From our xAPI Camp at Amazon's Headquarters in Seattle, WA on July 21, 2015. The decision to go with xAPI is an exciting one, but a successful xAPI project hinges on an understanding of what success looks like. In this presentation, I share a number of questions one should ask of technology partners and your own team depending on different ways one might use xAPI.
xAPI Making Sense of Industry and PracticeAaron Silvers
An overview of questions @MeganBowe and I recommend asking when considering your first big project with xAPI, and how the consortium that will steward xAPI will make this easier.
Experience API recipes/visualization services are free for education institutions, partners are welcome
Contact: mlearning@classroomaid.org
See detailed features list:
http://classroom-aid.com/xapi-and-analytics-services/
xAPI Making Sense of Industry and PracticeAaron Silvers
An overview of questions @MeganBowe and I recommend asking when considering your first big project with xAPI, and how the consortium that will steward xAPI will make this easier.
Experience API recipes/visualization services are free for education institutions, partners are welcome
Contact: mlearning@classroomaid.org
See detailed features list:
http://classroom-aid.com/xapi-and-analytics-services/
In this webinar, Andrew Downes will run through nine practical Tin Can API (xAPI) use cases that you can begin working on today. For each use case, he’ll explain the benefits to your organization, and then outline a step-by-step plan you can follow to pilot that use case. You’ll learn what you need to ask your existing vendors, what you need to buy, and what you need to build; everything you need to know to get started.
What use cases will you learn about?
* Learning Analytics
* Better Blended Learning
* Adaptive Pathways
* Just-in-Time Performance Support
* Mentoring
* Team Learning
* Multi-device Learning
* LRS to LRS communication
* Open Badges
Content Controller: The easiest way to share content with your customersRustici Software
Listen to Andy Whitaker share show you how to distribute your training content without losing control over your valuable intellectual property. He will walk you through how to use Content Controller to give your customers access to your courses and no longer have to worry about manually keeping up with how customers are using your content.
Learn more about Content Controller: https://rusticisoftware.com/products/content-controller/
xAPI Live - Why do I need something new? Day Hikes in xAPIRISC Inc
This presentation by Megan Torrance, President of Torrance Learning highlights short activities that can be used to leverage xAPI without breaking the bank. Torrance Learning's xAPI Cohorts groups teams of interested users to create xAPI projects that are shared to provide a starting point and foster discussion about xAPI and it's use for Learning & Performance Support.
The Business Case for Adopting Tin Can (xAPI) - Why and How Five Product Vend...Rustici Software
Many of our previous webinars have given general information about Tin Can or focused specifically on how organizations can adopt. If you’re a product vendor, this next webinar is specifically for you. You’ll hear the stories of five learning product vendors that made the decision to adopt, implement Tin Can in their products, and roll it out to their customers.
If you’re not sure whether you should adopt, or you’re struggling to make the business case within your company, then this webinar will be very helpful for you.
You’ll hear from the following vendors:
*Cognitive Advisors
*gomo
*TES
*Tribridge
*Unicorn
Adopting Data Science and Machine Learning in the financial enterpriseQuantUniversity
Financial firms are taking AI and machine learning seriously to augment traditional investment decision making. Alternative datasets including text analytics, cloud computing, algorithmic trading are game changers for many firms who are adopting technology at a rapid pace. As more and more open-source technologies penetrate enterprises, quants and data scientists have a plethora of choices for building, testing and scaling quantitative models. Even though there are multiple solutions and platforms available to build machine learning solutions, challenges remain in adopting machine learning in the enterprise.In this talk we will illustrate a step-by-step process to enable replicable AI/ML research within the enterprise using QuSandbox.
Megan Torrance's presentation at Learning Technologies UK, on xAPI, data providers, Learning Record Stores, and what xAPI has to offer learning & development above and beyond what SCORM provides. (Note these are only Megan Torrance's slides and do not include the case study presented by R Pedley)
Forces & Trends Shaping Higher Ed in 2016Kimberly Eke
A closer look at some of the trends closing 2015 and opening 2016 that are shaping the conversations and thinking around higher ed. Presented during the ELI 2016 Annual Meeting Pre-conference Workshop, "Powering the Innovation Engine" held in San Antonio, Texas (2/2/16)
Tales from the trails: Navigating a proven path from content creation to dist...Rustici Software
There’s more than one way to navigate through content creation and distribution. Listen to Joe Donnelly and Andy Whitaker as they guide you through all your options for creating, packaging, and distributing content for learners.
With innovations in hardware, algorithms, and large datasets, the use of Data Science and Machine Learning in finance is increasing. As more and more open-source technologies penetrate enterprises, quants and data scientists have a plethora of choices for building, testing, and scaling models. Alternative datasets including text analytics, cloud computing, algorithmic trading are game-changers for many firms exploring novel modeling methods to augment their traditional investment and decision workflows. While there is significant enthusiasm, model risk professionals and risk managers are concerned about the onslaught of new technologies, programming languages, and data sets that are entering the enterprise. With very little guidance from regulators on how to govern the tools and the processes, organizations are developing their own home-cooked methods to address model risk management challenges.
In this webinar, we aim to bring clarity to some of the model risk management challenges when adopting data science, AI, and Machine Learning methods in the enterprise. We will discuss key drivers of model risk in today’s environment and how the scope of model governance is changing. We will introduce key concepts and discuss key aspects to be considered when developing a model risk management framework when incorporating data science techniques and AI methodologies.
How to Plan for an xAPI Pilot at xAPI Camp DevLearn 2018 - Yet AnalyticsAllie Tscheulin
From an organization-wide executive directive to become more data-driven, a retail corporate L&D team took an internal look at their own data practices. Realizing that they had an overwhelming lack of transparency into their learning initiatives and a great amount of data that had gone unused, the team developed a transformation vision to create a single system of record for learning to enable observability, granularity, and accountability for all team members. The team was committed to the vision of xAPI; however, the data and information they needed in order to make actionable change for their learners was locked away in non-interoperable formats, and they recognized the need to develop a data strategy and implementation plan.
*Originally presented on 10/ 23/2018 at xAPI Camp during DevLearn 2018 by Allie Tscheulin
In this webinar, Andrew Downes will run through nine practical Tin Can API (xAPI) use cases that you can begin working on today. For each use case, he’ll explain the benefits to your organization, and then outline a step-by-step plan you can follow to pilot that use case. You’ll learn what you need to ask your existing vendors, what you need to buy, and what you need to build; everything you need to know to get started.
What use cases will you learn about?
* Learning Analytics
* Better Blended Learning
* Adaptive Pathways
* Just-in-Time Performance Support
* Mentoring
* Team Learning
* Multi-device Learning
* LRS to LRS communication
* Open Badges
Content Controller: The easiest way to share content with your customersRustici Software
Listen to Andy Whitaker share show you how to distribute your training content without losing control over your valuable intellectual property. He will walk you through how to use Content Controller to give your customers access to your courses and no longer have to worry about manually keeping up with how customers are using your content.
Learn more about Content Controller: https://rusticisoftware.com/products/content-controller/
xAPI Live - Why do I need something new? Day Hikes in xAPIRISC Inc
This presentation by Megan Torrance, President of Torrance Learning highlights short activities that can be used to leverage xAPI without breaking the bank. Torrance Learning's xAPI Cohorts groups teams of interested users to create xAPI projects that are shared to provide a starting point and foster discussion about xAPI and it's use for Learning & Performance Support.
The Business Case for Adopting Tin Can (xAPI) - Why and How Five Product Vend...Rustici Software
Many of our previous webinars have given general information about Tin Can or focused specifically on how organizations can adopt. If you’re a product vendor, this next webinar is specifically for you. You’ll hear the stories of five learning product vendors that made the decision to adopt, implement Tin Can in their products, and roll it out to their customers.
If you’re not sure whether you should adopt, or you’re struggling to make the business case within your company, then this webinar will be very helpful for you.
You’ll hear from the following vendors:
*Cognitive Advisors
*gomo
*TES
*Tribridge
*Unicorn
Adopting Data Science and Machine Learning in the financial enterpriseQuantUniversity
Financial firms are taking AI and machine learning seriously to augment traditional investment decision making. Alternative datasets including text analytics, cloud computing, algorithmic trading are game changers for many firms who are adopting technology at a rapid pace. As more and more open-source technologies penetrate enterprises, quants and data scientists have a plethora of choices for building, testing and scaling quantitative models. Even though there are multiple solutions and platforms available to build machine learning solutions, challenges remain in adopting machine learning in the enterprise.In this talk we will illustrate a step-by-step process to enable replicable AI/ML research within the enterprise using QuSandbox.
Megan Torrance's presentation at Learning Technologies UK, on xAPI, data providers, Learning Record Stores, and what xAPI has to offer learning & development above and beyond what SCORM provides. (Note these are only Megan Torrance's slides and do not include the case study presented by R Pedley)
Forces & Trends Shaping Higher Ed in 2016Kimberly Eke
A closer look at some of the trends closing 2015 and opening 2016 that are shaping the conversations and thinking around higher ed. Presented during the ELI 2016 Annual Meeting Pre-conference Workshop, "Powering the Innovation Engine" held in San Antonio, Texas (2/2/16)
Tales from the trails: Navigating a proven path from content creation to dist...Rustici Software
There’s more than one way to navigate through content creation and distribution. Listen to Joe Donnelly and Andy Whitaker as they guide you through all your options for creating, packaging, and distributing content for learners.
With innovations in hardware, algorithms, and large datasets, the use of Data Science and Machine Learning in finance is increasing. As more and more open-source technologies penetrate enterprises, quants and data scientists have a plethora of choices for building, testing, and scaling models. Alternative datasets including text analytics, cloud computing, algorithmic trading are game-changers for many firms exploring novel modeling methods to augment their traditional investment and decision workflows. While there is significant enthusiasm, model risk professionals and risk managers are concerned about the onslaught of new technologies, programming languages, and data sets that are entering the enterprise. With very little guidance from regulators on how to govern the tools and the processes, organizations are developing their own home-cooked methods to address model risk management challenges.
In this webinar, we aim to bring clarity to some of the model risk management challenges when adopting data science, AI, and Machine Learning methods in the enterprise. We will discuss key drivers of model risk in today’s environment and how the scope of model governance is changing. We will introduce key concepts and discuss key aspects to be considered when developing a model risk management framework when incorporating data science techniques and AI methodologies.
How to Plan for an xAPI Pilot at xAPI Camp DevLearn 2018 - Yet AnalyticsAllie Tscheulin
From an organization-wide executive directive to become more data-driven, a retail corporate L&D team took an internal look at their own data practices. Realizing that they had an overwhelming lack of transparency into their learning initiatives and a great amount of data that had gone unused, the team developed a transformation vision to create a single system of record for learning to enable observability, granularity, and accountability for all team members. The team was committed to the vision of xAPI; however, the data and information they needed in order to make actionable change for their learners was locked away in non-interoperable formats, and they recognized the need to develop a data strategy and implementation plan.
*Originally presented on 10/ 23/2018 at xAPI Camp during DevLearn 2018 by Allie Tscheulin
There's a paradigm shift that follows the use of the Experience API. The shift comes from seeking insights on how effective our designed experiences are versus judgments about how well people learn from them. This change in mindset focuses on the outcomes from the audience that manifest in observable ways, mapped directly to our design assertions. It's not about xAPI or any specific technology - it's about modeling our design to get the insights we need to improve our design.
How to Plan for Your xAPI Pilot - xAPI Camp at DevLearn 2018 - Yet Analytics Margaret Roth
From an organization-wide executive directive to become more data-driven, a retail corporate L&D team took an internal look at their own data practices. Realizing that they had an overwhelming lack of transparency into their learning initiatives and a great amount of data that had gone unused, the team developed a transformation vision to create a single system of record for learning to enable observability, granularity, and accountability for all team members. The team was committed to the vision of xAPI; however, the data and information they needed in order to make actionable change for their learners was locked away in non-interoperable formats, and they recognized the need to develop a data strategy and implementation plan.
*Originally presented on 10/23/2018 at xAPI Camp during DevLearn 2018 by Allie Tscheulin
Where Cognitive Science, Interaction Design and Data Dwells: The Competencies...Aaron Silvers
Web technology standards emerged in the early 2000s that reinforced the use of the desktop web browser. After 15 years, we all are part of a new revolution in what it means “to be online” thanks to APIs and connected devices. The Experience API (xAPI) is a new standard, encouraging a new type of practitioner who helps people learn and improve through cognitive science, interaction design and data. In this session, we'll talk about xAPI and highlight the new competencies needed to work with it.
Yet LXi — Learning Experience Interface Overview Margaret Roth
Yet’s Learning Experience Interface (LXi) enables the collection and tagging of resources across any source on the internet, providing a unified discovery and experience platform for informal, self-directed learning. Related content suggestions and a fully xAPI instrumented interface make the Yet LXi the best way to unify both your learner experience and your learning analytics.
This presentation was originally shared as part of the eThink Partner Webinar series on April 25, 2018. View the webinar recording at https://www.youtube.com/watch?v=rgxSEO-x2co&feature=youtu.be.
Improving Organizational Performance using the Experience APIAli Shahrazad
People are learning everywhere. Modern and natural learning happens on mobile devices, in social networks, on the job, and via formal assessments. It happens on numerous systems, from Yammer and SharePoint to SkillSoft and Khan Academy. Organizations are spending hundreds of thousands of dollars to create this training using old technology standards. As a result, data is stuck in silos and L&D has little to no idea what training is effective or how it impacts business results.
This session provided a brief non-technical overview of the Experience API and showed real-use cases inside organizations. It also covers how to assess organizational readiness, strategic planning, and practical implementation. Participants will acquire the knowledge needed to improve organizational performance using the Experience API.
AWS re:Invent 2016: Building the Future of DevOps with Amazon Web Services (D...Amazon Web Services
At Dynatrace, we challenged ourselves to build a virtual team member to help operations teams run large-scale cloud infrastructures. Think J.A.R.V.I.S. from Iron Man, but for operations. We built our cloud infrastructure on Amazon EC2, Elastic Load Balancing load balancers, and Auto Scaling groups for real-time scalability, Amazon Route 53 for instant customer access, Amazon Echo and Alexa for voice interaction, AWS Lambda for fast prototyping of the human-interaction layer, and Amazon DynamoDB for handling complex conversations. In this session, we will also discuss how we extend the service by using Amazon Machine Learning and AWS IoT to more naturally integrate our virtual assistant into the real world. Session sponsored by Dynatrace. This session sponsored by Dynatrace.
AWS Competency Partner
Jay Lyman 451 ResearchBrent Beer GitHubSteven Anderson Sendachi talk about these topics:
Cloud, DevOps, agile development capability and adoption of containers are all important in both perception and reality.
Enterprise adoption of cloud computing, DevOps, agile development and containers are all growing, including production use.
Modernizing applications to SaaS & migrating them to the cloud are equally important as net-new, so-called ‘cloud-native’ applications.
Advantages and benefits of these technologies and methodologies center on: flexibility and speed, cost reduction, improvements in resiliency and reliability and fitness for new/emerging applications.
Barriers center on: lack of internal skills, immaturity, lack of familiarity, satisfaction with current technology, cost and security.
You already have an LxP, you just don't know itJames Wann
James Tyas and Vinit Patel recently gave a talk at DevLearn about LxPs, and how they may be much more accessible than you realise. Leveraging the power of giant tech software ubiquitous in knowledge work, we can save a lot of time, and a LOT of money.
So you're dying to try xAPI. You've bought into the 70-20-10 rule and you know tat SCORM just doesn't give you the data you need. Now you are facing an uphill battle: how do you sell xAPI internally.
Aaron Silvers, President and Managing Director of DISC, the Data Interoperability Standards Consortium, was fundamental to the development of xAPI by the ADL. This presentation highlights DISC's activities under the remit of the ADL to define standardization processes and test suites as well as guiding the development of xAPI protocols, such as cmi5.
Modern Learning Ecosystem Design with xAPIMargaret Roth
While the L&D community is increasingly familiar with the Experience API (xAPI) and its value for data collection and interoperability, few examples exist to clarify the value of xAPI as applied within different existing learning infrastructures. This session focused on sharing the ways xAPI can connect and provide value in any eLearning environment.
These slides present a series of different learning ecosystem configurations and the ways xAPI and a learning record store (LRS) can provide value in each case. The three main learning ecosystem configurations examined range from the simplest (LMS and LRS) to three systems connected (LMS, LRS, and CMS) to the fully modular (LRS, LMS, simulations, microlearning, performance assessment, and other tools). For each of these configurations, the presentation shares specific values and practical applications gained by connecting an xAPI LRS to the existing system.
This presentation was originally shared as part of the eLearning Guild's 2018 Learning Solutions conference on March 28, 2018.
Prioritizing Ethical Use of Learning Data.pdfAaron Silvers
Given the context of adult learners in workforce development, in this presentation I (1) model a lifecycle of an xAPI Statement (json data) to understand the potential long-term impacts of once piece of data on real people; (2) curate relevant ethical challenges related to using learning data from a corpus of research literature specifically about the ethics of learning analytics; and (3) impart the need to continuously train the capacity for empathy to strengthen inquiry skills and prioritize ethical use.
Content Wrangling: Applying Content Strategy & Information ArchitectureAaron Silvers
Everything a learning organization does has workflows —including content strategy. To achieve those strategic goals, realizing content strategy requires two workflows to (a) establish a baseline on what content you have, and (b) how to improve its use to humans, based on a LEAN approach to learning as a way of doing hypothesis-based design and continuous improvement of the content and the delivery mechanisms for it.
Creating a Culture of Continuous ImprovementAaron Silvers
Many managers covet about continuous improvement process but "process" is what helps guarantee we get consistent and similar output for the work performed. Improvement is a change state, so we need to think about "workflows." For learning, talent management and human performance organizations, we can leverage what's been working in tech and manufacturing industries: a LEAN approach to learning as a way of doing hypothesis-based design.
My keynote slides from #DConf13 given independently on Spaghetti Westerns, the Experience API™ and Creating Things that Matter. While I provide support to the Advanced Distributed Learning (ADL) Initiative, the views expressed here are my own and do not necessarily represent the views or policies of ADL.
This is a presentation I gave at Innovations in eLearning, 2010. I also delivered this as a keynote at Games + Learning + Society / ADL AcademicFest (also in 2010).
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
4. The Experience API is a standard way of
talking about our experiences, using data.
5.
6. The Experience API (xAPI)
• Can track many different types of experiences — including
things that people do on the web, in mobile applications, with
wearables, in classrooms and in workplace environments
• Moves beyond a web-based, didactic model
• Promotes better design and technology practices
• Makes integration with other systems and practices easier
• Provides a way to gather and use more useful information.
7. It answers a lot of ‘How’ type questions…
• How can I inform better business decisions?
• How do I avoid locking us into a solution?
• How can I make investments in learning development last longer
and more future-proof?
• How can I make sure what I evaluate today is useful in the future?
• How will I connect a learner’s activities across multiple
applications?
9. How Does Experience API Work?
• People interact with “stuff”
(i.e. content, apps, business systems, etc.)
• These interactions are observed and described as
statements.
• The “stuff” sends the statements to a Learning Record Store.
10. What is a Learning Record Store, or LRS?
• It’s a database that stores activity statements - the “data”
• LRSs can be software (even hardware) that stands on its
own.
• LRSs can be a part of data appliances, enterprise
applications and learning management system (LMS)
11. LMS vs. LRS
A Learning Record Store (LRS) addresses one capability of a typical
Learning Management System (LMS).
User Management Learning Records Scheduling
Course Management Statistics Grade Book
Tracking eLearning Content Storage Search
Assignments Sequencing Delivery
Preferences Reports Assessment
13. Competencies / Attitudes
Systems Thinking Integration Facilitation
A Maker Mindset
Assume you have
permission to tinker
Make, maintain and grow
useful connections
Surface goals big & inviting
enough to motivate action
Be The Change
Interrogate perceived
boundary conditions
Identify new paradigms
supported by both sides of
double-binds
Inspire others, modeling
how to navigate through
shifting paradigms
“Yes. And..”
Augment rather than
change discrete systems
Seek connections and
overlaps that add value
beyond the immediate
context
Help others avoid negation
14. Who puts xAPI solutions together…
• Technology Partners
(vendors, consultants, tool providers, etc)
• Your Team
(stakeholders, team members…)
15. How xAPI solutions happen…
• Use a tool that is built with xAPI, natively, from the ground-up
( “Native” )
• Leverage an existing data source that is modified, extended
or translated into xAPI ( “Modified” )
• Build Your Own ( “BYO” )
16. Native Modified BYO
Technology
Partners
xAPI from
ground-up
APIs or other
data sources
that can
translate to
xAPI
Whatever
You Want
Your Team
Balancing
wants, needs
and
sustainability
Creating &
maintaining
middleware
Practices,
Resourcing &
Scaling
17. Native Modified BYO
Technology
Partners
xAPI from
ground-up
APIs or other
data sources
that can
translate to
xAPI
Whatever
You Want
Your Team
Balancing
wants, needs
and
sustainability
Creating &
maintaining
middleware
Practices,
Resourcing &
Scaling
18. Questions for technology partners
If there’s support for xAPI from the ground-up…
• What activities are designed?
19. Common Needs
Social
Custom mobile
applications
Play existing courses Create new courses
Track/report progress
Off-the-shelf
applications integration
Testing
Competency
management
See the learner’s
journey
See content usage Work activities Sensors
Simulations Recruitment Compliance activity Reporting
20. Questions for technology partners
If there’s support for xAPI from the ground-up…
• What activities are designed?
• How are activities tracked?
22. Questions for technology partners
If there’s support for xAPI from the ground-up…
• What activities are designed?
• How are activities tracked?
• What data points are in each statement?
24. Questions for technology partners
If there’s support for xAPI from the ground-up…
• What activities are designed?
• How are activities tracked?
• What data points are in each statement?
• How do I input or change endpoint credentials?
25. Prompt Hack Fixed
You’ll have a prompt to input
one or multiple LRS endpoint
credentials.
As an example, while there’s
a default configuration,
there’s JavaScript or other
code as an interface that can
be amended with knowledge
of how the technology
works.
The technology is in a
published or executable-
only state (a .exe file, a .swf
file — something server
side) that makes it difficult if
not impossible to change.
26. Questions for technology partners
If there’s support for xAPI from the ground-up…
• What activities are designed?
• How are activities tracked?
• What data points are in each statement?
• How do I input or change endpoint credentials?
• How does it rely on the LMS or other software applications?
27. Native Modified BYO
Technology
Partners
xAPI from
ground-up
APIs or other
data sources
that can
translate to
xAPI
Whatever
You Want
Your Team
Balancing
wants, needs
and
sustainability
Creating &
maintaining
middleware
Practices,
Resourcing &
Scaling
28. Questions for your team
If considering a tool built with xAPI from the ground-up…
• Is what’s baked-in going to be enough?
• Does the right data align across tools?
• If not…
can we support our own unbiased reporting,
knowing the caveats?
29. Data Alignment Example
Storyline Lectora
Uses a fixed vocabulary to
describe a limited set of
interactions with xAPI
Allows for freedom of
expression to describe any
interaction (or operation) with
an open vocabulary for xAPI.
31. Native Modified BYO
Technology
Partners
xAPI from
ground-up
APIs or other
data sources
that can
translate to
xAPI
Whatever
You Want
Your Team
Balancing
wants, needs
and
sustainability
Creating &
maintaining
middleware
Practices,
Resourcing &
Scaling
32. Questions for technology partners
If there’s support for APIs or other data sources that can
translate to xAPI…
• What APIs does the technology offer?
• Of these…
Can we capture the right activities?
33. Twitter maps easily, but…
• Should we use hashtags for
for context?
• Is location important?
• Do we need to track every
tweet?
34. Questions for technology partners
If there’s support for APIs or other data sources that can
translate to xAPI…
• What APIs does the technology offer?
• Of these…
Can we capture the right activities?
• What data will fill in the gaps in information we need?
35. Native Modified BYO
Technology
Partners
xAPI from
ground-up
APIs or other
data sources
that can
translate to
xAPI
Whatever
You Want
Your Team
Balancing
wants, needs
and
sustainability
Creating &
maintaining
middleware
Practices,
Resourcing &
Scaling
36. Questions for your team
If considering a tool built for APIs or other data sources that can
translate to xAPI…
• Can we get enough from this/these APIs?
• How much value will we get from this system?
• What resources will we have…
• to do custom API development?
• to keep up our code with the different specs, ongoing?
• to build the translation layer?
37.
38. Native Modified BYO
Technology
Partners
xAPI from
ground-up
APIs or other
data sources
that can
translate to
xAPI
Whatever
You Want
Your Team
Balancing
wants, needs
and
sustainability
Creating &
maintaining
middleware
Practices,
Resourcing &
Scaling
39. Questions for technology partners
If your technology partner will build whatever you want…
• What learning experience are you designing?
• What interactions are needed to support the learning
experience design?
40. Native Modified BYO
Technology
Partners
xAPI from
ground-up
APIs or other
data sources
that can
translate to
xAPI
Whatever
You Want
Your Team
Balancing
wants, needs
and
sustainability
Creating &
maintaining
middleware
Practices,
Resourcing &
Scaling
41. Questions for your team
If you can build whatever you want…
• What learning experience are you designing?
• What interactions are needed to support the learning experience design?
• What interactions are needed but don’t evidence or disprove the learning
experience?
• What recipes exist?
• What is the data model and information architecture it should conform with?
• What is our ability to support this at scale?
42.
43. How do I vet technology
partners for xAPI projects?
44. When considering technology partners…
• Consider the know-how and investment of those who
contribute to the actual spec
(example: https://github.com/adlnet/xAPI-Spec/graphs/contributors)
45. When considering technology partners…
• Consider the know-how and investment of those who
contribute to the actual spec
(example: https://github.com/adlnet/xAPI-Spec/graphs/contributors)
• Consider who can demonstrate xAPI interoperability
(example: http://tincanapi.com/2015/04/16/tale-three-lrss/)
46. When considering technology partners…
• Consider the know-how and investment of those who
contribute to the actual spec
(example: https://github.com/adlnet/xAPI-Spec/graphs/contributors)
• Consider those who can demonstrate xAPI interoperability
(example: http://tincanapi.com/2015/04/16/tale-three-lrss/)
• Consider those who stay current with the spec
(example: https://github.com/aaronesilvers/IEEE/blob/master/
2014_State_of_xAPI_Tools_Survey_Responses.csv)
47. When considering technology partners…
• Consider the know-how and investment of those who
contribute to the actual spec
(example: https://github.com/adlnet/xAPI-Spec/graphs/contributors)
• Consider those who can demonstrate xAPI interoperability
(example: http://tincanapi.com/2015/04/16/tale-three-lrss/)
• Consider those who stay current with the spec
(example: https://github.com/aaronesilvers/IEEE/blob/master/
2014_State_of_xAPI_Tools_Survey_Responses.csv)
• Consider those who won’t lock you into one size fits all
(example: http://connectionsforum.com/case-studies/)
49. 1) Describe the Dream
• What outcomes happen as a result?
• How are people learning or working?
• What problems are solved?
• How far out is this future?
• What might change beyond this?
50. 2) Define Gaps Between Today and the Ideal
• What capabilities exist vs. what capabilities are needed?
• What do people “do” vs. what they “need to do?”
• How do today’s business requirements match with business goals for
the ideal?
51. 3) Sketch It
• What are the workflows?
• How do existing tools support the workflows?
• What new tools are needed?
• How does this model fit with stakeholder expectations?
• What are the critical paths and how are they prioritized?
• How can this model be simplified/scaled/phased?
• What dependencies are inherent? What dependencies are external?
52. 4) Put a Plan Together
• What is the technical approach?
• How will the system(s) and/or service(s) architecture work?
• What do the interfaces look like?
• How will success be defined?
• What is the project plan?