This material is in early beta: over 300 suggestions and corrections are waiting to be folded in, some quite significant. Changes should be in place by July 2018, at which times printed copies and downloadable electronic copies will be made available.


After reading this chapter, you will be able to

  • Explain why teachers in schools and universities do and don’t adopt better teaching practices.
  • Summarize methods that can be used to effect changes in educational institutions.

Section 13.1 said that the first step in building a community is to decide if you really need to, or whether you would be more effective joining an existing organization. Either way, the organization you’re part of will eventually need to work with other, more established groups: schools, community programs, churches, the courts, and companies. This chapter presents a handful of strategies for figuring out how to do that, and when it’s worthwhile.

Unlike most of the rest of this book, this chapter is drawn more from things I have seen than from things I have done. Most of my attempts to get large institutions to change have been unproductive (which is part of why I left a university position to re-start Software Carpentry in 2010). While contributions to any part of this book are welcome, I would be particularly grateful to hear what you have to say about the issues discussed below.

Working With Schools

Everyone is afraid of the unknown and of embarrassing themselves. As a result, most people would rather fail than change. For example, Lauren Herckis looked at why university faculty don’t adopt better teaching methods. She found that the main reason is a fear of looking stupid in front of their students; secondary reasons were concern that the inevitable bumps in changing teaching methods would affect course evaluations, and a desire to continue emulating the lecturers who had inspired them. It’s pointless to argue about whether these issues are “real” or not: faculty believe they are, so any plan to work with faculty needs to address them.

[Bark2015] did a two-part study of how computer science educators adopt new teaching practices as individuals, organizationally, and in society as a whole. They asked and answered three key questions:

  1. How do faculty hear about new teaching practices? They intentionally seek them out because they’re motivated to solve a problem (particularly student engagement), are made aware through deliberate initiatives by their institutions, pick them up from colleagues, or get them from expected and unexpected interactions at conferences (either teaching-related or technical).
  2. Why do they try them out? Sometimes because of institutional incentives (e.g., they innovate to improve their changes of promotion), but there is often tension at research institutions where rhetoric about the importance of teaching is largely disbelieved. Another important reason is their own cost/benefit analysis: will the innovation save them time? A third is that they are inspired role models (again, this largely affects innovations aimed to improve engagement and motivation rather than learning outcomes), and a fourth is trusted sources, e.g., people they meet at conferences who are in the same situation that they are and reported successful adoption.

    But faculty had concerns, and those concerns were often not addressed by people advocating changes. The first was Glass’s Law: any new tool or practice initially slows you down. Another is that the physical layout of classrooms makes many new practices hard: discussion groups just don’t work in theater-style seating. But the most telling result was this: “Despite being researchers themselves, the CS faculty we spoke to for the most part did not believe that results from educational studies were credible reasons to try out teaching practices.” This is consistent with other findings: even people whose entire careers are devoted to research will disregard education research.

  3. Why do they keep using them? As [Bark2015] says, “Student feedback is critical,” and is often the strongest reason to continue using a practice, even though we know that students’ self-reports don’t correlate strongly with learning outcomes. (Note that student attendance in lectures is seen as an indicator of engagement.) Another reason to retaining a practice is institutional requirements, although if this is the motivation, people will often drop the practice and regress to whatever they were doing before when the explicit incentive or monitoring is removed.

The good news is, you can tackle these problems systematically. [Baue2015] looked at adoption of new medical techniques within the US Veterans Administration. They found that evidence-based practices in medicine take an average of 17 years to be incorporated into routine general practice, and that only about half of such practices are ever widely adopted. This depressing finding and others like it spurred the growth of implementation science, which is the scientific study of ways to get people to actually adopt better evidence-based practices.

As Chapter 13 said, the starting point is to find out what the people you’re trying to help believe they need. For example, [Yada2016] summarizes feedback from K-12 teachers on the preparation and support they want; while it may not all be applicable to your setting, having a cup of tea with a few people and listening before you speak can make a world of difference.

Once you know what people need, the next step is to make changes incrementally, within institutions’ own frameworks. [Nara2018] describes an intensive three-year bachelor’s program based on tight-knit cohorts and administrative support that tripled graduation rates. Elsewhere, [Hu2017] describes impact of introducing a six-month certification program for existing high school teachers who want to teach computing (as opposed to the older two-year/five-course program). The number of computing teachers had been stable from 2007 to 2013, but quadrupled after introduction of the new certification program, without diluting quality: new-to-computing teachers seemed to be as effective as teachers with more computing training at teaching the introductory Exploring Computer Science course. The authors report, “How much CS content students self-reported learning in ECS appears to be based on how much they believed they knew before taking ECS, and appears to have no correlation to their teacher’s CS background.”

More broadly, [Borr2014] categorizes ways to make change happen in higher education. The categories are defined by whether the change is individual or to the system as a whole, and whether it is prescribed (top-down) or emergent (bottom-up). The person trying to make the changes—and make them stick—has a different role in each situation, and should pursue different strategies accordingly:

Individuals/ I. Disseminating: Curriculum & Pedagogy
 Prescribed Change Agent Role: tell/teach individuals about new teaching conceptions and/or practices and encourage their use.
  Methods: Diffusion, Implementation.
Individuals/ II. Developing: Reflective Teachers
 Emergent Change Agent Role: Encourage/support individuals to develop new teaching conceptions and/or practices.
  Methods: Scholarly Teaching, Faculty Learning Communities.
System/ III. Enacting: Policy
 Prescribed Change Agent Role: Enact new environment features that require/encourage new teaching conceptions and/or practices.
  Methods: Quality Assurance, Organizational Development.
System/ IV. Developing: Shared Vision
 Emergent Change Agent Role: Empower/support stakeholders to collectively develop new environmental features that encourage new teaching conceptions and/or practices.
  Methods: Learning Organizations, Complexity Leadership

The paper goes on to explain each of the methods in detail (and [Hend2015a,Hend2015b] present the same ideas in more actionable form). Coming in from outside, you will probably fall into the Individual/Emergent category to start with, since you will be approaching teachers one by one and trying to make change happen bottom-up. If this is the case, the strategies Borrego and Henderson recommend center around having teachers reflect on their teaching individually or in groups. Since they may know more about teaching than you do, this often comes down to doing live coding sessions with them so that they know how to program themselves, and to demonstrate whatever curriculum you may already have.

Working Outside Schools

Schools and universities aren’t the only places people go to learn programming; over the past few years, a growing number have turned to intensive bootcamp programs. These are typically one to six months long, run by private firms for profit, and target people who are retraining to get into tech. Some are very high quality, but others exist primarily to separate people (often from low-income backgrounds) from their money [McMi2017].

[Thay2017] interviewed 26 alumni of such bootcamps that provide a second chance for those who missed computing education opportunities earlier (though the authors phrasing this as “missed earlier opportunities” makes some pretty big assumptions when it comes to people from underrepresented groups). Bootcamp students face great personal costs and risks: significant time, money, and effort spent before, during, and after bootcamps, and career change could take students a year or more. Several interviewees felt that their certificates were looked down on by employers; as some said, getting a job means passing an interview, but interviewers often won’t share their reasons for rejection, so it’s hard to know what to fix or what else to learn. Many resorted to internships (paid or otherwise) and spent a lot of time building their portfolios and networking. The three informal barriers they most clearly identified were knowledge (or rather, jargon), impostor syndrome, and a sense of not fitting in.

[Burk2018] dug into this a bit deeper by comparing the skills and credentials that tech industry recruiters are looking for to those provided by 4-year degrees and bootcamps. They interviewed 15 hiring managers from firms of various sizes and ran some focus groups, and found that recruiters uniformly emphasized soft skills (especially teamwork, communication, and the ability to continue learning). Many companies required a 4-year degree (though not necessarily in computer science), but many also praised bootcamp graduates for being older or more mature and having more up-to-date knowledge.

If you are approaching one of these groups, your best strategy could well be to emphasize what you know about teaching rather than what you know about tech, since many of their founders and staff have programming backgrounds but little or no training in education. The first few chapters of this book have played well with this audience in the past, and [Lang2016] describes evidence-based teaching practices that can be put in place with minimal effort and at low cost. These may not have the most impact, but scoring a few early wins helps build support for larger and riskier efforts.

Final Thoughts

It is impossible to change large institutions on your own: you need allies, and to to get allies, you need tactics. The most useful guide I have found is [Mann2015], which catalogs more than four dozens methods you can use, and organizes them according to whether they’re best deployed early on, later, throughout the change cycle, or when you encounter resistance. A handful of their patterns include:

Small Successes:

To avoid becoming overwhelmed by the challenges and all the things you have to do when you’re involved in an organizational change effort, celebrate even small successes.

In Your Space:

Keep the new idea visible by placing reminders throughout the organization.


To keep a new idea alive in a person’s memory, hand out tokens that can be identified with the topic being introduced.

Champion Skeptic:

Ask strong opinion leaders who are skeptical of your new idea to play the role of “official skeptic”. Use their comments to improve your effort, even if you don’t change their minds.

Conversely, [Farm2006] has ten tongue-in-cheek rules for ensuring that a new tool isn’t adopted, all of which apply to new teaching practices as well:

  1. Make it optional.
  2. Economize on training.
  3. Don’t use it in a real project.
  4. Never integrate it.
  5. Use it sporadically.
  6. Make it part of a quality initiative.
  7. Marginalize the champion.
  8. Capitalize on early missteps.
  9. Make a small investment.
  10. Exploit fear, uncertainty, doubt, laziness, and inertia.

The most important strategy is to be willing to change your goals based on what you learn from the people you are trying to help. It could well be that tutorials showing them how to use a spreadsheet will help the more quickly and more reliably than an introduction to JavaScript. I have often made the mistake of confusing things I was passionate about with things that other people ought to know; if you truly want to be a partner, always remember that learning and change have to go both ways.


Collaborations (small groups/30 minutes)

Answer the following questions on your own, and then compare your answers to those given by other members of your group.

  1. Do you have any agreements or relationships with other groups?
  2. Do you want to have relationships with any other groups?
  3. How would having (or not having) collaborations help you to achieve your goals?
  4. What are your key collaborative relationships?
  5. Are these the right collaborators for achieving your goals?
  6. With what groups or entities would you like your organization to have agreements or relationships?

Educationalization (whole class/10 minutes)

[Laba2008] explores why the United States and other countries keep pushing the solution of social problems onto educational institutions, and why that continues not to work. As he points out, “[Education] has done very little to promote equality of race, class, and gender; to enhance public health, economic productivity, and good citizenship; or to reduce teenage sex, traffic deaths, obesity, and environmental destruction. In fact, in many ways it has had a negative effect on these problems by draining money and energy away from social reforms that might have had a more substantial impact.” He goes on to write:

So how are we to understand the success of this institution in light of its failure to do what we asked of it? One way of thinking about this is that education may not be doing what we ask, but it is doing what we want. We want an institution that will pursue our social goals in a way that is in line with the individualism at the heart of the liberal ideal, aiming to solve social problems by seeking to change the hearts, minds, and capacities of individual students. Another way of putting this is that we want an institution through which we can express our social goals without violating the principle of individual choice that lies at the center of the social structure, even if this comes at the cost of failing to achieve these goals. So education can serve as a point of civic pride, a showplace for our ideals, and a medium for engaging in uplifting but ultimately inconsequential disputes about alternative visions of the good life. At the same time, it can also serve as a convenient whipping boy that we can blame for its failure to achieve our highest aspirations for ourselves as a society.

How do efforts to teach computational thinking and digital citizenship in schools fit into this framework?

Institutional Adoption (whole class/15 minutes)

Re-read the list of motivations to adopt new practices given in Section 15.1. Which of these apply to you and your colleagues? Which are irrelevant to your context? Which do you emphasize if and when you interact with people working in formal educational institutions?

Making It Fail (small groups/15 minutes)

Working in small groups, re-read the list of ways to ensure new tools aren’t adopted given in Section 15.3. Which of these have you seen done recently? Which have you done yourself? What form did they take?