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We’ve been having talks in my department about what our wish list for classroom spaces might look like, and we’ve consistently been interested in a “design studio” type space that could be used for collaborative student work and some smaller, design-focused classes. This industrial design case-study of a “cafe classroom” has some cool features and also raises some questions about how this type of classroom would fit into a larger academic building.

The combination of seating, writing surfaces, and whiteboards with lots of different heights and configurations is appealing for letting students figure out what type of space they need for a particular type of work. I have to admit to being a bit confused about how the power is integrated into the furniture – is the furniture moveable or does it have to be fixed in place to be powered?

The bench-type “perching” seats are interesting. I could see them working well for groups collaborating at a whiteboard. Rather than having everyone stand, or having one person write while others are sitting away from the board at a lower level, I can see how this would encourage more eye-level conversation across a group. Participants might be more likely to get up and start writing on the board when they’re leaning rather than fully seated. Obviously not a replacement for proper, supportive seating, but a neat idea.

I do think that the case study text exaggerates what is being achieved at the start. I’m thinking about this statement in particular: “This new environment enabled by CoLab can be used for both formal learning and informal peer-to-peer collaboration, without the need to reconfigure the space. This leads to a greater efficiency in the use of space and the ability to activate redundant classrooms.”

In reality, I think they are more accurate later in the presentation where they say that this type of furniture will work well to construct other types learning spaces outside traditional classrooms. But I’m having a hard time seeing, in these pictures provided, how this type of space works with 16-25 students in it all at the same time, particularly if all of them are needing to use their laptops or attend to the same presentation. Perhaps I’m misunderstanding what they mean by a “formal learning” space.

I’d love to see a case study like this break down how many square feet you should plan on allocating per person using the room in order to really take advantage of the flexibility of the space. It would be very helpful in advocating for the right size and shapes of classrooms to allow for more innovative arrangements. (Obviously, from the photos, windows absolutely everywhere is also a must.) I’d also love to know how students use these spaces – does that feedback indicate anything about the right combination of different types of seating, preferred layouts, etc. Can this type of furniture work when trying to equip a space that will be used as a semester-long classroom for a course as well as an information working space for students?

A couple of articles have been bouncing around in my mind, both of which touch on issues I’m sure most educators are thinking about, but where I feel like the most interesting part of the conversation starts at the point the articles end.

The first article from Inside Higher Ed, New Data Shows Attendance Fosters Student Success, initially caught my attention because of the sheer obviousness of the statement and curiosity about what more there might be to say about this. If my class sessions don’t foster student success, what am I even doing! The article, of course, is more focused on the tension between how faculty encourage students to attend (knowing that it will help them be successful) and students’ desire for flexibility in their schedules and dislike of attendance factoring into their grades (as compared to just their ultimate ability to demonstrate what they have learned).

From the article: “A professor at Colorado State University surveyed 175 of his students in 2023 and found that 37 percent said they regularly did not attend class because of physical illness, mental health concerns, a lack of interest or engagement, or simply because it wasn’t a requirement.” I find that list interesting, because the first two items are very different from the second two items. Other quotes mention transportation issues and class conflicting with work schedules. This range of reasons that students do not attend creates challenges for faculty, particularly the evidence that (possibly particularly when compared to the many classes that do require attendance), a lack of a grade-linked attendance policy contributes to students deciding not to attend, when compared to their other interests and priorities.

I appreciate that the article wraps up by basically advocating for teaching in a manner that makes evident to students the value of being present. That’s certainly been my strategy and for a good number of students, it can be effective. But it can also take time for students to make that connection, and first-year students in particular (in my experience) can find themselves only realizing what they have missed by not being in class when they are in a very hard spot for catching up. Having an attendance grade makes it easy to intervene when a student is heading down that road. I’m working on finding ways to have those interventions (e.g. email messages to students who aren’t keeping up with the activities that are supposed to be happening in class) but there always seem to be students who do the math and decide that formative work that’s only worth 5-10% of the overall grade is optional as compared to other priorities. It’s a conversation I keep coming back to with colleagues – I don’t judge students for having to balance priorities, but how do we help students have a more accurate sense of the cost-benefit tradeoff of attending class?

The other article, Meet Students Where They Are? Maybe Not, from the Chronicle of Higher Education, follows the title with “Lax standards will void the value of a college education.” A telling sentence: “If the college degree continues to lose its traditional function of signaling competency and grit, the outlook will be grim for a higher-ed system largely financed by student debt.”

The inclusion of “grit” in addition to competency is interesting there. In some ways, I agree – can you manage your time and priorities to be able to learn, are you willing to make use of the help available to you in order to succeed, etc. But if my competency assessments are the same, what is the merit in (per the previous article) assigning a specific point deduction to an absence if the student can demonstrate they’ve made up for the missed learning activities on their own time? Doesn’t the student juggling a 30-40 hour a week off-campus job as well as a full time course load show at least as much grit as the classmate with a 10-hour a week work student position or no job at all – even if I show some leniency around attendance?

The article states that “a third of professors in our survey admit to watering down their courses in recent years; we suspect that many more will have to dilute their syllabi in the future”. Perhaps that is accurate, in the way that the  sentence asks to be read, and that would be unfortunate. But I’ve also had a lot of productive conversations with faculty at many institutions (not just my own) about the balance between number of topics covered versus perhaps cutting back on some content in order to engage more deeply in the topics we do cover. Some of my best class sessions have been when I realized that my students were trying to understand a hard concept and, rather than pressing on with the next topic, I gave them space to really apply their critical thinking skills and work together to make sure everyone in the class reached a solid level of understanding – even if it meant looking at the class plans for the rest of the week and figuring out what to prune. Are we watering things down, or are we identifying that facts-conveyed may not be the best way to measure the learning value of a course? I’m also not sure that a syllabus level assessment is the best way to look at this, compared to a curriculum level assessment. If students are coming in with different preparation, why wouldn’t we change how our introductory courses operate? If, in turn, the structure of the curriculum can shift as students move through it, and we can still graduate students who depart with the needed competencies – rather than dropping or failing out – it seems like a bit of early “watering down” was all for the good.

I understand that this looks different at different institutions, and I do think the article has a good point that many institutions’ weak methods for assessing the quality of instruction incentivize making students happy (particularly for untenured faculty), so we should find better methods for instructional assessment. But, reading these two articles together in close succession, I think it is an overreaction to suggest that we should stop considering who are students are as they enter the college and the classroom and think about how we can continue to adjust our instruction to meet that reality.

Just the title of this long blog entry caught my eye, because YES!!! The Homework is the Cheat Code indeed!

The content didn’t disappoint. Written by someone teaching CS at the graduate level at U Chicago, I’m not sure if I’m shocked or relieved that they’re seeing similar patterns in their students as we’re seeing at the undergrad level. Maybe the most honest reaction is that if we want to graduate students who are job- and grad school-ready, addressing these tendencies has to be central to undergraduate education (bold mine):

I get a lot more requests now for extensions on the project they’ve known about all quarter (students reading this: lovingly, no ). I get a lot lower compliance on instructions I wrote down twice and then also said twice in class. I get a lot more homework reflection assignments that package considerable insight—they’re still very smart people, after all—into the syntax I’d expect in a group text among friends rather than prose submitted to a graduate school instructor.

I like the observation that overcommitment, or burnout from years of overcommitment is part of the problem. I definitely see students think that the best value will come from packing as much as possible into their college experience and we’ve started having conversations at my institution about how we encourage students to make choices so they can more deeply benefit from the smaller set of things they are doing.

This, inevitably, gets linked to the issue of students using generative AI for assignments in a way that is not productive for their learning. This particular instructor doesn’t forbid the use of AI. Beyond other good reasons, they point out that we just don’t have data on the impact of these tools on learning yet and allowing some usage lets them collect data on how students are choosing to use AI. They’re coming at it from the perspective of someone who studies how LLM tools affect the development process, so that is interesting.

I love how they break down the academic honesty issue of using generative AI by first defining the issue: “I define “cheating” as something a student does, usually in the interest of time, whose tradeoff is the circumventing of the assignment’s learning objective.” and then walking through reasons students might not invest the needed time or might circumvent learning objectives. The time element certainly circles back to being overcommitted – I think it also connects to a lack of understanding of what time it really takes to be a full time student.

For both the time and learning objectives elements, I think trust in the instructor (and possibly in the institution?) play a large role. Is the student willing to trust that the structure of the course and the assigned work have been thoughtfully designed and will support their learning? How do you build that trust? And, the following paragraph got me to thinking, how do you push past students’ focus on efficiency of learning over effectiveness of learning:

We’re steeped in a tech industry laser-focused on efficiency as a positive quality, but this term often becomes overloaded when we’re talking about capacity-building. I’ve lifted weights for about a decade now. The exercises that build my capacity the most are not the efficient ones. Walking is efficient—humans can walk a very long way without spending a lot of energy. Kettlebell swings are inefficient; they require an enormous amount of energy and muscle activation relative to walking. That’s why weightlifters do them: they produce capacity-building adaptations faster because of that. Learning works the same. The activities that promote learning are, by design, inefficient: they require an enormous amount of attention and active engagement, usually on a thing that the learner feels bad at. They deliberately present the learner with challenge, and sometimes frustration, because those uncomfortable states build cognitive capacity. Avoid this, and you avoid building cognitive capacity. That’s a weird choice to make in a class with the specific value proposition of teaching something.

This leads to the heart of how they connect this back to the use of generative AI in learning, which they break down into whether it is being used as an “outcome accelerant” (thus shortchanging the learning process by just getting to the product faster) or a “learning aid” (where the tool streamlines the time taken to really focus on the activity related to the learning objective).

The article includes tons of examples of syllabus language, assignment information, etc. about how all of this works in practice, including how they set up assignments where the “cheat code” is that doing the work as assigned is more efficient than trying to get gen AI to do the work for you (they like the tool of “instructive visualizations”). This may or may not relate to your particular classroom. But I think there’s good potential for this outcome accelerant versus learning aid contrast to apply across a lot of classroom settings.