Hi everyone, my name is Dakchita and I'm going to talk about building low-error efficient computational extractors in the CRS module. This is joint work with Ankit Garg and Yael Kalai who are both at Microsoft Research. In cryptography we nearly always need access to perfect sources of randomness. But such perfect randomness is really hard to come by in practice. Typically randomness is derived from physical sources which may be imperfect or sometimes the adversary may be obtaining partial side information about the secret randomness used by honest players and thereby skewing this randomness. And we have a whole lot of evidence including most recently worked by Breitner and Heninger who computed several Bitcoin private keys that shows that imperfect sources of randomness can lead to explicit attacks on cryptosystems. So a very natural meaningful question is can we convert weak sources of randomness into strong ones? Now let me next talk about what I mean by a weak source. So a weak source is represented by a distribution on n bits that has min entropy k where k is something that's much smaller than n. Now min entropy k corresponds roughly to each point in the distribution being selected with probability at most 2 to the minus k. An example of a weak source with min entropy k is the uniform distribution on a subset of size 2 to the k of the space of 0, 1 to the n. So going back, randomness extractors are sources that help convert these weak sources of randomness into nearly uniform sources. Say we have a weak random source with k bits of entropy on an n-bit input space. Ideally we would like to have a deterministic algorithm that converts this into a nearly uniformly random source on n bits where m can be as large as k. Unfortunately, it turns out that this dream deterministic extractor simply cannot exist even for really weak parameter settings. For example, when we just want to extract one single bit of randomness and the source has min entropy n-1 and let's say we want the resulting distribution to have a statistical distance of at most 0.25 from the uniform distribution on a single bit. Even in this really weak setting, it turns out that such extractors cannot exist. So what turns out to actually be possible is a variant that takes the help of a short uniformly random seed to convert an n-bit source with min entropy k to an almost k-bit uniform random distribution. This is pictorially represented on this slide as an algorithm that on input source and seed outputs a distribution that is close to uniform. In fact, the size of the seed can actually be much smaller than the min entropy of the input source or the size of the output source. And Guruswamy et al showed that the min entropy can actually be as small as polylogarithmic. The size of the seed can also be polylogarithmic and in this setting the error can be a negligible function of the size of the source. And finally, the definition of a seeded extractor can be further strengthened to what is called a strong seeded extractor where the requirement is that the output distribution of this extractor be statistically indistinguishable from uniform even given the seed. Now one problem with seeded extractors is that you need this uniform independent source of randomness called the seed and it turns out that having access, if having access to uniform randomness is difficult in the first place, then getting access to such a seed may be hard. So can we relax things so that the source and the seed can both be imperfect? It turns out that the answer is yes and this question motivated the setting of two source extractors where there are two weak sources of randomness that have a certain amount of min entropy each and the only assumption is that the two sources are independent but neither of the two sources needs to be uniform. Now a two source extractor is then a deterministic algorithm that given two independent sources with sufficient min entropy outputs a distribution that is close to uniformly random. Now for a long time we only knew how to extract randomness when at least one of the sources had min entropy about half of n and this was due to the results of Ra's and Burgein. A breakthrough work of Chatopadhyaya and Zuckerman broke down this barrier and built two source extractors in the setting where both sources can have polylogarithmic min entropy and in fact these log factors were further improved in several subsequent works but in all these works that go to polylogarithmic min entropy the running time of the extractor turns out to be inversely proportional to the desired error and in particular this means that the error cannot be a negligible function of n as this would lead to a construction that grows super-polynomially with the size of sources which would be an inefficient construction. So the dream especially from a crypto point of view would be to have information theoretic two source extractors where both sources have polylogarithmic min entropy and the error of the extractor is negligible in n or alternatively the run time of the extractor is inversely proportional to log of 1 by epsilon and not 1 by epsilon itself. Now this as such appears to be hard to achieve and it's unclear if this is even possible in the information theoretic setting. So we ask is this dream any easier to achieve if we make computational hard tense assumptions and use cryptography. Now prior work has indicated that if the assumptions are sufficiently strong then the answer is yes and in particular assuming an optimally exponentially hard one-way permutation prior work of Kali et al. showed that one can obtain negligible error but it's completely unclear whether such one-way permutations even exist and in fact we would like to rely on well studied cryptographic hardness assumptions. Now on the other hand when trying to relax assumptions and get a construction from standard cryptographic assumptions many known techniques seem to hit a barrier. The barrier is the following any reduction to an efficient challenger assumption would need to embed the challenge somewhere in the view provided to the adversary. Now this view is basically the result of sampling from arbitrary source distributions with sufficient entropy and applying an extractor to the samples. It's completely unclear how to embed an external challenge into these arbitrary source distributions. So therefore we introduce another relaxation the common random string model. This involves a trusted setup phase whereas a random string is sampled uniformly and fixed once and for all. Then the source distribution can be sampled arbitrarily depending on the common random string. Now this differs from the setting of seeded extractors where crucially the source and seed are required to be independent of each other. So what this model basically does is reduce the need for true randomness to a single one-time requirement on the common random string and crucially sources are now allowed to depend on this string. So in this model our main theorem is the following assuming sub exponential hardness of the DDH assumption there exists a constant between 0 and 1 such that there exists a two source extractor in the CRS model for two sources X on N1 bits with min entropy K1 and Y on N2 bits with min entropy K2 such that the extractor has error epsilon where the size of the first source is omega in N and N is considered as a security parameter. The size of the second source is N to the C where recall that C is a constant between 0 and 1. The first source has entropy N1 to the C and the second source has entropy polylogarithmic in N2 and finally the error is negligible in N that is the output of the extractor is computationally indistinguishable from a uniformly chosen random bit. Now here I want to point out that in the computational setting we have the following restrictions the sources are efficiently sampled and we only care about computational indistinguishability of the output of the extractor from uniform. Also note that we focus here on only extracting a single bit of randomness but actually our techniques can help obtain nearly K2 bits of randomness. So our construction of computational two source extractors proceeds in two steps. First we build a non-malleable extractor for high entropy sources in the common random string model and second we compile this non-malleable extractor for high entropy sources to a two source extractor for low entropy sources and both these steps give efficient constructions with negligible error. We will now go ahead and define non-malleable extractors a notion that was first considered by Zimbowski and Wicks. Now a non-malleable extractor can either be a seeded extractor which means it can involve an entropic source and a uniformly random seed or it can be a two source extractor which means it involves just two independent entropic sources. Now for the purposes of this talk we will only consider strong seeded non-malleable extractors for which in the computational setting we have the following definition. So in terms of syntax a non-malleable extractor is exactly like a seeded extractor which means that on input X sampled from a source distribution and a uniformly random seed the non-malleable extractor outputs a sample from a distribution but the security requirement is much stronger. This requirement is that the output of the non-malleable extractor be indistinguishable from uniform even given the common random string the seed and access to a special oracle. Now this oracle can be queried on any string Y that is not equal to the seed and on such a query the oracle returns the output of the non-malleable extractor computed on X and Y. Note that a polynomial time adversary can query this oracle only an arbitrary polynomial number of times. So moving on to our construction our construction of non-malleable extractors satisfying the definition that we just discussed is inspired by the construction of leaky pseudo random functions of Braverman, Hasidim and Kallai. Specifically we will assume the existence of a family of collision resistant hash functions and a family of lossy functions such that each function in the family is either lossy or injective and moreover lossy functions have image size that is much smaller than the size of the domain whereas injective functions have image size that is equal to the size of the domain and finally the lossy function family has the additional requirement that lossy and injective functions must be indistinguishable from each other. So now the CRS of the non-malleable extractor consists of a key for the collision resistant hash function and a set of 2K injective functions drawn from the function family F. Here K also corresponds to the output domain of the collision resistant hash function. Now the non-malleable extractor on input is CRS a source X and a seed S first interprets the CRS as consisting of a hash key as well as 2K functions then computes a hash of the seed S using the hash key from the CRS and let's denote the output of this process by S' Next it uses S' to sample K out of the 2K functions that were in the CRS specifically if the first bit of S' is 1 it picks F11 and otherwise F10 more generally if the ith bit of S' is 1 it picks FI1 and otherwise picks FI0 Next it applies the composition of all the functions that were picked to input X and the output of this process is denoted by X' and finally the output of the non-malleable extractor is the output of an appropriate 2 source extractor applied to X' and the original seed S Now the required 2 source extractor needs to have negligible error but we can allow one of the sources which is S to have high entropy so since we simultaneously don't require low entropy and low error at the same time such a 2 source extractor can be obtained in the high entropy low error regime based for example on Raz's construction So I'm going to leave the construction there for your reference and move on to discussing the proof intuition Recall that the adversary A has access to an oracle that on input any Y not equal to the seed S generates the output of the non-malleable extractor on input X and Y Moreover the adversary is given the CRS, the seed and value Z where Z is either sampled as the output of the non-malleable extractor on input the CRS, X and seed or Z is sampled uniformly at random and the adversary wins the game or breaks security of the non-malleable extractor if it can distinguish between these 2 cases To argue that the adversary cannot win this game we first observe that the adversary given seed S actually cannot query its oracle on any input Y such that S' which recall that S' is the hash of S is equal also to the hash of Y so essentially for any input Y that the adversary queries the oracle with the hash of Y is going to be different from S' and this is guaranteed by collision resistance of the hash function family Next we note that we can actually change the CRS to ensure that all functions indexed by S' are injected and all the other functions are lossy Now by property of the lossy function family this means that the image size of all functions not indexed by S' is going to become much smaller than n1 So what this means is that for every query of A to the oracle at least one of the composite functions in this sequence derived from hash of Y will be lossy and this is good news due to one of these functions being lossy X' will come from a very small space in all of the adversary's queries and this essentially means that this oracle can be simulated given only the CRS the value S' and small leakage G of X on X Now since S' and G of X are really small leakages this means that X and S actually have sufficiently high entropy left even conditioned on all the information needed to simulate this oracle As a result we can conclude that the output of the underlying two source extractor and therefore that of the non malleable extractor is going to be indistinguishable from uniform even given this additional oracle Now I've thrown several technical details under the rug there due to lack of time but we are essentially able to formalize those ideas to obtain seeded non malleable extractors in the CRS model Our next step is to compile the seeded non malleable extractor into a two source extractor for low entropy sources and I will now say a few words about how this is done Now this follows a template due to Benaroya, Chatopadhyay, Doron, Li and Tashma who take any non malleable extractor for high entropy sources or a seeded non malleable extractor that allows an adversary to make roughly T tampering queries such that the size of the seed does not grow too much with T and they combine this with dispersors to obtain a two source extractor for low entropy sources Now what we just described was a non malleable extractor with high entropy sources and T tampering queries but where the seed length is essentially independent of T which is great but this is still insufficient to instantiate the compiler of Benaroya et al because what they needed for their compiler was an unconditionally secure non malleable extractor and what we got was only computationally secure Additionally, our non malleable extractor is in the CRS model whereas the Benaroya et al transformation is for the plain model and this leads to additional complications in our setting Nevertheless, we are able to prove that the variant of their transformation also works in the computational setting in the CRS model and proving this actually turns out to be highly non trivial A key barrier here is that the Benaroya et al technique actually relies on an inefficient reduction that is, given any efficient adversary that breaks the two source extractor Benaroya et al build an unbounded adversary against the non malleable extractor Our technical contribution is in making this adversary against the non malleable extractor computationally efficient To do this, we rely on a leakage lemma due to Gentry UX Jechef Petrizzac and Chum Louis and Paz to actually efficiently simulate the inefficient reduction of Benaroya et al This actually turns out to be technically very complex to implement and requires sub exponential security of the non malleable extractor and this is also what ends up imposing the requirement that the sources be unbalanced Unfortunately, I'm out of time so I'm not going to be able to get into more details about this but I will conclude by reiterating our main theorem which is that under the sub exponential hardness of DDH the two source extractor in the CRS model for unbalanced sources with low main entropy and low error and where the sources are required to be efficiently sampleable and the security is only computational We also obtain non malleable extractors with similar parameters in the computational setting again in the CRS model and here I want to point out that a follow up work due to Agarwal et al obtains two source non malleable extractors that are incomparable to ours but in particular their tampering model is stronger in that they allow both sources to be tampered with Let me wrap up with some open problems The first interesting problem is whether we can completely get rid of the CRS and rely at the same time on well studied cryptographic hardness assumptions This would of course involve getting around the barrier that I discussed towards the beginning of this talk Another question is whether we can obtain two source extractors from polynomial hardness assumptions as opposed to the sub exponential assumptions that we required in this work and finally I think it would be interesting to explore relationships of these new improved non malleable and two source extractors with leakage resilient codes non malleable codes and other types of cryptography That's the end of the talk Thank you


यह वहाँ है, मुन्त्रीष बाद बाद है, पच्ध कोना और लग़ातान कोस मैथद लग़ागे है। जो साथा टीखुजे तीखौद सानप्रासें बाद है जो ईवर लेईउगे करगाद होगी, तो इस साथा झों यहद लिए अग़े करगागे भู้ग। under this method acquisition of trade stock is viewed as the initial steps in two-part transaction it's re issuance and the second step is completion of the transaction mean how the transaction is going to complete now let's see you have issued like example one thousand share common share ordinary share our piece hundred each power originally at 110 try to understand here normally if the company is very good then it can sell on premium instead of share power initially they basically sell all the power but if the company is old and wants to issue new share then it can be issued on premium instead of power but no way company can issue shares at a discount bond can be done on discount share discount can not be issued okay you have issued and after that you have bought 100 shares from the market in 112 now see you have issued in 110 but when you buy the gas in the market then you have to pay 1200 rupees for 100 shares so after that what happened in the third transaction is that you have resued 10 shares which were trading stocks on 12 so if you have sold it in cost to cost then there is no impact in your equity then you have issued at 130 so you have sold it in 112 and you are selling it in 130 so you have a profit gain here and next is that you are selling it in 98 so here you bought it in 112 so you are selling it in 98 so you are losing 14 rupees now 10 shares of stocks are re-issued at 105 and after that you have re-issued it at 105 now you have to see how their entries are recorded in the books number one issued so see 1000 shares 110 per cash debit share capital credit and share premium credit nothing happened so it will go into cash and in equity share capital and share premium but because you have required 100 shares on 112 so see the trading stocks debit means you cannot do the share capital debit straight away you will debit the trading stock and the payment you paid 11,200 per cash and now when you are going to re-issue remember that you have 100 trading stocks so from this you have issued 10 on 112 so you will still have 90 so the issue that you have cash to the same price then cash debit and trade stock credit in this gain or loss will not come because you have sold it in cost to cost next what you have issued is on 130 so see in this case 10 multiplied by 130 you have got 13,000 and trade stocks will go to 112 cost method remember so you have got the balance on the premium on the trade stock this also becomes the equity part in the balance sheet as the share premium is in the same way this premium on trade stocks also becomes the equity part then you have issued 98 now see here you are getting less money the cost of 10 shares was 112 according to the price it will be 1120 credit but cash debit is 980 the difference will be debit in your trading stocks because there you have the share premium account then from that you will minus it then you re-issue the trade stock is talking about 105 so see here cash you have debit 105 case and credit you have to do the trade stocks from 112 remember this you have to change this now the problem of the difference is that you have Rs 180 you have to see where the figure of 180 comes from see from the last slide you have 180 premium in this which you have sold in 130 this is the premium you have to see how to utilize this premium where you have to reverse the premium because you have sold 105 okay so the difference is gone in 40 and in the same way when you have sold more then it is in the retained earnings in the trading stocks that is the difference of 70 that you have taken in two portions one that you have debited the premium and one that you have debited the retained earnings actually the point is that it is the share of the share and the equity but remember that when you re-issue then after that whatever money you will get will become profit so the difference is that now what is the balance of the trade stock please note down I did not tell the calculation here but the figures have told that total trade stocks you had bought 11000 200 okay this means that you have sold four times the balance which you have left 448 in minus so balance 6 720 will be reduced from the equity that means this will be minus from the equity that means you will not see this in the asset remember that it is always minus from the portion of the equity thank you very much


What I wanted to tell you about today is we did actually do a study. We implemented what we came out of the study and I want to hear what we're now going on to. So first of all thank the National Vet E-Learn Strategy and the New Generation Technology Funding which actually funded the study a couple of years ago now. What we did for the study is we looked at a lot of different learning analytic tools, how they were going to interact with our Moodle system and which ones we thought would actually be able to implement in the long run and actually use with Moodle. So it was fun, I'd like to say, most of the time getting the different plugins into Moodle or using them around Moodle was often a little bit trickier than we thought even though we weren't using it in a live environment. So that was something that we did sort of stumble over a little bit. Getting data into a dummy environment to see how it's going to work was also something that sort of was a little bit tricky. But in the end we had some great successes with a couple of the plugins. So in the end we've gone with the Progress Bar which we've chosen because the students, one of the things that we got with the feedback with them was they really wanted to have something visual to show what they were doing. So we do have the course content lock-in and so students can see from that what the teacher set up to actually show them what they're doing and how they're doing with it but they wanted something that was visual which is another one on from that. The other one that we're using is Gizmo and so Gizmo's been an interesting plugin. One of the biggest reactions we had from it was we've got a teacher who is into all the animated presentations. So Animoto, something tunes. And he makes really long ones, inappropriate ones that you get like four lines of information out of watching 15 minutes and for years we've been telling him it's not a good way to teach. And finally he looked at the Gizmo and went, how come they've watched the first two videos and they don't watch the rest?  So it was really good for him that he could actually have some evidence to critically reflect and then move on from that as well. So what we found especially with the Progress Bar was the teachers were very innovative and used it in different ways and we sort of thought they might. At CRT because we are a vet institution we do tend to do something that we call cross-listing or clustering of courses. So we might have say 15 different competencies that are involved in a qualification and they're teaching that in a semester and we'll put them all into one Moodle course to actually teach it.  So it was actually one of our plumbing teachers that went, hmm, can I have more than one progress bar? And we went, yeah I suppose so. And suddenly he was putting one in for each of the competencies. So then the students knew exactly what they had to do for each competency and they could tick it off as they were going. The students actually really loved it because they could see how they were going and what they had to do in each one and they don't often do them linear. They do actually jump forward and back because it'll depend who the trade teacher is on the floor, which practical component they can do. So they might be doing theory from something else because the teacher who's practical on the floor isn't doing what they're up to and so they can jump back and forwards like that. So they found it was of great benefit to them to find out to know where they're up to. Now the gizmo picture there is the darker the colour is the more the students use the resource. It's been interesting for teachers to see how they actually, how many people are looking at resources. When we're doing the study you can see down the side there's the grade. So it's a graded subject so it goes from a P down to a distinction. A WA is that they attended but didn't actually finish but did actually engage. The darker the colour is on the gizmo the more that resource was looked at. So one of the things that we were doing was looking at how many times people hit on certain resources and whether that affected their grade. It did a little bit. The people who failed obviously didn't do enough to pass and obviously didn't look at the right resources or they might have actually had a more successful outcome. And between a pass, a credit and distinction there was a little bit of difference. So distinction and credit students often did look at resources more often. But then again it was also some pass students that probably if they had a little bit more support from teachers would have actually been more successful.  So that was interesting as well for the teachers to be able to target students who were looking at something but still not getting the grades. Why aren't they getting the grades? Is it a problem with the resources? Is it a problem with the student? One of our canning teachers had a beautiful course. She had so much content in it she tried to download her whole brain into the course. Lots and lots of different resources. They didn't need three quarters of it to actually pass. As she worked out when she looked at her gizmo for the semester. So she could see that the students were passing and they were looking at about a third of the material that she had up there. So she went through and paid back her course to exactly what they needed to know to be able to pass. And she was suddenly getting rave reviews about her course. So it was really good for her to self reflect on what she's got in there and to actually move forward from there. So this is the plumbing teacher that had all the different things in there. So please excuse the student names. Whoops. But yeah so you can actually see how they can actually go through and have a look at what they're doing and where they're doing things and if they've been successfully complained or not. One of the problems we had with the teachers is they wanted to put absolutely everything as a must do. So the progress bars were looking really busy and unless you actually moused over them you couldn't tell what you still needed to do because it was such a busy little toolbar there. The toolbar doesn't get any bigger. The little gaps just get smaller, the more resources that you have in there. And so that was a little bit of a cultural change the teachers had to do because they had to then make decisions about what they thought was the important things of their courses. And it's amazing how quickly once they've worked out the important things they can actually get rid of a lot of the other content because if it's not really important do the students really need it to pass. So the student comments have been that makes me feel good when it goes green, which is always nice. Most people have that every time they're sitting in a red light. They also love it so they can see what they're doing and what they have to do next. And so that was, it's a really important thing for the students to have that visual because we've had it with the course completion block but mostly students didn't even know that they could tick on that or click on that to actually get more information. We haven't made the progress bar as something that is automatically in the courses yet. We did do that with the course completion block. So that's an automatically now system-wide in every course. Teachers actually have to get rid of it if they don't want to use it rather than having to add it in. But the progress bar is something that we're looking for probably next year that will actually make as a standard item in every course. So if the teachers don't want to use it, they'll actually have to take it out. So with the teachers in Gizmo, made a big difference to their course design which I said before and yeah, I can't believe I spent all that time on those resources. I need two students in the class used it and the majority of students passed. One of the things that we're going to do from here is and I'm actually hoping that you guys might be able to give me some ideas and some help with this, is because we've worked out that a lot of the resources that teachers are developing probably aren't the best type of resource for the course that they're teaching and they don't need a lot because they're all over teaching, they're over assessing, they're spending way too much time actually marking and everything as well and we need to get that so it's actually more realistic. So what we're going to be doing this semester is we're going to be trying to benchmark what a good course is and what a good resource is. So we're doing another bit of a research project that we're trying to get all the students involved in as well as teachers in set areas to actually look at how we can benchmark the courses and the resources to then advise teachers how to actually go about developing. So we're hoping that the research we do this semester will actually enforce all of our teacher PD that we do next semester. So anybody got any really good ideas how we can actually go about benchmarking resources? I'll tell you how we're planning to go about it. We've done a little bit of a research already, just a literature research on it and there doesn't seem to be too many things out there that give us a great idea of benchmarking a resource. It all tells you how to develop a really great resource which isn't really what we need because we need a good resource for that. We're going to be doing focus groups with the students and we're going to do those in specific areas so it would be like the ICT students would do one, the hospitality students would do another one. We're not sure how many students would actually need to make that viable. One of the things that we were doing when we rolled out the learning management for the first time, the learning management system, is we got hundreds of students through to actually look at the system and tell us what they liked, what they didn't like about it and do you know what, we could have done it with one. They all told us the same thing. It was just in different words. So we probably actually could have done that with one student rather than hundreds. We're also going to be doing the same thing with teachers. So getting teachers together, showing us their good resources, showing us the ones that they think are fantastic, the ones that need work, showing us those as well. So we've got something for the students to compare and we're also going to do a desktop audit which is my team's going to absolutely hate me for because it'll mean they're going to get probably a couple of hundred courses each that they'll have to have a quick look through to decide what is good and bad about the courses and what's currently in courses so then we can know how we're going to actually upskill teachers from them. So has anybody done it before? We've done not so much on the general course but on the video resources. We actually moved to YouTube and one of the things I noticed once we started using YouTube was the stats give you very detailed information on how much of a particular video we watched. We found some videos people watched on average it was like 180% so they've watched it more than once. Again, it's such a good video. And other lecturers who thought they were really, really good had like 12% on average of their video and so that was really good for us to work out in terms of how people were shooting videos or how good the lecturers were in that kind of stuff. So what sort of information did you get out of that? Was it the length of the video that's good, the content that's desirable? There's a bit of it. I mean the length did have a factor on the drop off but also people who we thought were good, when people are only watching 12% of your video, something's wrong. Yeah, so that was good. So that gave you what you need to change. Yeah, just as far as video resources. I can't really offer anything on that. That's alright. Somebody else was, yeah. We actually just go back to the basis and use the assessment requirements that are provided on training.gov.au because our trainers will give us tons of information and they'll say put this, put this in. But our instructional designers go, it's really nice to know what do they need to know. Because our trainers work on a different model too, where we go out into the workforce and actually work within their workplace environment. And there they can tell them they're nice to know. But on their online learning, they need to know that they can actually do the assessment so they can be marked as competent and if it goes through an audit, then it can say yes, they're actually marked off the assessment requirements and the performance criteria. Yeah, we don't have too much problem with them during the right assessment. We don't have instructional designers, though, to develop our resources or make our courses. That's what the teachers do. Because we've got, I know, 54,000 courses, a couple of hundred, well, a couple of thousand teachers, as well as 74,000 students or something. So, yeah, that would be very nice. Take the performance criteria back to the teachers and they can just go, hey. Yeah. Which is good. Which is good. He's actually provided a good assessment tool to connect your unit in the mood or go, here's the elements and performance criteria of that unit. Do they map questions? Yeah. We do that. So, we already do that with the teachers and it's amazing how they say, no, no, this has to inform that. So, yeah, they're very good at sneaking little bits in that they probably haven't been counselled on doing it. I was going to say, you know, eventually I don't have anything on that subject. I had a quick look through their databases and I couldn't find anything that tells me a good methodology even to actually go about benchmarking for resources and courses. So, we all think we know what's a good course and we've recently just updated our subject guide, which is, you know, what's in the course and I took that to the student association as well with a group of students and said, well, you know, what do the students want? And they went, well, we don't want it. All we really want is we want to know our assessment and our teacher name other than that. We don't really care what we're doing weekly as long as we know where to go. We don't care about all the support systems that everybody says there must have information has to be in this guide. So, it was quite interesting that they went, yep, just pop it up on e-learn, which is our Moodle and we'll look at it there. Mind you, we need that to report back to ASQA when they don't complete, but anyway. One of the things that we've started doing is putting a feedback with 11 compulsory questions at every course across all of our Moodles must have. So, what we found is we had feedback before but we were comparing apples with oranges. So, we've got 11 compulsory questions that is just about the course and the functioning and the resources and the things that they use within a course. And we compared, so now we're comparing apples with apples. So, I can go to hospitality or business or community services and see what resources the students are using and why they liked them and why they didn't think of that. Yeah, and we've also got the Student Association going around to the end of courses. Does anybody know if in Moodle, you can, because we have the end of course feedback in every course as well, how can I get them from every course into one pool? Develop them all in one course and link them out to each resource. Oh, no. Thank you for your time in the series. Somehow, I remember there was a study just a simple thumbs up or thumbs down with each resource. I don't think Moodle's got it at this time but just getting a vote from each student on the resource. That's not a bad idea. I bet Facebook likes a lot of them would probably like that. Yep. Oh, sorry. You might be able to use just a simple poll just one question as like a yes or no button so if you've just got to agree or not agree yes or no just with the whole question at the bottom. Oh, the bottom of the course or the bottom of the resource? Of the resource. And in that, yeah. Yeah. That might be quicker. A quicker way to do it. Yeah, but teachers might not tell us though when they get those results back. They might hide them if they're not good. Don't you already have a lot of the data? You've got engagement data. Yep, that's part of the desktop order that we're trying to do to actually do that. I suppose the thing that we're after for more of is how to get the buy-in from the teachers because having like we've changed our culture within eLearning and with online learning from where people used it as a repository to now they are actually using it as they're building courses so they're interactive and the students are getting a lot more out of them. But we're looking for information that's going to change the way that the culture is so it's got to be really driven. So just saying like, well, the students all passed this one and this was the good resources that went into it is probably a good place to start but I don't know how well that'll go in the long run and all pulling them out of every course. How am I going to get all that data across Moodle? Add help reports. Yeah? Yeah. Sorry? We just want to ask people have got it working where we've got feedback tools being centrally. Okay, so every feedback tool feeds back centrally or can you turn that off and on? It's based on using conditional questions in the feedback tool. Okay. So I'm not the one who's subscribed but she's in the other lecture but she's in the other lecture. Okay, where are you from? Sorry? Riverenite. Riverenite. Oh, this is good. I'm developing my methodology through my presentation. Sorry. Yeah, the one that's looking behind in the purple. Yep. Were you going to say something before? Yeah. Why did you choose Gizmo? Why did you choose Gizmo? I was looking at a few other things. There's a couple of ones that look at forums only which is actually an add-on to your browser that works and at CIT we do not use forums. Well, we use them as a question and answer for teachers. It's no community building a community of learning or community of practice within the course at all in forums. The students don't seem interested in that and the teachers probably don't have the skills to moderate that and so anything that was looking at just one resource I knocked out pretty quickly. So Gizmo looked across all which was quite good. So I do have a... I suppose a matter of time, am I? I was going to say I do have a little bit of a demo just to show you what it looks like in the course. So you can actually go into... If you go into the program I do have... I've just put a very small course up there on the Moodle Moot site and you can see here that I've actually got a couple of resources in it and some students have actually already come in and done some things which is very nice of them. Other than Michael, he's very slack and has done nothing. So I'll have to have a talk to him about that. So this actually does print off quite well as well. One of the things we like about the progress bar is when it prints off it actually puts the date as well. One of the things that the auditor's really like is the date that they were successful. And so you can see here that some people have done it. So it's very easy to see at a glance how well or how not well students are doing and you can see here I've got more than one. So I've just put progress bars in there for every block which would be doing if we were a cluster delivery. So I'll just see if the gizmo will get up. Gizmo's interesting too because it doesn't give you a live feed of the information so it does have to wait 24 hours because whenever they do something at 2 o'clock in the morning it actually gets all the gizmo data to come in. Gizmo's not something I'd probably use in the future. So like when we actually did it there was nothing else around that we could find from the other research. It's not coming in very well at the moment is it? And it's a bit slow. Live data would be so much better. We're probably going to be looking at doing a data warehouse so we can get the information from our student management system, our learning management system and actually get some better data out of that. So at the moment we can't do that because our student management system doesn't talk to anybody because we've got banner. And I shouldn't say that like it's an apology should I but yeah. Any other banner users will understand. Okay it doesn't look like it's going to pull that in. Beautiful. Thank you very much. Thank you.


From San Francisco, extracting the signal from the noise, it's theCUBE, covering VMworld 2015. Brought to you by VMworld and its ecosystem sponsors. Now, your host, Stu Miniman and Brian Gracely. Welcome back to theCUBE, SiliconANGLE TVs, live, wall-to-wall coverage of VMworld 2015. I'm Stu Miniman with wikibon.com, here with my co-host on the director's set this week, Brian Gracely. So, Brian, you've been a guest many times on theCUBE, but now you're in, back to back to back sessions, context switching, we're talking cloud, we're talking hyperconvergence, we're talking containers, we're talking all sorts of stuff. What's your first impressions here from day one at VMworld? So, we came into the week, we weren't sure, there wasn't a lot of sort of pre-noise. People are excited, people are excited for, in some cases, the ecosystem, they're excited because VMworld's talking about hybrid cloud and things, they're talking about containers, they're talking about hyperconverge like crazy. That's when the big takeaway for me is, people are excited that VMworld is validating a lot of these markets that maybe a year ago were sort of buzzy. Yeah, so, it's interesting, one of the critiques we came in is there wasn't an overriding theme.  It was like, okay, any apps and any workload, I'm not sure, but I think you're right, there's a lot of different pieces going on and sometimes we miss out that, when we're looking for kind of a big bang. Right, right, well, when you're looking at it from your perspective, today was a little unusual, Pat typically goes first in the keynote, today was a lot of other things, but hyperconverged, VSan, the new Evo, what used to be Evo Rack is now Evo STDC, what's your take on both hyperconverge and hyperconverge and what's going on with STDC? Yeah, I think it's a great point because I tell you, VMware's been looking to expand into some areas, we're not just talking about 100% virtualized and what apps can or I can't do or what the competitive landscape is for the hypervisors, so let's start with VSan, actually I had a good conversation on Twitter that a lot of people have been hating on VSan and they said, oh, you know, Evo Rails is expensive and there's lots of solutions that are undifferentiated, I don't know how the community makes money, but first of all, the foundation of that technology is VSan and the storage group inside VMware has a lot of things they're doing, what's going on with V-Volls, what's happening with VSan, and that go-to-market for a converge or hyperconverged solution isn't easy, I mean, Brian, you and I lived through the early days of what was Acadia, then VCE and it took them almost 18 months to kind of get things copacetic with the channel and even though VSan might be a software piece, how do I bundle it, how do I package it, so we had Evo Rail last year and VSan now 6.0, 6.1 got announced, what was originally going to be called Evo Rack is now called Evo SDDC and a big piece of that is what they also call the Evo SDDC Manager, so really how do I pull together all the components of compute, storage, and networking, how things like NSX fit into it, pulled all together because if I'm really going to make that simplicity, it's not just software but the management of all of those pieces and boy, I mean hyperconvergence was buzzy last year and we did a bunch of interviews, big guys like Nutanix are here of course, SimpliVity, Big Booth giving away another car, I talked to Scott Lowe and David Davis, wrote a book actually sponsored by SimpliVity, and a bunch of startups, so it's only grown and lots of customers trying this stuff out. Any comments from you on the hyperconverge piece? For me it was, we're continuing to see startups want to get into this space which tells me that the VC community still sees there's value in there, as we talk to them, they've got customers, they're sort of working through the challenges of this, so that part is encouraging, because I know a lot of people had some concerns about if it's an all VMware stack, what do I do? And the fact that there's room for not only VMware and the things they're doing, but all these other companies is encouraging, it means that there's big market opportunities, it means there can be big market change. Yeah, absolutely, and you talk about, okay, the VMware stack, what about the hybrid cloud? The big message was one cloud, any apps, any device, and we were kind of going back and forth, it's like well, does it just mean I have VMware here and there? But when you kind of unpack the messaging that Karol and Ragu went through is that unified hybrid cloud, so they're not just saying it's only their environment, there is ties to AWS and Azure, even though they don't want to mention them. It was like, we can't give them validation if I say AWS three times, maybe they'll appear, but what's your take on that cloud messaging? Well, a couple things, to me, when I heard the unified hybrid cloud, what I really heard was them tying together the VMware cloud on both ends, but really making the network piece an important part of it, which is important. We know it's difficult to networking together, all that security and everything, but to me, I still think it misses this idea of calling it one cloud. We had Rodney Rogers on who's CEO of Virtustream. Rodney sort of said, look, the reality is most customers are gonna, they're really managing multiple clouds as resources, and so I think VMware still sort of, I mean, they're committed to this, it's the same everywhere. I think the reality based on our research is customers are saying, there's a lot of other clouds out there and a lot of them are doing really well, so yeah, if they're not gonna mention them by name, trust me, customers are mentioning them to them. Yeah, I mean, the recent revenue data that we put out there, if we look at what we expect the public cloud portion of what AWS sells and the cloud solutions that Microsoft sells, which includes Office in the SaaS space and Azure, both of those revenues are likely to be bigger than what VMware does in revenue this year, so it's big numbers, and boy, the growth rates are, you know, you're talking 60 to 80% typically, which is much bigger than the traditional infrastructure guys dwarfs what's happening in the virtualization space. All right, so we talked about kind of some of the infrastructure piece talked about cloud. Brian, there's some DevOps hackathon going on, there's vSphere integrated containers, what about, kind of the emerging cloud native and developer focused stuff, what's your take on what VMware's announced and doing this week? Yeah, so I want to get down there, they're having a whole track on DevOps, I want to get down and go see some of that, we've been swamped doing shows. Really excited though about all the things that were announced today about VMware integrated containers or vSphere integrated containers, Project Photon, that maturing, we had Patrick Chazan from Docker on here, he was excited about the Docker and VMware partnership. That's an area that I'm really excited about, because I think what I see is, you've got the people that are pure containers and a lot of those platforms are cool and we've seen them at DockerCon and other things, but the enterprise wants to know how to do it and VMware's got such a hold in terms of how to virtualize resources, it's good to see them making a big deal, it's on stage, they're showcasing it, it's open source, so to me that's one of the real highlights of what's going on and I'm excited to see what the marketplace thinks of DevOps Day and Developer Day here at VMworld, definitely different markets for them. Yeah, absolutely, even one of the interviews I did today talking to a practitioner that was doing hyperconverge, he was talking about how it helps him with DevOps it simplifies my environment, it can allow me to do some of those changes that I need organizationally and allow me the freedom to change my architecture of my organization to be able to move faster and to change the way that I'm doing things. The other thing that we said when we were coming into this was the big white elephant in the room is gonna be what's going on with VMware and their role in the Federation. Didn't, I mean, obviously they're not gonna say anything until what comes out, but a lot of people as we're talking in the hallway going, what will VMworld look like next year? Is it gonna still be VMworld? Is it gonna be something else? Did you get a feel from anybody in terms of like how much that concerns them or is that still just, it's just rumors? Yeah, we wonder how much of it is, those of us in the Twittersphere and the Clouderati just banding back and forth. When you talk about some of those fights or disagreements going on in the industry, a lot of times the customers aren't thinking about it. I haven't heard, I've talked to some companies sometimes when they're going through massive changes. When you've been acquired or there's threats of what's going on and you kind of get that fear. I haven't had that buzz yet. I've talked to a number of people that work for VMware and I'm not getting anything behind the scenes because we know that whatever happens with the Federation, VMware is an important piece of what's going on. I mean, that's why even there's discussion that says, hey, maybe VMware is the brand and the leader of what's there because that's going forward. What have you heard so far? I mean, we obviously heard from Rodney, Rodney was excited about what his role's going to be in terms of Clouderati. To me what I heard and you just reiterated it, the thing that's exciting out of all this is whether you're talking to the hyperconverged guys, you're talking to the cloud guys, it's about software and so software becomes that really important thing. So whatever ends up happening with the Federation, whether it's nothing or whatever, I think we're going to see more and more push towards what does software do, what do the software economics look like and quite honestly, if they're going to compete with an Amazon or Google or Azure, you better figure those out because at those growth rates, they're dealing with pure software. So. It's interesting, if you look at the initial partnered for the Evo SDDC, which isn't going to ship until 2016, but it's VCE, which you expect, but by the way, the underlying hardware on that, pretty sure that's some kind of ODM type thing. They're not sure how much they're sharing what goes in there. There's Dell. And the third one is Quanta. I mean, partnership with Quanta. We talked to Randy Baez, cloud scaling before he was bought with EMC. They were partnering with Quanta. It's been that discussion of how the software is going to change the underlying hardware and that's moving. See, Cumulus has a bigger booth here and is getting more involved on the networking side. Definitely some seismic shifts happening on the hardware space. Yep, absolutely. So a lot of things got announced today. Some of them were exciting, some of them incremental as you would expect. Tomorrow's going to be another big day. Pat's going to run the keynote. What are you looking forward to as we think about what we saw today versus what's coming? Anything, either trends you saw today or what might be coming tomorrow that you're looking forward to? Yeah, so there's always that, there's a couple of things here. First of all, what is the average VMware customer thinking? How much are they just coming in here to get certified and where are they with this mindset? So in the last few years we went through the, hey, that flash sounds interesting. Why am I doing it to, oh my God, of course I'm using flash. And a lot of storage here at the show. Hyper-converged is moving fastly along, I guess if you talk the traditional hype cycle. Cloud and how customers are thinking about cloud. We talk about this community. A lot of the people that did virtualization, they were the early adopters. They were the ones that got involved and they got excited to help make their infrastructure better and where are those people, are they digging in and saying, that DevOps stuff is all crap still and I'm not going to make change and where are they moving forward for new environments? So that's what I'm always kind of excited to see as to how open are we to the change and what is that environment going to look like going forward? How about yourself? So for me I look at it as, there's really four big shows that do infrastructure, right? There's this one, there's DockerCon is growing, OpenStack Summit's growing and then obviously Amazon or AWS re-invent. Those are the four big infrastructure sort of cloud shows. At the end of the day, VMware is still driving a lot of the momentum and they're still part of huge markets and so forth. So as much as people may have opinions on where they're at, how fast they're growing, they're still in the center of this stuff and in some cases they're driving the train. I'm excited tomorrow, we're gonna dive into NSX in a couple of different ways. We're gonna dive in with some of the partners working around OpenStack and we're doing a few different things so we're gonna figure out what the fringes of that SDDC look like that aren't just talking about the hypervisor. That part I think is gonna be pretty exciting to see how you unpack that. Yeah and actually I've been pretty happy. We've got a double set here. We're doing things a little bit different. Get to show off some socks sitting on the director's set and we've had room for some audience. So in the keynote area there were a ton of people packed in here. We definitely welcome people to come. We're gonna have panels on Tuesday and Wednesday, a bunch of them so they can come, they can ask questions. As always, hit us up through Twitter, send us notes. Always on the screen here to be able to find what we're doing. Brian, I'll give you last word, day one and going forward. Last word, so first off, had a great time today. Glad you guys are allowing me to be part of this thing. It's fun, you get to know the community. They wanna come talk to us. So good first day, lots of great energy. I think people are excited to hear what Pat's gonna talk about tomorrow and I think the guests we're gonna have are gonna help unpack that. So that part looks like it's gonna be fun and looking forward to tomorrow. All right, as always, find all the research on wikibon.com, the live videos as well as all the replays show up on siliconangle.tv. I'm Stu Miniman and thank you Brian Gracely for being here on this program. We are a wrap on the director's set for day one here, VMworld 2015 and this is theCUBE. Thanks for watching.