people are beginning to join the session today. If you haven't already, please say hello in the chat box so that everyone knows that you're here and where you're from. I've got a great session for you today. Some really, really wonderful panelists and just generally super, super nice human beings. Okay, wonderful introduction. Hello, everyone. My name is Lisa Marie Blaschke and I'm from the Eden organization, chair of the board of the Eden Fellows. And I have a wonderful session for you today. It's called Moving to the Next Phase of Online. How can we improve on what we've done so far? And as I mentioned, we have some really, really fantastic panelists today who are going to be talking about how can we move on to, how can we manage the current situation that we're in? We've gotten past the emergency phase. We're moving into trying to improve on things, trying to find a way to adapt to the new normal. How can we do that? And so we've got three wonderful presenters here to share their experiences with you today. But first I want to just say a couple of admin things. If you have questions, be sure to put them in the Q&A box. And if you are on YouTube, you can enter your questions into the chat area and they will be channeled into the Zoom room. But if you are in the Zoom session, please enter your questions into the Q&A area so that we don't have to follow a number of different communication channels. And we can get all your questions to our panelists. So as I mentioned, today's session today is about how can we improve on what we've done so far. Our first panelist is Alexandra Miha and she is education specialist and learning experience designer at the University of College London. And then we've also got Marcy Powell from Marcy Powell and Associates. She is the CEO of that organization from the United States. Thank you, Marcy, for getting up so early this morning to be with us. And we have Richard Powers, who is project coordinator at the Professional School of Education, a Stuttgart Ludwigsburg in Germany. And so I'd like to start out with Alexandra, who will be talking about what's next for faculty development. As I mentioned, Alexandra is a education specialist and learning experience designer with over a decade of experience in European higher education. She's currently working as a learning designer at the University of College London, UCL. And previously, she worked as a researcher and curriculum designer at the Institute of European Studies, free University of Brussels, and led the Center for Teaching Innovations at the Head to School of Governance in Berlin. Alexandra has a strong background in e-learning, learning design, and innovative learning and teaching strategies. And in her PhD, she analyzed how far technology is used in teaching practices at European universities. And I'm very, very much looking forward to hearing her share, her experiences and tips with us today. Alexandra, the floor is yours. Thank you very much, Elisa Marie, for your introduction. I will start sharing my screen. And let's hope it works. Yes. Thanks a lot for joining us today. And I'm really, really grateful to Eden for inviting me and inviting the three of us for a really important, for discussing a really important topic today. And this is how are we going to move beyond this emergency stage in tackling online education and what are the next steps? And today, we're going to talk both about next steps for teachers and for faculty and for students. What I'm going to talk about in my short presentation, but I would really love to start up the discussion, actually, with my slides, is more to stir up some ideas from your side. What is next for faculty development? So I'm going to present very, very briefly some ideas and thoughts I have from my own experience and from what I've been observing in the past six months, what happened in terms of faculty development and support at various universities, mainly across Europe, but of course, globally as well. I'm going to try to problematize that a bit and try to discuss what are the challenges with those approaches. Of course, they were rather emergency approaches. What were the challenges? What are the challenges? And then, of course, try to put forward some ideas on how we can respond to that and try to move forward in a more coherent and consistent manner. So first of all, some thoughts about faculty development and support in times of pandemics. So basically, in the past six months, the whole higher education landscape was turned upside down. And a lot of our assumptions on how we teach, how students learn, how our learning spaces look have been challenged to say the least. The role of the educator as well has been challenged. So there was a lot going on. And we all know that academia is not always very friendly towards change, but now we were all forced to at least reassess the old ways of doing things. So what happened in response to this was actually on a very positive note, extremely, extremely interesting to watch, at least for a person like me who has been observing and working with faculty for about 13 years now, especially on how they interact with technology. So what happened in the past six months actually was amazing. As many educators have taken up, of course, being forced teaching online, I'm not sure how that will develop in the future. It's too early to predict, but there has been a lot, a lot of support and faculty rapid faculty development going on in many universities across the globe in the past six months. So there has been a lot of effort and especially centers for teaching and learning or educational development, education, educational technology or digital education teams, depending how they are called in different institutions, they were at the center of this. They mobilized themselves very, very quickly and tried and managed in most cases to provide really excellent trainings, resources, workshops. I'm going to explain or talk more about it in a second. So that changed overnight. Sometimes they became really the center of the faculty development efforts within their institutions. Now, of course, this has taken or has gone through different stages already in the past months. First of all, it was really reactive. So overnight things had to move online. So teacher lecturers, academics had to basically shift their courses. It couldn't redesign. It was really a shift to the online environment. So they had to get a lot of help with that, literally moving the courses online for the remaining of the term or the semester. And of course, later on, so that was the reactive part later on, it all became a little bit more proactive. A lot of these centers and teams have worked throughout the summer tirelessly to actually bring or bring forward a more coherent program of training and resource management on the topic of online education. Another interesting thing I noticed is that it was all a mix between general and more discipline specific approaches. So on the one hand, of course, we as learning designers want to have everything done by the book. So let's say that using the general design learning design principles and instructional design principles. But of course, we have to also be very, very aware that each discipline has its own patterns. So of course, the new, the course, the online courses had to follow as well as the general design patterns, also more discipline specific approaches. So I'm going to talk about those as well in a second. And last but not least, it's also been a very, very difficult balance to reach between pedagogy and technology focused faculty development. I'm going to actually try to give some more examples of that now to actually illustrate what I've been saying. So of course, this is not an exhaustive list. As I said, there have been a huge number of initiatives across the world. And of course, the amount and the type of resources put into it varies a lot from institution to institution, even within the same country. But I just try to pick up on some examples that have been used relatively generally across the board. So first of all, self-paced online courses also usually based on the on the virtual learning environment of their respective university. They were actually developed in order to include a lot of resources, to include a lot of guidance, first in the emergency emergency stage, and then later on a little bit more coordinated towards the start of the fall term. Nevertheless, this became huge courses or slash repositories of information. They were done differently, of course, from institution to institution. I won't go here into detail, but I think that that was one type of faculty support and development quite used in the past months. Then we also saw a lot of live sessions. So that was asynchronous, mainly the online courses with some synchronous parts. But then there were also lots of live sessions. And sometimes they were more general, again, as I just said, but sometimes they were also targeted. They are actually targeted for a faculty or department level, just to be able to cover exactly those discipline specific questions that are usually not covered in the more general online learning design material. Also, it's a chance for faculty to actually come with their own questions on the topic and ask them. Then even more flexibly, we saw and we still see quite a lot of drop in sessions. So the idea here is to offer faculty a more flexible environment, a more flexible framework in which just to come and to ask questions and to actually get hands on support from learning designers and educational technologies to be able to work on their courses. And then of course, the more passive part, entire repositories of resources, both on the pedagogical side, but also on how different tools work. And I'm going to talk more about that here, because this is exactly one of the challenges that I've noticed. So we saw a lot of different approaches. These were just a few or let's say a grouping of the different approaches. But even though generally they have been effective, it's still too early to tell anyway, and everything is still in flux. But there are a few challenges that have become already apparent, especially to those of us delivering those, or at least part of that faculty development. And first of all, it's the risk of cognitive overload. Obviously, there is so much information. There has been so much information since the beginning of the pandemic and so many tools sort of thrown at faculty, of course, to help them, but still a lot of information to process and implement in a very short time. Then the idea is to try to find the balance between theory and practice. And what I mean here is of course, instructional theory and learning theory, but also more general advice that can help faculty develop their courses in the future in both online and blended or hybrid mode and practice. And by practice, I mean really faculty coming and asking for very, very easily applicable advice, something that they can take immediately and implement in their courses. So a quick fix, a silver bullet, let's say. So walking the line between these two has also been quite challenging. Then of course, there is the, at least from the very beginning, the reflex of faculty to really try to do a lot of synchronous interaction or to rely a lot on synchronous interaction. So the idea was to try to show them different ways, different ways, alternative ways of doing the same things, of achieving the same or similar learning objectives. So trying different ways to engage students also in an asynchronous environment. It's not very easy because it involves a shift of perspective. So a shift of looking at your own course. And the last challenge at the micro level that I identified here is something that we've been sort of confronted with as learning designers. There's been a lot of demand for technical rather than pedagogical guidance. It really goes with the second challenge on my list. Faculty basically wants something right now, a quick fix, something, a tool that we can recommend, and just something that will solve their problems rather than how can I design engaging activities or fair assessment. So it's really, really been quite tricky, again, to go between those two extremes, but aspects. But of course, there have been also more different challenges at the macro level. So a bit of a different perspective here, we kind of zoom out. And we're not looking at specific courses and needs of lecturers, but we're looking at the bigger picture. And here, perhaps I will start with my third one, because that's the broadest. There is a lack of a coherent and comprehensive pedagogical education approach for higher education. There is such an approach for teacher training at all the different levels, but not for higher education. In each country and each institution, there are different approaches, different ways this is being delivered. So there isn't a coherent approach on which to build now when we want to share more about online education. Then there is also a very diverse landscape in terms of resources and existing structures. In some countries in the US, in the UK, there are lots of resources put into this, human and financial. So centers of teaching and learning, digital education teams and so on that have been at least now really coming into their own and really working a lot during the past months, not to say that they haven't done anything before, but still now they showed really that how important the role is in some other countries actually are quite this sort of expertise is quite underdeveloped or sometimes even lacking. So this is very, very diverse. And then my third point, the first on my list, but my third point I want to emphasize as a challenge is actually that all this what I've talked, what I've been talking about right now involves a change in routines in the change because we are used to seeing teaching as quite an individual endeavor. And this doesn't have to be like this, but this is how we mainly have been looking at it. So the idea of working in a team, including academic and non-academic stuff like instructional designers or educational technologies, this is a new routine. And a lot of people have been really, really friendly to it and have really taken it up and seen it as very useful, but it still needs to be developed as a routine in the future. So my last two slides will focus on the way forward. I mean, we've seen what's been going on in the past six months, very, very briefly. We've seen what the challenges with this are. What I'm trying to propose here, again, is just focusing on a few issues. I'm aware that there are lots of possibilities. There are lots of things opening ahead of us, but I think what could really work, and this is really again from my experience and experience of my colleagues and my peers, what could work in the future to complement everything that has been done is showcasing good practice, practice in general. Also because I want, I mean, what actually is missing at the moment is colleagues hearing from each other about what worked and what didn't work, just because there hasn't been that much done so far. I mean, there has been the emergency part, but perhaps that's not really telling or not to a great extent. But what will happen in the next months is very important. And I think a lot of people will try a lot of new things. Some things will work for them. Some things will not work or will not work as expected. It's very important to share and to capitalize on this and to try to have people hear each other. Also to try to encourage people to work together in the sense of observing each other's online courses, doing even peer review. And I'm using peer review here because it plays on a sort of research routine that we all have. So we're also used to reviewing each other's research, but we're not doing that or we're not very used to doing that with each other's teaching. So that would be something very useful as well. And in terms of resources and materials, perhaps keeping it to a minimum, keeping it to the, I called it essentials. But what I mean here is not hundreds of pages and hundreds of minutes of videos, but really very, very short one pagers, two pagers maximum, or two, three minute videos on very, very focused topics so that faculty can mix and match and take whatever they need when they need it. And again, zooming out and looking at the bigger picture, what I noticed, and I really want to leave it on this very positive note, what I noticed in the past months has been really a increase in networking. I'm talking about social networks, but lots of different professional networks as well, like for instance, Eden and lots of other networks have been organizing a lot of experience and expertise sharing in order to be helpful, in order to actually try to help everyone. Because as I said, there are lots of places that have a lot of expertise, and there are many places that have very little to nothing, next to nothing. So for that, it's very, very important to try to be as inclusive as possible. So I really like this development, trying to break our institution, to break away from our institutional bubbles, not to share only with our colleagues, but to share more globally. And there are different ways to do that. And I'm really happy to talk about that. And there probably should also be a little bit more financing going towards that in the future, trying to build up new networks or actually to enforce old existing networks to enable this sort of sharing. And of course, the second point is related to what I just said before, but this probably will take much longer, trying to work towards a more coherent faculty development plan for higher education. But this is a different topic, but perhaps we can already have a head start right now after or in light of the pandemic. And I won't say after the pandemic, because unfortunately, it's not yet over. But yes, this is what I wanted to to share with you. And I'm really looking forward to your questions. Thank you. Thank you, Alexandra. You've really given us a comprehensive summary of where we've been, where we've come from, where we are now and the way forward. I've really done a great job with that. I especially liked your reference to the global communities of practice and how important that is sharing our experiences with each other. And this question that is coming up in the question and answer chat box is, do you really believe that people, faculty members, will share their negative experiences amongst each other? It's a very good question. I'm smiling. I smile the moment I saw it, because of course, it's hard to believe. And I'm sure many people are not willing to do it. But I think if I find the challenge for myself for the next months is try to get people to do it, because actually that's the way we can learn. It's hard until someone starts. It's really trying to get the ball rolling. But in general, we are not very happy, not only in academia, but in general, to report on our failures. Everything is just, you know, our CVs look perfect, only achievements, grants, everything. But actually, how are we going to learn if we don't see what hasn't worked? And so what I mean here is both personal at the personal level reflect on a personal level what hasn't worked. And actually sharing it, even if you share it with one peer, as I said, peer observation or, you know, there has to be a system, of course, in place. But, you know, in confidence and basically on a very collegial level, I think this can be really helpful. I mean, I actually personally would love to hear what hasn't worked for two, three, four people so that I don't repeat the mistake. But of course, I understand completely what you're talking about. And I think it's a very cultural thing as well. I think in the Anglo-Saxon world, that's from my experience in the Anglo-Saxon academia. This is much more sharing and peer observation and so on. It's much more common. I've worked in Germany, I didn't find it common. I don't know, my colleagues can confirm or say differently. But I think it's something we have to try at least. I'm not sure it will work or not at first, but I think we have to try. Okay, thank you. We're going to move on to our next speaker. But before I do, I just want to say be sure that you follow Alexandra on Twitter. She has lots of really great ideas that she shares on Twitter. And also follow her newsletter because you'll get lots of lots of valuable information there too. So moving on to our next speaker, this is Richard Powers, who is Professor Emeritus of English Language and Literature from the University of Maryland's Global Campus, an expert online teacher, trainer, and instructional designer. And I know because I happened to take a class with him almost two decades ago. And he's taught online since 1998 using WebTICO, Blackboard, Moodle, Brightspace, and Ilias. And currently he's the project coordinator at the Professional School of Education, Stuttgart Ludwigsburg here in Germany for blended learning courses on diversity for teaching and training. Since the coronavirus outbreak, Richard continues to be a key member of two task forces preparing students and teachers to teach remotely in this very confusing time. And with City Colleges of Chicago, Richard continues to support 3,000 teachers, 25,000 students online, and at Stuttgart, 3,000 teachers. He's been supporting and developing projects and courses and training. So Richard, he's going to be talking to us about how we can improve on our current curriculum, giving us some very valuable tips. So Richard, the floor is yours. Thank you. Hey, thanks very much, Lisa. In 20 years, wow, look how far we've come now. We're talking heads right here. That's great. Just a minute. I'm sharing the screen. So how does that look, everybody? Lisa, can you see the screen, the first one setting up? That's super. Okay, as Lisa mentioned, I'll be talking about some kind of immediate priorities that people can do now. What I put together initially is some statistics. It's always kind of helpful. These were done by a Cengage survey done by Bayview Analytics from 6 to 9 April of this year, just when the pandemic had started affecting most of our universities. They surveyed 826 admin and faculty over 641 United States institutions. So this information is very specific to that kind of thing, but I think you'll see a lot of tendencies and parallels for us as well. What the first infographic is really showing you is when it started, boom, 90% of the respondents said that they transitioned some or all of their classes online. The finding was a lot of the labs couldn't really do that, but 90% of courses overnight, as Alexander was telling us, that's a lot. 97%, more of a telling statistic here too, reported that they used faculty who had no online experience at all.  Sure, you could access your email, you could do things basically, but now to deliver a whole course online. The interesting part about that, the last 20 years have seen that some instructors have gone online and others haven't. There hadn't been a lot of pressure to do it. If you wanted to do it, you could, and if you didn't, you stayed out of it. But now all of a sudden, so there was probably that initial guilt too about, oh, I should have been doing this all along. That was adding a lot of extra stress to people too. As far as teaching techniques, super interesting. Some of these are very similar all over the world. I saw people logging in from Mexico, from Croatia, that's wonderful, the Middle East. 83%, if you're fortunate enough to have resources, used it some kind of LMS. Blackboard, Canvas, or if it's Schoolology, or some Google Classroom, some kind of thing going on. 80% were using some kind of teleconferencing, Zoom, or Skype, whatever way that you could do it. 65% used async recorded lectures. Now here's a telling kind of statistic. 51% went to external sources. Most of us teaching a classroom with a textbook, kind of easy to do. Now all of a sudden, boom, you've got no textbook and no digital type of thing. 51% of the people out there made that all over the globe too, had to kind of scramble and look for assets to try to do that. That's where OER come in wonderfully important assets for that. Open educational resources that are free. If you can have the time and experience, you need that background to put them together, and then use them rather than going for expensive publications and institutions such as that. So you can see with that. The sixth slide is about the quality. 63% changed what they usually did. They had to. That's a big number of what they're doing from exams and assignments. Some of our institutions are more exam oriented than others. That was a big deal. How are the exams going to be done this way? 48% lowered their expectations. Well, that kind of can't be good for the long run. You kind of see it in a chaotic type of way. So I talked today about my immediate priorities. Let's get those expectations to the same or even better from what they were before. Otherwise, where's the quality of this part? And Alex did a great job talking about the tumult and the chaotic nature of what was going on. And I like to refer this as kind of a phase two area where we're going to be more something that's more stable or not yet, but we're moving to something that's a little bit so now quality can come in where just delivery was part of that first part. 47% of American institutes went to a pass fail thing. So normally we use an ABCDF and a lot of schools in Europe, one, two, three, four, five, they said throughout the grades, it's just going to be a pass fail for this kind of environment. Now for some courses, that might not be the best way to assess learning outcomes during into and 46% dropped their assignments or exams. So depending on the course, that's kind of important of how that's going to work in there. So what were the top recommendations from the survey stats are always, you know, you can move them around be interesting to see they did another survey in August. So coming up will be the new ones that are coming in. Number one, right, was more information about how to support students. So this my talk is primarily for I don't know institution level VPs, administrators, deans, rectors, what are you thinking about and using this window of opportunity to build from that. If your country uses a year round school system and people are working throughout the terms, that's pretty good. A lot of the European universities, and we closed classes in July, we're just starting up right again now. So that July to October was lost space where people could have been working on projects and maybe you did that too. But if you're just coming back and trying to figure out what's going on, planning for the future of seeing whatever this new normal is, if we go back to the classrooms in the spring or whenever, what's really interesting is so many instructors are new have found new things that they're doing, they're probably beginning to take a lot of what they've learned online into their classroom for some kind of blend in there. But if you're out there thinking about what to do for faculty, what to do for your courses, don't forget about the students and their experience in there. Greater access to online digital instructional materials was number two. So that whole thing we were talking about OER, how do we get that if you're using a textbook or a publisher, perhaps ask if they have a digital project, a product that can just be plugged and played right into their LMS so that the teacher isn't scanning and doing all kinds of crazy things about that. Number three, advice about accessibility requirements. It's always important for learners with diverse needs. Certainly important this time that came out with learners who were having technical difficulties, not so much with visual impairments and hearing impairments, but now people who don't have access to those things. And then finally faculty resources and training, as Alexander mentioned, so important for how to move forward. But notice how important the student part of that was. A lot of faculty seemed like they could get it pretty good, but now they had 20-25 students and been 60-100 in classes. How do they get that kind of support so that it doesn't fall on the instructor to be a 24-hour help desk? But how do they go for help and where can they kind of find those things? All right, if you're a leader out there, a VP and you're up there at the top, it was okay from April until probably June or maybe up until now to say, yeah, it's hard, it's challenging, it's very, very kind of difficult. But what now in phase two needs to be done with change management stuff is the leadership energy and the attitude should shift to a more positive type of tone, right? So if you're talking to your administrators in your department heads, super busy people, tell them what I just told you. Look, this is a window of opportunity to develop for the future. It's not just trying to put a band aid to do it now. What do you want to do three or four years from now that you can be doing now to meet that part of the thing that's moving forward? This isn't going to be done overnight. It's baby steps. First, this gets done, but it's a process like anything else. So what are our goals to do with this one? If you're talking to students as an administrator, the online learning experience is enhanced. There can't be this negativity about being, oh, it's bad, it's terrible, or things to move in. We've learned enough about it that it can be a rewarding experience. So if you're the leader, you need to put that positive spin on it to help people stay motivated through this practice. And last one, if you're talking to faculty, start saying online learning isn't as bad as you think it's effective. Start having your faculty champions deliver surveys and webinars about how that's kind of work. Now, what else can you do? We live in a world of systems. I think we all know that, whether it's PeopleSoft with human resources, whatever's going in there too.  I put these Venn diagrams. Alexander mentioned the silos of the vacuum effect that's out there. Usually at most institutions, there are people responsible for the academic technology. And by that, sometimes it's the OIT people or the LMS, the Zoom, whoever's doing that. Then you have the departments that do the pedagogy and the academics. And then you have the IT people that put that all together. Find those people, put them together at the same time, the leaders at the meetings and Zoom or WebEx or whatever, and get them to start small task forces on different issues that you're trying to work so that you're not just doing one out of the three. And part of that is good due diligence with project manager meetings. A lot of academics have great PhDs, but they don't have a lot of project management experience. So turn them into project managers. Say, hey, Dr. Smith, you're the project lead for this. Now here's our template for minutes. Here's our spreadsheet with the milestones. Please fill that out and help them get trained to do this pretty well. You'll find that that works pretty well as they keep up with the meetings and the minutes. I mentioned these. If you don't do this, keep them in mind. This isn't just the temporary phase. What do you want to do in five years that now can be done as you move towards what your institution will look like? Have a separate technology plan, have an online curriculum plan, have professional development opportunities that people are working on, and finally, some way for feedback and evaluation throughout the whole way that's moving forward. Master courses. Okay. So what's coming at you fast and furious here because I want to leave some time for discussion. It's probably Richard, but I go by Rich. Kind of nice. Maybe one day it'll happen if everybody kind of calls you that too. But my top seven things that you should be doing some way in there. And that was the first we just talked about. Master courses have kind of a negative idea, but they're templated courses. Most universities have a freshman level course that over 600,000 students take. Those kinds of courses shouldn't be so variously different so that the learner experience is so different with them too. So start thinking about since we have the ASIC component, having that ASIC component applied to lots of courses. Determine which ones are your bread and butter courses that lots of people take that you want high quality for. Select learner or instructional design teams drawing from the talent. Train the teams first of all, establish milestones and deliverables, and then make sure the course goes through a quality review. We've done this at City College of Chicago, then at Stucco University, and talk more in detail about that. But it sounds like a lot, but it's a process that moves the student going together. Lots of things to do with faculty training, lots of different initiatives. Alexandra covered most of these. We found that the blended learning courses and workshops work very well. Lisa and I took a course. She's talking about 20 years ago. Marilyn was kind of on the forefront of that. I think it was a five-week course, and it went through modules one, two, three, four, five, and the teacher came out confident about what's going on. Have to return to those types of things. So we've whittled it down to about three weeks where there's a sandbox. The faculty gets the information, reads it, and then goes into a practice classroom and actually does it, and somebody comes in to see it do it. That's the component that seems to be missing out there with faculty training. Lots of virtual, here's how you do it, but then nobody's looking to see if the person can actually do it. So that's helpful. Virtual drop-in hours. Alexandra mentioned this. External training. You guys are in here for the webinar. That's super. OLCs and other organizations run these. Establish a knowledge base with a website, and then work towards maybe basic intermediate and advanced certificates at your institution so that people can award and move that to. Now, closely as I get through these other things that are moving in, there's differences in motivation out there. I divided these into two categories. Enrollment-based programs such as the states that tuition. So they're very expensive. Students are paying for their courses, private classes, and then state-provided. It might be in Europe or another continent or country where the state is providing a lot of that. So there's not a lot of school guilt coming in there. There's differences in motivation for your faculty to take all that training I just talked about. A lot of the American, Australian faculty will take it because it means job security. If they don't get certified, they won't be teaching. Whereas in Europe, at least in Germany, the schools I work in, the teachers, especially those with tenure that have been there for a long time, aren't really super motivated to take all this additional training and go in. So that's where the department leadership is coming in. And budget is different too. The way your school is funded. With Europe, it's super important to keep your ear to whatever's coming down. What are the grants? What are the funding for the next year? Did you get money for projects for institution because it's out there right now? Last few slides, teachers and training super interested. If you're a big wig out there at your school, look at where your teachers and training, the pre-service, the future teachers in the classroom and what's going to be done. Offer courses out there about how to teach online and digital tools. If you don't have them right now, get them in there. Your students are taking classes now. They're the perfect audience to become teachers. Lisa and I know Alex, too, and Marcy, the best way to become a good online teacher is to take a few classes as a student yourself. So these students right now, they're getting crash courses and how to be a good online teacher. Get them the official training now so when they finish their teaching degrees, they're ready to start teaching the minute they step in the door and they don't become a liability out there.  We do way too much probably with that 10 to 12 page essay. It's great. It's important. I'm gonna say get rid of it. But if you've got three of those in a course, maybe turn one into a digital project, an e-portfolio, a project that can be worked online so they experience with that. And then here in Europe, we've seen the E-20 projects. A lot of you know that. They're wonderful. There's that whole teacher trainer institute projects that are going on. So if your schools aren't involved with that, please do that. The thing with the student orientation is super important. One hour virtual student orientations at the beginning of the term. You can post the recording and the presentation on the website. After my quick talk, I'll put a link to City College of Chicago and just show you how kind of relatively simple that is and then gather feedback for the pilot orientations. We found that if you have these a week before classes start, the week during classes start takes a lot of the pressure off the teacher. Instructors can also be doing things. Course self-review for quality. A lot of you have probably heard these. I'll put the links after my talk.  So Sunny has their Oscar rubric. There's the Kokey rubric out of Illinois. The OLC scorecards are famous and the quality matters rubric.  I did this from April to August and now you want to check it and see how it's doing. Get one of these rubrics and just cross off so that you don't have to worry about waiting for that guidance coming. You can start designing it and making it work for you right now. They just some quick other tips you can read faster than I can and the slides will be made available to you. Maybe the big thing is up at the top. If you're writing people's job descriptions and positions, start hiring people with a digital background. It might not be the most academic person out there with 15 books and tons of articles, but they might know Ilya. So they might have designed programs that are coming in there. So if you're hiring and you're writing the contracts for people, include maybe like number two, that along with your job, you will do digital training and workshops to help people at our college putting in there. So looking at the PDs and the position descriptions for the next five years and make sure they have that in there. So you don't have to go out and pay extra money for that stuff that's moving in there. And Alexander showed a great example of her newsletter. Bravo. We should keep that kind of going in there too. So that and a nutshell are my top tips coming in and number seven. So I'm going to stop now. So at least Marcy has some time to talk, right? So thanks everybody. Thank you, Richard. We've got lots of feedback on your presentation, lots of comments about, yes, this is wonderful. We need to talk more about the opportunities with online learning. And we need to really focus on what's good. We need to focus on improvement. So you've got a lot of feedback from the audience about just basically saying this is exactly what we need. And so, I mean, there are so many tips. It's really hard to even find a question to ask because you've answered so many of the questions, I'm sure many of our attendees have. There is one question from one of our, from one of our audience members is from Larissa and she asks, is there research or some idea of higher educationist institutions that are approaching distance and open education that we can learn from? Yes, there really are quite extensive bits and all kinds of articles. I mean, I wish I could make this laundry kind of list out there. But one very good place is, let's see if I've got a quick link with the OLC. If I put up this, I think this is their whole website. But anybody can access the research that's in there and then you just kind of search with OER up there. The open educational resources and then finding the problem with it is there's so many search engines out there like Merlot, you can go to and then you can go to Creative Commons and these OER database resources, but it's very difficult finding those specific resources that you want. But the OERs that are out there, I can also recommend Susan Coe's book on blended learning and using online Susan Coe and Elena Zadko. I wish I had the link right to it. If you copy their names and put it in your Google search engine, it comes up and three chapters are available for download of that book. And it's very nice as she walks you through the process of how you put those things together and then how you do them. But the issue with OER is just that it depends on the discipline and then being able to find them and put them together for your course takes a little bit of time when you're putting them together. So, I hope that answered, but the research about how effective it can and can't be is also dependent on the program like you'll find adult education programs differing from the K through 12 programs differ from higher institution programs. I wanted to ask this question because I think it's really important that we'll move on to Marcie's presentation. And this is from Sukena and she asks, how do you communicate to faculty the time it's going to take them to realistically design and develop an online course? This is indeed a challenge and I know I found this in my practice as well. You just have to be brutal and frank and say it takes a long time and you're not going to get paid up front from it. And what you say then too is, but the value of it is once you put in that hard work with it, you have it for the next five, six, seven semesters. It's a lot of time and effort up front, but the effort and the time that you put in, it's very similar to writing your PhD or a master's thesis. You're going to work really hard with it, but you're going to get a lot out of it once you have it. Nobody can take your online course away and what happens is you start tweaking it. So the next term, you improve it. So after the third or fourth term, wow, you have something that's fun, that's engaging that you like and you keep adding it to it. So you just have to be brutal and kind of frank and say there is no quick and easy way to do this with that, but that the payoff in the end, the benefits are there over time. Thank you. I couldn't agree with you more. Is that what you found too, Lisa? Yes, definitely, definitely found that the paybacks are definitely worth it. Okay, we're going to thank you, Richard, a really, really great presentation. We're going to move on to Marcy Powell next, who's going to be talking about the strategies for staying productive in this time of Corona and sane. And just to give you a little background on Marcy, she is president and CEO of Marcy Powell and Associates and has been at the forefront of many pioneering advancements in the workplace for the last 25 years. She is an award-winning internationally renowned keynote speaker, business consultant and author, and has managed globally diverse teams and inspired over 100,000 leaders, employees and students across the country, across the globe, and at six continents in both education and industry. Some of her awards include the 2019 US Distance Learning Association, USDLA Higher Education Innovation Award, USDLA Hall of Fame membership, AT&T Presidents Club, Polycom CEO Award, and the second, she is the second American woman who has been elected to an Eden as Eden fellow. So Marcy, I'm with that list of accomplishments. I'd like to turn the floor over to you to share your experience and your expertise on how we can get through the next few months or years. Thank you, Lisa. I appreciate it. Let me get this PowerPoint going. And boom. Ta-da. All right. So glad to talk to you and I love listening to what Richard and Alexandra had to say. So spot on, especially in the need for teacher training. And we were blindsided. No one knew COVID was going to happen. And then suddenly, not only are we bringing many courses online, thank goodness, organizations like Eden have been doing this for many, many, many years. And organizations like it, collaborative organizations like USDLA and ICDE and others around the world. So we're very blessed that there's expertise and collaborative people you can connect with to learn. But what I would like to talk about today is the educator side besides the classes. So if we don't look for a moment at pedagogical, but let's look at what's going on with all the workload that's been put on us, the fact that we've been suddenly we're working remotely. Many of us, Lisa Marie and myself, several of us have been working remotely for several years, but not everyone has. And it hit a lot of people. Suddenly you're not on campus. You're working remotely. And you have to adjust. I have what I call the dingy effect. It's where you have the mothership, if you will, the main campus is like a big ship where we all come and we all collaborate and work together. All the departments and cross collaboration goes on and other universities we work with and institutions. But then suddenly we're on this little bitty dingy, this little bitty boat that's attached to the mothership but way out. It's only needed when it's needed, then it's loaded up and it's expected to handle all of that workload. But all in all, you're away from the hubbub of activity. And with that comes things we're very concerned with, the fear of missing out, the worry about out of sight, out of mind when you're on a good career path or you're trying to get that recognition or get those grants or whatever it is you're trying to accomplish and suddenly we're remote. You know, we've worked for years to make the distance disappear in online learning for our students. How can we make them feel connected to the campus and as if they could reach it and as if they're there? How do we develop in our online courses rules of engagement and ways to pull them in and that collaboration and that community? How do we recreate that? How do we turn the, as Alexandra said, the theory into practice? How do we do that in an online course? Well, how do we do this for us to feel connected? So what I thought I'd do was share a few little tidbits that I've come across that will help us with some of the things that have happened to us, this overwhelming, the overwhelmingness, if you will, of the new normal. We've had to adjust to new ways of working but most of all we need to figure out how to do it right now that we know it's still ongoing and we have to have a healthy work-life balance. So let's look at a few things. Many of you have already gotten your office is ready, you've found a space to work or in some cases some of us still float from room to room to room to work. There's some danger in that.  It's like Richard and I were talking earlier and he said I'm sitting on the couch and my phone starts beeping or maybe it was Timothy actually said that and my phone starts peeing and I'm find myself working again when it was time when I was supposed to be not working. That happens. So we have to create this remote mindset. Two of the most important features of the remote mindset is having that agility and that resilience. We need to be able to act quickly to the change that so many people don't like to see happen. We have to be agile and have resiliency in our movements and what we're doing and think okay I can't go travel to conferences anymore so how am I going to organically connect and collaborate with my peers? Well recreate your water cooler chats if you will where you would meet in the office and the interactions that you had when you looked down the hall and said hey John you want to go grab lunch together. How can you recreate those remotely? Well videoconferencing helps tremendously. Some people have even created everything from pet slack channels using a communications a social communication tool tool to stay connected to their colleagues posting pictures of their pets posting crazy pictures of them working remotely posting pictures of where they wish they were while they're working remotely but it builds that camaraderie it strengthens that trust it helps with that connectedness so we have to do those kinds of things and then finding your rhythm one of the advantages of working remotely is that you can find what hours and times work best for you and when you're at your peak performance mine is early in the morning as I was writing my last book I would get up sometimes at 4 30 or 5 30 in the morning and just work all the way through lunch and get so much done but if you ask me to sit down and write at three or four in the afternoon I don't know about you but my brain is dead I can't do it it's pride so you find your rhythm that works for you when you're at your peak performance and that will help you with productivity manage your time you are the boss of your time don't let others be the boss of your time and that's hard when people could keep piling more and more stuff on your plate so you have to figure out how to manage that there's some tips I'll talk about two little quick things and then I'll go on because I want to stay within my 10 minutes I want to hear all of your questions controlling distractions as we know is very important and that's hard especially if you have little kids and our chaos what I call loving chaos going on at your house you have to control those distractions and kind of lay some ground rules that everybody can follow I had to run out a lot of people so I could do this webinar right here to say let me focus don't distract me but there's also what I call intentional interruptions which is where you take those breaks if you've worked so hard on developing your course and you just got a module component done that you are so proud of you've been sitting there solidly for three hours four hours take an intentional interruption go walk the dog go hug a loved one go get a special cup of coffee go do something that rewards you for your work make the interruption intentional and guess what you'll come back completely refreshed you will have such a fresh perspective and be able to knock out more work and then then focus on what do what I call purposeful focus which means when you need to go dart don't let your phone interrupt you your email interrupt you and other people interrupt you on getting something done set your timer a time there's timer apps on computer set those and purposefully focus on what you want to accomplish until you're done and then add an intentional interruption so when you're crushing your to-do list as they say today there's some things you'll also need to do from high-powered prioritization where it's really where you figure out what's most what's absolutely has to be done what's good to be done and what can wait and put that prioritization in place and make yourself stick to it or you can work 24 7365 and never sleep so you have to decide what's important another one is sufficient excellence and that's where I say when you work really hard and you do something we can keep working it and working and working it and never get our course out or never get that project done we have to decide it's sufficient we put our excellence into it it's sufficient Sir Paul McCartney recently was interviewed and they asked him have you ever released one of your works that you weren't really satisfied with he laughed and he said have I ever released a work I was fully satisfied with that's the question because you can always change something and like Richard was saying you can tweak your course through the semesters so make sure it's sufficient it's excellent who's the stakeholders it's going to is it good enough that they it does for them what it needs to do and then get it off your plate and then finally numb commodity the thing that we worry about quite often is our career path and being out of sight out of mind remotely we worry about where we're going and the trick there is to have an air of presence make people connect enough with people connect with your colleagues even with conscious five minute chats even a quick text text to encourage someone volunteer for things that need to be done that no one else wants to do it might take a little more time but it can increase your presence on the campus even though you're remote we could go into that more but I won't finally um I could have spent a lot of time going over some of the innovations and online learning from around the world but here's a website that Dr. Susan Aldridge and I created under Drexel University online and what we did was showcase all over the world innovations and online learning that's going on all around us whether it's um often in the virtual reality gamification um even taking videos and making a documentary course with teachers from around the world instructors that would give that practical application from around the world uh using all kinds of technologies ed tech tools to innovate and make our courses completely engaging some use different departments and collaborations throughout the university other departments like graphic design and the center for teaching excellence there's so many resources out there and collaborate collaborating partners um so virtually inspired or go look at those and you're going to see over 50 examples with a little short three minute videos and a landing page that gives you more information and then the links so you can learn if you need some ideas and finally there's some other resources that we worked on we have three white papers that you'll see uh the online classroom of the future educating the next generation workforce and then one about transforming the higher education digital ecosystem so look at those resources on marcipal.co not .com and I'm marci with an i not a y not an ie and so go there and look resources and then I have a book that just came out this weekend I haven't even promoted it yet um but it's remote leverage the distance and achieve excellence when working remotely I pulled a lot of tidbits out of that book for the presentation today so if you want a more elaborate um details it's available on amazon and barns and noble and about 40 000 other um outlets you just go in and put my name in that's the easiest way to do it marci pal and search and hopefully it will come up um and with that here's my contact information I'd love to um help any of you that need anything or want to discuss anything and Lisa Marie I will turn it back over to you thank you marci uh lots of feedback from the people that are here talking about how you've really hit it on the head uh just the necessity of finding that time for yourself and and really being able to manage that time one of the questions that that I have um for you is what kind of tips would you give to us for for managing our time so that we don't become so overworked that we can't um that we just can't manage I mean this is it's so important that we that we stay healthy and that we stay in a state of mind where we can support um our students our our peers um our our families what kinds of tips would you give us well I think number one is to understand that your work is always going to still be there and need to be done so don't let yourself get so caught up in it that you make yourself unhealthy so for example I might get ready to head for bed I mean I'm tired I'm worn out and then I go oh wait I need to email Lisa Marie one more real quick thing and then three hours later I'm getting into bed we do that so the tips would be to set your own parameters and and stick to them um what I do is because I have more flexibility and how what hours I work I don't have a set time so I every day almost look at my calendar and say I'm going to work here and then I'm going to do this and then I'm going to work here and I'm going to do that and I set my parameters so very clearly set those um and if you'll practice some of those things I talked about with high-powered high-powered prioritization and sufficient excellence where you'll make yourself do that and manage your time um like going dark you wouldn't believe how much how easy it is to make yourself go dark and really get something done and say like I'm going to check my email before I get started this morning and I'm going to stop 30 minutes after I start looking at it and then I'm going to get this work done and then this afternoon before I close out I'm going to go back to my email and look and without looking at email during the day you knock stuff out like you wouldn't believe so that's very unhealthy way to look at time management and in really making sure you protect you protect your family time your personal time and that's what gives you the energy and strength to do what you do so think of it as you're doing it for the university it's a benefit for them if you do that protecting of your time they don't want to burn out unhealthy employee. Yeah well said well said Marcy thank you thank you very much I have a question for all of the panelists today all of our speakers you the the examples that you've shared with us the tips that you've provided us the the different approaches that that you've shared there was a common denominator I thought in all of them and and it was really about trust so let's talk about trust trust in oneself trust in trust in our peers trust in our management trust in our students and for many of like like I said for many of the solutions that you've talked about trust was really that that common denominator so how do you think we can build this trust what kinds of measures what kinds of steps actions can we take in order to build trust in a remote working environment where for example you don't have that opportunity to build relationships or to see those those um the things that that aren't said in an in an online environment who would like to answer that question first okay Marcy go ahead and I didn't want to go first but I one of the chapters in my book the letters of remote T is team and trust and so I because it's top of mind real easy for me to pull out um one of the most important things you can do is to be a student of those you work with be a student of your student be a student of your peers and that means to get to know them find ways remotely that you can get to know them and understand what their goals are and where the way they're held accountable at their job um some of these things that are important to them and then more importantly what their passions and their giftings are so that you know how to depend on on each other and can collaborate I might love doing something and I'm really fast at it and you might take three or four hours to get that same thing done because you dread it you just you don't like it well what if you said Marcy can you help me and I could help you go boom boom boom boom boom and you go wow that saved me so much time and then guess what you now trust me as I'm a trusted friend and you know I've got your back and you know that that uh you trust that I would I have your best interest that's my point be a student of those you work with and and put their interests uh on your list of being a good friend a good colleague thank you Marcy Alexandra I think my question is going to be on your point like I can do anything or training or empathy is the best that's the best kind of direction you can go right now because that's something that needs training to put ourselves in in each other's shoes and try to see things from each other's perspective but also believe me that that workforce trying to be born of and open ourselves both with our colleagues and with our students and of course put ourselves as well trying to be ourselves because often we are now a little bit intimidating by technology trying to explore this picture Alexandra your connection is really it's not coming over very well could you could you maybe yeah I could hear you well but can you hear me now no it's not very it's not coming very well over very well it has a nice outer space yeah it has like you're coming from well that's a good part for trust technology I'm gonna ask Richard to answer and then if you could check your technology Richard I just want to say that people probably already know anyway when we start off is that trust is over time it's not going to be like from day one it's just over time so if you're especially if you're in a collaborative group or working on a project make that project just as if not more important than the individual work so that you meet your deadlines you're not showing up late all the time you know be responsible another thing with trust is with your email you know ask if you if people send you email if they don't mind if you send to somebody else before you just send it out there and I'll be a little backstabbing in the game playing just there's no place for it in education you don't need it so a big thing that's hard maybe for me it always just tell myself check my ego at the door I work with a lot of arts all stars out there you know they've got websites got all kinds of things going for them you know all that stuff but it's nice if we say okay bring it down what's our project keep on that and I go kind of focus and it realize there's going to be some give and take with that too but it's it's amazing how long it takes to develop the trust how quickly you lose it just by one silly email one bcc that you didn't send or a comment that you wrote and you know just be really kind of what you write in the email because before you know it it's part of somebody else's snippet you didn't mean for that comment to be included in and that one and maybe one other little point is be be aware of the cultural differences and your own biases like if you've got certain things that you think about people know that about yourself so that when you're engaging with them and maybe this is just two confessions with me as an American working in German oftentimes I stereotype which is the wrong thing because in the end I found out that this quick fast kind of American way of doing it isn't always the the best way to get there that kind of a methodical logical practical approach you get to an end product about the same time as the other one so cultural biases you know have an open mind and uh yeah trust it's a great point because you know as it followed one slip up just destroys the whole trust you know that you've built so hard to grow yeah thank you Richard very very thoughtful comments very insightful Alexander are you able to to share with you share with us your thoughts oh I'm sorry I still we still can't hear you it still sounds a little bit like you're coming from outer space when I know you're not that far away well that's really too bad um well I would like to move forward we we you know have had a really really wonderful productive day today and I want to thank our speakers who gave us such a wealth of information sharing us sharing with us your your your expertise your experience your best practices exactly the kind of thing that that was recommended by Richard in in in Alexandra and also Marcy in terms of you know really helping each other out you know as we try to get through this this very challenging very challenging time and so I just want to thank our presenters you were really just fabulous so thank you very much for taking your time and spending it with us today finally I'd like to tell them all of our attendees to be very thank you to you as well for participating for for being so engaging within the chat and within the questions and answers and and for sharing your experiences as well it's it's it's just just a just a wonderful community I'd like to let you know that we're going to be having the Eden research workshop at the end of October from the 21st to the 23rd it is an online workshop so you will be able to participate wherever you are and also to give you just a quick note about next week's webinar session within the pandemic education within the new normal and that is how to build communities of support for teachers and that will have our speakers maha Bali Autumn Keynes and Maria Zamora so we hope to see you next week and as I said thank you again for all of you for attending and also to our presenters and and we'll see you next week


The tools we introduced last lecture, in particular docking, have been remarkably successful in aiding modern drag design, not because they're accurate, but because they're fast. However, as computers get faster and faster, this leads to another challenge. Computers can get so fast that we can't really use the computational power for docking, there simply aren't that many molecules we can just test. At the same time, we would like to use the computers to do something more accurately. And that brings us back in part to the molecular simulations. Remember, when we spoke about molecular simulations, we brought up free energy calculation. And in theory, the molecular simulation can help us to determine how much is the binding energy in a particular pose. This is going to be significantly more expensive than docking. But again, hopefully that problem is going to be solved by faster and faster computers. There are a couple of challenges with that. First, we're going to need a protein, right? In most cases, we can hope that we might have a crystal structure, or in particular, we might have a docked pose. So again, this might be a protein where we have docked the molecule in that particular binding site. And now we want to check, how good is the binding site? I accept that the docking pose is just a rough guess, but can I use the computers to get a more accurate answer? And in most cases, we can simply by applying that free energy cycle that you remember. Remember what we had? So we had the protein with the ligand bound. And then we had the protein and the ligand separately.  And finally, we had the protein and the dummy separately. And then we needed to get this part for the binding up here. We calculated these two legs instead. That is turning the ligand into a dummy, either when it's bound in the protein or when it's out of water. Today, this might take a day or so on a reasonably fast workstation. But the point is, a supercomputer can have tens of thousands of processors, meaning that we can run through not a billion compounds, but possibly a few hundred thousand or so. And in particular now with COVID, that is actually done in very large scale. For instance, in folding at home, four docked poses of small compounds bound to the spike protein or the protease, for instance. The challenge here is that while it's better than docking, it's still usually not as good as experimental values. At best case, I would say that you can get to an accuracy of two kilo calories per mole or so. But that's sorry, one kilo calorie per mole or maybe half a kilo calorie two kilo joules per mole if you're really lucky. It turns out that there are two reasons for this. First, there are some fundamental shortcomings in force fields and everything. There might be polarization involved, changes in charts that the code simply can reproduce. And then there are of course also the motion in the protein. The docking certainly doesn't include that. We get a bit of it in the simulation, but it's not perfect. The other challenge here, if we're doing this turning a very large ligand into a dummy, this is going to be still going to be a relatively complicated process, even though it's easier than this one on the top. So it will be noisy. And that in particular means that it's very difficult to get the exact absolute binding energy. If I'm literally taking my ligand and moving it from water into the protein, there is going to be fairly large. However, when I've done this for one ligand, it's much easier to calculate a series. That is, if I replace say one carbon here with a hydrogen or something, that's just a small change from one ligand to the next ligand. And that type of series, they're much easier to calculate. And in this case, we get a fairly nice correlation. The correlation is not always that good. This is another example for an ion channel. Actually, the correlation here is nice, but do you see the difference between the y and x scales? The correlation is beautiful, but there is an offset of several kcal per mole between them. And that is exactly due to that. It's difficult to get the absolute binding free energy right from a simulation, but it's somewhat easier at least to get the relative binding energy of a series right. These are very usable results and that will help us to rank at least a handful of compounds. And as computers get faster and faster, who knows, in a few years, we might be able to screen through a million compounds in a day or so. More slow and the development of, say, GPUs here is certainly helping us.


Welcome to this section of tutorial 4, Image Statistics in Python. So, till now in the previous section, we have been trying how to do graphical analysis of data using 1D, 2D and 3D plots. And we also understood how to summarize the information content in a data using box plots, histogram, relative frequency histogram and also we just played around with empirical distributions pdf and cdf. Towards the end, we also discussed about how to plot scatter diagrams both in 2D and 3D as well as how to fit a linear regression line and display the same along with r square value. So, in this part of tutorial 4, we shall try to analyze how to perform hypothesis testing as well as how to deal with autocorrelation particularly with respect to time series data which is predominant in hydrology and water resources engineering. So, just to give you a preview, we finished part 1, part 2 and part 3 and now through this section of the tutorial, we are going to focus on part 4 where we shall try how to do hypothesis testing that is student t test for mean as well as f test for variance and how to deal with autocorrelation and lag plots. Now, before I begin hypothesis testing, typically we collect sample data, try to generate statistics from the sample data and then we use this information to infer about population parameters. So, before I start hypothesis testing, I want to make a clear distinction between population and sample because in hypothesis testing just to reiterate, we collect the sample data and using the sample data we try to generate statistics. Now, the statistics can be mean or standard deviation or variance and using them we try to infer about my population parameters. So, say we assume a certain value for population mean. So, to test the validity of our assumption after collecting sample data, say we need to find out the difference between the hypothesized value and the actual value of sample mean. So, in hypothesis testing, we usually have something known as a null hypothesis that refers to the assumption which we need to test which is denoted by H naught. And, if our sample results fail to support the null hypothesis, we must conclude that the next that is alternative hypothesis is true which means whenever we are rejecting the null hypothesis, we are accepting the alternative hypothesis which is symbolized by H 1. So, just again in the screen that is present in front of you, what you see is the population mean variance and standard deviation and the sample mean sample variance and sample standard deviation. So, the whole purpose of hypothesis testing is to make a uniformed judgment about the difference between a sample statistic and a hypothesized population parameter which is why the slide is shown. Again, the sample statistic can be mean or variance or standard deviation and typically in hypothesis testing, we support it with p value. In this tutorial, we shall also show you how to arrive at two-tailed test for mean and variance. Now, the significance level typically in hypothesis testing indicates the percentage of sample mean that is outside certain limits. With this background, let us try to understand how to perform hypothesis testing in Python. So, here we will be discussing about two typical cases, case one is nothing but two sample test for mean using pooled t-test. Without going too much into the statistical part, let me try to show you how the commands are written in Python. As I mentioned earlier, in hypothesis testing, we always try to check whether H naught that is a null hypothesis is acceptable or whether H 1 that is the alternative hypothesis is acceptable. So, the first step is I am going to define the null hypothesis and the alternative hypothesis. So, here as a data analyst, I am going to assume that observation from each population are normal. So, we have two observations and null hypothesis says mean of both the observations are equal and alternative hypothesis says that means are not equal. Now, so the commands I am going to write is I am going to generate rv1 that is random variable 1 using stats.norm.rvs. And for this, I need from SciPy, I need to import the stats package, which is what is written which means all the statistical functions are located in the sub-package known as SciPy dot stats. So, that is why we are importing stats and then I am generating random variable 1 and random variable 2. So, here default underscore RNG is nothing but the constructor for the random variable class generator. You know, there are several means by which one can construct a random number generator, one such means is shown here. And stats.norm.rvs is nothing but random variates and stats.ttest underscore ind. So, this is the function to calculate the t test for the mean of two independent samples. It is basically the two-tailed test for null hypothesis. Again, assumption is that populations have identical variances by default. I also want to calculate the p-value. p-value is nothing but the largest significance level at which we would accept the null hypothesis. So, I am going to try type the commands that should be p-value. So, if p-value greater than 0.05, it should print accept null hypothesis. Again, when we are saying that we are accepting null hypothesis, it simply means that the sample data does not allow us to reject the null hypothesis. For this section of the tutorial, I am assuming that you will be having a fairly good idea of the basic statistics. So, what I will do is I am changing the location and then trying to see the result. It says accept null hypothesis which means both Rv1 and Rv2 are having same mean. So, in the same code, I can also change the location to say 20. I can change to 10 or 5 and then check. You will get the result as reject null hypothesis. So, what did we do? Instead of taking actual dataset, I have created two datasets, two random variables Rv1 and Rv2 both are normally distributed and then we try to check whether the mean of Rv1 and Rv2 are same or not using pooled T test. Now, similarly, we can also perform two-tailed test for variances. Two-tailed test for variances. So, my first step is to define what is the null hypothesis and what is the alternative hypothesis. So, null hypothesis I am going to define it such that the two variances are the same, two variances of what of Rv1 and Rv2. Alternative hypothesis just reverse the two variances are different. So, this is an inference about the population variance. Remember, I made a distinction between population statistics and sample statistics in the beginning. So, I am going to use np.var which computes variance of a given data. This step calculates the f value. Dof is nothing but the degrees of freedom, len returns the length of a list, a string or a dictionary etc. So, I am trying to define the degrees of freedom of Rv1 and Rv2 but as before I need the p value. What is p value? It is the largest significance level at which we would accept the null hypothesis. So, here I am going to use the stats.f.cdf function. I need to print the f statistic and p value. So, as before I am going to type if p value is greater than 0.05 print accept null hypothesis else print reject null hypothesis. So, there it is run to display the results of f statistic p value and the final inference that is accept null hypothesis. So, in a similar manner Python allows us to perform hypothesis testing, one-tailed test or two-tailed test. So, two sample codes were shown as part four of tutorial four. Moving further, let us now look at the fifth part of this tutorial that is autocorrelation, partial autocorrelation and lag. So, in hydrology we deal with time series data. Autocorrelation and partial autocorrelation are heavily continuously used in time series analysis and in forecasting because they graphically summarize the strength of a relationship. Here observations in a time series with respect to observations at prior time steps are used. So, to define autocorrelation refers to the correlation of a signal with itself in space or time. We saw what is correlation in part one of the section, isn't it? So, now let us try to achieve the same in Python as before. I am going to import numpy as well as matplotlib.pyplot. Let us assume a periodic signal. Let us use either sin theta or cos theta. So, for this example, I am going to use a periodic signal np.cos and what I will do is, let us try to corrupt this signal with noise. So, I am trying to synthetically create a data, corrupt it with noise using np.random.random, len gives the length as mentioned before and autocorrelation can be plotted using the plt.acorr function. Let us try to display the labels x label and y label. I want both the plots to be displayed one above the other. So, I am going to try to use plt.acorr function that takes x that is the synthetically generated periodic signal as input. I am going to keep the max lag as 50. I am going to keep the plt.grid as true. Typically, when you have lengthy lines of code say suppose you made a mistake somewhere, you know somewhere there is a syntax error or some other error, the code is going to prompt you so that you get to check and correct it before you run the code. And by now, I am assuming that you are familiar with the plt.grid or plt.x label and y label commands because we have been covering it over the series of tutorials. Let me also type the limit of x from say 0 to 100 and as before label it, I have to check and correct the spelling of label. So, x is shown and autocorrelation is shown below it. Now, let us try to increase the periodicity. Let me try to multiply the variable with 4 just to show you different ways to understand. You see lag as the x-axis and the plt below, you see autocorrelation as the y-axis and the variable that we generated is plotted above x as the y-axis and lag as the x-axis. A simple example using synthetically created dataset for us to understand what is autocorrelation and what is lag. So, just to reiterate autocorrelation refers to correlation strength of a signal with itself. It can be either in space or in time and particularly in hydrology and water resources, it has a very prominent part because it is used in time series analysis and also in forecasting. Moving on, Python also allows us to use certain tools like some packages in stats models and stat tools and it will be useful for us to understand how to use these as well. So, let us try to import the functions ACF and PACF. ACF stands for autocorrelation and PACF stands for partial autocorrelation. Let us try to import it from statsmodels.tsa.stat tools and for plotting the same, I am going to import plot underscore ACF and plot underscore PACF from again statsmodels.graphics.tsa plots. So, partial autocorrelation function gives us the partial correlation of a stationary time series with its own lagged value. What I mean by lag is here I am going to keep n lags as 5, number of lags as 5. What I mean by lag is lag 1 autocorrelation is the correlation between values that are one time period apart. So, that is the meaning of lag. Again, I am going to keep the lags as 5 for both x and y. Now, as we have calculated both AC and PAC for x and y, let us try to plot and visualize the results how they look like. As before, it gives us several options to print the results as well as, you know, beautiful ways in which you can graphically represent the results and change the font size or color of graphs. Let us try to use a few of these options. I want to specifically print the title as autocorrelation of precipitation up to 5-day lag and partial autocorrelation of precipitation up to 5-day lag. So, for the next two lines, the there is only a slight variation. So, in the interest of saving time, I am going to copy the commands and make the changes wherever necessary. So, instead of precipitation, it is going to be temperature because by now we are aware that when we started the tutorial, we started with two variables of precipitation from I mark and temperature from era and rim. Small correction in spellings, x is precipitation and y is temperature. I get to see the autocorrelation function of precipitation up to 5-day lag. I can see the values printed here. The autocorrelation function of precipitation and partial autocorrelation function of precipitation followed by the same for temperature up to 5-day lag. Though we have the results in the form of numbers, let us try to visualize how they look like. So, as before, I am going to use the plt.subplots command 2, 2, 2 rows, 2 columns, figure size. Let me use the plot underscore ACF function and it was taken from, if you remember, statsmodel.tsa.statTools. It was imported from statsmodel.tsa.statTools. What I am doing is I am specifying the variables, the title and where I want to see the figure displayed. 00 is first row first column towards the left, 01 is first row second column and as before, because there is only a small difference in the commands in the interest of saving time, let me try to paste the commands and then make the changes wherever necessary. So, in the third and fourth lines, only the variable name is changing that is y which stands for temperature. So, let me make the changes and I want this figure to appear in 10. Let me make those small changes y and again 01. This is going to be the last figure and then partial autocorrelation function of temperature. Let me try to use the plt.sctp set p function and display the x label and finally use the plt.show function. So, there you see the results. The first figure gives us the autocorrelation function of precipitation, the one towards the right side that is first row second column it gives us partial autocorrelation function of precipitation and similarly we have the figures representing temperature. Simple examples so that when you work with an actual time series data, you will be aware after this tutorial that several functions exist that help you to carry out these operations to help you to analyze the autocorrelation and partial autocorrelations and also to that help you to understand about hypothesis testing. So, as part of this tutorial, we started with how to visualize a set of data. Now, this data can be synthetically generated data which is what we saw in this tutorial. We try to synthetically generate the data sets using mathematical functions of sin theta and cos theta and we also try to add a little bit of noise to see how the spatial plots look like. We covered the visualization of data using box plots and histograms and we also had a fairly good idea about the empirical CDFs, what libraries have, what functions that help us to plot the empirical CDFs. And finally, we started with scatter plots moving on to linear regression and ending it with hypothesis testing and trying to understand autocorrelation and plotting the same for two different variables of time series of rainfall and temperature. Let me hope that you found this tutorial informative. I will see you in the next lecture. Thank you.