniors,” and at the bottom is a group of three adults labeled “masters.” The novices are making small simple pots; one cries out “my first pot!” while raising their fist in excitement. One teen is looking at the excited small child and thinking “I remember that time.” Another teen is being gazed at by a small child thinking “someday, I’m going to do that,” and is in turn looking at an adult practitioner and thinking the same thing. One of the teens has made a mistake on their pot; an adult is watching them and saying “I remember that time.” All together, the right column shows the developmental spectrum of potters from novice to master, with younger practitioners looking towards the older ones in anticipation of what they will do, and older ones looking back at the younger ones in remembrance of where they once were.

Below these two images is text that reads: one thing seeing these developmental cycles constantly reinforces is the sheer diversity of ways to engage with the profession/practice and the world. Each product and practitioner is fashioned from a different mold. The question becomes not “how do I fit the norm,” but rather…

“What might I make?” and “Who might I become?” (in a thought bubble coming from a person at the bottom center, head cradled thoughtfully in hands, with a variety of ceramic pieces surrounding them at either side)

At the bottom of the page is the copyright/authorship notice: Copyright 2016 CC-BY-SA Mel Chua.

Comic: 7 Techniques Adapted From Cognitive Apprenticeship Theory

The one-page comic below was created as a quick reference for faculty and students at Olin College, viagra order where students and faculty frequently have spontaneous, pancreatitis complex learning interactions in seemingly chaotic studio/project environments. Cognitive apprenticeship theory provides one of many ways to make sense of the sorts of implicitly taught and culturally engrained deep teaching and learning skills that might otherwise be lost in overwhelming chaos.

The text after the comic is also in the Scribd document description and functions as an accessible image description of the one-page comic.

7 Techniques Adapted From Cognitive Apprenticeship: “Making Thinking Visible” in spontaneous, complex learn… by Mel Chua on Scribd

Header: Cognitive Apprenticeship – 7 techniques for making thinking visible (studio version)

This comic is a one-page visual description of 5 Cognitive Apprenticeship techniques developed in the 80′s by Collins, Brown, Newman, and Duguid, plus two additions adapted by the author for adult learners (denoted with an *).

The techniques are:


  • scaffolding (faculty directs attention — a faculty member frames part of a complex problem, asking a student to “please focus your work here first”)
  • bounding* (student directs attention — a student frames part of a complex problem, asking a faculty member to “please focus your feedback here first”)
  • modeling (faculty does, faculty explains — a faculty member works with a complex problem, explaining what “I am trying to…” do)
  • coaching (student does, faculty explains — a student works with a complex problem while a faculty member coaches them on what “you might try to…” do)
  • narrating* (faculty does, student explains — a faculty member works with a complex problem while a student explains what they think “you are trying to…” do)
  • articulating (student does, student explains — a student works with a complex problem, explaining what “I am trying to…” do)
  • reflecting (comparing faculty/expert practice with student/novice practice)


These seven techniques are displayed in a thought bubble being pondered by a cartoon character who has lifted off the top of their head, pointing to the gears turning inside; this is a metaphor for “making thinking visible.”

Beside that character are two ways the 7 techniques can be used:

  • used to describe spontaneous, complex learning interactions (a faculty and student interacting over a complex problem, their illegible speech bubbles overwritten by a label saying “what is happening here? Bounding.”) A note at the bottom says that the technique “switches rapidly every 1-2 sentences.”
  • used to request spontaneous, complex learning interactions (a faculty and student interacting over a complex problem; the student says “could you please Model this for me?” and the faculty replies “sure!”)

The text at bottom left (cut off by the scan): *denotes new code adapted for adult learners. Comic CC-BY-SA Mel Chua 2016.

Startup/shutdown and research circuit routines

One of the best things I’ve started to do consistently this semester is to think of my research work the same way I think about my physical training. I do equipment setup, cialis 40mg warmup, cooldown, and takedown for all my workouts and rehearsals… so why not for my scholarly life?

This isn’t an analogy. As an experiment, I’m taking it as literally as possible and doing my research as a workout, with various research tasks as a part of circuits that include planks, rows, turkish get-ups, and so forth.

Sample circuit: As many rounds as possible (AMRAP) in 2 hours (I usually get through 3-4 circuits).

  • Shoulder mobility circuit, 20 each of T/Y/L/Ws (similar to this set of exercises, but standing)
  • Read and sticky-note a chapter in the book I’m reading. If all chapters are sticky-noted, type notes from one chapter into my personal Zotero format.
  • 2 turkish get-ups on each side, using kettlebell of appropriate weight
  • 5 kettlebell haloes in each direction
  • Complete and send feedback/assessment on one student project (20 minute maximum; set a timer)
  • 10 straight-leg situps, 10 burpees; another 10 straight-leg situps, another 10 burpees
  • Write setup/context paragraph before one piece of data in a dissertation chapter
  • At least 5 minutes of recovery, during which I must drink water.

This circuit changes each time I do work, depending on what I need to get done. However, there are some consistent things.

Setup checklist

  1. Put on appropriate clothes (in my case, I need to be able to move my shoulders so they don’t get stiff; this might mean changing a shirt or taking off a jacket).
  2. Ergonomics setup: wristguards on, or monitor raised and external keyboard in position.
  3. Earbuds ready, music set up (FocusAtWill)
  4. Water bottle (+ coffee, if applicable) on the table.
  5. Notebook and pen open to the next blank page.
  6. Pomodoro timer (Toggl button) ready to go.
  7. “Locating” text document from the end of last work session open

Warmup (every time):  Once everything in the setup checklist is complete, I do this; it should take 20 minute max.


  1. Shoulder muscle routine (combination of arm circles and other light mobility work)
  2. Use “Locating” document and notebook/text editor to design the current day’s research sprints/circuits
  3. …then do my physical warm-up (a ~5 minute series of stretches, squats, etc. that I do each time)
  4. …and then sprints/circuits can begin.


Cooldown (every time): This should take about half an hour max.

  1. One short (10-15 minute) pomodoro to get to a good closing place on whatever I have worked on that day.
  2. Stop pomodoro timer, put away.
  3. Stop music, put away earbuds.
  4. Clear browser tabs and open documents on my computer.
  5. Gather up water bottle, coffee/food and walk to put it away. Before returning to my computer from this trip, I think about (1) what I need to characterize about where I’ve left off to locate myself, and (2) whether tomorrow’s-Mel needs to keep anyting else in mind.
  6. Return to computer and type those things into “Locating” text document for tomorrow. Make this the first thing I’ll see when the laptop opens.
  7. Close laptop. I’m no longer allowed to open it again for the day.
  8. Put away ergonomics setup.
  9. Arm circles,  trunk spirals, and cooldown stretch routine.
  10. Shutdown complete; pack everything inside my bag, clean up any additional items, and I’m done.

Qualitative research: the discussion section, or: “kryptonite – so what?”

Originally written as an explanation for my qualitative research methods students.

The discussion section of your project is where you answer the question: “so what?” This typically comes at the end, otolaryngologist because you are discussing that question in relation to the results of your project, not the problem statement like you did at the beginning. Here’s the difference.

The introduction comes before you talk about the results, and tells us what problem you’re trying to solve (or what question you’re trying to address) and why it is important. For instance, ”we should find out what kinds of things make Superman weak, because if he’s going to keep saving the world, we need to know what might prevent him from doing so” would be an introduction that explains the motivation behind the research question of “what effect do various ore forms of radioactive elements have on the strength and flight abilities of Superman?”

Now, suppose you find that among the elements you tested, only kryptonite has a measurable effect on Superman’s strength and flight abilities, and that it strips him of his powers and makes him physically ill. Those are your results — see how they’re a direct answer to the question you asked earlier?

The discussion comes after your results. Now that we know that kryptonite weakens Superman… so what? What difference does this specific answer make to how we operate? Well, maybe we want to preserve Superman’s superpowers, so this means need to make sure Superman doesn’t come in contact with Kryptonite… perhaps we should make it illegal to possess the substance. Or maybe we want to give a subset of people access to Kryptonite so that they can take Superman down in case he goes evil.

That’s a discussion. Note that the discussion depends on the results you got — if the results change, the discussion changes. For instance, if you found that no ore forms of radioactive elements had measurable impacts on Superman’s abilities, you wouldn’t recommend outlawing Kryptonite because it’d make no difference in this case. If you found out that all ore forms of radioactive elements came close to killing Superman, but only on alternate Tuesdays, and only if he ingests them, you might talk about creating a Superman Radioactivity Food Scanner that only operated once a week to save resources. You get the idea.

The discussion question of “so what?” is not a question you need to have an answer to until the end, but you should know at every point in time that you will need to answer it… in other words, it’s something to constantly keep in mind, and you’ll find it along the way as you develop your project. The introduction and discussion are both important places where you tell us why your work matters — but the introduction is where you tell us why the question is important, and the discussion is where you tell us why the answer is.

QualMIP week 11: semester feedback

Part of the QualMIP series, mind introduced here. 

Technically, medicine it’s week 12 but blog entry 11, pestilence since week 11 was a review of the semester plus a presentation of projects. Tonight… was feedback night.

Major takeaways

  1. Constant awareness of positionality and related concepts — bias, personal experience, etc.
  2. Rich awareness of everyday interactions. Formerly “boring” situations reveal a depth of interaction, and there are more tools with which to analyze what’s going on; there are always questions we can ask.
  3. Along the same veins, “having a larger toolbox” with which to experience the world (one of our original goals, so that’s fantastic.)
  4. The importance of self-care and sensitivity to one’s own state and emotions. “You are your own research instrument.” Along these lines, the policy of grace weeks was a MASSIVE hit, and… I will do this again.

Other takeaways, in absolutely no particular order

The value of team dynamics in learning qualitative research, which I’ll need to consider for future (presumably larger-group) iterations. It’s nice to have a team and learn about your differences in perception, and to get comfortable tossing ideas around with — but there’s also value in switching it up. Cesar, Paige, and Emily worked together super-well, and this contributed tremendously to the success of the project.

NINJAs. Instructor-student ratio is key. If I scale up much, I absolutely need course NINJAs (teaching assistants) and/or coinstructors.

More memo assignments. In perhaps the first instance of students asking me to give them more homework, the group requested more exercises focused on forcing them to try different memo formats during exercises. In a 2-credit independent study, I tried not to overload them, but this is top priority to add in for a full-scale class. Suggestions include having some group-facing memos (both small and large) in addition to individual ones, so they can see what it’s like to memo with and for different audiences as well as in different formats.

Interview nonverbals were a good skill to gain — you don’t really need to talk during an interview. (Quote from last night: “It’s kind of like therapy. They just listen so you can talk and figure it out yourself.”) Each individual has distinctive movement patterns. (I think of them like voices.)

More rounds of interviewing/observing skill practice. There was universal acclaim for more repeated practice for interviewing and observing, specifically. This fits nicely with the request for more memos. I think “more structure” will be the order of the day in the next (larger) round of the class.

Ambiguity, followed by framework introductions (worksheets, whiteboard grids, etc.) is a good pattern. Don’t give the frameworks at the beginning — let students try to figure it out — but at some point, it’s really nice to see how others have ordered topics. (I agree! It’s hard to do this without introducing reading assignments… or is it? I could make worksheets from the readings, and leave the citations at the bottom for students to optionally look at if they want, I guess.)

The introduction to various qualitative research paradigms was good (although I feel it was too theoretical). This might be something valuable to use reading assignments for (one of my restrictions in this independent study design was “no course readings,” and in a full-scale course I would relax that somewhat). Showing examples of work in each paradigm and having students do work across at least two (somehow) would be a plus, since everyone ended up in the interpretivist camp this time.

Project development lifecycle examples. Similarly, the close reading was useful so they could see parts of a project at a different stage than where their own projects were at. Finding some way to see (close readings of) different projects at different stages in development earlier on might help.

Instrument development was useful to see! This time around, it happened accidentally when Emily created one as part of her project (a massive table for sorting data about dance events). Do this more explictly next time.

Inter-rater reliability and validity could have used better discussions. (Yeah, I kinda pulled those out of the top of my head when it became clear we needed to discuss it during studio. More planning would have been good, I admit.) Also, we did not have a unit on member-checking, and should.

Using Olin as a convenient study location was a plus, largely for the exercise of “making the familiar strange,” and the ease with which we could (potentially) experiment with environmental disruptions (something we did not do this time). Using locations other than Olin on occasion was also a big plus, so… mix it up. (Me: “I’m sure I can find strange, safe, but uncomfortable situations to dump people into.”)

Protocol testing was a good exercise. However, we won’t have a convenient AHS capstone in need of protocol feedback in future iterations of the course, so teams will have to come up with protocols for that exercise and swap them (a good addition to the exercise, really). Make sure to specify those protocols be made on non-sensitive topics; this time the AHS capstone topic was about something that some people considered touchy, and about something others didn’t have experience with, which made it difficult to test as they scrambled to fabricate stories.

Keep the unicorn exercise (that we did with Insper).

The artifact analysis scavenger hunt was too much to pack into one day — split it over two class periods so we can take more time doing it.

Bounding projects was something everyone did, and a good skill to develop in general. Perhaps develop exercises specifically targeting this? (I’ve talked with faculty at other times about “project bounding” being a skill that Olin students need to develop more generally.)

Derrida. In a simultaneous I-am-proud-but-also-sort-of-scared moment, the idea that “everything is text” ended up being an impactful phrase… I think the students meant it as “everything is data” and “everything can be analyzed” or something similar, but I’ll need to be careful about introducing Derrida in the future, because… there is such a thing as just enough postmodernism to be dangerous (I’m at that stage myself, right now).

The machine trick/geneaology. Related to the above thought, the constant asking of “how did that get there? how did this come to be?” is a habit of mind that I am silently rejoicing over. Even the most intimidating, formal-looking things have some kind of backstory (and psst… the world is hackable.)

Apparently, my metaphors are popular (and help with conceptual understanding, I… think). I don’t even remember what they were, but I supposedly compare things to programming and dancing quite a bit, and there was laughter.

Mental health. One of the most surprising but gratifying comments was that QualMIP was a good influence on student mental health this semester — that it contributed to better self-care, ways to move on from cycles of overthinking, permission to be kind to oneself, awareness of one’s own state, and… well. Mental health. I’m glad for this — I’m glad this could be a space for that — and I’d like to find a way to keep making it a better space for that, because it’s SUPER important, especially at a place like Olin.

And finally, having a giant teddy bear in the office is fantastic.

QualMIP week 10: topic tracking and project progress

Part of the QualMIP series, vitamin introduced here.

Another short post this week because of a time crunch and my inability to write longer coherent things today (thanks, ascariasis ADHD! Sometimes you just gotta roll with it).

Today was an analysis day — project updates, studio time, collaborative analysis — not a lot of scaffolding, more tracking where people are in their work and how to move forward. This post will likely be most useful for my future self as a way of tracking which topics are good to build more scaffolding around. Here are some:

Subject protection - using pseudonyms, talking with participants about how their data will be used, etc.

Positionality (yet again) - How does your prior exposure to a topic shape the analysis you do with it — and the way you triangulate your analysis with others’ when you’re checking inter-rater reliability? Our group has a mix of people with extensive social dance experience to no social dance experience (with social dance as the chosen context of study this semester). This gives a great variety of perspectives and positionalities that become visible in projects — and need to explicitly be pointed out (what terminology should you assume familiarity with, etc?)

Relationship between methods, results, and discussion - what you did, what you learned, and what difference it makes (“so what?”)

Instrument design as a subjective act – a reminder once again that all surveys, all instruments, all scales, etc. are reflections of human decisions about meaning creation. This does not mean they are all created equal, but it does mean they can and should be tested and interrogated and developed themselves (for instance, the IQ scale has a long history of “what does it mean to be intelligent?” debates behind it).

Validity. One thing I wish I’d prepared — and perhaps will prepare for next week, we’ll see — is a discussion on validity. In the context of qualitative research, what does it mean for a study to be “rigorous” and “valid”? (I have a lot to say about assumptions in this domain…)

It’s pretty cool to see the projects shaping up — intermediate artifacts are popping out. Emily has a nice table shaping up, which spurred a discussion on externalizing one’s process and the iterative nature of instrument design. Cesar should be bringing at least one draft poster in next week so we can start the “so what?” discussion (the “discussion discussion”), and Paige will be going through her emergent analysis process and then working to articulate it. Just a few weeks left to go…

QualMIP week 9: alignment of project components

Part of the QualMIP series, sickness introduced here.

You can tell the semester is ending soon, because my posts are getting terser… this week our studio focus was on three things: project design alignment, creation of a data inventory, and discussion of what “done” means for individual projects.

The week will be spent moving towards whatever “done” is for each person’s project — but having alignment and clarity as to what the project is is an important prerequisite to being able to do that. We spent the day workshopping alignment, with the (draft! handwritten! first version!) worksheet below as representative of how we scaffolded that discussion. (I’d love comments on the worksheet, by the way.)

Qualitative Research Design Alignment Worksheet

QualMIP Week 8: narrowing research question and unit of analysis

Part of the QualMIP series, cost introduced here.

Sparse notes again because of the busy time, approved but today each person:

  1. Gave an overview of the data collection/analysis they did over the past two weeks
  2. Had someone else in the group write an “abstract” consisting of 3-6 points they saw throughout our reported data. After a time of trying to diverge and divest ourselves of as many filters as possible, allergy we are starting to converge and filter once again — but this time, much more consciously.
  3. Figured out what research paradigm they seemed to be working in (everyone is interpretivist for this project; I re-presented a version of the main paradigms for this discussion).
  4. Honed down on their unit of analysis and research question (by me giving examples and then everybody iterating on theirs with studio critique).

This is the last week before our Data Collection Cutoff. A constant part of our iterative focus is trying to make sure that our data and questions coevolve in such a way that the data can answer the questions. (I’m also thinking on how this dynamic scales up the next time I teach this as a course; I suspect more scaffolding and possibly even some readings will appear.)

We also looked at the classic paper “Body Ritual Among the Nacirema” as an example of… well, I’ll leave it to the reader to decide what one could use it as an example of — quite a few things, as it turns out. (It wasn’t assigned reading; we read parts of it aloud in studio, so my “no readings” rule stands unbroken.)

QualMIP week 7: close reading of data

Part of the QualMIP series, malady introduced here.

Sparse notes today, because we worked with data that’s non-public… and I have about 5 minutes to write this blog post before my next meeting.

Today we went through a close reading exercise; we took my data from a prior project and read it — out loud — in small increments, with discussion in-between. Each person in the group took a small sample of data from a different respondent, effectively “adopting” them for the duration of the conversation — with the disclaimer that we were working from a limited dataset from people we didn’t know, so our guesses were exactly that: guesses.

In between rounds of reading their words, we talked a bit about what “putting data in conversation” meant. It can mean many things; do you see commonalities between “your” data and “other people’s” data? How do you think “your person” (the person who wrote the response you’re reading out loud) would reply to notes/thoughts from or about the other data/observations? If you were going back to do a member-check, what would you want to ask — and how does that help you think about the fieldwork you are doing now, where you still (might) have that opportunity?

In all these responses, we kept on trying to go back to specific phrasings and sections of the data to back up our guesses, working to keep awareness of possible biases we might be bringing to the conversation.

Honestly, right now — it’s hard to sum up in a blog post writing “about” the practice… we’re in the middle of doing qualitative analysis/fieldwork, not talking about it. Over the next two weeks, we’ll be responding to each other’s data (and doing a fair amount of self-care). I’ll be modeling half-hour bounded response sprints for each person’s data on Thursday, because one of the hardest parts of the semester is learning just how much work goes into qualitative research… how tiny and bounded projects need to be to actually get done.