Watershed

JUNE 16, 2023

When I first started working in the learning space, I assumed that HR, talent management, and the world of L&D were all one and the same. After all, they share the same end goal of nurturing a productive, engaged, and skilled workforce. But dive a little deeper, and the reality appears a little different. HR and L&D events are often miles apart from the tech to the talk tracks.

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Watershed

DECEMBER 8, 2015

Kaufman's Levels of Learning Evaluation is one of several training evaluation models that builds on or reacts to Kirkpatrick’s model. This blog post explores the Kaufman method, including the two main differences that set it apart from Kirkpatrick's evaluation method.

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Watershed

JANUARY 6, 2016

Many learning evaluation models outline different ways of assessing whether our learning solutions work and why. It's the first step in ensuring our future learning solutions work. And as part of our learning and training evaluation series , this blog post explores Anderson's Value of Learning Model and its three-stage learning evaluation cycle that's meant to be applied at the organization level rather than for specific learning interventions.

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Watershed

MARCH 6, 2023

Most L&D professionals agree it’s essential to set aside a budget for learning measurement, but few are able to do so. Yet, organizations with a budget for learning analytics are more likely to believe in data and learning measurement, feel executive pressure to measure, and have learning analytics capability on their team.

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Watershed

MAY 25, 2023

Learning analytics supports learning and development in many ways. So how do organizations use learning analytics today? And how do they want to apply these analytics in an ideal world? This blog post explores findings from two L&D surveys to gauge how learning analytics is currently being used, and the metrics that sit behind measurement efforts.

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Watershed

MAY 15, 2023

Dancing robots, generative AI, and a focus on integrating skills into your learning strategy were all featured at Learning Technologies 2023. While we can write the dancing robots off as crowd-drawing distractions (along with the poor souls wearing full Stormtrooper and tiger outfits), it’s fair to say generative AI will be here to stay. Everyone talked about it, but how widely will L&D embrace it, and does anyone truly understand its impact yet?

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Watershed

MARCH 1, 2021

Is the learning record store (LRS) in your LMS or LXP providing the data and information you need to understand all the learning that’s happening across your organization? Or, are you limited to the data within that particular system? Remember, without a comprehensive view, it’s hard to know what’s really working and where your learners need support.

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Watershed

MARCH 6, 2023

Most L&D professionals agree it’s essential to set aside a budget for learning measurement, but few are able to do so. Yet, organizations with a budget for learning analytics are more likely to believe in data and learning measurement, feel executive pressure to measure, and have learning analytics capability on their team.

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Watershed

FEBRUARY 14, 2023

Implementing your learning analytics strategy requires people, technology, and budget. In this post, we focus on the people who create, organize, and evaluate learning analytics. Find out how many organizations have a dedicated learning analytics team, if their L&D department has analytics capability, and if they plan to change their learning analytics staffing in the near future.

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Watershed

FEBRUARY 7, 2023

Measurement, data, and benchmarking naturally go hand-in-hand. Many in L&D will instantly make the connection with how this statement could apply to either learner or program performance. But take a step back and you’ll realize the same principles apply when it comes to assessing your organization’s learning analytics capability. This blog post explores the results of recent survey questions on learning analytics maturity and capability.

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Watershed

AUGUST 24, 2016

Learning happens everywhere—from formal online compliance training to in-person training simulations and observations—and we simply can’t track all of it. That’s why you need to choose the most important blended learning experiences to target first and then tackle them one by one. From there, you can use tools, such as xAPI, to capture and track data from those experiences.

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Watershed

DECEMBER 8, 2021

A learning ecosystem can quickly grow and evolve into a complex web of unique tools and technologies serving specific needs. So inevitably, gaining meaningful L&D insights from these disparate systems can be difficult. The good news is that your learning analytics platform can bring all that L&D data together so you can track and explore all your learning in one place.

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Watershed

NOVEMBER 16, 2021

This blog series has covered L&D data requirements spanning a wide range of learning technologies commonly found in learning ecosystems. But there are so many other product classes we haven’t had a chance to talk about—until now. So, in this penultimate post of the series, we’re going to blast through several types of learning tools and technologies we haven’t covered yet.

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Watershed

NOVEMBER 10, 2021

Augmented reality (AR) and virtual reality (VR) are becoming increasingly mainstream modes of training—especially in industries that conduct training where real-world, in-person training is costly or risky, such as training with expensive equipment. Virtual experiences have the potential to generate huge amounts of data, as the head-mounted displays (HMDs) must track every movement as part of how they work.

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Watershed

NOVEMBER 3, 2021

We saw a massive and sudden movement from ILT to vILT during 2019 and 2020. But whether it’s virtual or in-person, instructor-led training represents an important mode of learning for many organizations. The personal human interactions of instructor-led training do not lend themselves to digital tracking as easily as e-learning or video content, so how do you track them?

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Watershed

OCTOBER 27, 2021

Organizations are increasingly relying on data to make informed decisions and maintain a competitive edge. This trend isn’t limited to a particular region, industry, or business size. Whether it’s a local grocery store ensuring their shelves are properly stocked or a Fortune 100 organization creating a global transportation plan, data plays an integral role in our daily lives.

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Watershed

OCTOBER 7, 2021

Business intelligence tools and learning analytics platforms are complementary products that process data and provide reports and analytics to different audiences and for different purposes. BI tools are generally used by your data team to generate reports requested by the business, whereas a learning analytics platform may be used by the learning team and by operational managers to keep track of their learning, learners, and programs.

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Watershed

SEPTEMBER 29, 2021

One of the key benefits of a learning analytics platform is the ability to easily combine your organizational data with your learning data so you can filter by and compare different organizational units. This combination of data also means you can give operational managers access to reports, using data permissions to ensure they only see data about their own people.

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Watershed

SEPTEMBER 22, 2021

DevLearn is one of the biggest conferences on the L&D calendar, and after a digital-only conference last year, we’re excited to be attending DevLearn 2021 in person! Sadly, due to COVID-related travel restrictions, I can’t be there in person, but our booth (609) is right next to the main entrance. Bill, Craig, Stephen and Izzy will be there, and we’d love it if you popped by to say hello!

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Watershed

SEPTEMBER 15, 2021

It might not always feel like it, but not all learning happens online. In industries such as healthcare, construction, retail, hospitality, and travel, work happens in the real world. And while advances in virtual reality (VR) are exciting, practical skills are often best developed with hands-on training. Observation checklist applications let you record these real-world experiences, and knowing how to capture and aggregate that data is critical for comprehensive L&D reporting.

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Watershed

SEPTEMBER 8, 2021

We’ve been exploring how to define data requirements for learning analytics —including the questions and considerations to discuss with vendors when connecting platforms to your learning ecosystem. In this blog post, we’ll focus on why a robust data integration is critical when it comes to badging and credentialing software. We’ll also explain how you can extract that data so you can combine it with other L&D data and report on it in a learning analytics platform (LAP).

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Watershed

SEPTEMBER 1, 2021

Surveys are a vital tool in the learning analytics toolkit, capturing the learners’ ratings and feedback on training and more. This data is most valuable when reported alongside data about the learning itself, but how do you get that data out of the survey tool in the first place? This post explores the data requirements you should look out for when extracting data from a survey tool into a learning analytics platform.

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Watershed

AUGUST 25, 2021

Having explored data requirements for the central systems of a learning ecosystem , the LMS and LXP, let’s turn to the products you might bring into your ecosystem to enhance those core platforms with additional functionality. Video platforms turbo-charge your training capabilities and can generate a lot of useful data about what learners are watching—right down to the level of where they’re pausing, skipping, or rewatching.

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Watershed

AUGUST 11, 2021

Our data requirements blog series explores the data you might collect from the various tools in your learning ecosystem, how you might get that data out, and what questions it might answer. In this post, we’ll look at one of the most critical platforms in your learning ecosystem—the learning management system (LMS).

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Watershed

AUGUST 2, 2021

If you want good, comprehensive reporting that answers all your questions, you need good, comprehensive data. But when you have multiple tools, systems, and platforms across your learning ecosystem , how can you ensure you’re getting all the data you need and in the proper format? In this blog series, we’ll explore data requirements for the various tools and technologies that are commonly found in learning ecosystems as well as requirements and best practices for extracting data from each system

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Watershed

JULY 13, 2021

The Watershed team is mainly based in Nashville, Tennessee, but there are a couple of us on the other side of the pond in England. There’s been a lot of excitement over here the last few weeks as the England soccer team (we call it football) have been doing uncharacteristically well in the postponed-due-to-COVID Euro 2020 Championship. England reached the final against Italy and, despite not being a huge sports fan, I decided to watch the match and cheer them on.

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Watershed

APRIL 28, 2021

So far in this series, we’ve explained the differences between internal and external learning record stores , how xAPI conformance affects reporting, and data extraction methods. Now, we’ll wrap things up as we mash together all the bits we’ve discussed during the past four blog posts and look at how the LRS can play a role in the larger data ecosystem.

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Watershed

APRIL 14, 2021

The more learning data you have (assuming it’s good data), translates into better, more comprehensive reporting and insights around your training programs and initiatives. For instance, you can create reports from multiple source systems, import it into a BI tool or data warehouse, or merge training data with your HR data so you can slice and dice that info any way you want.

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Watershed

APRIL 7, 2021

Even the learning platforms with conformant LRSs —ones that generate great xAPI data from non-xAPI content and the platform’s interactions—can have issues. For instance, they don’t generally allow you to send outside xAPI statements into the internal LRS, so you can only report on the data contained in that platform. They also often have canned reports that can be quite difficult to change or configure without additional support from vendors—which can be time-consuming and costly.

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Watershed

MARCH 10, 2021

Does it matter if your internal learning record store (LRS) is fully xAPI conformant? The short answer: Yes, but it also depends. In this blog post, we’ll explain how xAPI conformance plays a role in both internal and external LRSs and the type of data and resulting learning analytics you can expect from each.

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Watershed

MARCH 1, 2021

Is the learning record store (LRS) in your LMS or LXP providing the data and information you need to understand all the learning that’s happening across your organization? Or, are you limited to the data within that particular system? Remember, without a comprehensive view, it’s hard to know what’s really working and where your learners need support.

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Watershed

FEBRUARY 18, 2021

We’ve come a long way in the last five years when it comes to how people perceive and prioritize learning measurement. And the past year has definitely impacted the way we think and approach the way we deliver and measure training. In this blog post, we’ll discuss some highlights from our fifth annual “Measuring the Business Impact of Learning” report and what these might mean for the year to come.

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Watershed

FEBRUARY 10, 2021

Data strategies are important for ensuring that efforts by data teams and stakeholders have a consistent approach and purpose. And the Department of Defense’s (DoD) data strategy is a published example of the sort of guidance needed to achieve consistent quality out of data efforts in a high-stakes enterprise environment. It’s also a signal that the DoD is taking data seriously and claiming it as a strategic asset.

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Watershed

FEBRUARY 3, 2021

As data continues to grow in volume and frequency, it’s vital that organizations have well-documented, scalable digital strategies. That’s because a comprehensive plan ensures that specific efforts by data teams and stakeholders have a consistent approach and purpose. In this blog post, we’ll discuss the elements of a smart data governance strategy and how you can create and maintain one across your organization.

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Watershed

JANUARY 25, 2021

One of the most important offerings that a company has is their expertise, which is why skills increasingly are becoming the new global currency. And while many people have heard of badging and micro-credentialing , they may not completely understand what these terms mean or how this process works in the broader context of skills development. In this blog post, we’ll cover what we learned about badging and micro-credentialing from a recent webinar where PwC showcased their global badging program

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Watershed

JANUARY 8, 2021

For many of us, the terms analytics and analysis regularly come up in our daily work. But what do these words actually mean, and are we using one when we should be using the other? In this two-part blog series, we’ll first explore the difference between analytics and analysis and how that relates to learning analytics , followed by how analytics and KPIs differ when it comes to learning and development.

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Watershed

DECEMBER 3, 2020

We often stress the importance of measuring the impact of learning programs, especially if you hope to develop training that actually improves outcomes. But what happens when you aren’t able to actively analyze learning’s impact because the organization is focused fully on shifting operations to support whatever crisis is thrown at us? In this blog post, we’ll explore what’s happening right now in the world of learning evaluation and analytics and what this means for you.

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