"We must avoid, at all costs, having students rely on us for their learning."
Throughout the last 7.5 years of trying to figure out the most effective, and the most delightful, Learning Experience (LX) that will prepare someone to be a valuable, productive teammate immediately upon being hired as a software developer, we have learned a few things.
Sometimes we improved the LX by intently experimenting and methodically refining the results. Sometimes we stumbled into the Perimeter of Wisdom by pure luck and instinct.
The most recent version of the LX is a tremendous leap forward, but before you read about it, here's a quick overview of our evolution over the last 7.5 years. There were many small experiments along the way, but this is the highlight reel of the changes that had a significant, positive impact on the student's experience and learning during their time with us.
"By the end of 2021, the stage was set for a massive new experiment that would either define the future of the experience or end in colossal failure."
2015: Lecture for initial instruction followed by lab time to work on exercises
2016: Group projects for collaborative problem solving
2018: Group projects with starter code to be fixed and augmented
2019: Project-based learning
2020: Faded worked examples
2021: Peer learning and flipped classroom
The Adaptive Experiment of 2022
Since I first started coaching cohorts of people in 2015, I had a burning desire to make the process more individualized. I was stymied at every attempt because the program is accelerated. Time is, by far, our biggest constraint.
It is much easier, without any alternative strategy, to expect every student in the cohort to follow a fairly rigid schedule that is dictated by the course and the instruction team. Within two cohorts, I clearly saw the downside to this. People come into the program with wide variations in their ability to think analytically and algorithmically.
By the time we got to the first group project, which every student started on the same day, there were always a handful of students that simply had not had enough time for the neural rewiring needed to learn anything from it or contribute to the team. It was a frustrating experience for the unprepared students, the rest of the team, and the instructors because we had no alternative at that point other than to leave certain students out of the group project.
By the end of 2021, with the successful implementation of peer learning and a flipped LX, the stage was set for a massive new experiment that would either improve everything about the experience or end in colossal failure. It was a calculated risk that I was prepared to take.
Years ago, I read a book called "Synergogy: A New Strategy for Education, Training, and Development" that proposed that learning could be accelerated and deepened when it is done in teams. It is very similar to peer learning but encourages a more strategic approach to building teams. The book was written, understandably, with a focus on the traditional educational model and corporate learning, but it planted a seed in my head as a possible approach to an accelerated professional training program.
In 2022, I decided to implement my own system, inspired by Synergogy but adapted to a highly accelerated learning timeline.
"I was constantly stunned by the trust, vulnerability, and collaboration I saw in the teams."
Further details will be provided later, so here is a summary of what the new LX entails.
- All lecturing eliminated.
- Cohort divided into weekly teams driven by learning levels and goals. Each coach is assigned to n teams, which changes based on the size of the cohort.
- At the beginning of the Sprint, teammates identify their learning goal for the week. Coaches then design a project to be built in collaborative problem solving (CPS) sessions.
- Daily status report given by each teammate and recorded by their coach.
- Daily CPS sessions, with a coach there for support, each day of the Sprint.
- After the CPS session, teammates work on core course projects with peers.
- Team runs their retrospective at end of Sprint. The coach does not attend.
- Deep learning group projects, which supplement the course projects, are started only when students achieve the requisite learning objectives.
The first experiment ran with our 54th full-time web development cohort. In a nutshell, it was a runaway success. It also destroyed every instinct about student development that I had built up over 7 years. I was constantly stunned by the trust, vulnerability, and collaboration I saw in the teams in the first few weeks.
Adaptive Weekly Teams
After initial installations and orientation are complete, we immediately break the cohort down into teams of 4 or 5 people. That number was chosen because, for years, we had observed that teams of that size had a wonderful balance between productivity and psychological safety when working on a group project.
As each student starts and then achieves each learning goal, that progress is recorded by the coaching team. During each Sprint, members of a team can, and often do, diverge by the end of the Sprint depending on two factors:
- Level of analytical/algorithmic thinking
- Learning efficiency
Therefore, after the end of the Sprint, the teams are changed to ensure that the next Sprint starts with all of the teammates at, roughly, the same learning level. This ensures that collaboration is highly effective.
The most powerful outcome that we saw with this approach was seeing psychological safety, which is the most important key factor for effective and productive teams, skyrocket when compared with previous cohort structures. By the end of the 2nd week on a team, teammates regularly shared how much they enjoyed the approach, publicly shared their anxieties and fears, and celebrated their teammates.
We normally did not see that level of psychological safety until weeks 10-14.
Reflection and Learning Efficiency
On the first day of the Sprint, we have each teammate review the official list of technical learning objectives for the course. We ask that each student identify which of those objectives is their top priority for that week. We don't tell them, they tell us.
Each person is expected to have ownership over their learning, and strengthen their ability to reflect on their learning and objectively report their progress. This also happens when they review their self-assessments during the course. The first question they must answer is, "What is your assessment of your progress on the concepts covered in this project?" This is a crucial skill in order to be prepared for a career in software development.
The field evolves rapidly, and our job is to ensure that our students are prepared to identify what they need to learn and have the skills to be highly efficient at learning those things.
There are no teachers, instructors, or professional coaches on the job. We must avoid, at all costs, having students rely on us for their learning. Thus, our first, and most important job when the cohort starts is to coach them to be efficient learners.
Collaborative Problem Solving
"Cognitive science has shown that our working memory can get overloaded in as little as 20 minutes."
After we record each teammate's learning goal for the week, we collaborate to decide what kind of project we can build with them during the Sprint. There are plenty of projects in the course for the students to build, but they are targeted at one, or two, specific concepts.
That is why we design a custom project for each team that allows everyone to get practice on what they have identified as their goal. The project is built collaboratively using CodeSandbox so that every teammate can analyze, plan, discuss, and code the project in real-time with near zero friction. No need to swap out who is sharing their screen or watch someone fumble around with their code editor and browser.
We limit these CPS sessions to approximately 45 minutes every morning after status reports. On rare occasions, they can go longer if the team feels they have enough cognitive energy remaining, but I never encourage it. Cognitive science has shown that our working memory can get overloaded in as little as 20 minutes. Add to that the high instrinsic cognitive load of learning software, and you push people to the limit quickly.
The coach is present for these CPS sessions, which serves two main purposes.
- Prevent the team from making critical errors in their algorithm that would inhibit learning the concepts. Yes, we learn through mistakes and failing, but our time constraint for these sessions means that major mistakes in design would detract from more valuable activities.
- Deepen learning by providing context, discussing strategies, and asking deep learning questions.
Real Time Data
Now that the coaching team is getting daily interactions with every student, we can effectively assess students on their Core skills and technical skills as often as we want. This has been a boon for the coaching team because we no longer need to be concerned with writing formal assessments at the end of the course. By the time the student is ready to build their capstone project, we know the exact capabilities of the student.
This allows us to have honest and open conversations with students that we feel would benefit from getting more time. The student knows exactly where the learning gaps are, as does the coach. There are no surprises. At that point, it comes down to letting the person decide if they can afford to spend more time by moving to a new cohort or keep going and become a more efficient learner.
Also in 2022, my teammate, Dr. Teresa Vasquez - who I look to for many inspirations - shared the results of an experiment she ran with her evening cohort with the whole team. She presented several topics of research to her students, with no initial instruction at all, and asked them to research the Web to discover what they could about the topic.
The topics were curated by the instruction team to be concepts that were immediately useful to the students at that point in their learning journey.
After being given some time to research with their peers, and record what they found, each team presented their findings, and an open discussion happened with all students and coaches. What she discovered is that students were able to learn a tremendous amount in a short amount of time that, traditionally, was done in a lecture format. Thus, students still got the initial instruction on the topic, but they were in control, just like they will be as professionals.