Terms defined: Conway's Law, alpha geek, big-bang integration, chaotic decomposition, confirmation loop, feature creep, feature decomposition, functional decomposition, modular decomposition, rotating decomposition, sociotechnical congruence, team contract, to-don't list
Most people learn better together than they do on their own Michaelson2004. As long as their teams work well, they achieve higher grades, retain information longer, are less likely to drop out of school, and graduate with better communication skills and a better understanding of what will be expected of them in their subsequent careers.
But that "as long as" is important. A badly-run team is worse than no team at all, since people will waste hours or days arguing with one another, duplicating or undoing each other's work, and wishing that they had gone into gardening instead. These conflicts are more wearying than any number of buffer overruns or accidentally erased files, which is why most computer science courses stick to individual assignments.
It doesn't take much to make a team work smoothly, though. The rules in for running meetings, making decisions, and resolving conflicts are a good start; this chapter will look at what else you can do.
I once heard an anthropologist ask, "How big is a sports team?" When people said it depends on the sport, she explained that in fact they all have about half a dozen members. Anything larger than that splits into smaller groups: the forwards and backs in rugby, the infield and outfield in baseball, and so on. She went on to explain that hunting parties in non-agricultural societies are usually that size as well, as are basic military units around the world (a platoon is two squads of six people). Since we can only keep a handful of things in our short-term memory at once () that's as big as a team can practically be.
The same observation applies to software development. Three or four people can work tightly on a single piece of code, but when there are more they define some interfaces and develop in parallel. Collaborative tools like software portals () help groups coordinate more effectively, but the groups themselves stay the same size.
Teams of three to five provide a good balance between skills and accountability. A team of two may not have enough breadth and background to tackle a large piece of work; more importantly, one or the other person is likely to take a dominant role. If you put six or eight people in a team, on the other hand, you may not be able to divide up the work in a way that will keep everyone engaged and busy. Teams that size or larger also increase the odds that at least one member will be a hitchhiker, and make scheduling meetings much more difficult.
Many students prefer to select their teammates, and students with high grades tend to want teammates with a similar profile. Post2020 found that matching students by grade led to a small improvement in outcomes, with a larger impact on team grades than on individual ones. The same study found that members of self-selected teams were more likely to already have friends on their team, but that this was negatively correlated with outcomes (possibly because people are less willing to hold friends accountable for missed work).
One surprising finding is that having students with a range of grades in the same team either has no effect or improves outcomes for everyone Mosher2013,Donovan2018,Farland2019,Auvinen2020. It's easy to see how this benefits teams of weak students: they are likely to get coaching from their stronger teammates. One theory for why it also helps stronger students is that the best way to learn something is to explain it to someone else; bringing a weaker teammate up to speed will usually do more for your grade than spending those same hours hacking or reading.
In my experience, teams of strong students are also more likely to use a divide and conquer strategy, effectively reducing the project to a set of parallel sub-projects handled by one person each. This may feel more efficient, but most of the benefits of working in a team are lost: there's less back-and-forth discussion of design issues, and little improvement in communication skills. Those may not be important to you at first, but if there is a final exam in your course with questions about the project work, your mark on it may depend on how much you know about your teammates' work ().
The most powerful argument for instructors selecting teams, though, is that's how it works in the real world Oakley2004. You probably won't get to pick your colleagues if you join a company or an academic research group. Instead, you'll be put on a project and expected to work well with whoever else is on it. Your performance will depend as much on your ability to get along with others as it will on your raw technical ability, so you might as well start practicing those skills now.
If instructors create teams, they should avoid isolating at-risk students. Women and members of racial minority groups are more likely to drop out of computer science than other students, particularly in first and second year, and one of the main reasons is feeling isolated or out of place. Research has shown that putting at-risk students together in the first couple of years can mitigate this problem Margolis2002. It is less necessary in upper years, since by then students have a stronger commitment to whatever program they're in, but it still helps to prevent some of the problems discussed in the next section.
The biggest headache when instructors select teams is scheduling. COVID-19 has made distributed work more normal, but the last university I taught at had three campuses spread across a large metropolitan area, and some students commuted an hour and a half each way to get to classes. Instructors should therefore take students' schedules into account when forming teams. If the class is small, the simplest way is to get each student to fill in a weekly timesheet showing when they're available, and then group people who have large blocks of overlap. If the class is larger, a web-based calendaring tool may be easier. Instructors can even try to use whatever software the university uses to figure out course timetables, although that usually doesn't scale down to in-class scheduling.
Another factor to take into account is that some people are naturally early birds, while others are night owls. Putting the two on the same team pretty much guarantees that someone will miss meetings, or sleep through them, no matter when they're held. Simply asking people, "Do you prefer to work in the morning, or the evening?" can be surprisingly effective.
However you form teams, each team should have at least one block of two hours to work together each week outside of class. Teams should also try to find a second block that's half an hour long for a weekly meeting. Try to keep the two blocks separate so that it's clear to everyone when they're supposed to be talking about the project and when they're supposed to be doing design, writing code, testing, and so on. If the two are scheduled back-to-back, the meeting will drag on into working time or vice versa.
Who Does What
All right, you've formed a team: now what? How do you decide who does what? How do you make sure that everyone actually does what they're supposed to? And most importantly, how do you do this fairly?
Some jobs have higher social status than others, and what is or isn't considered important usually reflects racial and gender divides within society—so much so that sociologists use the phrase "women's work" to describe the phenomenon. It is also known as "quarterback syndrome": two thirds of NFL players overall in the United States are Black, but only 17% of quarterbacks, which is the position on a team with the highest social status.
Among programmers, writing operating systems or other software that is close to the hardware has higher status than building user interfaces; people doing the former are both paid more and more likely to be male than people doing the latter, regardless of ability or value delivered to the employer. This creates a feedback loop: white and Asian men pursue certain career paths because they have high status (they want to be "real programmers"), and the fact that they are pursuing those careers is what maintains their higher status. It also creates a confirmation loop: since women and people of color get fewer chances to do certain tasks, they are less good at them, which "confirms" the initial bias.
All of this starts in the classroom. In mixed-gender teams, for example, female students are more likely to be given responsibility for taking notes, writing documentation, and other low-status tasks. Some have experienced this so often that they have come to accept it as the price they have to pay for being in tech. Others protest, but those who do are often dismissed as being "difficult" (). Many take a third path and decide to leave programming—after all, why play a game that's unfair?
In the beginning
Programming was originally considered a female occupation, but as it became more lucrative it came to be viewed as "naturally" male. Abbate2012 and Ensmenger2012 describe how this happened, while Hicks2018 looks at how Britain lost its early dominance in computing by systematically discriminating against its most qualified workers: women. Some men become quite uncomfortable whenever this is brought up, but we need to learn how to discuss our own history if we want to be able to think clearly about how the things we're doing today might change society tomorrow.
Division of Labor
There are many ways to divide project work between team members, and as Conway1968 observed, the software you get will reflect the division of labor, a phenomenon known as Conway's Law or socio-technical congruence Cataldo2008. In a modular decomposition, each person is responsible for one part of the program. For example, one person might design and build the GUI, while another writes the database interface, and a third implements the business rules. Having people own parts of the code like this produces lower failure rates in industry Bird2011, but is generally a bad strategy in a course project:
It increases the risk of people from marginalized groups being assigned lower-status work.
It leads to big bang integration, in which all the components meet each other for the first time right at the end of the project. Big bang almost always fails.
Each team member only really understands one aspect of the project. This can hurt a lot if there's a final exam that checks for overall understanding.
If someone drops out or fails to complete their module, the project as a whole will fail.
Functional decomposition, in which each person is responsible for one type of task, is usually more successful. With this strategy, one person does the testing, another handles the documentation, a third does the bulk of the coding, and the fourth takes care of build and deployment. This guarantees that everyone understands most of the project by the end of the term. The obvious drawback is that each person only gets to hone one set of skills.
Another drawback stems from the fact mentioned above that some activities are viewed as being more prestigious than others. If the team decomposes work functionally, the self-appointed alpha geeks will usually snag the plum jobs like architecture and coding, leaving less appealing work to people who aren't as pushy, privileged, or self-confident. This tends to reinforce existing inequities; it also tends to lower the team's overall grade, since there's often little relationship between how outspoken people are and how well they work.
The Dunning-Kruger effect
Kruger1999 reported that people who know a subject well can usually estimate their knowledge accurately, but people who don't will often overestimate their competence because they don't know what they don't know. More recent work has cast doubt on this finding: it could simply be an artifact of the way the original researchers did their statistics Jarry2020. Either way, you should never trust self-reported expertise, as there's no easy way to tell if someone really knows what they're talking about or if what they're actually reporting is their self-esteem.
Feature decomposition is a variation on modular decomposition that works well in practice. Instead of owning an entire subsystem for the life of the project, each team member handles the design, coding, testing, and documentation for one small feature after another. Working this way is central to agile development ()) and is a good way to cope with the never-ending timeslicing of student life.
Finally, there is rotating decomposition: everyone does one task for a few weeks, then a different task for the new few, and so on. This is initially less productive in absolute terms than either of the preceding strategies, since the team has to pay for ramp-up several times over. In the long term, though, it outperforms the alternatives: it is more robust (having a team member drop out is less harmful), and if everyone on the team is familiar with every aspect of the software, they can all contribute to design and debugging sessions.
Any of these strategies is better than chaotic decomposition, which unfortunately is the most common approach. If people have different ideas about who's supposed to do what, some things won't be done at all while others will be done several times over. (You can tell if your decomposition is chaotic by counting how many times people says, "I thought you were doing that!" or "But I've already done that!" The more often you hear this, the more trouble you're in.) All other decompositions tend toward chaos under pressure, so it's important to establish rules early and stick to them when the going is easy so that the instinct to do the right thing will be there when you need it.
No matter how you allocate work, make sure that everyone understands who is doing what, when. As Barke2019 found, actual roles can be fluid; what matters most is that team members understand and accept their responsibilities and everyone else's at any particular moment.
No matter what decomposition you use, your team should write, sign, and submit a team contract outlining what everyone has agreed to do to make the project a success. In my experience, this is most effective if each team creates their own as part of their first assignment so that they actually have to think about what they're promising their teammates. Here's an example:
We, the members of Team 12, agree that:
Work on each assignment will divided according to role. Two people will code, one will test, and one will be responsible for documentation. One of the coders will run the weekly meeting; the other will take minutes and post them to the project wiki on the same day as the meeting. These roles will rotate for each assignment; no one will code two assignments in a row.
The tester will be responsible for submitting the assignment. A team member will only be listed as contributing to that assignment if at least two other members of the team agree they completed, or made significant progress on, at least one work item.
We will aim to get at least 80% on each assignment.
We will hold a half-hour status meeting every week on Thursdays at 4:00 pm. Everyone will be in the meeting by 4:05 pm; if someone cannot attend, they will let the rest of the team know by email no later than 2:00 pm that day.
Everyone will add a brief point-form summary of their progress that week to the project wiki no later than 12:00 noon on Thursday. Everyone will read everyone else's summary before the 4:00 meeting.
All discussion about the project will take place on the team's Slack channel so that everyone can see it and search through it later.
No one will check code into version control that fails to compile. No one will check in code that fails to pass existing tests without first getting the permission of that round's tester. No one will change the database schema or add dependencies on new libraries without first getting permission from the whole team.
It may sound a little silly, like the contracts that some parents and children make up regarding chores and allowances, but it's very effective. First, people may have very different ideas about what being in a team means: some may be happy with a bare pass, while others may want the team to shoot for an A+ on everything. Knowing who wants what won't make these tensions go away, but it helps focus the argument.
Drawing up a contract also prevents later disagreements about who actually promised or agreed to what. As with meetings, people often remember things differently; having a signed record is everyone's second-best defense.
Who's it for?
I still don't know if teams should have to give copies of their contracts to their instructors or not. On the one hand, it's a great way to let your instructor know how you're planning to operate, and what you're planning to achieve. Given that she probably has a lot more experience than you, it gives her a chance to tell you if you've forgotten anything or that your teammate's really cool idea is unlikely to work in practice. On the other hand, as soon as something has to be handed in, some students will write what they think the instructor wants to read, rather than what they actually think.
Most software development teams in industry and open source don't bother with contracts like these. There may be corporate guidelines on good citizenship, or performance metrics written into job descriptions, but in general people expect that if you're doing this for a living, you know what others can reasonably expect of you, and you will live up to those expectations.
If your instructor has you draw up a team contract at the start of the project, then she can and should base part of your team's grade on how well you stuck to it. If she handed you a team contract, she should definitely base part of the grade on compliance. If there was no contract at all, though, it's unfair to turn around at the end of the project and ask people to rate one another, since they won't have known while they were working what they were going to be rated on.
Asking people on a team to rate their peers is a common practice in industry. Instructors sometimes shy away from it because they're afraid students will gives everyone in the team a high rating in order to boost grades. However, this actually occurs fairly infrequently Kaufman2000.
What's more, as long as evaluation is based on observables, rather than personality traits, peer assessment can actually be as accurate as assessment by the instructors and other outsiders. "Observables" means that instead of asking if the person is outgoing or if they have a positive attitude, assessments should ask if they listen attentively during meeting or attempt to solve problems before asking for help. The performance review guidelines in are a useful starting point.
Problems and Solutions
When I first put these notes together fifteen years ago, I wrote a section titled "People to Watch Out For" that described a dozen people who make teams less productive in different ways. As several reviewers have pointed out since, it was arrogant and harmful: arrogant because what I was really saying was, "If you don't work the way I do then you're wrong," and harmful because it would make people who already doubt themselves do so even more.
If you read one of those earlier versions, I apologize. What I've tried to do below is describe ways in which I've seen people undermine themselves. If you go through this list with your teammates and tell them what you'd like to get better at, they'll probably help you. And if what you want to get better at isn't on this list, please see .
- Not everything needs to be completely correct.
- Before correcting a factual error, ask yourself whether it really matters. If it's the name of the configuration file the program reads on startup, the answer is probably yes; if it's the name of a minor villain from the Marvel Cinematic Universe, the answer is probably no.
- The devil doesn't need more advocates.
- We remember when contrarians turn out to be right because it happens so infrequently, but because those moments are memorable, some people fall into the habit of taking the opposite point of view no matter what is being discussed.
- You wouldn't have gotten this far if you weren't good at this.
- Some people have so little confidence in their ability despite their good grades that they won't make any decision, no matter how small, until they have checked with someone else. This is often a result of social conditioning: in particular, women are more likely to doubt themselves, while men often over-estimate their ability.
- Not everything worth doing should be done.
- For many years my favorite phrase was, "Why don't we?" Why don't we write a GUI to help people edit the program's configuration files? Hey, why don't we invent our own little language for designing GUIs? This energy and enthusiasm are hard to argue with, but argue you must. Otherwise, for every step you move forward, the project's goalposts will recede by two. This is called feature creep, and has ruined many projects that might otherwise have delivered something small but useful. My solution these days is to keep a to-don't list of things that would be fun and worthwhile, but that I'm not going to tackle.
- Success is a habit.
- The more you follow a routine, the more your brain will be able to focus on the right things at the right time. Gawande2011 found that checklists improve results even for experts, and talked about the value of to-do lists for managing your time. Making these a habit reduce cognitive load () and gives you more mental capacity for dealing with the work itself.
- Acting like an asshole doesn't make you cool—it just makes you an asshole.
- I had a teammate once whose favorite phrase was, "That's stupid." If anyone complained, he said, "It's just the way I talk." The problem with people using vulgar or aggressive language in everyday conversation is that for many other people, that language has often been followed by bullying or discrimination. They're right not to trust you if those are the signals you choose to send. (And no, calling someone out for being vulgar or aggressive is not the same as tone policing.)
- Sometimes it's hard to care.
- You have a teammate who doesn't read the assignment specs, hasn't bothered to learn the tools and libraries you're supposed to be using, and commits code that doesn't even compile. Before treating them like a hitchhiker, try to find out if there's a reason for their behavior: if he's caring for a family member or struggling with mental health issues, the most compassionate thing to do is to help them get back on their feet.