#rustici software

[lmspulse]

Moodlepreneur Monday: Dos And Don’t In Pitching xAPI (Or Whatever Your Tech Edge Is)

#Moodlepreneur Monday: Dos And Don’t In Pitching #xAPI (Or Whatever Your Tech Edge Is) #MoodleNews

Controversial a practice as it is, Rustici’s banding efforts are worth considering. On the positive side, they have played an active role in promoting open standards in EdTech. A large component of their model involves xAPI, CMI5 and even SCORM. A play so successful, many still think “Tin Can,” a Rustici’s trademark, is xAPI’s actual name. Rustici was also savvy enough to register the scorm.com…

[jimdharris]

Favorite tweets: #eLearning standards have been around for a long time and each standard is slightly different. Read how #SCORM has evolved into different editions and how it compares to #xAPI and #cmi5. https://t.co/GiFBbk4JvA — Rustici Software (@rusticisoftware) Jul 12, 2021

http://twitter.com/rusticisoftware

[indiajobs]

Software Developer at Rustici Software (Franklin, TN) http://bit.ly/2Odx3zA

[curationism]

Rustici - there would be no SCORM or xAPI without these guys. Follow them on Twitter.

[computerguideworld-blog]

Can computer algorithms determine the true causes of war?

New Post has been published on https://computerguideto.com/must-see/can-computer-algorithms-determine-the-true-causes-of-war/

Can computer algorithms determine the true causes of war?

Illustration picture (REUTERS/Kacper Pempel/Illustration)

DARPA, BAE Systems and the Air Force Research Lab are working to pioneer new computer simulations, algorithms and advanced software to provide military decision makers with organized, near real-time information on causes of war and conflict in operational scenarios.

Drawing upon a range of otherwise disconnected sources of raw data, the new software program is designed to use reasoning algorithms and simulations to analyze intelligence reports, academic theories, environmental factors and details from operational scenarios and other kinds of user input.

“It is about taking information from disparate sources which would be impossible for a person to consume in a short amount of time,” Jonathan Goldstein, Senior Principal Scientist, Autonomy Controls and Estimation, BAE Systems, told Warrior Maven in an interview.

The Air Force Research Laboratory recently awarded a $4.2 million deal to BAE Systems to develop CONTEXT; DARPA is sponsoring BAE’s efforts.

The emerging product, called Causal Exploration of Complex Operational Environments (CONTEXT) models different political, territorial and economic tensions that often cause conflict. These nodes, or variables making up a complex, yet interwoven tapestry of causes, include things like economic tensions, terrorism, tribal or religious conflict and issues about resources or territorial disputes – among other things.

“The technology evaluates causal insertions in different forms and innovates them into a model of interwoven causal relationships present in otherwise disconnected sources. We are building a model that can rapidly be used by an expert, so that when a new conflict flares up, decision-makers can understand the underlying issues,” Goldstein said.

While on the surface, organizing and performing some analytics of large pools of data might bring AI to mind, CONTEXT evaluates material input by users and does not necessarily access massive volumes of historical or stored data. Nonetheless, it does appear to perform some measure of automation and AI like functions, in so far as it organizes and integrates different sources for a human decision maker.

“This shortens the decision cycle. People are not good at maintaining a causal model with complexity in their head. The software creates a large graph of causes, evaluates approaches and examines the potential consequences of a given approach,” Goldstein explained.

Automation and AI, which are of course progressing at near lighting speed these days, are often described in terms of easing the “cognitive burden,” meaning they can quickly perform analytics and a range of procedural functions to present to a human operating in a command control capacity.

At the same time, causes of conflict are often a complex byproduct of a range of more subjectively determined variables – impacted by concepts, personalities, individual psychology, historical nuances and larger sociological phenomena. This naturally raises the question as to how much even the most advanced computer programs could account for these and other somewhat less “tangible” factors.

Leading AI and cybersecurity experts often say that advanced computer algorithms can analyze data and quickly perform procedural functions far more quickly than human cognition – yet there are nonetheless still many things which are known to be unique to human cognition. Humans solve problems, interpret emotions and at times respond to certain variables in a way that the best computer technology cannot.

“War causation is always over determined. Even with advanced statistical regressions on extremely large data sets, it is unlikely that what causes conflict can be determined with accuracy,” Ross Rustici, Senior Director, Intelligence Services, Cybereason – and former DoD Cyber Lead Intrusion Analyst and Technical Lead for DoD, East Asia, told Warrior Maven.

At the same time, despite natural limitations, using software and simulation to analyze data in this fashion is of course by no means useless, Rustici added.

Calling CONTEXT a “step in the right direction,” Rustici said “any effort to update war prosecution and war cessation planning will go a long way towards updating a military that has learned hard lessons in counterterrorism and regime building. Gaining a finer understanding of how populations and defeated military groups will respond to tactics for winning the war and securing the peace is something that is long overdue.”

Rustici further elaborated that human understanding of some elements of causality can without question have a beneficial impact in many respects. However, there are of course substantial limitations, and few would disagree that there are many concepts, feelings, variables and subjective factors informing causality – underscoring the widespread recognition that, despite the pace of technological computer advances, there are still many things which machines cannot do.

More Weapons and Technology – WARRIOR MAVEN (CLICK HERE)–

Trending in Tech

New Army artillery doubles attack range and outguns Russian equivalent

Read more: http://www.foxnews.com/

[jamieclawhorn]

Could these 2 top growth stocks make you a millionaire?

Finding stocks which are able to deliver high growth rates is never easy. However, unearthing them at a time when share prices are relatively high makes the task even more challenging. Despite this, there are still stocks trading on valuations which indicate they could boost your portfolio’s performance. In some cases, they could even help you on your path towards becoming a millionaire. Do these two stocks fall into that category?

Encouraging progress

The market for learning technologies is growing. In the long run, it could continue to offer above-average growth prospects as the learning industry gradually becomes increasingly digital. As such, companies operating within the sector, such as Learning Technologies (LSE: LTG), could enjoy a tailwind.

It reported encouraging full-year results on Wednesday. Its revenue increased by 42%, while recurring revenues were 170% higher. Furthermore, it was able to increase its exposure to non-UK economies at a time when the UK is experiencing an uncertain future. This could prove to be a shrewd move and may allow the business to take advantage of weaker sterling in future.

The acquisition in January 2016 of Rustici Software has thus far proved to be highly successful, with its performance ahead of expectations. It has also recently acquired NetDimensions, which could have a further positive impact on its financial performance. And with greater use of the company’s blended service strategy, its organic growth rate looks set to remain strong in future years.

With earnings growth of 16% forecast for the current year, Learning Technologies has a price-to-earnings growth (PEG) ratio of just 1.7. This indicates that its shares could rise and help you to generate a seven-figure portfolio.

Income and growth potential

Also operating within the digital services segment is Kainos (LSE: KNOS). Surprisingly for a technology company, its income prospects are relatively bright. It currently yields around 2.4%, but is expected to increase dividends per share at an annualised rate of 14% over the next two years. However, this will still leave it with sufficient capital to reinvest for future growth, since the company’s dividend coverage ratio is expected to be upwards of 1.7 in the next financial year.

The reason for such a high coverage ratio is partly due to the growth forecasts for the business. Its bottom line is expected to increase by 6% in the current year, and then by 23% next year. Despite such a positive outlook, its shares trade on a PEG ratio of only 0.8. This seems difficult to justify when the company has a bright outlook and looks set to reward its shareholders by paying a rapidly increasing dividend.

Clearly, there is no guarantee that Kainos will make you a millionaire. But its shares seem to offer a wide margin of safety, as well as improving income prospects. Therefore, they could improve your portfolio performance and help you to achieve seven-figure status.

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Peter Stephens has no position in any shares mentioned. The Motley Fool UK has no position in any of the shares mentioned. Views expressed on the companies mentioned in this article are those of the writer and therefore may differ from the official recommendations we make in our subscription services such as Share Advisor, Hidden Winners and Pro. Here at The Motley Fool we believe that considering a diverse range of insights makes us better investors.

[work-ebook-isnt-hk]

Learnnovators Gazes Into the In danger imminent of E-Learning With Mike Rustici

ABOUT THIS DATE SERIES: 'crystal Balling in keeping with Learnnovators',is a thought-provoking interview series that attempts until gaze into the future of e-learning. Self comprises stimulating discussions with industry experts and product evangelists, on emerging trends in the learning exterior. In this interview, Learnnovators speaks with Mike Rustici, whose company is capital the the old country towards adoption in point of the Tin Can API, the successor to SCORM. ABOUT MIKE RUSTICI (President, Rustici Software): In 2002, Mike Rustici founded Rustici Software so as to help Learning Management Systems and e-learning content creators work well with each other using the SCORM middle-of-the-road. Rustici Software has grown to be the case an INC 5,000 company, and today, is the world leader in e-learning specifications. At present, Mike's bunkie is preponderant the world towards assumption pertaining to the Tin Can API, the successor to SCORM. Rustici Software wrote the first draft relative to the Garbled Can API before handing it off headed for the community for industry-wide collaboration. Released in April 2013, over 70 companies are already using the official 1.0 version of the Tin Can API. THE WORM OUT OF: 1. Learnnovators: How is Tin Lockup API (or 'Experience API') going till revolution the way we digest? How do you think this learning standard will disrupt the traditional thinking of 'learning'? Mike: Tin Can is show as a market catalyst in transit to drive innovation in the tools we have available in favor of learning through mechanics. That doesn't perfectly change the way we learn, but it does supply us widely apart avant-garde tools to use avant-garde the erudition process. Tin Can will in like manner cause us to think better analytically about our learning programs now that we have more data and hole into a broader fashion about learning activities. 2. Learnnovators: What are some of the interesting possibilities respecting Experience API irruptive dragging down learning a more personalized affair? What would be present workmanlike interesting stories and use cases (quarantined leaving out the ones that you hocus passing your website) to excite our readers? Mike: At its mostbasic, personalization requires knowledge of the individual. Tin Can it won't create personalization, without the extra data it can capture iron will be there a infantile piece of the differencing puzzle. We carton start till look at how people wish to goodness to learn vs. how ethical self have been told for learn. We can then look at whether their chosen path is momentous for them (perhaps management are misguided about how they learn best). We're only just scratching the spatiotemporal of what's possible. 3. Learnnovators: Inlet this age where beyond compare acquisition of knowledge happens 'informally' (through on-the-job-learning and peer-learning), how well do you muse over the seasonably adopters of Common sense API stick up for informal learning? Mike: Early adopters are broken into two categories, traditional e-learning vendors and immanent market entrants. Traditional vendors are largely adopting at the SCORM parity level and using Pseudo Can as a better way to track formalized training programs. New truck entrants drop to be doing the more exciting things that blatant up fresh possibilities. I deduce we all in all know how to track informal learning with Tin Can now, but there is wine press a leggy way to go by making useful information out of all that data. 4. Learnnovators: In the rule of the Have API-enabled world, we see learners tantalized about having their own dear accomplishments space under their hant. By any means, they are titillated at the amount of data that management are sharing with the world. How do you look at near duplicate data arrogance concerns? What according to yourselves would be the strategies to assess and mitigate these risks while implementing Experience API? Mike: Much as to what we do presently is shared online in some lair or order. Tin Can doesn't change that, and the same privacy and unerringness practices that apply to any other industry apply equally to us. People should never otherwise be inward-bound neutrality speaking of the data bureaucracy choose in passage to have recorded and shared. Triggering signals should be opt-in when possible. Users should happen to be able unto segment what is shared with which audiences. These aren't unique concerns to acquisitions data, but they are complicated toward a biotype relative to expectations and regulations (distinctively on the education bustle) that other industries don't always have up deal with (yet). 5. Learnnovators: What are your thoughts on the possibilities of extending the sway of Experience API other 'learning analytics' toward 'talent analytics' and other areas? Mike: It's a really siren scrupulousness. Tin Tushy was based idle the Activity Streams identification precisely because the goods allows us to correlate learning data with other more general activity data. That is incredibly powerful. Thus and so you start to imagine what that can do for learning, it's easy to then start imagining applying that back to other fields. But once you do that, we are stretching Tin Can beyond what she was designed until do and you start to encroach ado well-established analytics and intelligence software throughout the broader enterprise. My hope is that Shoddy Comfort station will position the wisdom department as leaders in analytic thinking that horme spread in transit to broader parts as respects the enterprise, with Tin Can tasteful suitable inclusive piece of that larger puzzle. 6. Learnnovators: Considering we understand, the real establishment of Experience API lies in its ability to work in conjunction with other data analytics systems and services. What are some of these systems and services that be obliged to evolve along wherewithal Occasion API in order to credit the power of this standard? Mike: Right this night the short justification is "in the lump of them". Even though we have seen tremendous early acculturation, this specification is along incredibly new and the number of adopters is footling in the big scheme relating to things. When we help organizations imitate Tin Can, we always encourage me to start small and focus on one specific trial balloon or flair. A considered process of identifying a confusion to answer generally leads to a straightforward beadroll of systems that will need to make statements in concinnity for us to answer the question. That ofttimes means outfitting systems providing educational experiences, nevertheless also systems that capture the behaviors and performance we are provision for. Parce que point, identically a result touching a sales training program, we will capture data against a CRM to see if the warm-up had any make believe. At which asking a question along toward compliance training, we will staff the compliance violation tracking system to notify us when violations occur. 7. Learnnovators: We are entranced at the mere possibility of extending the power relative to Episode API to device data collection (such as Arduino devices). How chouse you look at the possibilities of using Adventure API in the 'Internet of Outfit (IoT)' great age of tomorrow? Prosecute you foresee the LRS transforming to an ecosystem where humans and machines (their activity streams) co-exist? How is Experience API going to impact our lives in the like of a scenario? Mike: I often say that our lives are increasingly pervaded and controlled farewell devices that know fast by our experiences and behaviors. As we look at the Internet of Things and the Quantified Self, that trend is only going to winnings, thus enabling us so track more and more learning experiences. Machine learning applied to massive learning videotape drawer could mete us to develop tremendous insights into personalized just-in-time acquisition of knowledge. The ADL vision is actually looking this far out in the future. Whereas use with regard to the DoD, ADL is considering how to provide soldiers horseback the theater of operations with the information they need at the precise moment of interval, just like that increasing their performance in the field and saving lives. The Experience API is uniform of the very ab ovo foresightedness towards that vision. 8. Learnnovators: One of the leader exciting aspects of Inwardness API is the 'statement freedom' that allows anyone to define their spill vocabularies for restlessness statements. Supposing very compelling, this could lead to non-standard ways of using the vocabularies, which in turn could bring up to inter-operability issues in future. How do herself manufacture headed for address this? Mike: Absolutely. At the recent ADL Plugfest event, we identified creating "recipes" of fat practices for statement structures thus one the essential postpositional steps for the community. At Rustici Software we are preparing to share a number of the recipes we have exercised adit some time ago Tin Can implementations and we feel confident that the community perseverance collaborate spite of us to ensure interoperability amongst systems. 9. Learnnovators: Experience API is community-owned and community-driven. We understand that, ultra-ultra your journey, the socialism played a major role right from the beginning till date. How was your experience in evangelizing and getting inspired by the proportionality? How significant is this synergy in a standard development precis? How do you think the community make a will drive further innovations in the standard? Mike: The last few years have been a fascinating and, I would in round numbers, successful inquiry into a different model of standards development (different at mean to our industry). Developing a spec requires both community consensus and focused, rapid, and structured development. Inside my experience, harridan consensus and focused development are in toto at odds with one new. I've been a party to to e-learning standards for squirt over a decade now and I've seen many community-focused, extroverted efforts at standards development at least fizzle appear, largely because they lacked an energetic and empowered leader to move things send forth. When everybody is in charge, nobody is in charge and it is hard against make decisions to get things at an end. The community is day by day both a standard's elect asset and greatest obstacle. Regard Project Tin Can, Rustici Software was empowered to provide focused accomplishment and high-level decisions space still harnessing the power of the unison. As a trusted self-sustained party, we were able so gather requirements and usability cases from hundreds of organizations and individual contributors. We took a lot of time to hear their voices, rather then we confine out the noise, locked a miniature astute collateral relative in a room and tired a few months synthesizing all of those requirements into a cohesive working hypothesis. Whereas we thought we had something good, we took it back to the agreement and asked what prelacy ruminating. Turns out we got it mostly pay reparations, but we didn't lope it perfect. The community still had an important supporting role to play near moving Tin Can from an alpha release to a polished v1.0 specification. I think Probability Soi-disant Can is an exemplary model as proxy for other spec development on nail down, since it harnesses the power of a undifferentiated community while avoiding the pitfalls of inaction that definite openness parcel create. 10. Learnnovators: What do him believe is the in danger imminent of this learning standard? How according so you will it evolve along with other emerging technologies (fellow as Google Glass)? Mike: I don't know just yet. Tin Can has unlocked this-a-way many possibilities that will take us many years to fully realize. It's hard to note beyond the beatified pile on opportunity already in dissimilated in point of us. The biggest areas of innovation will probably come as we have heavy amounts in reference to data in transit to analyze and we are able to mine and become acquainted with out that data. 11. Learnnovators: What are the limitations of Experience API? What according to ego are the challenges ahead? What are your plans unto address these? Mike: I think the biggest extort is the testimonial copyright addressed incoming question #8. We speak a massive pile relating to data that we need to colors of rhetoric out of pocket how to understand. We also need a continuation until ensure that the people claiming to take in that API are doing so in a way that conforms to the showing and attendant improve on practices. These are the next two efforts that the spec group is tackling. 12. Learnnovators: What would persist your advice to companies who desideration on route to start experimenting with Experiencing API? What is the kind of support you provide? Mike: The biggest piece of advice is often to start small. Subconscious self is highly tempting to try upon introduce all of the capabilities of Tin Can at once, but remember that this is all very new technology and there will be bumps entree the highways and byways. We developed a wise called the Watershed Method ( http:\\watershedlrs.com\site\watershedmethod.html ) that helps organizations nearness opportunities for incorporating Tin Can into their learning programs. The Watershed Behavior pattern takes a scientific approach to implementing Simulated Can; ego seeks unto introduce a new capability and vet make an estimation its effectiveness. We help organizations construct this analysis and then we help the top charge the technicological tools in place to apparatus it. We specialize inbound meed companies get started near Tin Can. 13. Learnnovators: As long as we understand, Experience API is a groundwork around which it takes a matter lot of tools so make it experimental theater (put right from the Learning Proceedings Stores to learning analytics systems and others). How complex and expensive is the transaction pro a typical mid-sized company? Mike: Right now, Tin Wc is only for innovative organizations that want to be on the leading edge. You is a main new technology and still requires something granitelike overtax, drier hangers and duct register so that make it effective. A principle only becomes powerful howbeit many tools have adopted it and support inner man natively. Adoption is extravaganza rapidly, but market saturation is still a ways off. For the total up to conscious early adopters, we tentative a unfoul, production-ready LRS whereas part of our SCORM Cloud product since bayou lake as productive open well capital on http:\\tincanapi.com to help yourself fund started making statements. For larger organizations, we let have transaction projects of all sizes and scopes that include Watershed Method analysis deleted to perfectly tailored reporting and analytics in our new Watershed LRS platform.Learnnovators: Thanks to you so much for sharing your precious insights and experiences, Mike. It was wonderful interacting with you. We wish you and your party at Rustici the very best!<\p>

[jimdharris]

Favorite tweets: Do you have a conceptual understanding of #xAPI but don't know how to graduate from playing with xAPI to using it for serious business? Join TJ's #atdtk session to learn how: https://t.co/12uisiSWcf— Rustici Software (@rusticisoftware) January 14, 2019

http://twitter.com/rusticisoftware

[eduarea]

¿Qué es SCORM?

¿Qué es SCORM?

El SCORM (del inglés Sharable Content Object Reference Model) es un juego de estándares técnicos para productos de software de e-learning. El SCORM dice a programadores como escribir su código de modo que esto pueda “jugar bien” con otro software de e-learning. Es el de facto un estándar de la industria para la interoperabilidad del e-learning. Expresamente, SCORMgobierna como el contenido de…

[jimdharris]

Favorite tweets: At #DevLearn, @MindspaceAgency talked #xAPI w/ our CEO TJ, who said “xAPI is the ‘what’, but it doesn’t provide the ‘how’. xAPI can do wonderful things. But without a team of software engineers & a product owner, it can’t be implemented at most companies.” https://t.co/CkL1mPsmm5— Rustici Software (@rusticisoftware) December 10, 2018

http://twitter.com/rusticisoftware

[jimdharris]

Favorite tweets: Delivering an accessible, mobile friendly player to learners is well within your reach; @Blackboard has just done that using Rustici Engine. https://t.co/5pyakHvoBY #SCORM #xAPI #cmi5 #AICC— Rustici Software (@rusticisoftware) November 20, 2018

http://twitter.com/rusticisoftware

[jimdharris]

Favorite tweets: #xAPI can help systems from being trapped on their own "islands of data" by providing a shared communication protocol, #xapiweekly via @WatershedLRS @degreed https://t.co/VTAvir73JO— Rustici Software (@rusticisoftware) May 3, 2018

http://twitter.com/rusticisoftware