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Ginger Swart is a community manager at Articulate. She’s also an ERG co-lead and a member of Articulate’s Accessibility Working Group. Prior to joining the community team, she was part of the Articulate 360 Training team. Before coming to Articulate, Ginger worked as a technical writer for ten years before moving to the training world, where she created courses using Articulate 360 products. Her background is in theatre, and she previously worked for a theatrical lighting manufacturer for 15 years.

Ginger Swart

Vice President of Sales and Marketing, Jigsaw Ginger has more than 25 years’ experience in the healthcare technology sales industry. She has worked in both profit and nonprofit organizations, with experience in sales, marketing, business development, administration, and operations. Ginger’s interactive management style has led sales teams to consistently exceed their sales goals. Her primary focus and sales technique is to ensure quality customer service while identifying customer needs and matching them to specific solutions. Ginger’s experience ranges from working with smaller organizations to leading multiple sales and marketing teams for large companies such as Caremark International, NDCHealth, RPM, and CareMedic. She is also an entrepreneur; she helped start several companies and led the growth of those companies through sales and marketing.

Ginger Ackerman

Master the essentials of Articulate Rise with hands-on practice, expert feedback, and pro tips in this course. Start creating engaging e-learning today!

Articulate Rise Certificate

When things are changing rapidly, fear doesn’t just linger—it multiplies. It moves through teams quietly, often unspoken but deeply felt. Deadlines are missed, meetings lose direction, and initiative dries up. Employees do the minimum to avoid risk, and leaders (especially new ones) find themselves reacting rather than leading.We’ve seen what fear does to an organization: it drains energy, clouds decision making, and halts forward motion. We’ve also seen what happens when leaders choose something different. They don’t ignore fear. They acknowledge it, then replace it with something far more powerful: clarity, trust, and action.Fear Isn’t Just Emotional—It’s OrganizationalFear shows up in systems, not just people. When it becomes baked into how your organization operates, you start seeing common patterns:Teams avoid tough conversations or delay key decisions in hopes that conditions will improve.Managers micromanage, trying to control outcomes instead of building trust and ownership.Innovation stalls because employees are rewarded for playing it safe, not thinking big.Excuses multiply because accountability feels unsafe when outcomes are unclear.This fear-based stagnation is what we call “paralysis in disguise.” It looks like busy-ness, but no one’s making meaningful progress. It sounds like caution, but no one’s taking ownership. It feels like uncertainty, but really, it’s a lack of leadership clarity.Great Leaders Don’t Eliminate Fear. They Replace It.Optimism is a choice, but it’s not naive. It's not about ignoring risk or forcing positivity. It’s about training your brain to focus on what you can control, even when the external environment is uncertain. That mindset shift, when modeled by leaders, starts to cascade.Great leaders replace fear-based patterns with high-trust, high-accountability cultures. Here’s how they do it:They communicate with purpose and transparency, especially when stakes are high. Uncertainty thrives in silence, and clarity shrinks it.They create psychological safety, where people are encouraged to speak honestly, take smart risks, and learn from failure.They use the Decision Ladder to clarify ownership, so no one’s left wondering who should act next.They define success clearly through tools like Team Key Results (TKRs), making progress measurable even when the future isn’t.Your Mindset Sets the ToneIn Power in 30, we compare human mindset to battery power. When you're drained, you lose the ability to lead effectively. Fear accelerates that drain. Leaders who intentionally recharge, through reflection, connection, and clarity, show up with energy that fuels their team. They refuse to let fear set the pace.You don’t have to be fearless to lead, but you do have to act. Leadership is about modeling the mindset and behaviors that help others move forward, even when the path is unclear.Questions to Ask Yourself (and Your Team)If fear has quietly crept into your culture, ask these questions to bring it into the light:Where in our work are people hesitating instead of acting?What decisions are stalled right now and why?Have we created clarity around what success looks like?Are we rewarding smart risk-taking or punishing imperfection?Do I show up with energy and direction or with uncertainty and reactivity?These questions won’t solve fear on their own, but they’ll give you the insight to replace it deliberately and effectively.In ConclusionFear will always have a seat at the table, but it doesn’t have to lead the meeting. When leaders create clarity, demonstrate optimism, and move with intention, they set a new tone for the organization, one rooted in trust, ownership, and momentum. That’s what real leadership looks like when fear tries to take over. Uncertainty isn’t going anywhere, but neither are you.

How Leaders Overcome the Fear That Is Paralyzing Their Organizations

With modern technology, accurately measuring the impact of virtual training programs is a very real possibility. When used properly, this kind of measurement catalyzes change in industries like healthcare, financial services, consulting, manufacturing, and others that rely heavily on effective training programs. But the ability to measure doesn’t guarantee success. You also need to know what metrics to track, how to avoid bias, and how to get buy-in from stakeholders and instructors.Let’s examine how best to use data and automation to save instructors and administrators time and improve the learner experience.3 Top Challenges to Effective AnalysisWhile there are several things to consider when implementing the most effective measurement program for virtual training, let’s take a closer look at three top challenges that we recommend tackling first, as well as our tips for clearing these hurdles with ease.1. Difficulty quantifying engagement. Look for a virtual training measurement platform that collects and analyzes the data for you, assessing factors like tardiness, the number of minutes instructors speak versus learners, and the number of learners raising their hands and using customized reactions, to name a few. Once you start measuring, set benchmarks based on your historical data, setting ambitious yet realistic goals for improvement. 2. Unintentional bias using qualitative measurement.Those responsible for measuring the effectiveness of training programs shouldn’t completely ignore qualitative methods of judging engagement, but must also introduce data to reinforce the findings of qualitative measurement to ensure accuracy.3. Lack of instructor focus on measuring engagement. Put plainly, the onus should not be solely on instructors here. The introduction of technology and data can be a welcome solution. Teachers can focus on teaching while reliable tech measures the results in the background, helping tell a complete story.Use Results to Improve InstructionTo improve instruction, it’s critical to analyze various metrics like total class time, instructor speaking time, participant speaking time—including the total number of times participants spoke as well as the average speaking time from all participants—and the total number of times participants raised their hands or gave feedback through the platform. Technology solutions can help compile all these metrics into one easy-to-digest dashboard and allow you to view results for an entire session, as well as drill down into individual participant results. Use the insights from your results to inform the changes you make to your training programs, and continue to iterate as more results come in.Technology can also automate time-consuming tasks like attendance recording, time in, time out, and tardiness, which both increases the accuracy of this data and frees instructors up to focus on quality education, improving the learning experience overall.Demonstrating Program EffectivenessIf you’re trying to effect change in your training programs by determining what’s working and not working, having quantifiable results and trends can go a long way in showing stakeholders the impact. Remember to utilize automation in your reporting technology, which can help expand reporting efforts and demonstrate effectiveness at a larger scale. When you’re communicating the value of your reporting to stakeholders, it also helps to have a framework for your metrics that’s backed by research and proven success. The Kirkpatrick Model for evaluating learner engagement lends itself perfectly here. This model distills training evaluation down to four distinct levels: The reaction of learners, including their thoughts on the training experienceThe learners’ increase in knowledge after the training experienceThe learners’ behavioral change and performance after applying the skills learnedThe results the learners’ performance has on the business or organizationMake sure whatever metrics you’re tracking to measure effectiveness follow a similar model to the Kirkpatrick Model. The key is persistent tracking to evaluate success at several points in time, allowing you to present a complete picture with your results.Access to accurate data and smart automation is the backbone of a successful training program. A powerful virtual classroom platform that’s purpose-built for learning and development, like Class, ensures that you can always keep your finger on the pulse of how your programs are performing, allowing you to focus on innovating and providing the best possible education for your learners.

Measuring the Impact of Your Virtual Training Programs

At the beginning of the past two years, I’ve written a post on important points I think you should know. In 2021 I mentioned the importance of context, emotion, and learning to learn. In 2022 I discussed some of the newer cognitive science models of cognition—including distributed, social, and embodied cognition—as well as the role of mental models. This year, I’d like to focus on a trend that we should extinguish: the belief that we are formal, logical, reasoning beings.The cognitive revolution transcended the view of behavioral psychology; we couldn’t talk about what went on in the brain. While many valuable insights were generated by that scientific paradigm, including the role of performance objectives, the move to thinking we could isolate necessary components provided further advances. Results that have stood the test of time—the recognition of sensory, working, and long-term memory as well as core cognitive processes like attention, elaboration, and retrieval—were identified.We tend to adopt existing models as frameworks for thinking about the brain, and the cognitive revolution was no exception. For example, consider the computer as a general-purpose information processing system. It made sense to adopt that model to reflect our abilities to process information and complete a variety of tasks. Thus, the dominant framework for thinking about thinking was to view our brains as formal, logical, reasoning machines.Such models, with some assumptions like mapping the world into formal representations, accomplished impressive tasks. Systems built upon that model could break down problems into components and solve them. They could even learn. Artificial intelligence (AI) advanced as a result. So-called “expert systems” were built upon interviews with the best practitioners. Sadly, these models failed in practical situations, leading to an AI winter. This was a disconcerting time, when behavior naturally observed in humans did not reflect these symbolic systems.The Postcognitive RevolutionOne of the most impressive capabilities of our thinking is the ability to organize the world into flexible frameworks. What David Rumelhart called schemas, Marvin Minsky called frames, and Roger Schank called scripts all reflect our ability to infer knowledge about the world. Thus, we had representations such as wheels that scaled up to vehicles but differently for automobiles versus bicycles. Symbolic logic struggles with this, however. Attempts were made to adapt, such as Lofti Zadeh’s Fuzzy Logic and Douglas Hofstedter’s Slipnets, but suffered in practice.An alternative framework emerged that could be characterized as “subsymbolic,” operating below the symbolic level. John Holland, Keith Holyoak, Richard Nisbett, and Paul Thagard created a genetic algorithm approach in Induction, which borrowed mutation from biology, but wasn’t aligned with neuroscience. Rumelhart, along with Jay McClelland, proposed connectionist models instead in their two-volume set Parallel Distributed Processing with a neuroscientific inspiration. These models were found to exhibit rational behavior similar to humans. They represented the same types of behaviors, including errors, that were empirically obtained from psychology research.These neural net models created not only a psychological revolution, capturing elements of cognition, but also a renewed basis for artificial intelligence, underpinning much of today’s work in machine learning.A Cognitive LegacyOne small legacy of the formal, logical, reasoning model of cognition, however, seems to linger. It appears that many of our practices in learning and development (and business in general), still seem to be based on this idea. This is a potential problem.If we’re formal logical beings, there are several things we should be able to assume. For one, if we give people new information, they’ll appropriately adjust their behavior. Moreover, the person with the greatest access to information should be the one to make a decision, and that decision will be the best one possible. We see this manifest in several ways.For one, our training frequently resembles the presentation of new information with an expectation of behavior change. Too often, we see bullet points of information extracted from (and even presented by) experts. After this, there’s an expectation that we’ll do something differently. Similarly with annual or quarterly reviews. People need feedback at the appropriate time and support for change. We don’t just change when we wish to; it takes time and practice.We also see decisions made by individuals without consultation. Folks will decree a new approach because it’s been determined by the person at the appropriate decision point. Yet the evidence suggests that we get better outcomes when we bring more people into the decision-making process, such as in Keith Sawyer’s Group Genius. When we follow practices that help us suitably explore a problem individually, and then collectively brainstorm solutions, test, and adapt, the outcomes are better.A Problematic LegacySadly, there is also evidence that this approach to work isn’t working. We see it in the outcomes of learning investments, and when we evaluate organizational success as an outcome of our approaches, we see that more informed ones work better.In the 2012 Harvard Business School working paper The Great Training Robbery, Michael Beer, Magnus Finnstrom, and Derek Schrader cite metanalyses that suggest only 10 percent of training investment has an impact. There may be multiple causes for this, but it does suggest that we’re wasting money with our approaches. The Serious eLearning Manifesto suggests that much of traditional learning is based on information presentation, so it’s safe to say that we’re not doing as well as we could.Similarly, efforts like Laura Overton’s Toward Maturity and Lauri Bassi’s Human Capital Capability Scorecard suggest that organizations do better when they’re better aligned with how people think, work, and learn. Organizational performance reliably improves with better employee approaches.Overall, the continued use of ineffective practices undermines our organizational success. We need to effectively achieve our organizational goals, which includes ensuring we can optimally execute what we know we need to do and continually innovate when we have to invent or adapt.Moving ForwardWhat should you do differently?Truly understand how your brain actually operates. Know the basics of the human information processing loop and extensions for learning and performance.Avoid the myths that continue to hinder our industry.Conduct deep needs analyses to find important performance gaps and their root causes. There are many causes of problems besides a lack of knowledge or skills. Stop thinking that if you give people knowledge, behavior will change.Leverage external resources. Decision making is best done collectively and iteratively. To do otherwise is to minimize your potential.Move from legacy practices to evidence-based practices. There are vested interests that continue to exist based on perpetuating approaches that aren’t effective. Many products that are quite lucrative—profiling instruments and development programs —aren’t effective.Start measuring impact. This doesn’t mean what people prefer (there’s no correlation with what people think of a program and its impact). Instead, assess the actual change in the organization. You can’t collect this yourself; you must partner with the business units that require change.Align programs to demonstrable gaps, and then measure until they’ve improved.Ultimately, L&D should be the folks that are responsible for not only optimal execution but also continual innovation. When you’re innovating (problem solving, designing, or researching), you don’t know the answer when you start, so inherently it is learning. It’s informal learning, and no one knows the answer (yet)! Still, it’s an opportunity for L&D to attain a more valuable role in the organization.To make this strategic move and start bringing evidence-based practices from formal to informal learning, take ownership of these practices within your teams. Make it safe to fail; share stories of what you tried; and learn together. Create and understand a learning microculture before taking it to the rest of the organization.Last, identify the organizational legacies that are holding you, and your organizations, back. Then, find alternatives, and implement them. When you’re free of your unexamined past, you can move forward to an evidence-based future that means better outcomes. That’s a trend I’d like to see and encourage you to undertake.

A Trend to Supersede

December 2022 - TD Magazine

Reduce the friction that is preventing learners from engaging with your learning.Businesses spend billions of dollars trying to understand consumer behavior, resulting in marketing strategies that aim to get consumers to buy their products. However, in those companies, many L&D functions are not leveraging the same insights and strategies to reach their learners. Treat your learning solutions like products, and minimize the friction between the solutions and learners. One way to do so is using BJ Fogg's behavior model to evaluate your learning initiatives.Identify the frictionThe Fogg behavior model looks at three conditions that must be present for someone to engage in a behavior: motivation, ability, and a prompt. When one of them is absent or diminished, so is the likelihood that the desired behavior will occur.For example, let's say you have a missed call on your cell phone. Why didn't you answer the phone? Maybe you heard it ring, looked down and saw who was calling, and decided you didn't want to talk to that person right now. You heard the ring—that was the prompt. Nothing was keeping your from answering the call (that is to say, you had the ability). You just didn't want to—you didn't have the motivation to engage in the behavior.Now let's say the phone rings, and you're expecting the call and want to take it. But you can't find your phone, or it's in another room and you can't get there in time. Again, you heard the ring (the prompt), and this time you wanted to take the call (motivation), but you weren't able to get to the phone in time (ability).Finally, let's say you're expecting the call, and your phone is right next to you. However, the ringer is set to silent. The phone rings, you want to answer and are able to do so, but you never hear the ring—you received no prompt to answer it.That's how Fogg's behavior model works. The presence or absence of any of the variables can contribute directly to the likelihood that you'll engage in a given behavior.What if we look at learner behavior through that lens? You've created a great learning initiative and spent a lot of time and money on the learning ecosystem. However, you don't seem to be getting the traction you're hoping for. Here are some questions to consider:Are learners aware of the learning solution? Are there prompts that alert learners to its availability?Are learners motivated? Do they want to engage in learning?Are they able to engage with the learning solution?Is there anything preventing them or making it more difficult for them to access it?If you have opportunities in any of those areas, then you have friction between learners and the learning solution. Friction, in this context, is the absence of prompts or is anything that impedes motivation or ability when it comes to a learning initiative.PromptsIf learners don't know about your learning initiative, it may as well not exist. These days, people are inundated with prompts—pop-ups on smartphones, ads on social media, digital billboards, and the like. How can we ensure that learners are prompted to our initiatives? The traditional methods are static and push prompts.A static prompt is one that is in a fixed physical location, such as a poster in a breakroom. It works fine when your audience tends to be isolated in one particular location. But if someone is not in that exact location, they won't see it.A push prompt is much more targeted. It entails identifying your audience members and sending a prompt to them, such as an email reminder that a course is available. However, you often can't customize that prompt by audience member—everyone gets the same message. And you can't time the prompt so that it reaches an individual right when they need it most. Thus, there are some limitations to what we have traditionally used as prompts in our learning ecosystems.This is an area we should pay close attention to because it has the potential to change rapidly. Imagine if we could activate a prompt for a specific learner at a specific time and in a specific location with a learning solution that is designed precisely for the activity that they are engaging in in that moment? It would be similar to finding an exclusive offer from Starbucks popping up on your phone whenever you're within 50 yards of a store.MotivationMotivation should be the easiest variable in this equation. If your initiative meets a learning need, learners should be inherently motivated to engage with it. However, that isn't always the case. In my experience, there are two major reasons. The first is that the solution does not meet a learning need (which is a subject for another article). The second, and more egregious, reason is that learning solutions get bogged down with demotivators that dilute learners' eagerness.Given the massive increase in video use for learning, there are some lessons to be learned from how people engage with YouTube and how we think about the videos and other learning initiatives we create.I often use the example of having a hole in my drywall and turning to YouTube to see how to fix it. Not surprisingly, there are numerous options from which to choose. We've all become accustomed to using filters to narrow down internet search results, although we often do our own visual filtering first. For example, I can take a quick look at a results list on YouTube for drywall repair and immediately rule out, or at least deprioritize, some of the videos. The first thing I'll look at is time. I expect that this should be a relatively simple task, so I'm not looking for a long video. The shorter the better.Likewise, learners have an expectation of how simple or complex a task is and at least some sense of how long it should take to learn. If they see that a video is 30 minutes long, and their perception of the task doesn't line up with that amount of time, you may lose them right away.I start playing a six-minute video from the list. After a lengthy introduction, a bio of the host, and several examples that don't apply to what I'm looking for, the host eventually starts the process of explaining how to execute the repair. It took over one minute to get there. That is an informal measurement I call "time to learning"—or how long it takes before I get to the actual learning. Time to learning is especially important when considering whether our goal is knowledge retention or knowledge acquisition. In other words, are learners in this for the long haul, or do they just need a quick one-off fix that they will rarely if ever need again?When looking at learning from a knowledge retention standpoint, time to learning is slightly less important. We know we're going to get deep, and participants learning about the instructor's credibility can be helpful to set the tone. But if we seek knowledge acquisition, or disposable knowledge, time to learning matters a lot—especially if there are several options from which to choose.For example, imagine I need to generate a report for my manager, who is out sick. I've never done the task before, and it's highly unlikely that I'll ever have to do it again. After some digging, I find a few videos that will help me figure out what to do. However, the videos don't cover only the report I need to generate; they cover all the reports in the entire program and explain where the data from those reports comes from and why they're important to the business.Are those bad things for me to know? Of course not. But they're not relevant to what I need to do right now. Getting what I need is like searching for that how-to needle in a haystack of video instruction. I may resort to other options, such as trial and error (risky) or asking a colleague (now two of us are wasting time trying to figure this out).Going back to the drywall video: I stuck with it for more than a minute only to see how long it would take for the purposes of this example. If I had a real need, I doubt I would have held out for more than 10–15 seconds.We can and should apply the same lessons to our video content libraries and consider where we are adding friction that we should remove. In most cases, those are demotivators that don't reflect the quality of our instructional design yet may deter learners from ever finding that out.AbilityAnother go-to source for information in people's nonwork lives is Google. Here's what happens if I search for "how to repair drywall"—let's count the clicks: I open the browser to Google and type the search term, then click Search. One click. What I see first are a few links to associated terms like "water damage" and "peeling" that enable me to refine my search. Below that is a frame from a video already queued to a specific timecode that is likely to address my need. Below that are links to a few more videos, all with descriptions and timecodes of key moments in the videos. Next up is the "People also ask" section, which displays several ways that others have posed their question that may be more in alignment with my need. And finally, I get a list of results that I would normally expect to see on Google. All from one click.Now think about your learners and, more importantly, your learning ecosystem. Most likely your version of Google is some sort of learning management system or learning experience platform. How many clicks does it take learners to get there? Once someone arrives at your version of Google, how many of the features described above does it have? How easy is it for learners to find what they need?Many of us are presumably still in a situation where learners must go through six, eight, or even 10-plus clicks to find what they need. Number of clicks and speed to solution are ways we can assess learners' ability to engage in the desired behavior.Nobody wants to click through a never-ending menu. Individuals have been conditioned that they shouldn't have to, and they are far more likely to give up somewhere along the way than they are to reach the end.Other ability barriers include bandwidth and hardware. Sometimes our instructional design comes with ability barriers. If you have motivated learners who know about your initiatives, make it as easy as possible for them to access and engage with learning.Enhance learning's impactThis article has numerous questions you can ask about any given learning solution. It's going to be difficult to get satisfactory answers to all of them. But what you can do is identify an area that you believe may be causing friction for your learners and is something that you can influence.In other words, we all want better bandwidth, but you probably have an extremely limited ability to influence that yourself. You may have a better chance implementing some prompts for learners that can move the needle. Or you may be able to reduce the number of clicks required to access content with some adjustments to your internal websites or portals. Start small by looking for areas to reduce friction with existing learning solutions, and then incorporate the ideas into the design phase of future ones.If you treat your learning program like a product and view your learning ecosystem as a mechanism for reaching your audience and providing that product, it may change your perspective.

Are You Driving Learners Away!

ATD Talent Development and Training in Healthcare Handbook (ATD Press, November 2021) addresses the many opportunities and challenges TD professionals face in the growing and rapidly changing healthcare space. Effective talent development is the thread that weaves through an entire healthcare organization to ensure it is up to standard with the latest practices in treating patients while providing a safe and engaging environment for staff. TD professionals have the unique role of tying together organizational and employee advancement in healthcare systems—and likewise, this handbook dives into areas for business and professional evolution.Written by 25 fellow healthcare practitioners with extensive experience in the field—from nurses, physicians, and administrators to instructional designers, chief learning officers, technology experts, and leaders across the industry—the book covers six key themes across 26 chapters:Learning and development basicsOrganization developmentEmployee developmentBusiness acumen for the health systemDigital transformation and literacyPatient-centric careLearn more about Scott Kashman, market president for St. Dominic’s and the Franciscan Missionaries of our Lady Health System (Jackson Market), and his chapters on leadership development, business acumen, and well-being in this spotlight Q&A.How have your experience(s) in leadership development, business acumen, and well-being shaped the best practices you shared?Leading with a strategic lens, being grounded in operations with the support of a healthy team provides a balanced leadership approach. Based upon experience, I find these three need to stay in harmony or else an organization will achieve inconsistent performance and team engagement.Leaders should engage the hearts and mind of their team by providing a clear vision and sharing the importance, purpose, and why behind the vision. Then they should step back, trust, empower, and support their team as they develop plans and achieve the collective goals. While it sounds basic, it is not always practiced consistently. If you re-enforce how much the team is valued, cared for, and connected, you will unleash the full potential of your organization.How do you foresee advancement of talent development in these areas within healthcare? (i.e. in an ideal world, how do you see this area flourishing for employee or organizational development)?Developing talent takes an ongoing commitment by healthcare leaders and organizational development specialists. Ensure leaders know how to coach other leaders and staff. Many leaders mentor others by telling them about their own experiences and having others shadow them. Learning to be leader-coach takes a different skill: being present and focused on the person you are developing. By asking questions, staying curious, and allowing others to find the answers within, you will create the necessary bandwidth to solve for new and emerging opportunities.What is something unexpected you learned while working on this book?Through this process, I had a chance to connect with other authors. It broadened my understanding of the many facets that contribute to talent development. I appreciated learning from my colleagues and applying these skills within my own leadership practice.Is there something professional or personal you are proud of accomplishing in the past year?Holding space for others to develop personally and professionally. Completing a coaching certification through the NeuroLeadership Institute helped me think differently about how to coach and develop others. For more than a year I was fortunate to develop a strong, healthy leadership team across my previous health system. This served as a foundation of collaboration and trust as we opened our incident command in March 2020 and started navigating through the pandemic. At the same time, we engaged our community partners and internal team to advance our quality, safety, and overall performance.What is a fun fact about yourself or one sentence of advice you’d like to share?Start with self. In the past, I ran many marathons, counseled patients as a psychiatric counselor, joined an improv comedy troupe, and worked on stage at a karaoke bar (and I’m a terrible singer). Each of these experiences shaped my leadership, focused on humility, strategy, operations, and the health of a team.

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