BSEE selects Radiant Digital as a training development vendor

Radiant Digital (Radiant) was awarded the NOTC Training and Learning Curriculum Development Blanket Purchase Agreement (BPA) for the Department of Interior’s Bureau of Safety and Environmental Enforcement (BSEE).

BSEE selected Radiant as a training development vendor to enhance the capabilities of its compliance professionals. BSEE sought a firm experienced in developing curriculum for inspection, maintenance, and operations personnel in facilities where the consequences of unplanned incidences can have a severe impact on the health and safety of workers, on the well-being of surrounding communities, and the environment. It also required a firm with the experience to bring contemporary approaches to its learning programs, including mobile and extended reality (XR) applications.

“We’re excited to have been selected by BSEE to help them improve and expand the learning opportunities for their employees,” said Erik Fullerton, Radiant’s Director, Learning and Organizational Change. “BSEE’s mission is a critical one, and Radiant is proud to play a part in helping them maintain the safety of workers and protect our coastal environment.”

Radiant’s extensive experience designing learning interventions for companies involved in industrial applications requiring a high emphasis on safety makes them a perfect partner for BSEE as it seeks to maintain the highest level of safety at US offshore energy exploration and production facilities. Radiant’s breadth of services, such as user experience design, application design and development, and multimedia design, form an excellent complement to the instructional systems design from which future products will spring.

“Radiant has been helping oil and gas firms train their employees to inspect, maintain, and operate their facilities for over a decade,” Fullerton continued, “and we’re looking forward to bringing that experience to bear on BSSE’s unique challenges.”

About Radiant

Radiant is a value-driven organization focused on outcomes while delivering advanced and innovative solutions across the digital enterprise. Radiant provides digital transformation and digital experiences aligned to support their client’s needs to be more operationally efficient, more competitive through insight into their customers, and have a motivated and knowledgeable workforce. To learn more, please visit Radiant’s website or LinkedIn.

About BSEE

The Bureau of Safety and Environmental Enforcement (BSEE), located within the Department of Interior (DOI), has a requirement to produce training and multimedia products for its National Offshore Training Center (NOTC) program. BSEE’s mandate is regulating, monitoring, and inspection of energy production operations on the Outer Continental Shelf (OCS). The BSEE compliance personnel currently consist of approximately 400 professionals. To learn more, please visit BSEE’s website or LinkedIn.


Radiant and Dojo partner to scale digital transformation and cloud at the "industry-level"

Seattle, WA - Radiant Digital and Dojo Partners announced a partnership to bring Radiant's global capabilities in digital design, rapid prototyping, cloud transformation, and sector leadership with Dojo Partners’ approach to industry-level corporate growth planning. Radiant Digital is a leader in delivering and enabling advanced and innovative solutions across the digital enterprise.

“Immersion in customer needs and an obsession with using data and cloud to address real-time personalization has always been a part of our core DNA. Partnering with Dojo allows us to ignite a vision that can work at the industry level, such as retail, transportation, manufacturing, financial services, and many others," said Jon Clark, SVP at Radiant Digital.

“Radiant has an exceptional track record at building world-class digital experiences for globally relevant brands and truly putting the user at the center,” said Dheeraj Batra, Managing Partner and Co-Founder of Dojo Partners. “Bringing Dojo's history of research, growth planning, and venture portfolio development together with Radiant allows any client to develop a vision and roadmap for the cloud and IoT future. We can then bring that to life using the most contemporary design and development best practices,” Batra added.

“Our partnership with Dojo Partners is significant because it allows customers of every shape and size to align user experience, disruptive digital transformation, and customer engagement at the industry level,” said Jon Clark. “Moreover, as IoT, cloud, DeFi, digital twin, and other immersive tools continue to emerge, our teams can factor all of those ideas into a horizon 1,2, and 3 roadmaps for clients to see results immediately and then scale over time” said Clark.

About Radiant

Radiant Digital delivers advanced and innovative digital transformation solutions that align with their client’s needs to be more operationally efficient and competitive. Radiant’s solutions help their clients reduce costs, advance agility, increase customer insight, and improve employee skills and knowledge. To learn more about Radiant, please visit www.radiant.digital or www.linkedin.com/company/radiant-digital-solutions.

About Dojo Partners

Dojo Partners is a new consulting firm that brings strategy, design thinking, and programs realization together to drive corporate growth and innovation. Dojo Partners build solutions that bring disruptive digital solutions to large, mid, and small-cap enterprise customers across a wide variety of industries. To learn more about Dojo Partners, please visit www.dojopartners.com or www.linkedin.com/company/dojo-partners.


Radiant Digital acquires Beacon Systems to scale and deliver outcomes beyond digital transformation

Vienna, VA, January 11, 2022 — Radiant Digital Solutions, Inc. (Radiant Digital) announced the acquisition of Florida-based Beacon Systems (BeaconGov) to strengthen the company’s capabilities in accelerating digital transformation and achieving high-value outcomes for commercial and public sector clients. BeaconGov is a small business firm that provides technology, engineering, and business solutions to customers in the commercial and public sectors, focusing on state and local government agencies.

“We are very excited about this acquisition. BeaconGov brings a portfolio of new clients that will not only help Radiant Digital expand its public sector practice, but also increase the scale and strength of our capabilities in emerging technologies such as AI/ML, data and cloud services, blockchain and decentralized finance,” said Dr. Shankar Rachakonda, CEO of Radiant Digital.

“Radiant Digital has an impressive track record of helping customers quickly envision, prototype, and launch user-focused digital solutions to accomplish desired business outcomes. With this acquisition, Radiant will strengthen its ability to deliver cost-effective and lean digital transformation solutions for commercial and public sector organizations,” said Ms. Marada M. Reddi, President of Beacon Systems.

“We are proud to welcome the BeaconGov Team to the Radiant Digital family,” added Dr. Rachakonda, “I’ve had the opportunity to see first-hand the execution discipline they apply to business problems, and I am excited by what we can accomplish together for our customers. With access to even more talent through BeaconGov, we can help our customers go deeper into the lifecycle of innovation and execute across a broad transformation roadmap with increased scale.”

About Radiant Digital

Radiant Digital delivers advanced and innovative digital transformation solutions that align with their client’s needs to be more operationally efficient and competitive. Radiant's solutions help their clients reduce costs, advance agility, increase customer insight, and improve employee skills and knowledge. To learn more, please visit www.radiant.digital or www.linkedin.com/company/radiant-digital-solutions.

About Beacon Systems 

BeaconGov is a rapidly growing SDB certified technology and engineering firm that provides strategic technology, engineering, and business solutions to the federal, state, and local governments. BeaconGov’s client base includes NASA, the U.S. Army, the U.S. Department of Agriculture, the Voice of America, and the states of Florida and Oregon. Additional information on BeaconGov can be found at www.beacongov.com or www.linkedin.com/company/beacongov.


The Importance of UX Principles

UX principles help guide designers in thinking, creating, and collaborating. Unfortunately, in many cases, designers take advantage of UX Laws and UX Effects in their designs without even knowing their actual impact. User experience design is about more than just visual design. Understanding user psychology is key to making designs that work effectively and look great.

In this post, we wanted to highlight the importance of UX principles by looking at a few of the most common principles and exploring how they help designers fulfill their ambitions.

UX Principles

Hick's Law

This principle supposes that the time it takes to decide increases with the number and complexity of user choices. Therefore, when creating user experience designs, you want to limit the time it takes to make decisions and ensure users can quickly fulfill their needs with your product, services, software, or website.

Goal Gradient Effect

This effect is about the idea that as people get closer to a reward, they speed up their behavior to attain their goal as fast as possible. This is because they are motivated by the end goal. So, for example, users will take time to fill out a form if they are shown that the result of filling out the cast is positive (e.g., Amazon's Product Ordering or the 'Time to Reach' mechanic for Ola, Uber, and Swiggy & Zomato).

Zeigarnik Effect

According to the Zeigarnik Effect, people remember uncompleted or interrupted tasks better than completed tasks. The Russian psychologist Bluma Zeigarnik discovered this effect by observing that waiters at a restaurant could recall the orders they had not yet delivered far better than those they had distributed. This effect has the same solution as the 'Goal Gradient Effect' and has been used by companies like Naukri and LinkedIn to affect 'Profile Completion significantly.'

Von Restorff Effect

This principle contends that when multiple similar objects are present, the one that differs from the rest is most likely to be remembered. This is an easily verifiable principle that is consistently worked into UX designs. For example, messaging apps like WhatsApp, Facebook Messenger, and Telegram use the Von Restorff Effect to show unread messages. And along the Macbook Menu Bar, bright red notification circles ensure that certain apps receive more attention than others.

Miller's Law

Miller's Law says that the average person can only keep 7 (plus or minus 2) items in the working memory. This is an important principle to abide by when creating UX designs meant to be used by many users. You don't want to overload your user with information. This is why many modern menus have 4 or 5 prominent navigation buttons, and in Amazon's reviews section, they will show around 5-7 reviews at first and hide the rest.

Law of Proximity (Gestalt Principles)

The Law of Proximity is quite a simple one. It supposes that objects near or proximate to each other tend to be grouped. Therefore, UX designers should ensure that they don't place items that have no practical relation next to each other on the screen layout. For example, the actionable buttons like footers will be separated from others on most websites to show the difference.

Jakob's Law

There is comfort in the familiar. Jakob's Law is about the idea that users prefer your site, product, service, or design to work the same way as the other sites, products, services, or techniques they already know. For example, with websites, you want to have a simple 'Login' or 'Sign Up' page that is not too dissimilar to those of your competitors and other popular user options. In general, Login pages and search bars are not the right places for innovation because users are already so used to a standard format.

The Heuristic Principles

Now that we've highlighted some of the essential UX principles let's concentrate on the Heuristic Principles. There are 10 in total, but we're going to focus on 5 in particular and how these broad usability tips can help you make products user-friendly, convenient, and enduring during the design stage.

1. Consistency and standards

Like Jakob's Law, this heuristic principle is about sticking close to platform and industry conventions. As a result, users should not have to take long to understand your design. But, equally, they should not have to wonder whether the words or actions used within your design mean something different than the industry standard.

2. Visibility of system status

The design should keep users informed about what is happening at all times. There should be an appropriate feedback mechanism, and it should be clear whether or not they are using your system correctly. There should be indications or messages concerning the system status, like how a loading circle appears in Google Chrome when you click on any link from the search.

3. Flexibility and efficiency of use

Make sure that it is easy to use your design and that there are ways to speed up the process for those familiar with your design. The design should cater to both experienced and inexperienced users. There should also be a degree of flexibility.

4. Help and documentation

The user should understand and use your design at face value. However, there should also be help and documentation for users keen to learn and receive an additional explanation.

5. Aesthetic and Minimalist design

Everything that the users see and interact with should be relevant and essential. The interfaces should be as simple and as clean as possible. This principle can be applied to any design and help create accessible websites, products, apps, and services.

To learn more about the importance of UX principles, contact our UX experts here at Radiant Digital.


Inclusivity in UX Design: How to Better Represent Everyone

How can we ensure that as many people as possible are considered in the UX design process? Are we prioritizing inclusivity when we are developing the designs of tomorrow? These are the sorts of questions that are necessary for progress in the world of digital design. Below we explore the importance of inclusivity in UX design, how it can improve the design, and how inclusivity can be maintained throughout the industry.

What does inclusivity in UX design mean?

No two people are alike. This is an essential thing for UX designers to remember. There are so many ways to categorize people that it would take another article to describe them all. Everyone has unique needs, wants, and characteristics.
Inclusivity in design is about recognizing that we have a responsibility to acknowledge, create, design, and serve as many people as we can. Users will typically come from a vast array of backgrounds, both economic and ethnic, will be of different genders, and have additional physical capabilities. And these are just a few of the factors that need to be considered in discussions about inclusivity. Inclusivity in design means that anyone should use your design and achieve successful results. Inclusivity in design also means anyone should contribute to the development process. If designs are only made by one type of person with only one kind in mind, the design is bound to fail when presented to a diverse user base.

Why is inclusivity in UX design important?

The consequences of not embracing inclusivity can be enormous. For example, initially, Apple Health launched without a simple period tracking function which effectively excluded half of their users from properly experiencing their product. Similarly, research has shown that cars are 71% less safe for women because crash test dummies are primarily based on the male physique. This shows how our products are designed mainly by one kind of person. Unfortunately, it can be easy to forget to represent everyone.
Inclusivity doesn't merely mean accessibility. Even the word 'Accessibility' can be reductive and create an "Us versus Them" dynamic. Inclusivity doesn't mean creating a base product that suits one type of person and adding bits and pieces to your design to include 'other' types of people. Inclusivity must be at the root of the creative process. This will help to ensure innovative and enduring solutions are made that serve a broad and diverse user base. When we look at it from a viewpoint that at any point in time, we might have to change the way we operate in this world, it becomes easier to empathize with others. Therefore, designers must put themselves in the shoes of their users and understand how they serve them as best as possible.


How can we achieve and maintain inclusivity in UX Design?

While it's often said that you can't make everyone happy, the second best thing to recognize is that we, as designers, are not our users. This means recognizing our own biases and understanding the perspective of our users. To design is to empathize, not merely sympathize, intending to improve the world around us. In practical terms improving inclusivity in UX design may mean diversity in decision making, research groups, meeting rooms, etc. Equally, being inclusive means being thorough in how we think about how diverse users can use our designs. Inclusivity should inform every stage of the design and development process. For example, designers should constantly be questioning themselves when creating a web page. First, they might ask, "Who is the target audience for this page?" or "How can I expand the options available on the page and widen that target audience?" Then they might ask themselves, "How accessible is the page to someone who is partially sighted?" or "How accessible is the page to someone who does not have English as their first language?". This self-scrutiny is key to creating and maintaining inclusive designs.

Here are some literal examples:

1. Consider Users with Reading Disabilities
2. Optimize Clicks and Navigation
3. Provide Captions or Transcripts
4. Offer Multiple Options for Contact

And here are some more general examples:

1. Provide a comparable experience for all users
2. Consider situational differences in location, interaction, and ability
3. Be consistent with user patterns and functionality
4. Give control to users when it makes sense
5. Offer choices and alternative user journeys
6. Prioritize content with one thing to do or focus on at a time
7. Add value with features, content, and visual frameworks

All of the examples have one goal in mind: inclusivity in UX design. Hopefully, you will take some of the tips on board and continue creating designs that serve all kinds of users.
To learn more about inclusivity and innovation in UX design, reach out to our UX experts at Radiant Digital.


Atomic Design 101: Creating Structured Design Systems

Atomic Design is a design system created by Brad Frost and inspired by chemistry. It is a modular system founded on the principle that a whole system can be subdivided into smaller parts (modules) that can be independently created, replaced, modified, or exchanged with other smaller parts or across different systems. It is a methodology that has helped develop modern, structured design systems capable of evolving and incorporating the input of various designers. Atomic Design is an interesting topic if you are looking to improve the way you design, which is why we’ve created this brief overview to help you understand how it all works. 

Atomic Design: Atoms, Molecules, and Organisms

As mentioned earlier, this modular system is inspired by chemistry. When you studied chemistry at school, you probably learned (but you may have forgotten by now!) that atomic elements combine to make molecules. In turn, molecules combine with other molecules and atoms to create organisms. Organisms combine with atoms, molecules, and other organisms to create even more complex structures.

Here’s a quick chemistry refresher:

  • Atoms are the basic building blocks of everything. All matter consists of atoms, the smallest functional unit of ordinary matter. Each element has unique properties and cannot be reduced further without losing its chemical meaning. As a result, they often must be combined with other factors to create sense.
  • Molecules are formed when two or more atoms are held together by chemical bonds. Molecules have their purpose and are slightly more complex than an atom. A design system generally has more than one function or purpose. 
  • Organisms combine molecules and atoms (and sometimes other microorganisms). Organisms tend to be much more complex, larger in size, and in a design system, are multi-functional elements. 

This is a very simplified version of the chemical composition of the universe, but it should help you understand the basic principles behind Atomic Design. Everything can be broken down into atoms, and subsequently, anything can be built by combining any variety of particles. It is more of a mental model than a consistent linear process and is a way to think creatively and methodically design. 

How do you create a design system using atomic design?

The Atomic Design framework can inform the way you think about design and the practical steps you take to implement designs. Using the chemical hierarchy we’ve just highlighted, Atom Design functions via five stages, in the following order:

  • Atoms - Labels, buttons, inputs, etc.
  • Molecules - Tangible UI elements such as search forms, survey forms, list forms, etc.
  • Organisms - When atoms and molecules combine to create complex structures such as headers or form entry modals
  • Templates - Page-level objects that solidify the content structure, such as a dashboard, landing page, or login screen
  • Pages - Templates with specific content that represent the final product

As mentioned, Atomic Design is a mental model. Therefore, it is essential to see all UI elements as parts of a whole. However, only atoms can stand on their own. Therefore, all molecules, organisms, templates must be smaller components. The best way to start using the atomic design system is by thinking about all of the basic needs for your website and understanding which essential components you’ll need to create your more significant design elements, such as: 

  • Labels
  • Iconography
  • Buttons
  • Interactive Elements (Checkboxes, switches, radio buttons, etc.)
  • Typography
  • Form Fields

Am I limited to creating my designs using only the atomic design system?

Remember, Atomic Design is a modular system. This means that not every single UI element you create needs to be part of the design system; only the UI element components need to originate from the design system. If a new atom needs to be created for a molecule or organism, you should work with the owner of your design library to be added to the design system officially. There is room for expression within the atomic design system, as it is a system of thinking that encourages and rewards experimentation. Furthermore, once you have a library of UI elements, there are so many variations to experiment with that it is unlikely you will feel limited in any way.

When should I consider creating/adding a new element to the design system?

It would help if you considered creating or adding a new element when you have used the same few elements multiple times on multiple projects. One of the ways you can make sustainable progress to your design system, and prevent it from growing stale, is by adding elements that force you to innovate and come up with exciting ideas.

Equally, you can create new UI elements with pre-existing atomic elements and store these new UI elements locally in your design file. You don’t have to start from scratch every time. The atomic design system also ensures that you have solid foundational elements in your designs to create reliable and robust designs.

To learn more about creating structured design systems, feel free to contact our team of UI and UX experts. 


Does Fidelity Matter in Simulation-based Learning?

Simulation

One of the earliest renditions of simulation-based learning is credited to Edwin Link. He created the modern flight simulator predecessor between 1929-1931 in response to World War I, where more pilot and plane losses were attributed to accidents rather than combat (Hays & Singer, 1989). Since then, simulation usage and design have progressively improved, with simulation-based practices currently being utilized across several industries with a powerful presence in the military, aviation, and health care industry as a means to conduct training, evaluation, and research. Simulations are defined as “approximations to the reality that require trainees to react to problems or conditions as they would under genuine circumstances” (Tekian, McGuire, & McGaghie, n.d.). Examples of commonly used simulation devices include VR Head Mounted Displays (HMDs), computer-operated life-size medical mannequins, full-motion flight simulators, and various computer-based simulation programs (e.g., driving simulator, industrial processes simulator, machinery operator simulator, etc.). A few of the benefits offered by simulations over traditional learning methods include long-term cost reduction, the experience of alternative conditions and courses of action, provides a realistic job preview, a more effortless transfer of training to the operational environment, provides a practice setting without risk of harm nor negative consequences. It produces a lower carbon footprint (Myers, Starr, & Mullins, 2018).

The Fidelity Question

As technological advancements continue to enhance the capabilities of simulation design, the question of simulation fidelity (the degree to which a simulation device can replicate the actual environment (Gross et al. (1999); Alessi (1988)) and its relationship to learning effectiveness have become a highly debated topic among instructional design and training professionals. Framed as the fidelity question researchers are asking – how similar to the actual task situation must a training situation be to provide practical training? And further, does maximum fidelity equal maximum transfer of training? To answer these questions, we first need to understand the construct of fidelity better.

Simulator-based training is often categorized as either low-fidelity simulations (LFS) or high-fidelity simulations (HFS). In general, high-fidelity refers to simulations that more closely replicate the actual environment or feel more ‘real.’ In contrast, low-fidelity refers to simulations that are typically simpler in design and functionality and may only replicate certain aspects of the environment. It should also be noted that there are no standardized parameters to distinguish low from high fidelity simulation, nor a universal definition of fidelity, as the meaning and definition of each may vary depending on the industry and the designated environment being simulated. This lack of construct validity is one of the main challenges observed in infidelity research.

When considering the best method for measuring simulation fidelity, it would be inaccurate to look at simulation fidelity as a singular variable, as it is by definition the culmination of the experience that occurs when all seven fidelity types merge. As shown in Table 1 below, there are eight distinct definitions of fidelity, including simulation fidelity's combined factor. These fidelity types serve a different function within the simulated environment and should be taken into consideration both as a whole and individually in the calculation of total simulation fidelity.

Table 1: Fidelity Definitions (Hancock et al., 2019)

Fidelity type References Definition
Simulation fidelity Gross et al. (1999); Alessi (1988) The degree to which the device can replicate the actual environment, or how “real” the simulation appears and feels.
Physical fidelity Allen (1986) The degree to which the device looks, sounds, and feels like the actual environment.
Visual-audio fidelity Rinalducci (1996) Replication of visual and auditory stimulus.
Equipment fidelity Zhang (1993) Replication of actual equipment hardware and software.
Motion fidelity Kaiser and Schroeder (2003) Replication of motion cues felt in the actual environment.
Psychological fidelity Kaiser and Schroeder (2003) The degree to which the device replicates psychological and cognitive factors (i.e., communication, situational awareness).
Task fidelity Zhang (1993); Roza (2000); Hughes and Rolek (2003) Replication of tasks and maneuvers executed by the user.
Functional fidelity Allen (1986) How the device functions, works, and provides actual stimuli as the actual environment.

 

Table 1 lists several definitions of fidelity as defined in research. Simulation fidelity provides the fundamental purpose of fidelity in simulation experience, describing how “real” the simulation appears and feels. Meanwhile, the other definitions of fidelity can, for the most part, be broken into two main categories: those that describe the physical experience and those that represent the psychological or cognitive experience (Hancock et al., 2019). The most commonly discussed fidelity category is physical fidelity which encompasses visual-audio fidelity, equipment fidelity, and motion fidelity. These combine to simulate the look, sound, feel, and occasionally smell of the environment. While the second category of psychological-cognitive fidelity goes beyond the look and feel of the simulation to describe the degree to which the user is psychologically and cognitively engaged in the same manner when compared to the degree to which the actual environment would engage the user (examples: simulated stress and workload). The remaining fidelity types of task fidelity and functional fidelity are concerned with how the user interacts with the simulated environment including the degree to which the simulator replicates the tasks of the environment and the degree to which the simulator reacts to performed tasks as they are executed by the user.

Fidelity and Transfer of Training

The main goal of a training simulator is to promote the development of a skill, ability, or area of knowledge that is required for the successful completion of a target task. The effectiveness of the simulator thus depends on the extent to which the acquired knowledge/skills/abilities through practicing the simulated task can be transferred to the target task.

Intuitively, a positive correlation between the degree of realism of a simulator and the effect on transfer of training would be assumed, especially as it is supported by a number of theories including the theory of identical elements (Thorndike, 1913) which states that the most effective transfer of skills occurs between simulator and the operational environment when both share common elements. But, despite this assumption and theory, numerous studies have found no distinct advantage of High Fidelity (HF) compared to Low Fidelity (LF) simulation with regards to improvement of knowledge or skills, with several studies even reporting increased declarative knowledge of participants in the LF simulation groups. These results reveal that there are likely several other important factors that need to be considered in the transfer of simulation-based training apart from simulation fidelity.

One of the models discussed fairly regularly in the articles which failed to prove the high-fidelity advantage was the “Alessi Hypothesis,” which provides several theorized explanations for the failed transfer of training. The first theorized explanation states that there is a certain point at which adding too much fidelity results in negative learning experiences as high fidelity equals high complexity, which requires more cognitive skills thus increasing trainee workload, which in turn impedes participant learning (Alessi, 1988). The second theorized explanation discusses the connection between fidelity and learning describing it as a nonlinear relationship largely dependent on other factors such as the trainees' experience level and stage of instruction. Meaning, to experience optimized training effectiveness, the degree of fidelity in a simulation should attempt to match the level of difficulty expressed by the learning objective as well as the training stage of the learner (Alessi, 1988). Depicted in Figure 1 is Alessi’s model of the relationship between the degree of fidelity and learning for novice, experienced learners, and expert learners.

Figure 1: Degree of fidelity and stage of learner (Alessi, 1988)

This strategy of defining the level of capability and training objectives first followed by the degree of fidelity not only makes practical sense but would also contribute to cost reduction in the overall use of simulation-based education. In another article written on maritime training facilities, they describe their strategy of keeping training costs low while maximizing training effect by employing a similar strategy of utilizing LF simulators in the initial stages of learning to familiarize and train basic skills, while developing HF simulators to train advanced technical and non-technical skills (Renganayagalu, et. al., 2019).

Relevant Theories

Cognitive Load Theory (CLT)

In addition to the model above, a number of developed theories were also discussed in the research, both to explain possible reasons for lack of transfer in HF simulation, as well as to guide future simulation development. One of the most commonly referenced theories in the explanation of the failure to transfer includes the cognitive load theory (CLT), an instructional theory that describes learning and problem solving within the context of how information is processed and addresses the limitations of working memory. While long-term memory has a limitless capacity, working memory is limited to five to nine informational elements at any given time, with many of those elements forgotten within 20 seconds, unless rehearsed or practiced (van Merrienboer & Sweller, 2010). Therefore, if the cognitive load is too high, learning and performance will be affected as the learner is not able to properly process and retain the content being delivered. In the case of high-fidelity simulations which involves completing tasks with a high level of intractability and often through the manipulation of multiple elements at once, increased cognitive load is highly possible, especially in the case of novice learners. To combat this, one study, in particular, held an introductory course covering the fundamental basics of the training to decrease the initial level of cognitive load trainees would experience.

NLN Jeffries Simulation Theory

In addition to the cognitive load theory there was one other theory mentioned throughout the research, but in relation to future recommendations for simulation, development to ensure that transfer of training occurs. This theory known as the NLN Jeffries Simulation Theory (2005, 2007, 2012) is a theoretical framework that has received extensive empirical support and is recommended as a guide in the development of simulated experiences. The framework is composed of seven aspects, beginning with the background and design aspects which should be considered before the simulation experience and define simulation goals and resource allocation, the four aspects involved in the conducting of the simulation experience including the facilitator, the participant, the educational strategies, and the dynamic relationship between each of them, and finally, the aspect which defines the outcomes of the simulation including participant reaction, learning development, and behavioral transfer. As seen in the model below this process is intended to aid instructional designers in the implementation of an effective simulation design, from developing objectives, to evaluating effectiveness.

Figure 2: NLN Jeffries Simulation Theory

Additional Participant Outcomes Related to HFS

Even though the main body of this article is meant to examine the relationship between fidelity and learning effectiveness, through the review of the literature there were several other participant outcomes demonstrated to have a relationship with high-fidelity simulations. These outcomes include heightened levels of participant self-efficacy, stress, and self-confidence in skill deployment.

Increased Self-Efficacy

Increased self-efficacy was one of the most commonly discussed factors in relation to high-fidelity simulations. Perceived self-efficacy concerns an individual’s perception of self-confidence to successfully complete a task (Bandura, 1977) and is believed to be influential on the student’s level of performance, choice of tasks, and the amount of effort put into performing those tasks. Self-efficacy which has been acquired before or during training leads to an increased motivation to learn and better learning outcomes (Salas et al., 2012). One article for example utilized a measure of self-efficacy which was given to participants at the beginning, middle, and end of their designated simulation training, and found that those who participated in the high-fidelity simulation showed statistically significant improvement in self-efficacy following each completion of the survey, as compared to the control group who only showed improvement once during the survey completion. Additionally, another study that examined high-fidelity and self-efficacy in law enforcement officers found that high fidelity increased self-efficacy, emotional arousal, and led to positive training transfer from the lessons learned in the simulator scenarios.

Increased Stress

Another factor observed to be unique to high-fidelity simulations was the increased level of stress experienced by participants as compared to those in low-fidelity simulation. Some of the possible explanations given for this increased stress response included the amplified level of external audio and visual stimuli, as well as the hyper-realistic form factor of the simulated patient who in this specific simulation was bleeding and outwardly experiencing pain. Even though stress from an outside consideration may be considered a negative experience, the authors of this article argued that induced stress during high-fidelity simulation may be beneficial for the participants as they may be able to develop their stress management skills within this simulated environment to be carried over into actual clinical practice.

Increased Self-Confidence

One article, in particular, attempted to assess the level of confidence participants felt in employing skills learned during the simulation-based training, after having found inflated levels of self-confidence in participants of previously conducted studies using high-fidelity simulation. In this article, participants were randomly assigned to two groups of LF and HF simulation during curricular advanced life support (ALS) training courses. Before the course, 69% of participants in the HF group were assumed to have a significant advantage over the LF group in skill development, which did not significantly decrease over the training, with 53% of the participants still reporting assumed advantage at completion. Additionally, 41% of students in the HF group considered themselves better performers in handling resuscitation despite having no knowledge of the LD group's training process. Even though confidence of skill development would typically be considered a positive outcome, in this case, the authors of this article wanted to specifically highlight the dangers associated with overly elevated levels of confidence after the completion of an HFS as there is a positive link between overconfidence and risk-taking behaviors.

Additional Distinctions Between Effective & Non-Effective HFS

Since this article has refuted the notion that high-fidelity alone can predict simulation effectiveness, it may be helpful for future applications to recognize the simulation features, when combined with high-fidelity simulation, to help to produce better results (Issenberg et. al., 2005).

  1. Providing feedback - 47% of journal articles report educational feedback is the most important feature of high-fidelity simulation-based education
  2. Repetitive practice - 39% of journal articles identified repetitive practice as a key feature involving the use of high-fidelity simulations in education
  3. Curriculum integration - 25% of journal articles cited integration of simulation-based exercises into the educational curriculum as an essential feature of their effective use
  4. Range of difficulty level - 14% of journal articles address the importance of the range of task difficulty level as an important variable in simulation-based education
  5. Multiple learning strategies - 10% of journal articles identified the adaptability of high-fidelity simulations to multiple learning strategies as an important factor in their educational effectiveness
  6. Capture clinical variation - 10% of journal articles cited simulators that capture a wide variety of clinical conditions as more useful than those with a narrow range
  7. Controlled environment - 9% of journal articles emphasized the importance of using high-fidelity simulations in a controlled environment where learners can make, detect, and correct errors without adverse consequences
  8. Individualized learning - 9% of journal articles highlighted the importance of having reproducible, standardized educational experiences where learners are active participants, not passive bystanders

At Radiant Digital we have the ability to create training that best meets your organizational needs. Our team of instructional designers and content creators will guide you in creating training that is both engaging and effective, contact us today to learn more.

 

References
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Cognitive theory of multimedia learning (Mayer). Learning Theories. (2020, March 5). Retrieved December 8, 2021, from https://www.learning-theories.com/cognitive-theory-of-multimedia-learning-mayer.html.
Hancock, P. A., Vincenzi, D. A., Wise, J. A., & Mouloua, M. (2019). Human factors in simulation and training. CRC Press.
Hays, R. T., & Singer, M. J. (1989). Simulation fidelity in training system design: Bridging the gap between reality and training. Springer-Verlag Publishing. https://doi.org/10.1007/978-1-4612-3564-4
Issenberg, S. B., McGaghie, W. C., Petrusa, E. R., Lee Gordon, D., & Scalese, R. J. (2005). Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review. Medical teacher, 27(1), 10–28. https://doi.org/10.1080/01421590500046924
Jeffries, P. R., Rodgers, B., & Adamson, K. (2015). NLN Jeffries Simulation Theory: Brief Narrative Description. Nursing education perspectives36(5), 292–293. https://doi.org/10.5480/1536-5026-36.5.292
Makransky, G., Andreasen, N. K., Baceviciute, S., & Mayer, R. E. (2021). Immersive virtual reality increases liking but not learning with a science simulation and generative learning strategies promote learning in immersive virtual reality. Journal of Educational Psychology, 113(4), 719–735. https://doi.org/10.1037/edu0000473
Massoth, C., Röder, H., Ohlenburg, H., Hessler, M., Zarbock, A., Pöpping, D. M., & Wenk, M. (2019). High-fidelity is not superior to low-fidelity simulation but leads to overconfidence in medical students. BMC medical education19(1), 29. https://doi.org/10.1186/s12909-019-1464-7
Myers, P. L., Starr, A. W., & Mullins, K. (2018). Flight simulator fidelity, training transfer, and the role of instructors in optimizing learning. International Journal of Aviation, Aeronautics, and Aerospace, 5(1). https://doi.org/10.15394/ijaaa.2018.1203
Nicolaides, Marios & Theodorou, Efthymia & Emin, Elif & Theodoulou, Iakovos & Andersen, Nikolai & Lymperopoulos, Nikolaos & Odejinmi, Jimi & Kitapcioglu, Dilek & Aksoy, Mehmet & Papalois, Apostolos & Sideris, Michail. (2020). Team performance training for medical students: Low vs high fidelity simulation. Annals of Medicine and Surgery. 55. 10.1016/j.amsu.2020.05.042.
Renganayagalu, Sathiya Kumar & Mallam, Steven & Nazir, Salman & Ernstsen, Jørgen & Hogström, Per. (2019). Impact of Simulation Fidelity on Student Self-efficacy and Perceived Skill Development in Maritime Training. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation. 13. 663-669. 10.12716/1001.13.03.25.
Roza, Z & Gross, D & Harmon, Scott. (2000). Report Out of the Fidelity Experimentation ISG.
Tekian A, McGuire C, McGaghie W. Innovative simulations for assessing professional competence: from paper-and-pencil to virtual reality. Univ of Illinois at Chicago Dept.
van Merriënboer, J. J., & Sweller, J. (2010). Cognitive load theory in health professional education: design principles and strategies. Medical education, 44(1), 85–93. https://doi.org/10.1111/j.1365-2923.2009.03498.x

 


What Motivates Employees to Learn?

How does motivation function in a business environment? And what is the difference between intrinsic and extrinsic motivation? We believe understanding motivation is integral to achieving sustainable business success. There are plenty of theories about motivation, and exploring their reasoning will help us become better leaders and team members. Below we've highlighted how motivation works and how you can use specific types of inspiration to produce better results. 

What is motivation? 

Motivation is an energizing force that directs behavior toward a goal-oriented task or action. Work motivation is a hot topic within the social sciences. Several studies have been done to understand the psychological processes that cause arousal, direction, and desire to complete a work-based task.

There are generally thought to be two types of motivation: Intrinsic & Extrinsic.

Intrinsic Motivation 

Intrinsic motivation is about the experience rather than the results of that experience. It is about doing an activity for its inherent satisfaction. Are you deriving positivity and a feeling of accomplishment from merely undertaking your work tasks? If so, you may have a strong sense of intrinsic motivation. 

Intrinsic motivators include recognition, a sense of belonging, enjoying the challenge, problem-solving, and curiosity. This side of motivation is about internal satisfaction. 

There are several components to intrinsic motivation: 

  • A sense of meaningfulness. Does the purpose or objective of the task matter? Is the result worth your time and energy? 
  • A sense of progress. Are you moving towards your goals? Are you accomplishing something worthwhile? 
  • A sense of choice. Do you have a choice in the activities and tasks you complete? Are you free to use your judgment? 
  • A sense of competence. Do you feel skillful? Are you improving your skills? 

Extrinsic motivation 

In contrast, extrinsic motivation is about doing something for the results and being motivated by the external rewards or encouragement you'll receive by completing the tasks. Extrinsic motivators can include financial rewards, e.g., bonuses, promotions, benefits, salary bumps. However, it can also have non-financial factors such as the type of work, job security, opportunities for career development, or recognition by your organization.

Research shows intrinsic motivation produces better results.

In general, people want more from their jobs than extrinsic compensation. Temporarily the security and excitement that comes with extrinsic motivators like bonuses, competition, and praise may suffice. Still, ultimately intrinsic motivation has been proven to be the more sustainable and effective option.

According to McClelland's 'Need Theory,' intrinsic factors proved to be more influential than extrinsic ones like salary, rewards, and compensations. For example, people want a pleasant work environment, an atmosphere of mutual respect, and to feel like they belong to an organization that aligns with their values and goals. These intrinsic motivators play a vital role in building long-term work relationships and organizational commitment.

Further, according to Self-Determination Theory, individuals are more motivated to complete tasks when they fulfill the basic needs of autonomy, competence, and relatedness. Independence is concerned with the amount of control they have over a job—the more freedom of choice, the higher motivation. Competence involves the feeling of mastery, where motivation is increased through high self-efficacy. Finally, relatedness concerns the sense of interconnectivity, where one is more driven to complete a task when they feel supported and when working toward a larger organizational goal.

Increased motivation leads to increased knowledge retention.

Research shows that when your employees have a high degree of intrinsic motivation, their learning will be more effective, and their knowledge retention will improve. Furthermore, it has been verified through several studies that the relationship observed between intrinsic motivation and knowledge transfer is significant and positive. In contrast, extrinsic motivation has shown little in similar results.

If an individual is intrinsically motivated by a sense of personal curiosity or a willingness to solve practical problems, studies have shown they will find it easier to enhance their skills and knowledge. Intrinsic motivation has been heavily tied to persistent self-directed workers and learners. Intrinsic motivation has also been shown to improve the way teams work together towards a common goal. Employees are more likely to share information, bounce off each other, and develop creative solutions if they have intrinsic solid motivations. 

How to promote intrinsic motivation:

So how can we promote intrinsic motivation? We believe there are four key areas where businesses can implement change:

  • Give employees some control over their learning. Employees want to feel they have a say in education and when/how they complete learning modules. This sense of responsibility and autonomy is essential when promoting intrinsic motivation. Therefore, encourage employees to take control of their learning, offer structured learning paths with suggested self-study options, include interactive elements designed to personalize the learning experience, and create opportunities for individuals to complete tasks and projects aligned with their newly acquired knowledge and skills.
  • Keep employees on their toes. Constantly challenge and provide employees with opportunities for professional growth. When goals being pursued are out of one's comfort zone, they become more meaningful and have a greater associated sense of accomplishment, thus motivating one to follow them more intensely. Challenging learning also promotes increased communication around novel ideas and tasks, leading to career development and increased employee engagement.
  • Offer collaborative and social opportunities. Let employees compete and collaborate in situations where they can learn from each other and help each other overcome challenges. Not only does increased discussion improve learning and help learners persist longer on complex subjects, but healthy competition among employees can push them to achieve their individual goals further.
  • Establish the relevance of training and learning. Show employees how their knowledge and experience can be used in real-world applications. Use simulations or decision-based scenarios to show employees how their knowledge and skills may be applied outside the virtual classroom. This helps to develop an internal sense of meaning and purpose.

At Radiant Digital, we can create personalized training content suited to your employee and company needs. Contact us today to learn more about our service and see how to take your employee learning to the next level.


Why the User Experience Inside the Car is just as Important as Outside the Car

Electric vehicles have been around for a long time. Still, they have experienced somewhat of a renaissance in the last ten years with the emergence of industry-leading companies like TeslaThe number of electric passenger cars used globally increased from close to zero to 10.2 million between 2010 and 2020. Owning an electric vehicle has become more affordable, practical, and fashionable. In electric cars, several topics draw particular attention within the industry. One of the most critical issues for manufacturers, designers, and users is charging stations. In this post, we wanted to highlight how the user experience of EV charging stations has evolved and how it can improve in the future. 

Electric Vehicle Charging Stations 

The history of electric vehicles is longer than most people expect. Since the 1800s, electric cars have been used worldwide, but the 'Charging Station' concept didn't become apparent until the 2010s. Today, EV Charging Stations, otherwise known as Electric Vehicle Charging Stations, are sprouting up everywhere across the U.S. and the world. In the past, you would have had to swap your battery out for a whole new battery for your electric vehicles to run for an extended period. Tesla wanted to break that mold. So they developed the first charging station for electric cars. It works just the same as a gas or petrol station. Drivers pull up to a charging station, pay, and plug in their vehicle. 

Nowadays, with thousands of charging stations across the United States, it's hard to imagine not seeing this simplistic approach to building a network of charging stations. But that wasn't always the case. Tesla had to make the first step and got a headstart on many other electric vehicle companies. This has been reflected in how different companies currently run their charging stations and how many struggles to keep up with Tesla's EV charging station experience. 

Image: Tesla Model S

Emerging Problems 

So what problems are companies experiencing in their attempts to keep up with the established UX of Tesla's charging stations? 

Many companies struggled with identifying users early on and did not know how to manage their user base to hold an RFID card to pay at their stations. This was one of the old pain points of EV charging stations, but plenty of pain points still emerge today. For example, today, many EV charging stations are still excessively loud during the charging process. Additionally, the cable lengths at the charging stations are often inconveniently short, and it can be difficult for users to even plug in their vehicle. 

On top of these problems sometimes even the charging station is broken and it's impossible to charge up your vehicle. Many charging stations also lack weather protection. Although this is not a vital issue, it still dramatically impacts the user experience. There are several problems with EV charging stations, and currently, the charging network in many countries is fractured.  

Tesla dominates the world of EV charging, and in 2020 they will own 7,600 supercharger stations compared to 1,400 owned by ChargePoint in North America. The good news for EV owners is that many proprietary networks like Tesla's charging stations are opening up to all EV owners. This increased accessibility is key to the future of electric vehicles. So, how can companies improve their network and make better use of previously proprietary networks that are now becoming more accessible? 

Solving the Urgent EV User Experience Problems

EV owners' central pain point is finding a place to charge their vehicles. In the past, it's hard to imagine owners not having to worry about where they might charge up. Many car companies have struggled with this dilemma since creating the cars themselves. Tesla has spent time perfecting the user experience of their charging station, and their work has been groundbreaking. A massive benefit for Tesla is that they are a software company more than a car company. This has a significant impact on how their EV charging network is displayed and run. They have a system that is attuned to modern user sensibilities, and they understand how the details of their interface impact their customer's experience. 

Tesla has solved the big user experience problem ("Where can I charge my vehicle?") by allowing drivers to set GPS routes and auto-populate the closest charging stations to help drivers never feel lost when they need to charge up. Furthermore, Tesla also provides users with detailed information on how fast a station charges, how much it costs to charge at a particular station, whether it's out of order or occupied by another car. Finding an EV charging station navigation represents all this necessary and valuable user experience information. Other electric car companies must take a cue from Tesla regarding designing their user experience for EV charging stations. They'll succeed by being open, connected, and informative about what is happening on a station-by-station basis. The EV companies that will endure for years to come will make their charging point experience transparent, interactive, and effective. 

To learn more about creating a first-class user experience, feel free to contact our UX experts here at Radiant Digital.


Dark Mode vs. Light Mode: Which is Better?

We spend a lot of time staring at screens. Our reliance on digital interfaces has increased during the pandemic, and our screen time has also arisen. Half of the respondents to a survey taken earlier this year stated that, on average, they spent five to six hours on their phone daily, not including work-related smartphone use. Today, you now have a choice for how the interface on your phone looks. One of the simplest choices that can significantly impact your user experience is whether to go 'Dark Mode' or 'Light Mode.'

In this post, we've explored the debate between Dark Mode vs. Light Mode.

What is Dark Mode?

In the world user interface, 'Contrast Polarity' describes the contrast between the test and the background on a screen. In this context, 'Positive Contrast Polarity' refers to dark text on a light background (Light Mode). And 'Negative Contrast Polarity' refers to light text on a dark background (Dark Mode). Since digital screens first emerged on the market, devices have flicked back and forth between dark and light modes. For a long time, the light mode was the default on modern smartphones, but the dark way has made a strong resurgence in recent years. Dark mode displays produce less light than light mode displays which may affect both power consumption and how we perceive the information presented to us on the screen. To understand the impact of using dark mode compared to light mode, we must look at how the human eye works.

Sensitivity and visual performance

The pupil is a gateway through which light reaches the eye's retina. The human pupil changes size depending on ambient and direct sunlight in the environment. When there is plenty of sunshine, the pupil contracts, and when it is dark, the pupil dilates to let in more light. These biological elements are something that UI and UX designers and developers have to consider when putting together interfaces. For example, when the pupil is smaller, the eye is less susceptible to aberrations and increases the depth of field. In this context, the eye doesn't have to work as hard, and it is less likely to tire.

However, if the pupil is too small, which sometimes happens as we age, not enough light will enter the eye, and our ability to read the text and perceive images on a screen in low ambient light will be impaired. Equally, as we get older, we often become more susceptible to glare, a frustrating element that is more likely under bright sunlight. Beyond a stylistic desire, the creation of dark mode seems to be an attempt to accommodate a wide variety of sensitivities to light. Even though people with normal vision are well catered for with positive contrast polarity, dark mode is a valuable way to broaden the accessibility options for the user interface.

Dark Mode

Advantages

  • May use less energy than light mode allowing your phone battery to last longer.
  • It can potentially lessen eye strain in low-light conditions.
  • Suitable for low-light conditions, especially when you don't want your phone to be a beacon of light, e.g., in bed or a cinema.
  • Preferably to light mode before you sleep because it emits less 'blue light.'

Disadvantages

  • The dark mode is not always suitable for eye strain, as text is sometimes washed out against a dark background.
  • Less valuable if you are surrounded by bright ambient light

Light Mode

Advantages

  • Many web pages, apps, and interfaces will have been optimized for the standard light mode.
  • If you have standard/normal vision, light visual performance is usually better with light mode.

Disadvantages

  • May drain your battery faster than dark mode, depending on your screen.
  • Not discreet.
  • More likely to keep you awake if used before sleep because of the amount of 'blue light' emitted.

Your choice: Dark Mode vs. Light Mode

Ultimately, visual performance tends to be better with light mode for most people. However, some people with cataracts and related disorders may prefer the visuals provided in a dark mode. The advantages of dark mode over light mode also depend on the type and duration of usage. For most people, the decision will come down to personal preference and habit. Additionally, the overall effectiveness of either mode can be modified, on the iPhone, by switching on Night Shift or by utilizing True Tone. With every new release and new phone, the accessibility options are growing. This is true for Apple, Samsung, and Google regarding hardware and software.

To learn more about digital interfaces and visual performance, feel free to reach out to our UX experts.