Learning Analytics Courses

George Siemens

After about a year of planning, we can finally announce the following courses on edX focusing on learning analytics. The intent of these courses is to eventually lead into a MicroMasters and then advance placement in an in-development Masters of Science in Learning Analytics at UTA. Each course runs about three weeks and we’ve tried to settle on prominent analytics tools for educational data so the experience is one where skills can immediately be applied.

Open Learning Analytics

George Siemens

While those sensemaking approaches won’t disappear, they will be augmented by data and analytics. Educators often find analytics frustrating. Or can analytics actually measure what matters instead of what is readily accessible in terms of data? All educators need to be familiar with data and analytics approaches, including machine and deep learning models. Open Learning Analytics. Learning Analytics Masters Program (LAMP).

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Open Learning Analytics. Again

George Siemens

Several years ago, a group of us wrote a concept paper on Open Learning Analytics (.pdf). Our goal was to create openness as a foundation for the use of data and analytics in education. Few things are more important in education today than the development of an open platform for analytics of learning data. Most educators and students are unaware of how much algorithmic sorting happens in the educational process.

Social Physics - Reinventing Analytics to Better Predict Human Behaviors

Irving Wladawsky-Berger

They’ve enabled the construction of AI algorithms that can be trained with lots and lots of sample inputs, which are subsequently applied to complex problems like language translation, natural language processing, and playing championship-level Go.

Open Learning Analytics: A proposal

George Siemens

Learning analytics are increasingly relevant, and prominent, in education. Startups and established software vendors are targeting learning analytics in their product offerings for the education and training and development sector.

Notes On "Global Guidelines: Ethics in Learning Analytics"

Stephen Downes: Half an Hour

In my post referencing the ICDE's Global Guidelines: Ethics in Learning Analytics yesterday I said: This document summarizes the considerations of an ICDE working group on learning analytics. The presumption throughout is that a global ethic in learning analytics is needed, can be known, and comprehends the issues in this document. Definition and purpose of the use of Learning Analytics Where is data drawn from? What data must be included in learning analytics?

The Competitive Value of Data: From Analytics to Machine Learning

Irving Wladawsky-Berger

Business analytics predates the big data era. Beyond business analytics, new data science methods could now be used to extract actionable knowledge from all that data, that is, knowledge to help make better decisions and predictions.

Light-weight learning analytics tools

George Siemens

The process is simple: install a simple bookmarklet in your browser, go to your LMS, select the discussion forum that you want to analyze, and then activate the SNAPP plugin. I’ve heard of SNAPP before – &# software tool that allows users to visualize the network of interactions resulting from discussion forum posts and replies&# – but decided to play around with it today.

Sensory Processing and School Underachievement

Eide Neurolearning

Disabilities that occur often without obvious physical signs, like sensory processing disorders or dyslexia, are often harder to 'prove', harder to qualify for accommodations, and often faulted as being due to laziness, poor effort or motivation, or retardation.

Analytics – The Usability Lab of the new decade

Adaptive Path

But more nimble development processes and new tools seem to have superseded the usability lab. survey tools for straight-up surveys and concept evaluations public betas, previews, and opt-ins By picking a smart set of these tools, I think an organization can make smarter decisions throughout the design and development process in a live dialog with more users than a traditional usability lab ever could. The gist of the internal response was, “Analytics!&#

Bravais 3.0: Taking Learning Beyond the LMS to Analytics & Personalization

Xyleme

Gathering intelligence requires tracking and analytics - enter the Tin Can API, or xAPI. adds a fully integrated Learning Record Store (LRS), which tracks and stores data at every single step of the learning process, whether that learning process occurs inside the LMS or elsewhere.

Social Media Measurement and Learning Analytics: How Do I Love Thee, Let Me Count the Ways

Beth Kanter

I tested out the five phases of falling in love with measurement. Given the topic was measurement, I couldn’t help but go a little meta and play with incorporating learning analytics into the instruction. This blog post shares some insights about those two somewhat disconnected ideas.

Online Community Purpose Checklist | Full Circle Associates

Nancy White

What are the group’s specific outcomes or process goals? A process oriented group may be about building relationships that can then be deployed in the field, such as a group of emergency relief workers, building relationships before disasters so they ca better respond and relate in the field.

My Old Online Facilitation Workshop Materials | Full Circle Associates

Nancy White

We share the best processes, experience and methodologies, along with the latest in social technology, to inspire a better way to work.

Getting on the AI Learning Curve: A Pragmatic, Incremental Approach

Irving Wladawsky-Berger

Two-thirds of the opportunities to use AI are in improving the performance of existing analytical use cases,” is the paper’s overriding finding. And, in the remaining 15% of cases, machine learning provided limited additional performance over existing analytical methods. .

Getting on the AI Learning Curve: A Pragmatic, Incremental Approach

Irving Wladawsky-Berger

Two-thirds of the opportunities to use AI are in improving the performance of existing analytical use cases,” is the paper’s overriding finding. AI is now being successfully applied to tasks that not long ago were viewed as the exclusive domain of humans, - machine translation, natural language processing, defeating the world’s top Go players, - but only 16% of the use cases studied by McKinsey are greenfield cases, where only machine learning techniques can be used.

My Old Online Facilitation Workshop Materials | Full Circle Associates

Nancy White

We share the best processes, experience and methodologies, along with the latest in social technology, to inspire a better way to work.

humans working socially

Harold Jarche

As machines do more repeatable processes and even complicated work, people have to look at what we do best. Working socially, we can address barely repeatable processes for complex situations and over time make parts of them repeatable for the machines to handle.

Multiple pathways: Blending xMOOCs & cMOOCs

George Siemens

I’m running a MOOC on edX in fall on Data Analytics & Learning (registration will be open soon). As part of this process, we organized a designjam recently bringing together 20 or so folks to think through the design process.

The Emergence of Industry 4.0

Irving Wladawsky-Berger

The Third, - following World War II - saw the advent of computers, digital technologies, the IT industry, and the automation of process in just about all industries. focused on the automation of single machines and processes, Industry 4.0

How to Support the Widespread Adoption of AI

Irving Wladawsky-Berger

Surveys with thousands of executives, showed that most firms are only using AI in ad hoc pilots or applying it to a single business process.

How to Transform a “Big, Old” Company into an Agile Digital Business

Irving Wladawsky-Berger

Many of these established companies have already deployed mobile apps, cloud computing and data analytics, and have brought to market a variety of digital products and services. It takes a high-level view of the interactions among people, process, and technology.

Social Physics and Cybercrime Detection

Irving Wladawsky-Berger

These patterns can be used to detect emerging behavioral trends before they can be observed by other data analytics techniques. Endor’s analytics engine identified 80 Twitter accounts as potential EOIs because they were similar enough to the positive samples that the agency provided.

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Can AI Help Develop and Execute a Competitive Business Strategy?

Irving Wladawsky-Berger

In today’s data-rich markets, top business leaders rely heavily on analytics and quantitive measures to define, communicate and drive strategy. As ‘accountable optimization’ becomes an AI-enabled business norm, there is no escaping analytically enhanced oversight.

A Framework for Building AI Capabilities

Irving Wladawsky-Berger

Based on a study of over 150 AI-based projects, the authors found that AI can play a major role in three important business needs: advanced process automation, cognitive insight through data analysis, and cognitive engagement with customers and employees. Advanced Process Automation.

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democracy and equality

Harold Jarche

Private Algocracy: the power over data, data analytics and decision making are fully moved to multi-national data companies who is taking over the regulation. Will technology empower or frustrate learning and will established powers control individuals or will something new emerge?

Requisite conflict …

Dave Snowden

Distribution the cognitive or interpretive process. frequently contradictory, experiments that can fail, mutate and sometimes succeed we explore a space and allow common meaning and objective to emerge without the heavily facilitation and compromise of most conflict resolution processes.

Organizing Big Data Initiatives: Lessons from the Internet

Irving Wladawsky-Berger

my fellow guest columnist Tom Davenport reflected on whether institutions should appoint a dedicated executive to oversee their company-wide big data and analytics initiatives, and if so, which C-level senior executives should such a position report to.

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Predictions for Learning and Development for 2018 and Beyond

Xyleme

Without having analytics to help provide insights into the value of their content, and how learning is being used, being able to appeal to business goals will be difficult. As work is more online, there is the opportunity to integrate learning with the work process.

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… and nearer to the Dust

Dave Snowden

Now this was in the early days of data analytics, we were just getting started with key word searches and the like. One of the deeply negative aspects of the knowledge management period of a decade or more ago was the gross confusion of information with knowledge.

Decision Making in Our Increasingly Complex Organizations

Irving Wladawsky-Berger

Over the years, we’ve learned to define all kinds of tasks in terms of such digital operations, e.g., inventory management, financial transactions, word processing, photography.

A Framework for Building AI Capabilities

Irving Wladawsky-Berger

Based on a study of over 150 AI-based projects, the authors found that AI can play a major role in three important business needs: advanced process automation, cognitive insight through data analysis, and cognitive engagement with customers and employees. Advanced Process Automation.

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Announcing Bravais 1.2!

Xyleme

Users that have both Xyleme LCMS and Bravais have a huge advantage- consolidated analytics. Furthermore, because Xyleme follows an Agile Development process, analytics will soon be enhanced with new features such as social comments and ratings on a continuous basis. Bravais 1.2

New Horizon Report: Alan Levine – Mindmap

Clark Quinn

Their process is interesting, using a Delphi approach to converge on the top topics. For the longer term (4-5 years), the two concepts were gesture-based computing and learning analytics.

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The Emergence of Industry 4.0

Irving Wladawsky-Berger

Industrial revolutions are momentous events,” said A Strategist Guide to Industry 4.0 , - a 2016 article in strategy+business. “By most reckonings, there have been only three.” The First Industrial Revolution , - starting in the last third of the 18th century, - introduced new tools and manufacturing processes based on steam and water power, ushering the transition from hand-made goods to mechanized, machine-based production.

What I’ve learned in my first week of a dual-layer MOOC (DALMOOC)

George Siemens

This last week we launched our open course on Data, Analytics, and Learning on edX. In the process, I’ve used roughly any tool I can get my hands on, including Second Life, Twitter, Facebook, G+, Netvibes, blogs, Wikispaces, Diigo, and so on.

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Institutional Innovation - I Have a Dream

John Hagel

Performance improvement: Shift from process to practice. With the growth of service oriented architectures and more and more powerful sensor and analytic technologies, these institutions will focus on how to flexibly support workgroups in learning faster in rapidly changing contexts by giving them richer and real-time visibility into the context and richer feedback loops regarding the actions they take to address the context.

Solow Paradox 2.0: The Lagging Impact of Technology Advances on Productivity Growth

Irving Wladawsky-Berger

It took until the 1920s for companies to figure out how to restructure their factories to take advantage of electric power with new manufacturing processes like the assembly line. Companies realized that using IT to automate existing processes wasn’t enough.

Moving forward

Clark Quinn

Big analytics, or even little analytics are good basis, as are models and support tools to facilitate the processes. A few weeks ago, I posted about laying out activities in a space dividing the execution side from the innovation side, and in the head from in the world.

Artificial Intelligence is Ready for Business; Are Businesses Ready for AI?

Irving Wladawsky-Berger

A successful program requires firms to address many elements of a digital and analytics transformation: identify the business case, set up the right data ecosystem, build or buy appropriate AI tools, and adapt workflow processes, capabilities, and culture.”.

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LMS vs. LCMS

Xyleme

Also, LMSs do not provide IDs with the deep analytics required to understand what content is working and what content is not. . Modern LCMSs manage every aspect of the learning process, from rapid authoring to delivery. Analytics API.

Anticipating the Future of the IT Industry

Irving Wladawsky-Berger

Let me share some of my personal impressions of this journey through the lens of three key areas, each of which has played a major role throughout IT’s history, and will continue to do so well into its future: data centers, transaction processing, and data analysis.

Nothing Has Changed. Everything Has Changed.

Charles Jennings

It’s about the output rather than process. A Revolution or a Slow Demise? I’ve recently read Clark Quinn’s excellent new ‘Revolutionize Learning & Development’ book. Clark always provides a thoughtful and enlightening perspective.

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