 Okay. Can everyone hear me? Okay. It's a pretty small room, but yeah. Okay. Great. So this is my first CSV conf. I didn't know there was a cat theme. Is that a Portland thing or a CSV conf thing? Okay. All right. I'm glad to know that dog lovers are also allowed to attend CSV conf though. So that's good. So I'm really excited to be here today. I've never been to kind of this interdisciplinary type of conference. I'm really excited to have the opportunity to talk with all of you during the breaks. I'm going to be talking today about data and software carpentry and how we help empower people by teaching them software development skills and data analysis skills that they can be more efficient and more effective in their work and open up career options for themselves. Software data carpentry are non-profit organizations. We train people in software development and data science skills so that they can do the work that they need to do more efficiently and avoid doing repetitive error prone tasks by hand. I'll talk a little bit more about how we do that. We also help build local communities to help people be able to continue learning these skills in a supportive network after they go through our workshops. Since 2014, we've led over 850 workshops and taught over 17,000 learners in every continent except Antarctica. So if anyone is doing research at McMurdo and would like to run a workshop, please let us know. We'd love to put that on our map. And you can see that historically we've been localized in kind of a few regions, but we're working on building our geographic spread and I'll talk more about that near the end of the talk. Okay, so why do we do what we do? So software carpentry was formed in 1998 by Greg Wilson who at the time was a professor of computer science at the University of Toronto. And he noticed that even graduating computer science students really didn't have the skill set that they needed to do software development in kind of an industry setting and didn't know the best practices that were currently in use for software development. And so he thought about this and realized that there's just really not good avenues for learning these skills in K-12 or at the University and we need to have some other way of training people in these sorts of skills. And since 1998 this has obviously only become more important as we've built in to so many different types of careers and different types of jobs, the need for using any sort of computational skill, whether it's software development or analyzing data of some type. So many more jobs now than in 1998 require some of these skills. So, and this has also been recognized in report after report that comes out of NSF and similar reporting agencies. So you can see that there's this recognition that computational science and data science play increasingly relevant roles, sorry play increasingly important roles and that in a recent survey over 90, nearly 90% of PIs who were funded by the NSF reported that the biggest unmet need that they had was training. Training in how to integrate their data, training in data management and that there's this growing data and knowledge gap and that we need to offer more support for computational training to people who are doing these sorts of work. There's another survey out of the bioinformatics resource in Australia back in 2013 that asked their users what the biggest bioinformatics difficulty was and what they could do to help. And the biggest bioinformatics difficulty that people were facing by far was lack of expertise, so lack of knowledge in how to conduct these types of analyses and training. And the most useful thing that could be done was offer training and you'll notice that this far surpasses funding so it's not very often that something is more important than funding but people recognize that the ability to do these types of things is the most limiting factor in the work that they're trying to do. So the question then becomes as we're scaling up our ability to produce this data and as we're creating more and more jobs that require the use of these types of skills how do we also scale the training? How do we make more and more people who have the skills to do these new types of jobs? So software and data carpentry tackle this by building up communities for learning these skills. We run hands-on intensive workshops where learners have many many opportunities to practice learning these technologies. I'll talk about which technologies in a little bit. Our workshops are all led by instructors who volunteer their time to work with us. They go through a hands-on training in pedagogy and evidence-based teaching practices so they all learn how the research says to teach computational skills and I'll talk more about that. We use lesson materials that are collaboratively developed by our community so they continuously improve and are continuously updated for use in our our lessons. They're also open anyone can use them for anything they want and we also work to to create and support local communities for people to continue learning after they go through our workshops. So I'll talk a little bit more about how our workshops work. They're generally two days and they're very full action-packed days. They're extremely hands-on. Every learner has their laptop and they're actively typing along with the instructor as they go through learning all of these things. Our instructors go through this this training program that teaches them not just how to teach computational skills in general but also how to create a motivating environment, how to be supportive, how to deal with learner frustration, how to create good assessments that will help learners assess their own knowledge. And one of the things that we use in our workshops that is really simple but also gets people really excited is post-it notes. So anyone here been to a software data carpentry workshop? Raise your hand if you love post-it notes. Yes. Everybody who's been to a software data carpentry workshop loves post-it notes and these are used by our learners in the workshops to signal to the instructors when they're having trouble. And then the instructors can send over what we call helpers who are people who haven't gone through instructor training but are at the workshops and can offer more one-on-one interaction with individual learners. And if you're interested in learning more about how we use post-it notes, you should read this blog post I wrote about post-it notes and how awesome they are. And I also talked a little bit about the importance of creating a friendly learning environment. So all of our instructors go through training on how to be supportive and how to avoid using dismissive language which can be a real barrier when people are trying to learn technical skills. And we know that we can't teach everything in two days but what we try to do instead is give people a beginning toolkit, a set of tools that they can use the minute they walk out the door that they can apply in their own research or work. And this helps reduce the barrier for them for further learning. We also try to give them skills that they can manage errors in their own work. How do you deal with coming across error messages? How do you deal with reading documentation? Those are the skills that you really need in order to continue learning. And we also try to give them a preview of what's possible to motivate them to learn these tools. So I'll talk a little bit more about our curriculum. Software Carpentry focuses on best practices for software development. They are domain agnostic in the sense that all of the workshops are intended to be applicable to learners in all different fields as long as they're doing some sort of software development practice. They focus on teaching command line through the Unix shell, version control with Git and GitHub so that learners can manage their projects and not have to have things like CSV comp, what was it, CSV comp, version three, Portland copy. And they also do some programming in either Python or R. Data Carpentry, at Data Carpentry we are focused on teaching people how to work effectively with the data that they have. And because data is highly contextualized, that means that our lessons are more domain specific. So we choose data sets that learners can relate to that they will see the connections to their own work so that the tools that they learn, they can immediately start applying to their own research. We teach how to organize your data, how to clean your data in reproducible ways. And also do data analysis and visualization with either R or Python. And we actually just yesterday had our first official lesson release of our ecology based workshops which are actually, even though they use an ecology data set, there are most generalized workshop in that they can be used with anyone who uses tabular type data sets. So that button for publication just got pushed yesterday so I'm very excited about that. And I'll talk more about our lesson development as we get to the end of the talk. So that's our curriculum. But our workshop goals don't just focus on teaching a specific set of tools because we recognize that the tools are going to change. And people need to learn how to learn new tools as they go about their work. So really, we teach people how to build their confidence in learning these types of tools. We know that a lack of confidence is really the one of the most important factors in determining whether people continue to persevere in learning a new skill. So we teach self confidence, we teach error management, how to get yourself out of problems when you're learning new technical skills. And we also help encourage people to continue learning by building up a community and having a very positive learning experience. The instructors that we train go through a two day training program. It's focused on pedagogical techniques. We don't teach get we don't teach show we don't teach are in our instructor training. We expect our instructors to come in knowing the skills that they'll be teaching. But we teach them how to do formative assessment and we teach them how to use motivating language. And we teach them how to how to give good interactive lessons. We have over 900 instructors that we've trained again on six continents. If anyone's working in house and working in Antarctica, please let us know. Our curriculum like I said before is collaboratively developed. All of our 900 instructors at some point or another have contributed to one of our lessons. It's actually a requirement for becoming an instructor. And then of course, once they're done with their instructor training, they often go on to continue to be involved with curriculum development. And this ensures that the lessons are not only continuously improved, but also stay up to date with changes in the tools and changes in what people are actually using in their work. So our curriculum, I think is really great. But the most important thing I think about software and data carpentry is the community that we've built up. So we have a very active community of instructors and curriculum developers and other people who are involved who are excited about sharing software development skills and data skills. And we have different avenues that these people interact. And so for example, we run a mentoring program that helps onboard our new instructors and get them integrated into the community, helps them plan their first workshop and helps them go through the curriculum and make sure that they're comfortable with all of the steps in the workshops that they're teaching. We run weekly discussion groups where instructors all around the world get together virtually and discuss lessons that they've learned from teaching and they trade tips and tricks. And those are always really, really fun to lead and to be a part of. We also run monthly community calls that are focused on issues relevant to our community. So we just had a community call about our Windows installer, which I actually wasn't part of, but apparently it was a big controversy about which Windows installer we use. So there was a great really productive community call about that. We also have very active email lists that people talk about the tools and technologies. They talk about job opportunities and also instructors, our instructors often travel to other institutions to teach. So they've told us that this helps them build up their network and helps them get a lot of connections at those other institutions and broaden their career paths. So you might be thinking, well, that sounds really cool, but how do we know that we're actually having any impact on our learners? So we've done both short term, so immediately after the workshop and long term, at least six months after you take a workshop follow up surveys that give us evidence that the learners are not only learning the skills, but they're putting them into practice and they're continuing to learn them after the workshop. And I'll show a little bit of that data. But first, and this is really important, people actually like the workshops. So people tell us that the workshop was worth their time and that they would recommend this workshop to a friend or colleague, which is great. It means our workshops are always booked up within a couple of days of opening. And they're really high demand and people really enjoy coming to the workshops. But beyond that, they actually tell us that they use the tools after they go out of the workshop. So on the left, you'll see people self rating their use of the tools that we teach in the workshop before and six months after. And you'll see that a greater proportion of them use them daily or weekly than did before the workshop. They also tell us that they're more confident in using the tools and more confident means more willing to learn. So that's that's really important. If we weren't affecting their confidence, even if we were teaching them a small set of tools, they wouldn't be able to learn more tools as they go forward. So I think the confidence bit is even more important. People love our instructors. So this is just a word cloud of their instructor ratings. You can see that they they they really do love our instructors. And I think that's great. So this is some like art data. So I'll explain a little bit about how to read this graphic on the right hand side or agree or strongly agree to like art scale items on the left is disagree or strongly disagree. And so you can see that at least six months after the workshop and longer people are very positively rating the atmosphere of the workshop, the utility of the material that was in the workshop. They still would recommend us to a friend. That's the third one down. They've learned great useful skills. It was worth their time. And and there was a great information provided at the workshop. So that's a little bit of an overview about what we've done so far. I want to spend just a minute talking about where we're headed in the future, what the next steps are for our community. One of the things that we're working to do more is supporting learners after they finish workshops. So we have some communities that have really built up these great organizations where they get together every week or every month and continue learning the skills that were presented in the workshop. And we haven't built that at scale yet, but we're really hoping to be able to develop a pathway to help people build those local communities and continue to support their learners. We're also expanding our mentorship program to include more individualized one on one mentoring. So we launched a mentoring program a couple of months ago now, and people are reporting really good outcomes from that. So we'll have some data for that to follow up in a few months. We are working to expand our disciplinary reach. So I told you we just published our ecology materials. We have a genomics workshop that we offer. It's currently in the process of becoming officially published. We're hoping for that in the next couple of months. And then towards the end of the year and going into the beginning of next year, we're hoping to also publish our geospatial data workshop and a social sciences workshop, which is in active development now. And then I mentioned briefly that we were working to expand our geographic reach. So the two areas that we're actively working to grow in, we've run a couple of instructor training events in South Africa, which served instructors from a number of Southern Africa countries. And we're now working to develop partnerships and run workshops in 11 countries in Africa over the next year. We also are looking to expand in Latin America. So I'd be very excited to talk with anyone who has connections with communities in Latin America as we continue to grow. All right. So I'll just end with a little quote. So there's a quote that says, if you want to go fast, go alone. But if you want to go far, go together. And so what we try to do at Software and Data Carpentry, and I think we do really well, is we help people continue their learning journey by building up a supportive community so that we all have that support and build that confidence to continue our learning. So the next question you should have is, how do I bring Software and Data Carpentry to my institution? So I'd be happy to talk to you about that. Tracy, the executive director of Data Carpentry is also here. Tracy, can you wave? So either one of us can talk to you about how to get a workshop or instructor training going at your institution. And Belinda, sorry, Belinda also. We'd all be happy to talk with you about, and Tim. And Karthik. And Karthik. Yes, there's lots of Data and Software Carpentry folks here. Please flag one of us down and we can talk. There's also an interest form online that you can fill out and we'll follow up with you there. And just a quick shout out to the Data Carpentry and Software Carpentry steering committees, which don't include anyone in this room except for two people, and our support. And thank you.