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Today I am at the UK Learning Analytics Network organised by the University of Edinburgh in Association with Jisc. Read more about this on the Jisc Analytics blog. Update: you can also now read a lovely concise summary of the day by Niall Sclater, over on the Jisc Analytics blog.
As this is a live blog there may be spelling errors, typos etc. so corrections, comments, additions, etc. are welcome.
Introduction – Paul Bailey
I'm Paul Bailey, Jisc lead on the Learning Analytics programme at the moment. I just want to say a little bit about the network. We have various bits of project activities, and the network was set up as a means for us to share and disseminate the work we have been doing, but also so that you can network and share your experience working in Learning Analytics.
Housekeeping – Wilma Alexander, University of Edinburgh & Niall Sclater, Jisc
Wilma: I am from the University of Edinburgh and I must say I am delighted to see so many people who have traveled to be here today! And I think for today we shouldn't mention the election!
Niall: I'm afraid I will mention the election… I've heard that Nicola Sturgeon and Alex Salmond have demanded that Tunnucks Teacakes and Caramel Wafers must be served at Westminster! [this gets a big laugh as we've all been enjoying caramel wafers with our coffee this morning!]
I'll just quickly go through the programme for the day here. We have some really interesting speakers today, and we will also be announcing the suppliers in our learning analytics procurement process later on this afternoon. But we kick off first with Dragan.
Doing learning analytics in higher education: Critical issues for adoption and implementation – Professor Dragan Gašević, Chair in Learning Analytics and Informatics, University of Edinburgh
I wanted to start with a brief introduction on why we use learning analytics. The use of learning analytics has become something of a necessity because of the growing needs of education – the growth in the number of students and the diversity of students, with MOOCs being a big part of that realisation that many people want to learn who do not fit our standard idea of what a student is. The other aspect of MOOCs is their scale: as we grow the number of students it becomes difficult to track progress and the feedback loops between students and instructions are lost or weakened.
In learning analytics we depend on two types of major information systems… Universities have had student information systems for a long time (originally paper, computerised 50-60 years ago), but they also use learning environments – the majority of universities have some online coverage of this kind for 80-90% of their programmes. But we also don't want to exclude other platforms, including communications and social media tools. And no matter what we do with these technologies we leave a digital trace, and that is not a reversible process at this point.
So, we have all this data but what is the point of learning analytics? It is about using machine learning, computer science, etc. approaches in order to inform education. We defined learning analytics as being "measurement, collection, analysis, and reporting" of education but actually that "how" matters less than "why". It should be about understanding and optimising learning and the environments in which learning occurs. And it is important not to forget that learning analytics are there to understand learning and are about understanding what learning is about.
Some case studies include Course Signals at Purdue. They use Blackboard for their learning management system. They wanted to predict students who would successfully complete students, and to identify those at risk. They wanted to segment their students into at high risk, at risk, or not at risk at all. Having done that they used a traffic light system to reflect that, and they used that traffic light system for students was shown both to staff and students. When they trialed that (Arnold and Pistilli 2012) with a cohort of students, they saw greater retention and success. But if we look back at how I framed this, we need to think about this in terms of whether this changes teaching…
So, also at Purdue, they undertook a project analysing the email content of instructors to students. They found that more detailed feedback, they just increased the summative feedback. So this really indicates that learning analytics really has to feed into changes in teaching practices in our institutions, and we need our learning analytics to provide signalling and guidance that enables teaching staff to improve their practice, and give more constructive feedback. (see Tanes, Arnold, King and Remnet 2011).
University of Michigan looked at "gateway course" as a way to understand performance in science courses (see Wright, McKay, Hershock, Miller and Triz 2014). They defined a measure for their courses, which was "better than expected". There were two measures for this: previous GPA, and goals set by students for the current course. They then used predictive models for how students could be successful, and ways to help students to perform better than expected. They have also been using technology designed for behavioural change, which they put to use here… Based on that work they generated personalised messages to every students, based on rational for these students, and also providing predicted performance for particular students. For instance an example here showed that a student could perform well beyond their own goals, which might have been influenced by the science course not being their major. The motivator for students here was productive feedback… They interviewed successful students from previous years, and used that to identify behaviours etc. that led to success, and they presented that as feedback from peers (rather than instructors). And i think this is a great way to show how we can move away from very quantitative measures, towards qualitative feedback.
So, to what extent are institutions adopting these approaches? Well, there are very few institutions with institution-wide examples of adoptions. For instance University of Michigan only used this approach on first year science courses. They are quite a distributed university – like Edinburgh – which may be part of this perhaps. Purdue also only used this on some course.
Siemans, Dawson and Lynch (2014) surveyed the use of learning analytics in the HE sector, asking about the level of adoption and type of adoption, ranking these from "Awareness" to "Experimentation" to "Organisation/Students/Faculty", "Organisational Transformation" and "Sector Transformation". Siemens et al found that the majority of HE is at the Awareness and Experimentation phase. Similarly Goldstein and Katz (2005) found 70% of institutions at phase 1, it is higher now but bear in mind that 70% doesn't mean others are further along that process. There is still much to do.
So, what is necessary to move forward? What are the next steps? What do we need to embrace in this process? Well lets talk a bit about direction… The metaphors from business analytics can be useful, borrow lessons from that process. McKinsey offered a really interesting business model of: Data – Model – Transform (see Barton and Court 2012). That can be a really informative process for us in higher education.
Starting with Data – traditionally when we choose to measure something in HE we refer to surveys, particularly student satisfaction surveys. But this is not something with a huge return rate in all countries. More importantly surveys are not the accurate thing. We also have progress statistics – they are in our learning systems as are data but are they useful? We can also find social networks from these systems, from interactions and from course registration systems – and knowing who students hang out with can predict how they perform. We also find that we can get this data, but then how do we process and understand that data? I know some institutions find a lack of IT support can be a significant barrier to the use of learning analytics.
Moving onto Model… Everyone talks about predictive modelling, the question has to be about the value of a predictive model. Often organisations just see this as an outsourced thing – relying on some outsider organisation and data model that provides solutions, but does not do that within the context of understanding what the questions are. And the questions are critical.
And this is, again, where we can find ourselves forgetting that learning analytics is about learning. So there are two things we have to know about, and think about, to ensure we understand what analytics mean:
(1) Instructional conditions – different courses in the same school, or even in the same programme will have a different set of instructional conditions – different approaches, different technologies, different structures. We did some research on an University through their Moodle presence and we found some data that was common to 20-25% of courses, but we did identify some data you could capture that were totally useless (e.g. time online). And we found some approaches that explained 80% of variance, so for example extensive use of Turnitin – not just for plagiarism but also by students for gathering additional feedback. One of our courses defied all trends… they had a Moodle presence but when we followed up on this, found that most of their work was actually in social media so data from Moodle was quite misleading and certainly a partial picture. (see Gasevic, Dawson, Rogers, Gasevic, 2015)
(2) Learner agency – this changes all of the time. We undertook work on the agency of learners, based on log data from a particular course. We explored 6 clusters using cluster matching algorithms… We found that there was a big myth that more time on task would lead to better performance… One of our clusters spent so much time online, another was well below. When we compared clusters we found the top students were that group spending the least time online, the other cluster spending time online performed average. This shows that this is a complex questions. Learning styles isn't the issue, learning profiles is what matters here. In this course, one profile works well, in another a different profile might work much better. (see Kovanovic, Gasevic, Jok… 201?).
And a conclusion for this section is that our analytics and analysis cannot be generalised.
Moving finally to Transform we need to ensure participatory design of analytics tools – we have to engage our staff and students in these processes early in the process, we won't get institutional transformation by relying on the needs of statisticians. Indeed visualisations can be harmful (Corrin and de Barba 2014). The University of Melbourne looked at the use of dashboards and similar systems and they reported that for students that were high achieving, high GPA, and high aspirations… when they saw that they were doing better than average, or better than their goals, they actually under-perform. And for those doing less well we can just reinforce issues in their self efficacy. So these tools can be harmful if not designed in a critical way.
So, what are the realities of adoption? Where are the challenges? In Australia I am part of a study commissioned by the Australian Government in South Australia. This is engaging with the entire tertiary Australian institution. We interviewed every VC and management responsible for learning analytics. Most are in phase 1 or 2… Their major goal was to enable personalised learning… the late phases… They seemed to think that magically they would move from experimentation to personalised learning, they don't seem to understand the process to get there…
We also saw some software driven approaches. They buy an analytics programme and perceive job is done.
We also see a study showing that there is a lack of a data-informed decision making culture, and/or data not being suitable for informing those types of decisions. (Macfadyen and Dawson 2012).
We also have an issue here that researchers are not focused on scalability here… Lots of experimentation but… I may design beautiful scaffolding based on learning analytics, but I have to think about how that can be scaled up to people who may not be the instructors for instance.
The main thing I want to share here is that we must embrace the complexity of educational systems. Learning analytics can be very valuable for understanding learning but they are not a silver bullet. For institutional or sectoral transformation we need to embrace that complexity.
We have suggested the idea of Rapid Outcome Mapping Approach (ROMA) (Macfadyen, Dawson, Pardo, Gasevic 2014) in which once we have understood the objectives of learning analytics, we also have to understand the political landscape in which they sit, the financial contexts of our organisations. We have to identify stakeholders, and to identify the desired behaviour changes we want from those stakeholders. We also have to develop engagement strategy – we cannot require a single approach, a solution has to provide incentives for why someone should/should not adopt learning analytics. We have to analyse our internal capacity to effect change – especially in the context of analytics tools and taking any value form them. And we finally have to evaluate and monitor chance. This is about capacity development, and capacity development across multiple teams.
We need to learn from successful examples – and we have some to draw upon. The Open University adopted their organisational strategy, and were inspired by the ROMA approach (see Tynan and Buckingham Shum 2013). They developed the model of adoption that is right for them – other institutions will want to develop their own, aligned to their institutional needs. We also need cross-institutional experience sharing and collaboration (e.g. SOLAR, the Society for Learning Analytics Research). This meeting today is part of that. And whilst there may be some competition between institutions, this process of sharing is extremely valuable. There are various projects here, some open source, to enable different types of solution, and sharing of experience.
Finally we need to talk about ethical and privacy consideration. There is a tension here… Some institutions hold data, and think students need to be aware of the data held… But what if students do not benefit from seeing that data? How do we prepare students to engage with that data, to understand this data. The Open University is at the leading edge here and have a clear policy on ethical use of student data. Jisc also have a code of practice for learning analytics which I also welcome and think will be very useful for institutions looking to adopt learning analytics.
I also think we need to develop an analytics culture. I like to use the analogy of, say, Moneyball, where analytics make a big difference… but analytics can be misleading. Predictive models have their flaws, their false positives etc. So a contrasting example would be the Trouble with the Curve – where analytics mask underlying knowledge of an issue. We should never reject our tacit knowledge as we look at adopting learning analytics.
Q – Niall): I was struck by your comments about asking the questions… But doesn't that jar with the idea that you want to look at the data and exploring questions out of that data?
A – Dragan): A great question… As a computer scientist I would love to just explore the data, but I hang out with too many educational researchers… You can start from data and make sense of that. It is valid. However, whenever you have certain results you have to ask certain questions – does this make sense in the context of what is taking place, does this make sense within the context of our institutional needs, and does this make sense in the context of the instructional approach? That questioning is essential no matter what the approach.
Q – Wilma) How do you accommodate the different teaching styles and varying ways that courses are delivered?
A – Dragan) The most important part here is about the development of capabilities – at all levels and in all roles including students. So in this Australian study we identified trends, found these clusters… But some of these courses are quite traditional and linear, others are more ambitious… They have a brilliant multi-faceted approach. Learning analytics would augment this… But when we aggregate this information… But when you have more ambitious goals, the more there is to do. Time is required to adopt learning analytics with sophistication. But we also need to develop tools to the needs of tasks of stakeholders… so stakeholders are capable to work with them… But also not to be too usable. There aren't that many data scientists so perhaps we shouldn't use visualisations at all, maybe just prompts triggered by the data… And we also want to see more qualitative insights into our students… their discussion… when they are taking notes… And that then really gives an insight… Social interactions are so beneficial and important to benefit student learning.
Q – Wilbert) You mentioned that work in Australia about Turnitin… What was the set up there that led to that… Or was it just the plagiarism prediction use?
A – Dragan) Turned out to be the feedback being received through Turnitin… Not plagiarism side. Primarily it was on the learner side, not so much the instructors. There is an ethical dilemma there if you do expose that to instructors… If they are using the system to get feedback… Those were year one students, and many were international and from Asia and China where cultural expectation of reproducing knowledge is different… So that is also important.
Q) Talking about the Purdue email study, and staff giving formative feedback to students at risk – how did that work?
A) They did analysis of these messages, and the content of them, and found staff mainly giving motivational messages. I think that was mainly because traffic light system indicated at risk nature but not why that was the case… you need that information too..
Q) Was interested in rhetoric of personalised learning by Vice Chancellors, but most institutions being at stage 1 or 2… What are the institutional blockers? How can they be removed?
A) I wish I had an answer there! But the senior leaders are sometimes forced to make decisions based on financial needs, not just about being driven by data or unaware of data. So in Australian institutions many are small organisations, with limited funding… and existence of the institutions is part of what they have to face, quite aside from adoption of learning analytics. But also University of Melbourne is a complex institution, a leading researcher there but cannot roll out same solution across very different schools and courses….
Niall: And with that we shall have to end the Q&A and hand over to Sheila, who will talk about some of those blockers…
Learning Analytics: Implementation Issues – Sheila MacNeill, Glasgow Caledonian University
I was based at CETIS involved in learning analytics for a lot of that time… But for the last year and a half I have been based at Glasgow Caledonian University. And today I am going to talk about my experience of moving from that overview position to being in an institution and actually trying to do it… I'm looking for a bit of sympathy and support, but hoping to also contextualise some of what Dragan talked about.
Glasgow Caledonian University has about 17,000 students, mostly campus based although we are looking at online learning. We are also committed to blended learning. We provide central support for the university, working with learning technologies across the institution. So I will share my journey… joys and frustrations!
One of the first things I wanted to do was to get my head around what kind of systems we had around the University… We had a VLE (Blackboard) but I wanted to know what else people were using… This proved very difficult. I spoke to our IS department but finding the right people was challenging, a practical issue to work around. So I decided to look a big more broadly with a mapping of what we do… looking across our whole technology position. I identified the areas and what fitted into those areas:
- (e) Assessment and feedback – Turnitin – we see a lot of interest in rubrics and marking and feedback processes that seem to be having a big impact on student success and actually plagiarism isn't its main usefulness the more you use it, Gradecentre, Wikis/blogs/journals, peer/self assessment, (e)feedback.
- (e) Portfolios – wikis/blogs/journals, video/audio – doing trials with nursing students of a mobile app in this space.
- Collaboration – discussion boards, online chat, video conferencing etc.
- Content – lectures, PDFs, etc….
I've been quite interested in Mark (?) idea of a "core VLE". Our main systems group around SRS (students records system – newly renamed from it's former name, ISIS), GCU Learn, the Library, 3rd Party Services. When I did hear from our IS team I found such a huge range of tools that our institution has been using, it seems like every tool under the sun has been used at some point.
In terms of data… we can get data from our VLE, from Turnitin, from wikis etc. But it needs a lot of cleaning up. We started looking at our data, trying it on November data from 2012 and 2013 (seemed like a typical month). And we found some data we would expect, changes/increases of use over time. But we don't have data on a module level, or programme level, etc. Hard to view in detail or aggregate up (yet). We haven't got data from all of our systems yet. I would say we are still at the "Housekeeping" stage… We are just seeing what we have, finding a baseline… There is an awful lot of housekeeping that needs to be done, a lot of people to talk to…
But as I was beginning this process I realised we had quite a number of business analysts at GCU who were happy to talk. We have been drawing out data. We can make dashboards easily, but USEFUL dashboards are proving more tricky! We have meanwhile been talking about Blackboard about their data analytics platform. It is interesting thinking about that… given the state we are in about learning analytics, and finding a baseline, we are looking at investing some money to see what data we can get from Blackboard that might enable us to start asking some questions. There are some things I'd like to see from, for example, combining on campus library card data with VLE data. And also thinking about engagement and what that means… Frustratingly for me I think that it is quite hard to get data from Blackboard… I'm keen that next license we sign we actually have a clause about the data we want, in the format we want, when we want it… No idea if that will happen but I'd like to see that.
Mark Stubbs (MMU) has this idea of a tube map of learning… This made me think of the Glasgow underground map – going in circles a bit, not all joining up. We really aren't quite there yet, we are having conversations about what we could, and what we should do. In terms of senior management interest in learning analytics… there is interest. But when we sent out the data we had looked we did get some interesting responses. Our data showed a huge increase in mobile use – we didn't need a bring your own device policy, students were already doing it! We just need everything mobile ready. Our senior staff are focused on NSS and student survey data, that's a major focus. I would like to take that forward to understand what is happening, and more structured way…
And I want to finish by talking about some of the issues that I have encountered. I came in fairly naively to this process. I have learned that…
Leadership and understanding is crucial – we have a new IS director which should make a great difference. You need both carrots and stick, and that takes a real drive from the top to make things actually start.
Data is obviously important. Our own colleagues have issues access data from across the institution. People don't want to share, they don't know if they are allowed to share. There is a cultural thing that needs investigating – and that relates back to leadership. There are also challenges that are easy to fix such as server space. But that bigger issue of access/sharing/ownership all really matter.
Practice can be a challenge. Sharing of experience and engagement with staff, having enough people understanding systems, is all important for enabling learning analytics here. The culture of talking together more, having a better relationship within an institution, matters.
Specialist staff time matters – as Dragan highlighted in his talk. This work has to be prioritised – a project focusing on learning analytics would give the remit for that, give us a clear picture, establish what needs to be done. To not just buy in technology but truly assess needs before doing that, and in adopting technology. There is potential but learning analytics has to be a priority if it is to be adopted properly.
Institutional amnesia – people can forget what they have done, why, and what they do not do it before… More basic house keeping again really. Understanding, and having tangible evidence of, what has been done and why is also important more broadly when looking at how we use technologies in our institutions.
Niall: Thanks for such an honest appraisal of a real experience there. We need that in this community, not just explaining the benefits of learning analytics. The Open University may be ahead now, but it also faced some of those challenges initially for instance. Now, over to Wilma.
Student data and Analytics work at the University of Edinburgh – Wilma Alexander, University of Edinburgh
Some really interesting talks already to do, I'll whiz through some sections in fact as I don't need to retread some of this. I am based in Information Services. We are a very very large, very old University, and it is very general. We have a four year degree. All of that background makes what we do with student data, something it is hard to generalise about.
So, the drivers for the project I will focus on, came out of the understanding we already have about the scale and diversity of this institution. Indeed we are increasingly encouraging students to make imaginative cross overs between schools and programmes which adds to this. Another part of the background is that we have been seriously working in online education, and in addition to a ground breaking digital education masters delivered online, we also have a number of online masters. And further background here is that we have a long term set of process that encourages students to contribute to the discussions within the university, owners and shapers of their own learning.
So, we have an interest in learning analytics, and understanding what students are doing online. We got all excited by the data and probably made the primary error of thinking about how we could visualise that data in pretty pictures… but we calmed down quite quickly. As we turned this into a proper project we framed it much more in the context of empowering students around their activities, about data we already have about our students. We have two centrally supported VLEs at Edinburgh (and others!) which are Blackboard Learn, our main largest system with virtually all on campus programmes use that VLE in some way, but for online distance programmes we took the opportunity to try out Moodle – largely online programmes, and largely created as online distance masters programmes. So, already there is a big distance between how these tools are used in the university, never mind how they are adopted.
There's a video which shows this idea of building an airplane whilst in the air… this projects first phase, in 2014, has felt a bit like that at times! We wanted to see what might be possible but also we started by thinking about what might be displayed to students. Both Learn and Moodle give you some data about what students do in your courses… but that is for staff, not visible to students. When we came to looking at the existing options… None of what Learn offers quite did what we wanted as none of the reports were easily made student facing (currently Learn does BIRT reports, course reports, stats columns in grade center etc). We also looked at Moodle and there was more there – it is open source and developed by the community so we looked at available options there…
We were also aware that there were things taking place in Edinburgh elsewhere. We are support not research in our role, but we were aware that colleagues were undertaking research. So, for instance my colleague Paula Smith was using a tool to return data as visualisations to students.
What we did as a starting point was to go out and collect user stories. We were asking both staff and students, in terms of information available in the VLE(s), what sort of things would be of interest. We framed this as a student, as a member of staff, as a tutor… as "As a… I want to… So that I can…". We had 92 stories from 18 staff and 32 students. What was interesting here was that much of what was wanted was already available. For staff much of the data they wanted they really just had to be shown and supported to find the data already available to them. Some of the stuff that came in as "not in scope" was not within the very tight boundaries we had set for the project. But a number of things of interest, requests for information, that we passed on to appropriate colleagues – so one area for this was reading lists and we have a tool that helps with that so we passed that request onto library colleagues.
We also pooled some staff concerns… and this illustrates what both Dragan and Sheila have said about the need to improve the literacy of staff and students using this kind of information, and the need to contextualise it… e.g: "As a teacher/personal tutor I want to have measures of activity of the students so that I can be alerted to who are "falling by the wayside" for instance – a huge gap between activity and that sort of indicator.
Student concerns were very thoughtful. They wanted to understand how they compare, to track progress, they also wanted information on timetables of submissions, assignment criteria/weighting etc. We were very impressed by the responses we had and these are proving valuable beyond the scope of this project…
So, we explored possibilities, and then moved on to see what we could build. And this is where the difference between Learn and Moodle really kicked in. We initially thought we could just install some of the Moodle plugins, and allow programmes to activate them if they wanted to… But that fell at the first hurdle as we couldn't find enough staff willing to be that experimental with a busy online MSc programme. The only team up for some of that experimentation were the MSc in Digital Education team, which was done as part of a teaching module in some strands of the masters. This was small scale hand cranked from some of these tools. One of the issues with pretty much all of these tools is that they are staff facing and therefore not anonymous.So we had to do that hand cranking to make the data anonymous.
We had lots of anecdotal and qualitative information through focus groups and this module, but we hope to pin a bit more down on that. Moodle is of interest as online distance students… there is some evidence that communication, discussion etc. activity is a reasonable proxy for performance here as they have to start with the VLE.
Learn is a pretty different beast as it is on campus. Blended may not have permeated as strongly on campus. So, for Learn what we do have this little element that produces a little click map of sorts (engagements, discussion, etc)… For courses that only use the VLE for lecture notes, that may not be useful at all, but for others it should give some idea of what is taking place. We also looked at providing guidebook data – mapping use of different week's sections/resources/quizzes to performance.
We punted those ideas out. The activity information didn't excite folk as much (32% thought it was useful). The grade information was deemed much more useful (97% thought it was useful)… But do we want our students hooked on that sort of data? Could it have negative effects, as Dragan talked about. And how useful is that overview?
When it came to changes in learning behaviour we had some really interesting and thoughtful responses here. Of the three types of information (discussion boards, grade, activity) it was certainly clear though that grade was where the student interest was.
We have been looking at what courses use in terms of tools… doing a very broad brush view of 2013/14 courses we can see what they use and turn on from: some social/peer network ability – where we think there really is huge value, the percentage of courses actively using those courses on campus are way below those using the VLE for the other functions of Content+Submission/Assessment and Discussion Boards.
So context really is all – reflecting Dragan again here. It has to work for individuals on a course level. We have been mapping our territory here – the university as a whole is hugely engaged in online and digital education in general, and very committed to this area, but there is work to do to join it all up. When we did information gathering we found people coming out of the woodwork to show their interest. The steering group from this project has a representative from our student systems team, and we are talking about where student data lives, privacy and data protection, ethics, and of course also technical issues quite apart from all that… So we also have the Records Management people involved. And because Jisc has these initiatives, and there is an EU initiative, we are tightly engaging with the ethical guidance being produced by both of these.
So, we have taken a slight veer from doing something for everyone in the VLEs in the next year. The tool will be available to all but what we hope to do is to work very closely with a small number of courses, course organisers, and students, to really unpick on a course level how the data in the VLE gets built into the rest of the course activity. So that goes back into the idea of having different models, and applying the model for that course, and for those students. It has been a journey, and it will continue…
Using learning analytics to identify 'at-risk' students within eight weeks of starting university: problems and opportunities – Avril Dewar, University of Edinburgh
This work I will be presenting has been undertaken with my colleagues at the Centre for Medical Education, as well as colleagues in the School of Veterinary Medicine and also Maths.
There is good evidence that performance in first year will map quite closely to performance as a whole in a programme. So, with that in mind, we wanted to develop an early warning system to identify student difficulties and disengagement before they reach assessment. Generally the model we developed worked well. About 80% of at risk students were identified. And there were large differences between the most and least at-risk students – the lowest risk score and the highest risk score which suggests this was a useful measure.
The measures we used included:
- Engagement with routine tasks
- Completion of formative assessment – including voluntary formative assessment
- Tutorial attendance (and punctuality where available) – but this proved least useful.
- Attendance at voluntary events/activities
- Virtual Learning Environment (VLE) exports (some)
- Time until first contact proved to be the most useful of these
We found that the measures sometimes failed because the data exports were not always that useful for appropriate (e.g. VLE tables of 5000 colums). Patterns of usage were hard to investigate as raw data on, e.g. time of day of accesses, not properly usable though we think that is useful. Similarly there is no way to know if long usage means a student has logged in, then Googled or left their machine, then returned – or whether it indicates genuine engagement.
To make learning analytics useful we think we need the measures, and the data supporting them, to be simple, to be comprehensible, accessible – and also comparable to data from other systems (e.g. we could have used library data alongside our VLE issues), to scale easily – e.g. common characteristics between schools, not replicating existing measures, discriminates between students – some of the most useful things like the time to first contact, central storage.
We also found there were things that we could access but didn't use. Some for ethical and some for practical reasons. IP addresses for location was an ethical issue for us, discussion boards similarly we had concern about – we didn't want students to be put off participating in discussions. Or time taken to answer individual questions. We are concerned that theoretical issues that could be raised could include: evidence that student has been searching essay-buying websites; student is absent from class and claims to be ill but IP address shows another location, etc.
There were also some concerns about the teacher-student relationship. Knowing too much can create a tension in the student-teacher relationship. And the data one could gather about a student could become a very detailed tracking and monitoring system… for that reason we always aim to be conservative, rather than exhaustive in our data acquisition.
We have developed training materials and we are making these open source so that we can partner with other schools, internationally. Whilst each school will have their own systems and data but we are keen to share practice and approaches. Please do get in touch if you would like access to the data, or would like to work with us.
Q – Paula) Do you think there is a risk of institutions sleep walking into student dissatisfaction. We are taking a staged approach… but I see less effort going into intervention, to the staff side of what could be done… I take it that email was automated… Scalability is good for that, but I am concerned students won't respond to that as it isn't really personalised at all. And how were students in your project, Avril, notified.
A – Avril) We did introduce peer led workshops… We are not sure if that worked yet, still waiting for results of those. We emailed to inform our students if they wanted to be part of this and if they wanted to be notified of a problem. Later years were less concerned, saw the value. First year students were very concerned, so we phrased our email very carefully. When a student was at risk emails were sent individually by their personal tutors. We were a bit wary of telling students of what had flagged them up – it was a cumulative model… were concerned that they might then engage just with those things and then not be picked up by the model.
Niall: Thank you for that fascinating talk. Have you written it up anywhere yet?
Avril: Soon!
Niall: And now to Wilbert…
The feedback hub; where qualitative learning support meets learning analytics – Wilbert Kraan, Cetis
Before I start I have heard about some students gaming some of the simpler dashboards so I was really interested in that.
So, I will be sort and snappy here. The Feedback Hub work has just started… this is musings and questions at this stage. This work is part of the larger Jisc Electronic Management of Assessment (EMA) project. And we are looking at how we might present feedback and learning analytics side by side.
The EMA project is a partnership between Jisc, UCISA and HeLF. It builds on earlier Jisc Assessment and Feedback work And it is a co-design project that identifies priorities, solution areas… and we are now working on solutions. So one part of this is about EMA requirements and workflows, particularly the integration of data (something Sheila touched upon). There is also work taking place on an EMA toolkit that people can pick up and look at. And then there is the Feedback Hub, which I'm working on.
So, there is a whole assessment and feedback lifecycle (as borrowed from a model developed by Manchester Metropolitan, with they permission), This goes from Specifying to Setting, Supporting, Submitting, Marking and production of feedback, Recording of grades etc… and those latter stages is where the Feedback Hub sits.
So, what is a feedback hub really? It is a system that provides a degree programme of life wide view of assignments and feedback. The idea is that it moves beyond the current module that you are doing, to look across modules and across years. There will be feedback that is common across areas, that gives a holistic view of what has already been done. So this is a new kind of thing… When I look at nearest tools I found VLE features – database view of all assignments for a particular student for learner and tutor to see. A simple clickable list that is easy to do and does help. Another type is a tutoring or assignment management system – capturing timetables of assignments, tutorials etc. These are from tutor perspective. Some show feedback as well. And then we have assignment services – including Turnitin – about plagiarism, but also management of logistics of assignments, feedback etc.
So, using those kinds of tools you can see feedback as just another thing that gets put in the learning records store pot in some ways. But feedback can be quite messy, hard to disentangle in line feedback from the document itself. Teachers approach feedback differently… though pedagogically the qualitative formative feedback that appears in these messy ways can be hugely valuable. Also these online assessment management tools can be helpful for mapping and developing learning outcomes and rubrics – connecting that to the assignment you can gain some really interesting data… There is also the potential for Computer Aided Assessment feedback – sophisticated automated data on tests and assignments which work well in some subjects. And possibly one of the most interesting learning analytics data is on the engagement with feedback. A concern from academic staff is that you can give rich feedback, but if the students don't use it how useful it is really? So capturing that could be useful…
So, having identified those sources, how do we present such a holistic view? One tool presents this as an activity stream – like Twitter and Facebook – with feedback part of that chronological list of assignments… We know that that could help. Also an expanding learning outcomes rubric – click it to see feedback connected to it, would it be helpful? We could also do text extraction, something like Wordle, but would that help? And the other thing that might see is clickable grades – to understand what a grade means… And finally should we combine feedback hub with analytics data visualisations.
Both learning analytics and feedback track learning progress over time, and try to predict the future. Feedback related data can be a useful learning analytics data source.
Q – Me) Adoption and issues of different courses doing different things? Student expectations and added feedback?
A) This is an emerging area… IET in London/University of London have been trialing this stuff… they have opened that box… Academic practice can make people very cautious…
Comment) Might also address the perennial student question of wanting greater quality feedback… Might address deficit of student satisfaction
A) Having a coordinated approach to feedback… From a pedagogical point of view that would help. But another issue there is that of formative feedback, people use these tools in formative ways as well. There are points of feedback before a submission that could be very valuable, but the workload is quite spectacular as well. So balancing that could be quite an interesting thing.
Jisc work on Analytics – update on progress to date– Paul Bailey, Jisc and Niall Sclater.
Paul: We are going to give you a bit of an update on where we are on the Learning Analytics project, and then after that we'll have some short talks and then will break out into smaller groups to digest what we've talked about today.
The priorities we have for this project are: (1) basic learning analytics solution, an interventions tool and a student tool; (2) code of practice for learning analytics; and (3) learning analytics support and network.
We are a two year project, with the clock ticking from May 2015. We have started by identifying suppliers to initiate contracts and develop products; then institutions will be invited to participate in the discovery stage or pilots (June-Sept 2015). Year 1 in Sept 2015-2016 we will run that discovery stage (10-20 institutions), pilots (10+ institutions); institutions move from discovery to pilot. Year 2 will be about learning from and embedding that work. And for those of you that have worked with us in the past, the model is a bit different: rather than funding you then learning from that, we will be providing you with support and some consultancy and learning from this as you go (rather than funding).
Michael Webb: So… we have a diagram of the process here… We have procured a learning records warehouse (the preferred supplier there is H2P). The idea that VLEs, Student Information Systems and Library Systems feeding into that. There was talk today of Blackboard being hard to get data out of, we do have Blackboard on-board.
Paul: Tribal are one of the solutions, pretty much off the shelf stuff. Various components and we hope to role it out to about 15 institutions in the first year. The second option there will be the open solution, which is partly developed but needs further work. So the option will be to engage with either one of those solutions, or to engage with both perhaps.
The learning analytics processors will feed the staff dashboards, into a student consent service, and both of those will connect to the alert and intervention system. And there will be a Student App as well.
Michael: The idea is that all of the components are independent so you can buy one, or all of them, or the relevant parts of the service for you.
Paul: The student consent service is something we will develop in order to provide some sort of service to allow students to say what kinds of information can or cannot be shared (of available data from those systems that hold data on them). The alert and intervention system is an area that should grow quite a bit…
So, the main components are the learning records warehouse, the learning analytics processor – for procurement purposes the staff dashboard is part of that, and the student app. And once you have that learning records warehouse is there, you could build onto that, use your own system, use Tableau, etc.
Just to talk about the Discovery Phase, we hope to start that quite soon. The invitation will come out through the Jisc Analytics email list – so if you want to be involved, join that list. We are also setting up a questionnaire to collect readiness information and for institution to express interest. Then in the discovery process (June/July onward) there will be a select preferred approach for the discovery phase. This will be open to around 20 institutions. We have three organisations involved here: Blackboard; a company called DTP Solution Path (as used by Nottingham Trent); and UniCom. For the pilot (September(ish) onward) we have a select solution preference (Year 1-15 (proprietary – Tribal) and 15 open).
Niall: the code of practice is now a document of just more than two pages around complex legal and ethical issues. They can be blockages to move that forward… so this is an attempt to have an overview document to help institution to overcome those issues. We have a number of institutions who will be trialing this. That's at draft stage right now, and with advisory group to suggest revisions. It is likely to launch by Jisc in June. Any additional issues are being reflected in a related set of online guidance documents.
Effective Learning Analytics project can be found: http://www.jisc.ac.uk/rd/projects/
Another network on 24th June at Nottingham Trent University. At that meeting we are looking to fund some small research type projects – there is an Ideascale page for that. About five ideas in the mix at the moment. Do add ideas (between now and Christmas) and do vote on those. There will be pitches there, for ones to take forward. And if you want funding to go to you as a sole trader rather than to a large institution, that can also happen.
Q) Will the open solution be shared on something like GitHub so that people can join in
A) Yes.
Comment – Micheal: Earlier today people talked about data that is already available, that's in the discovery phase when people will be on site for a day or up to a week in some cases. Also earlier on there was talk about data tracking, IP address etc, and the student consent system we have included is to get student buy-in for that process, so that you are legally covered for what you do as well. And there is a lot of focus on flagging issues, and intervention. The intervention tool is a really important part of this process, as you'll have seen from our diagram.
For more information on the project see: http://analytics.jiscinvolve.org/wp/
Open Forum – input from participants, 15 min lightning talks.
Assessment and Learning Analytics – Prof Blazenka Divjak, University of Zagreb (currently visiting University of Edinburgh)
I have a background in work with a student body of 80,000 students, and use of learning analytics. And the main challenge I have found has been the management and cleansing of data. If you want to make decisions, learning analytics are not always suitable/in an appropriate state for this sort of use.
But I wanted to today about assessment. What underpins effective teaching? Well this relates to the subject, the teaching methods, the way in which students develop and learn (Calderhead, 1996), and awareness of the relationship between teaching and learning. Assessment is part of understanding that.
So I will talk to two case studies across courses using the same blended approach with open source tools (Moodle and connected tools).
One of these examples is Discrete Math with Graph Theory, a course for the Master of Informatics course with around 120 students and 3 teachers. This uses problem (authentic) posing and problem solving. We have assessment criteria and weighted rubrics (AHP method). So here learning analytics are used for identification of performance based on criteria. We also look at differences between groups (gender, previous study, etc.). Correlation of authentic problem solving with other elements of assessments – hugely important for future professional careers but not always what happens.
The other programme, Project Management for the Master of Entrepreneurship programme, has 60 students and 4 teachers. In this case project teams work on authentic tasks. Assessment criteria + weighted rubrics – integrated feedback. The course uses self-assessment, peer-assessment, and teacher assessment. Here the learning analytics are being used to assess consistency, validity, reliability of peer-assessment. Metrics here can include the geometry of learning analytics perhaps.
Looking at a graphic analysis of one of these courses shows how students are performing against criteria – for instance they are better at solving problems than posing problems. Students can also benchmark themselves against the group, and compare how they are doing.
The impact of student dashboards – Paula Smith, UoE
I'm going to talk to you about an online surgery course – the theory not the practical side of surgery I might add. The MSc in Surgical Sciences has been running since 2007 and is the largest of the medical distance learning programmes.
The concept of learning analytics may be relatively new but we have been interested in student engagement and participation, and how that can be tracked and acknowledged for a long time as it is part of what motivates students to engage. So I am going to be talking about how we use learning analytics to make an intervention but also to talk about action analytics – to make changes as well as interventions.
The process before the project I will talk about had students being tracked via an MCQ system – students would see a progress bar but staff could see more details. At the end of every year we would gather that data, and present a comparative picture so that students could see how they were performing compared to peers.
Our programmes all use bespoke platforms and that meant we could work with the developers to design measures on student engagement – for example number of posts. A crude way to motivate students. And that team also created activity patterns so we could understand the busier times – and it is a 24/7 programme. All of our students work full time in surgical teams so this course is an add on to that. We never felt a need to make this view available to students… this is a measure of activity but how does that relate to learning? We need more tangible metrics.
So, in March last year I started a one day a week secondment for a while with Wilma Alexander and Mark Wetton at IS. That secondment has the objectives of creating a student "dashboard" which would allow students to monitor their progress in relation to peers; to use the dashboard to identify at-risk students for early interventions; and then evaluate what (if any) impact that intervention had.
So, we did see a correlation between in-course assessment and examination marks. The exam is 75-80% (was 80, now 75) in the first year. It is a heavily weighted component. You can do well in the exam, and get a distinction, with no in course work during the year. The in-course work is not compulsory but we want students to see the advantage of in course assessments. So, for the predictive modelling regression analysis revealed that only two components had any bearing on end of year marks, which were discussion board ratings, and exam performance (year 1); or exam performance (year 2). So, with that in mind we moved away from predictive models we decided to do a dashboard for students to present a snapshot of their progress against others'. And we wanted this to be simple to understand…
So, here it is… we are using Tableau to generate this. Here the individual student can see their own performance in yellow/orange and compare to the wider group (blue). The average is used to give a marker… If the average is good (in this example an essay has an average mark of 65%) that's fine, if the average is poor (discussion board which are low weighted has an average of under 40, which is a fail at MSc level) that may be more problematic. So that data is provided with caveats.
This interface has been released – although my intervention is just an email which points to the dashboard and comments on performance. We have started evaluating it: the majority think it is helpful (either somewhat, or a lot). But worryingly a few have commented "no, unhelpful", and we don't know the reasons for that. But we have had positive comments on the whole. We asked about extra material for one part of the course. And we asked students how the data makes them feel… although the majority answered 'interested', 'encouraged', and 'motivated', one commented that they were apathetic about it – actually we only had a 15% response rate for this survey which suggests that apathy is widely felt.
Most students felt the dashboard provided feedback, which was useful. And the majority of students felt they would use the dashboard – mainly monthly or thereabouts.
I will be looking further at the data on student achievement and evaluating it over this summer, and should be written up at the end of the year. But I wanted to close with a quote from Li Yuan, at CETIS: "data, by itself, does not mean anything and it depends on human interpretation and intervention".
Learning Analytics – Daley Davis, Altis Consulting (London)
We are a consulting company and we are well established in Australia so I thought it would be relevant to talk about what we do there on learning analytics. Australia are ahead on learning analytics and that may well be because they brought in changes to funding fees in 2006 so they view students differently. They are particularly focused on retention. And I will talk about work we did with UNE (University of New England), a university with mainly online students and around 20,000 students in total. They wanted to improve student attrition. So we worked with them to set up a system for a student early alert system for identifying students at risk on disengaging. It used triggers of student interaction as predictors. And this work cut attrition from 18% to 12% and saving time and money for the organisation.
The way this worked was that students had an automated "wellness" engine, with data aggregated at school and head of school levels. And what happened was that staff were ringing students every day – finding out about problems with internet connections, issues at home etc. Some of these easily fixed or understood.
The system picked up data from their student record system, their student portal, and they also have a system called "e-motion" which asks students to indicate how they are feeling every day – four ratings and also a free text box (that we also mined).
Data was mined with weightings and a student who had previously failed a course, and a student who was very unhappy were both aspects weighted much more heavily. As was students not engaging for 40 days or more (versus other levels, weighted more lightly).
Universities are looking at what they already have, coming up with a technical roadmap. But they need to start with the questions you want to answer… What do your students want? What are your KPIs? And how can you measure those KPIs. So, if you are embarking on this process I would start with a plan for 3 years, toward your perfect situation, so you can then make your 1 year or shorter term plans in the direction of making that happen…
Niall: What I want you to do just now is to discuss the burning issues… and come up with a top three…
And [after coffee and KitKats] we are back to share our burning issues from all groups…
Group 1:
- Making sure we start with questions first – don't start with framework
- Data protection and when you should seek consent
- When to intervene – triage
Group 2:
- How to decided on what questions to decide on, and what questions and data are important anyway?
- Implementing analytics – institutional versus course level analytics? Both have strengths, both have risks/issues
- And what metrics do you use, what are reliable…
Group 3:
- Institutional readiness for making use of data
- Staff readiness for making use of data
- Making meaning from analytics… and how do we support and improve learning without always working on the basis of a deficit model.
Group 4:
- Different issues for different cohorts – humanities versus medics in terms of aspirations and what they consider appropriate, e.g. for peer reviews. And undergrads/younger students versus say online distance postgrads in their careers already
- Social media – ethics of using Facebook etc. in learning analytics, and issue of other discussions beyond institution
- Can't not interpret data just because there's an issue you don't want to deal with.
Group 5:
- Using learning analytics at either end of the lifecycle
- Ethics a big problem – might use analytics to recruits successful people; or to stream students/incentivise them into certain courses (both already happening in the US)
- Lack of sponsorship from senior management
- Essex found through last three student surveys that students do want analytics.
That issue of recruitment is a real ethical issue. This is something that arises in the Open University as they have an open access policy so to deny entrance because of likely drop out or likely performance would be an issue there… How did you resolve that?
Kevin, OU) We haven't exactly cracked it. We are mainly using learning analytics to channel students into the right path for them – which may be about helping select the first courses to take, or whether to start with one of our open courses on Future Learn, etc.
Niall: Most universities already have entrance qualifications… A-Level or Higher or whatever… ethically how does that work
Kevin, OU) I understand that a lot of learning analytics is being applied in UCAS processes… they can assess the markers of success etc..
Comment, Wilma) I think the thing about learning analytics is that predictive models can't ethically applied to an individual…
Comment, Avril) But then there is also quite a lot of evidence that entry grades don't necessarily predict performance.
Conclusions from the day and timetable for future events – Niall Sclator
Our next meeting will be in June in Nottingham and I hope we'll see you then. We'll have a speaker, via Skype, who works on learning analytics for Blackboard.
And with that, we are done with a really interesting day.


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neutron spin wrote:Can anyone recommend which postal service they prefer...Endicia or stamps.com and the cost effectiveness of each? Right now I mostly ship via UPS through Paypal and want to have an alternative method of shipping especially to international locations. Any info appreciated.
StampsComCorp wrote:Let me know if you have any questions.
email@example.com wrote:Thank you very much for passing us this information. I am working on getting someone in there as we speak. In the mean time you may let the forum know they can email me directly at email@example.com Just put ATTN JOSH in the subject line and I can answer questions directly.

subset: commoncrawl


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After its lawsuits against Nokia and HTC, it's Apple's turn to be on the receiving end. Elan Microelectronics, a Taiwanese chip designer which sued the iPhone maker last year, has stepped up its actions, asking the US International Trade Commission for an injunction barring imports of the iPod Touch, iPhone and iPad.
The smaller firm accuses Apple of violating an Elan patent that covers "touch sensitive input devices with the ability to detect the simultaneous presence of two or more fingers". It claims the three portable devices, plus the MacBook and Magic Mouse, are in violation of its patent, No. 5,825,352.
There is irony that the suit focuses on multitouch, given that this is a key area where Apple claims to have intellectual property, and where it has been litigious itself.
"We have taken the step of filing the ITC complaint as a continuation of our efforts to enforce our patent rights against Apple's ongoing infringement. A proceeding in the ITC offers a quick and effective way for Elan to enforce its patent," the company said in a statement. Apple gave no statement.
Elan won a similar legal action against Synaptics, a company that has set itself up as the alternative to the Apple gesture controls and which has its own gesture patents.
Copyright © 2010, Wireless Watch
Wireless Watch is published by Rethink Research, a London-based IT publishing and consulting firm. This weekly newsletter delivers in-depth analysis and market research of mobile and wireless for business. Subscription details are here.


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Magnet 'Zap' to the Brain Might Jumpstart Aging Memory
WEDNESDAY, April 17, 2019 -- Folks start forgetting things as they get older, like where they put their car keys or what they had for breakfast.
But their memories might get a boost from an electromagnetic device that gives the brain a helpful zap, a new study reports.
A small group of older people experienced improved memory function after five daily sessions with the device, to the point that they were performing memory tasks as well as a "control" group of young adults.
"After receiving stimulation, they were no longer worse than young individuals performing the same task," said lead researcher Joel Voss. He is an associate professor of neurology at Northwestern University Feinberg School of Medicine in Chicago.
The process, called transcranial magnetic stimulation, is already approved by the U.S. Food and Drug Administration to help people suffering from depression, Voss said.
The researchers wondered whether such magnetic stimulation might help invigorate regions of the brain associated with memory, particularly the hippocampus. That's the brain region that atrophies as people grow older, and it is suspected to be responsible for memory decline.
So, the investigators recruited 15 people aged 64 to 80 with normal age-related memory problems, and used magnetic stimulation on specific brain regions targeted with the help of an MRI brain scan.
The stimulation took place in half-hour sessions on five consecutive days, Voss said. It essentially involves researchers placing a figure-8-shaped magnetic coil against the head of each patient.
"This uses a magnetic field that you turn on and off really, really fast," Voss said. "That induces electrical activity at a distance. There's no electricity passing through their skull or anything like that."
The hippocampus is too deep inside the brain for the magnetic fields to penetrate, so the team instead targeted an area of the parietal lobe -- behind and slightly above the left ear -- that is highly connected to the hippocampus, he explained.
The test subjects then were brought back after a day's rest to see if the magnets had any lasting effect on the brain.
Prior to the experiment, the older study participants performed worse on memory tasks than a group of young adults with an average age of 25. The older folks got about 40% of questions right, compared to 55% correct, the researchers said.
But after stimulation, the seniors tested on par with their younger counterparts, the findings showed.
The report was published online April 17 in the journal Neurology.
"Activity in the hippocampal network went up as a function of stimulation, suggesting that the network is doing a better job of building memories after receiving stimulation," Voss said.
Among the older study participants, the ability to recall memories improved 31%, and on average they were able to correctly answer 43 out of 84 questions on a memory test -- versus 33 out of 84 before stimulation.
Unfortunately, the effect did not last. A one-week follow-up test showed that the memory improvements had dissipated, Voss said.
It's possible that by stimulating people for longer periods, or changing up the stimulation in some way, memory improvement could be longer-lasting, he suggested.
The device is very expensive, but its use in depression has already created a model by which people come by daily for therapeutic stimulation, Voss noted.
This is one of a number of approaches that use noninvasive methods to interact with the brain, said Rebecca Edelmayer, director of scientific engagement at the Alzheimer's Association.
This device currently is used to treat depression, and electrodes that provide electrical stimulation to the brain are used to help ease the symptoms of Parkinson's disease, Edelmayer said.
A study published just last week in the journal Nature Neuroscience used electrodes attached to a special EEG (electroencephalogram) cap to improve working memory in older adults, by helping different brain regions better harmonize with each other.
"The idea we could have something that's not necessarily a drug but something that could help with neuronal communication certainly may be a direction forward for therapies for those living with neurodegenerative disease," Edelmayer said.
However, Edelmayer noted this was a very small study, and it needs to be replicated before there's enough evidence to support this as a treatment for age-related memory loss.
© 2020 HealthDay. All rights reserved.
Posted: April 2019
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According to North Carolina Secretary of State Elaine Marshall, e-notaries simplify the notarization process while upholding current state laws and standards.
North Carolina standardized a new process that allows for notarization to be completed electronically. Some state officials are calling the program the first and most robust move to e-notarizations on a statewide level.
Notarizations are traditionally completed manually with paper documents and require an authorized "notary public" to approve, sign and seal official documents – often for legal purposes. Laws require that when documents are notarized, both the notary public and the parties involved with the documents are physically present for the notarization.
Although notarizations can now be completed electronically in North Carolina, often with the help of laptops or other mobile devices, the state still requires that both the notary and involved parties be physically present when the e-notarization transaction is completed. The move to digital notarizations was spearheaded by the Secretary of State's office and its current Secretary Elaine Marshall to enhance the signature value on official documents while still upholding statewide standards.
Marshall said e-notarizations will save time and money since notaries won't have to spend as much time driving to meet with individuals in need of a notarization and won't have to cover additional costs like sending documents via courier or through the mail. But despite the simpler completion process that resulted, the state did encounter some challenges along the way, such as gaining overall acceptance from local officials, Marshall said.
"Becoming an electronic notary is optional, nobody has to do it," Marshall said. "The next challenge was acceptance by the most common [notarization] filing office which would be the Registers of Deeds." Each of North Carolina's 100 counties has an elected Register of Deeds, she added.
So far, the state has nearly 150,000 notaries public officially trained and authorized, and 1,000 of them are official e-notaries, she said. The e-notary availability in North Carolina was made possible by extending the state's existing use of Docusign, a software-as-a-service e-signature transaction management platform.
Last year, the state selected Docusign, which was deployed in the State Controller's Office to electronically sign documents like travel reimbursements and background checks. The e-signature platform was approved for every North Carolina state department, and according to Marshall, is the only state to standardize notarizations on a single e-signature platform.
Marshall said Docusign had to be evaluated by the state to ensure that the company could comply with the state's e-signature standards.
Currently North Carolina is the only state where individuals perform notary public duties using the Docusign platform. Founder Tom Gonser said they intend to expand Docusign's e-notary component to other jurisdictions in the future.
Notaries can use the Docusign platform to create a personal profile that includes information about commissions, when their license expires and other background and credential details. If an individual is an authorized notary, the platform will recognize that his or her credentials are legitimate and allow acces to the Docusign tools.
"If you are a real notary and you put the right credentials in, [Docusign] will say, 'Presto, you actually are a notary,'" Gonser said.
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Grate Patrol sandwich making
Second Friday, Fourth Friday of the month, 1:30 PM - 3:00 PM
A lively group gathers twice a month in the Satterlee Hall kitchen to make sandwiches and assemble the meal for delivery to the hungry and homeless that evening. Come and join this wonderful community. Contact Wendy Garner.


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Chocolate-Covered Recipes & Chocolate-Dipped Recipes
For a healthy treat to indulge your sweet tooth, try one of our healthier chocolate-covered recipes, including chocolate-covered strawberries recipes and chocolate-dipped pretzel recipes. Make it a family activity by having your kids help dipping these treats into the melted dark chocolate. These chocolate-dipped recipes can even be customized; try our chocolate dipping technique with your favorite dehydrated fruit nuts or pretzels.


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Ranch House/Rambler
Generally referred to as the "California Ranch", this single-story sprawling home became popular in post-war America. The home takes cues from modernist homes with its open layout, indoor/outdoor entertaining spaces, and large windows. The ranch/rambler style house experienced the height of success in the 1950s and 1960s with the boom of the suburbs, and can be found all over the United States. As the style evolved, split level homes became available. The ranch/rambler style home was also one of the first architectural styles to incorporate a garage into the housing design to accommodate the needs of the modern American Family.
Elements of design:
- Influenced by modern architecture with open living spaces
- Single story with large footprint
- Outdoor entertaining space
- Building materials dependent on region: wood, stucco, or brick
- Large windows
- First home design to incorporate attached garage


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"Our experience in the port sector has been good across India. We just acquired Dharma port on the east coast. It is all set to become the Mundra of the East in the next 5-6 years, handling about 100 MTPA (million tonnes per annum)," said B Ravi, chief financial officer (CFO) of APSEZ while speaking at an international seminar organised at the Adani Institute of Infrastructure Management (AIIM) here on Wednesday.
Ravi was referring to the Mundra port in Kutch district that clocked about 100 MPTA of cargo in March this year. "We are the only port to have handled done 100 MPTA in March this year. The second in rank is Kandla port which has done about 92 MTPA.," he said emphasing how APSEZ that was just a single port company in 2010 operating the Mundra port in Gujarat, has now grown in stature and now runs about eight ports across the country.
In May, Gautam Adani-promoted APSEZ executed a definitive agreement with L&T Infrastructure Development Projects Limited and Tata Steel Limited to acquire 100 percent stake in Dhamra Port Company Limited (DPCL) which was a 50:50 joint venture between L&T and Tata Steel. The Dhamra-port deal was completed on Monday.
Dhamra port currently has a capacity of 24 MMT (million metric tonne) per annum. "We are planning to expand the capacity by an additional six MMT in the next two years time," he added.
The Dhamra port is a deep draft, all weather multi-user port that commenced operations in May 2011 and handled total cargo of 14.3 million tonnes in financial year 2013-14. The port has two fully mechanised existing berths, 63 kilometers of private rail line connecting the Bhadrak station to the main trunk line and has already achieved environmental clearance for the development of 12 additional berths.
Talking about APSEZ business in Kutch, Ravi said, "Mundra has about 40 kilometers of continuos water front. Only eight kilometers have been developed. We also have 24 fully mechanised berths which include 16 berths for bulk cargo, six container berths and two SPMs. We also have a strong marine fleet consisting of 13 dredgers and 22 tug boats."
"We are trying to build SEZ (at Mundra) in such a manner that a lot other companies come into this SEZ. We gain as a port company by handling all the cargo for all these companies," he added.
Ravi also appreciated the way Gujarat government has handled the Mundra project. "We have had the best experience and we had no delays in the projects. We had good clarity in projects," he said.


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Having fun yet?
Our photo assignment threads (this is our sixth) are averaging 1,800 hits. That's a lot of folks looking in to see what's going on. If you are one of them, we hope you'll consider joining us to share your photographic interpretations of the themes.
However, to forestall chaos, we humbly offer these simple rules:
- Photos must be shot this weekend: Fri, Sat, or Sun.
- You must provide the EXIF information if asked (we'll help you, if you'd like to know how to get it).
- No photoshop alteration (we're looking to improve your skills with your camera, not software).
- Your photograph must adhere to the theme, which will be described below.
- Post only one photo per post, so that commentary can be easily provided for that photo.
- Post your photos in this thread only. Do not start a thread in reply to this assignment. Please post your photos no later than next Wednesday.
- And, the most important rule: have fun! We're looking to spread the joy that many of us derive from taking pictures, particularly ones that tell a story of some kind.
This week's theme: "Group Dynamic."
Our friends at Wikipedia define group dynamics as "the study of groups, and also a general term for group processes. In psychology and sociology, a group is two or more individuals who are connected to each other by social relationships. Because they interact and influence each other, groups develop a number of dynamic processes that separate them from a random collection of individuals. These processes include norms, roles, relations, development, need to belong, social influence, and effects on behavior.
As with other challenges, interpret this theme as you will. I merely offer the definition above as a jumping-off place. You need not limit your definition of groups to "individual" humans.
Now get out there and take some pictures.


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- Williams news
Maldonado backing unaffected by Chavez death
- Drivers:
- Pastor Maldonado
- Teams:
- Williams
Pastor Maldonado's backing from Venuzuela's government should remain unaffected by the death of Hugo Chavez, according to Sky Sports pundit Martin Brundle.
Maldonado is backed by Venuzuela's state oil company to the tune of around US$30 million and Chavez was personally a staunch supporter. There has been speculation in the last 48 hours as to the prospects of the funding continuing.
"He became a national hero for winning the Spanish Grand Prix last year and I think that has been good for Venezuela and good for his sponsors, so why would they want to run away?" Brundle said. "Obviously, politics may well play a part but I think he has shown he has tremendous speed [but] the state of play in F1 and global economics means that cheque helps him a lot."
Maldonado was one of the guards of honour at Chavez's funeral on Friday.


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Creamy Vegan Cashew Cream Cheese
Don't get me wrong, I love vegan cream cheese alternatives from companies like Tofutti. It's just that I've been wanting to have an option for something that's a little more natural. Creamy Vegan Cashew Cream Cheese doesn't taste like cream cheese as much as some of the space age alternatives but it's close enough for me. Keep in mind that if you forego using the xanthan or guar gum in this recipe it won't be as creamy. It's use is recommended- we're trying to emulate lactose here so we need all the help we can get.
Also check out my other Vegan Cashew Cream Cheese recipe which is more involved but more similar to traditional dairy-based cream cheese.
Find more Cashew recipes on Veganbaking.net
Creamy Vegan Cashew Cream Cheese Recipe1 ½ cups raw, unsalted cashew pieces
2 Tablespoons canola, light olive oil or rice bran oil
1 Tablespoon non-dairy milk, unsweetened
2 teaspoons apple cider vinegar
1 teaspoon lemon juice
¼ teaspoon salt
¼ teaspoon xanthan or guar gum (optional)
1) Soak the cashewsRinse the cashews then soak them for 12 hours.
2) Blend the cashews with the flavor building ingredients then allow it to restDrain the cashews and add them to a food processor with the canola oil, non-dairy milk, canola oil, apple cider vinegar, lemon juice, salt and xanthan or guar gum. Blend for several minutes until the mixture is smooth. Wrap the mixture in a cheesecloth and place it in a clean bowl. Let it sit in a lukewarm place such as on top of the stove for 12 hours. This allows the mixture to "rest" and develop slightly more complex flavors.
3) Remove the cheesecloth from the vegan cream cheeseRemove the cheesecloth. Keep the cream cheese in a covered container in your refrigerator for up to one week. This recipe makes about 8 fluid ounces or 1 cup of Creamy Vegan Cashew Cream Cheese.
Get a price on the Food Processor I Recommend at Amazon.
User reviews
1 reviews
Wow! Looks really delicious, thanks for sharing this recipe in this site.
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Such a great taste
Wow, my husband and I absolutely loved this! I put it on all kinds of my dinners and I always sneak it into my husband's sandwiches for his lunches. :) He has never complained.
Thanks from Tammy and Doug with https://www.masonryscottsdale.com/
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Top 50 Reviewer
View all my reviews (3)
the link to the more involved cream cheese seems to not be working, and I tried using the search function but could only find this one.
Role of xanthan gum?
Is there a substitute for the xanthan gum, such as flax seed, chia seed or corn starch, that could be used in this recipe?
Can the canola oil be replaced with peanut or rice oil? Here in Europe canola oil is almost impossible to find...
Not bad!
I liked the creaminess and it was very easy to make. I feel like it could be a liiiiittle more flavorful? Maybe I just need to tweak it to taste though. I'm probably just being too needy and missing the regular flavor of cream cheese.. Definitely a good cream cheese alternative though!
Super D licious
I can't get over the taste of this. Who knew cashews could taste soooo creamy and delicious. I'm not a tofutti fan and neither are my children. What took us soo long of becoming vegans was the dairy. By watching a dairy farm that claims to be organic proved to us we were in just denial of what really goes on. I still crave dairy products but am learning and tasting new things. I am overly sensitive to taste and smell. I am vouching this is soo far better than anything we've tried.
Super Awesome! Thank you!!
I think this cream cheese is sooo much better then the tofutti brand! I made it today (tomorrow I am going to use it to make the cheesecake) and I will now have this a constant in my fridge. I can't keep spreading it on toast and just eating it plain because it's so creamy. Now I had to add a bit more soy milk because I don't have a food proccessor and made it in my blender and it still came out great. I was glad to have such a great recipe and am very grateful! Tomorrow I buy bagels!
Good Stuff
I'm giving this a 4 because it didn't taste as good as Tofutti Cream Cheese but hey it's from Cashews so how close are you gonna get? Good as a dip or spread either way.


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The 100+ MPG Plug-in Hybrid Hummer H3
Raser Technologies unveiled a Hummer H3 late last year with a plug-in gas/electric hybrid 4×4 powertrain and a claimed mpg rating of 100+, they were working closely with Hummer and FEV on the project and have made it clear that the E-REV power train is easily portable between large SUV's (see the image below). There are no plans to put this power train into production as of yet, which seems a shame as even if they offered a conversion service it would doubtless be very popular in states like California and Texas. Lanjut →


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Hi everyone,
The elite team of Selmer#607 is about the record a 3rd album. It features some of the best gypsy jazz players in the world.
To support the project and preorder the CD, just google 'kisskissbankbank Selmer 607'.
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Nikon announces redesigned Nikkor 50mm f/1.4
In celebration of the firm's 75th anniversary, Nikon has launched a redesigned Nikkor 50mm f/1.4.
A mainstay of many amateur and professional gear bags alike, the 50mm f/1.4 is a classic lens design providing a fast maximum aperture and a perspective that "closely replicates the visual perspective of the human eye" on a full frame camera.
The AF-S Nikkor 50mm f/1.4G's redesigned optics and Nikon's Super Integrated Coatings lead to improved flare and aberration control with the new lens. A nine-blade rounded aperture also touts smoother out-of-focus area presentation than previous versions.
Designed for use with either FX or DX format Nikon DSLRs, the 50mm f/1.4G should be available through dealers in December. Projected street price is around $440.