Developing Soft Skills in eLearning
Where should you direct your efforts if you’re trying to improve your business? Should you focus on hard skills or soft skills? It is best to have a healthy balance between the two. Still, in recent years businesses have begun to realize the true value soft skill improvement can deliver to their organizational success. In this article, we’ll be highlighting the difference between soft skills and hard skills, examining successful cases of soft skill development in eLearning formats, and finally providing recommendations for creating successful soft skills eLearning training.
Hard Skills vs. Soft Skills
So what’s the difference between hard skills and soft skills? Let’s take a look.
Hard Skills
Hard skills are job-specific abilities that you need to have to fulfill your day-to-day responsibilities. Hard skills, also known as technical skills, will differ significantly depending on the job position. For example, a retail worker will use customer-focused hard skills far more than someone who works in manufacturing and spends their time dealing with complex technical tasks.
Examples of hard skills include:
- Bookkeeping
- Accounting
- Operating and repairing equipment
- Analytics
- Developing and programming (CSS, Python, Java, HTML)
Soft Skills
Soft skills are the non-technical skills and abilities that can help you function in a specific work environment. There are a variety of soft skills such as communication skills, cognitive skills, problem-solving, teamwork, and work ethic. Any individual can display a combination of these soft skills, and they can be learned and nurtured in all walks of life.
According to leading psychologist Daniel Goleman (1998), soft skills are a combination of competencies that relate to how we know and manage ourselves and our relationships with others. It’s about how we think and interact with those around us. Some categorize soft skills into three main components: Personal Qualities, Thinking Skills, and Interpersonal Skills.
The US Department of Labor even provides definitions of these three components. The skills relating to Personal Qualities have to do with responsibility, self-esteem, sociability, self-management, and integrity. Equally, they note that Thinking Skills include creative thinking, decision making, problem-solving, knowing how to learn, and reasoning. Their definition of Interpersonal Skills concerns how individuals participate as a member of a team, how they teach others, serve customers, exercise leadership, negotiate and work with diversity.
The importance of developing soft skills
Not only are soft skills important in one’s day-to-day interactions, but they have also been proven to be found to be highly relevant in the business space. Developing soft skills also seems to be a top priority for many employees today, with 1 in 3 Americans believing soft skills to be the most important skills in the current job market.
In a national survey of 2,574 American adults aged 18 and older, 41% reported using soft skills frequently in their current or most recent jobs. In contrast, only 11% use hard skills (coding, technical knowledge, and lab skills) most frequently. These statistics support the idea that soft skills are integral to success at most jobs today, and it is worth investing more into growing a diverse set of soft skills within your employee base.
Teaching hard skills vs. soft skills in eLearning
Both hard and soft skills have plenty of potentials to improve eLearning processes. So, what are the advantages of investing in soft skills in eLearning specifically?
Advantages of soft skills in eLearning
Electronic learning (eLearning) is defined as education or training initiatives that take place anytime a learner uses electronic means to gather information acquired without an instructor's physical presence on location (Gustafson, 2002; Swan, 2003). E-learning is growing rapidly and can help significantly reduce a company’s training time and cost.
By teaching soft skills via eLearning, you can improve your employees’ communication, problem-solving, and teamwork skills at a lower cost and in a way that is more easily assessed. Additionally, employees also benefit from utilizing trial and error exercises which enable the learner to try multiple responses to a single situation, improving critical thinking and promoting retention. In the development of soft skills, repetition is key to developing better behavioral habits; thus, readily available eLearning may be a better option than the traditional one and done in-person training method.
The challenge: How can you measure if skills are being obtained?
Hard Skills are more accessible to track than soft skills in any format because they are qualitative. Assessing these skills can be as simple as a yes or no question. Do you know this specific programming language? Can you operate this type of machine? You can easily measure the hard skill competencies of your employees and how they are developing over time.
Soft Skills are a bit trickier to measure. How do you know whether an employee has the right behavioral or communication skills to execute their responsibilities effectively? Measuring the results of soft skills training delivered via e-Learning is no easier than measuring soft skills training given any other way. However, when eLearning is used, it provides unique tracking metrics such as scoring simulations and knowledge checks, tracking the amount of time spent on a particular subject, the number of attempts made to reach the correct answer, and overall how often employees are accessing these soft skills training, with the more significant the repetition, the greater the chance of soft skill development.
Examples of soft skill success in eLearning training
Even though eLearning is still a developing field, there have been many studies in the past which have attempted to capture and document the ability of eLearning to develop soft skills.
- Situational Leadership II
Through a CD-based course called “Situational Leadership II,” the Navy successfully offered soft-skills training in employee coaching, management, and development to several thousand chief petty officers. A study was conducted to measure the effectiveness of the course, and it found that the officers who took the online leadership course increased their leadership understanding by 44%.
In further follow-up conversations with those who undertook the training, many officers said the course helped improve their abilities in mentoring, career advancement, and on-the-job training.
- Business simulation course
In a similar study, students enrolled in a business simulation course at a university or business school on French campuses (Paris, Lille, Nice) and abroad (Morocco). Each group participated in an immersive business game addressing all aspects of business organizations. Even though the simulation only lasted three days (six half-days), all 11 of the soft skills that were measured increased. The most significant improvements were noted for ‘Ability to express orally,’ ‘Ability to manage a project, and ‘Ability to manage the environment.
Recommended strategies to employ when training soft skills
Even though eLearning, in general, provides a better avenue for soft skill development, specific techniques can be put into place to ensure learning and retention occurs.
1. Create manageable and digestible learning
It isn't easy to develop soft skills overnight. To give your employees the best chance of success, create manageable, bite-size eLearning segments that allow digestible and sustainable learning.
2. Promote learning through observation
Video is one of the best eLearning formats to help employees expand their repertoire of soft skills. Through video, learners can observe soft skills in real-life scenarios and quickly translate them into everyday work life.
3. Utilize innovative and engaging formats
eLearning allows employees to engage in simulated scenarios to put them to the test with interesting exercises and deliver tangible results. Today, simulated systems are more sophisticated than ever, thanks to virtual reality, gamification, and other online formats.
4. Make it measurable
As we’ve mentioned, it can be pretty difficult to measure soft skill progression, especially when compared to hard skills. So it is important to try and make your learning process as measurable as possible. Ensure that the training is centered on reaching a set of attainable goals tied to key performance indicators such as reduction in customer complaints, increases in positive feedback, reduction in staff turnover, etc. While anecdotal evidence, observation of performance, and surveys of participants have value, measuring key performance indicators has more weight. They enable you to see which soft skills are being applied to the job and whether the training enhances job performance.
At Radiant Digital, we create eLearning modules to reach set goals. To learn more about how you can develop soft and hard skills through eLearning, feel free to get in contact with our experts.
Should Learning Styles be Considered in the Training Process?
Fixed vs. Fluid Learning Styles
In the understanding of how people learn, there has been a longstanding discussion on whether or not individualized learning styles exist and if they have any influence on a learner’s retention of knowledge. Sarasin (1999) defines learning styles as “The preference or predisposition of an individual to perceive and process information in a particular way or combination of ways.” While many scholars do agree that individuals all learn and process information differently, many do not believe in the commonly discussed VARK model proposed by Neil Fleming (shown below), which divides learners into four primary learning styles, including visual (learning through graphs, charts, diagrams), aural (learning through discussions, guest speakers, recordings), read/write (learning through lists, notes, and text), and kinesthetic (learning through practical exercises, trial, and error, case studies). This model falls under the presumption that learning styles are fixed. In addition to lacking scientific evidence and research, this theory places unnecessary labels and limitations on how an individual should learn.
Instead, a more fluid model of learning styles is more readily accepted, which states that there are many other approaches to learning than the traditional four and that preferred learning styles change over time and depend on the context of the knowledge and task. The fluid viewpoint of learning styles proposes that there are several factors to consider when creating and presenting content, with learning styles being just another component of that. Proponents of the fluid model of learning styles assert that learning styles are less about restricting learning. Instead, they should be used as tools for the learner to know and understand their style of education, which gives them the power to achieve effective learning and knowledge acquisition. In research on the impact of understanding one’s learning styles on academic progress, the author found that “when students understand how they learn best, they inevitably adjust conditions and devise strategies for facilitating their progress” (Dunn et al., 2009). There are several other learning style theories that have attempted to expand upon the earlier VAK and VARK model such as David Kolb’s model, which focuses on experiential learning and the learning process, Peter Honey and Alan Mumford’s model, which stages learning cycles according to the learner’s experience level, and Anthony Gregorc’s model based on concrete vs. abstract and logical vs. non-ordered information. Each of these takes a more fluid stance on learning, basing the styles upon each individual’s background knowledge, the complexity of the context, and other outside factors which are flexible to the situation and individual.
Applying Learning Styles to Adult Learning
One learner category where learning style consideration may be most pertinent is adult learners' teaching. Adults, in particular, learn differently from younger learners because they come into the learning environment with previous work and life experiences before academic knowledge and often prefer the ability to take control of their learning progression. According to the principles of adult learning developed by Malcolm Knowles (1980), adult learners are self-guided, draw upon past experiences, have an increased readiness to learn, more often transition teaching into practice, and are internally motivated to learn. Since adult learners are particularly self-guided and provide unique vantages for each learning opportunity, making each adult learner aware of their learning preferences dependent on the context and situation can help them to adapt better and facilitate their learning process. Making learners more aware of their learning styles, the impact that knowledge can have on learning, and how to make the best of this knowledge can be many ways educators assist the evolution of more reflective, motivated, satisfied, self-directed adult learners.
Considering Content
Although learning styles and understanding them may give insight into each individual's preference for consuming information, this does not directly relate to a learner’s effectiveness in knowing and retaining content. Thus, the best format for presenting content has less to do with learning preferences and more to do with the substance of the content, learners’ existing knowledge, and the circumstances under which learners will consume and use the information.
One factor that instructional designers must consider is how different learning or teaching approaches lend themselves to other content. For example, an extensive infographic job aid illustrating a complex procedure containing numerous steps may not be the best tool to utilize when teaching an employee who has never seen or done the process themselves. Instead, a video demonstration or hands-on approach would be more effective in teaching said content, followed by visual aids to support said learning as a reminder to remember critical steps.
Similarly, one must consider the complexity and type of content and the prior knowledge level of each learner. For example, a brief safety presentation may not be sufficient to teach new employees how to operate machinery properly because they have no prior information regarding the equipment in the discussion. Whereas for a senior employee, a refresher video that discusses the essential safety points would most likely suffice.
Although learning styles should not be the sole basis upon which content is developed, they can provide an excellent understanding of how they prefer to learn and strategize to achieve their learning goals. Aside from the knowledge of each person’s learning styles, instructional designers separately should take into consideration the different forms of learning techniques and how each one relates to other content areas and levels of understanding to ensure that not only is content understood, but that it will be retained and utilized long term.
At Radiant Digital, our team of instructional designers understands the importance of curating individualized plans for achieving learning goals. Each learning module is designed to best support the content being delivered and the type of learner being taught.
Citations:
Dunn, R., Honigsfeld, A., & Doolan, L. (2009). Impact of learning-style instructional strategies on students' achievement and attitudes: Perceptions of educators in diverse institutions. The clearinghouse, 82(3), 1.
Sarasin, L.C. (1999). Learning Style Perspectives: Impact in the Classroom.
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.
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).
- Providing feedback - 47% of journal articles report educational feedback is the most important feature of high-fidelity simulation-based education
- Repetitive practice - 39% of journal articles identified repetitive practice as a key feature involving the use of high-fidelity simulations in education
- Curriculum integration - 25% of journal articles cited integration of simulation-based exercises into the educational curriculum as an essential feature of their effective use
- 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
- 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
- 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
- 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
- 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
Alessi, S. M. (1988). Fidelity in the design of instructional simulations. Journal of Computer-Based Instruction, 15(2), 40–47.
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 perspectives, 36(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 education, 19(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.
How to make your investment in Training and Development worth it
In 2020, an estimated 82.5 billion U.S. dollars were spent on training across the United States (Statista, 2020). Organizations today are spending more on training than they ever have in the past, as the numerous benefits provided by investing in employee training and development opportunities continue to be recognized. Yet the question remains, how much of that training being developed is genuinely translating into noticeable positive differences in employee performance?
According to the research, probably not enough. Arthur, Bennett, Stanush, and McNelly (1998) conducted a meta-analysis of skill decay studies. He reported that trainees exhibit little to no skill decay the day after, but after 1-year trainees have lost over 90% of what they learned. It's being experienced that a lack of training transfer is estimated by the level of correlation between learning scores (in training) and performance metrics (on the job). The transfer is critical because without it an organization is less likely to receive any tangible benefits from its training investments.
In the traditional sense of the word, training is most often characterized by a one-off format of instruction typically involving a classroom setting where a facilitator guides the learner through the information designated explicitly for that training session. The problem with this format is that there is no guarantee that anything taught will be retained (and applied) by the employees in attendance after the training finishes. This situation is one of the key reasons why training may not pay off, as it is not so much about the learner's abilities to retain information, but rather about the content being delivered, the method being used for delivery, and the lack of follow up within the current processes. The popular colloquialism "use it or lose it" especially holds in this situation, for one particular training session cannot be relied upon to produce noticeable and lasting results. So, what should organizations be doing differently when it comes to training their employees if they want to see an actual return on their investment? The answer is providing ongoing training opportunities instead.
The graphic below based on the Continuous Learning Model shows that even though traditional training does initially provide some level of understanding, retained knowledge will steadily decrease over time. Meanwhile, learning remains constant if there are available eLearning courses, mobile education suited for easy access, designated time to speak with supervisors about career/skill development, communities built around learning, and opportunities to interact and learn alongside peers. This continuous model of learning, which promotes an ongoing relationship between the organization and the learner, is the solution needed to ensure that the time and money that goes into training is returned through increased employee skill and performance.
After learning how beneficial ongoing training can be compared to the traditional one-off method for retention and performance, what can companies do to move toward an organizational learning culture characterized by promoting continuous learning?
Adopt a companywide strategy of continuous learning
First things first, to have a thriving learning culture, the organization involved must actively promote the idea of learning and training to its employees. Doing so becomes natural and habitual for employees to explore developmental options, the norm rather than the exception. Research has shown that a supportive organizational culture for newly acquired Knowledge, Skills, and Abilities (KSA's) results in trainees applying training more effectively on the job (Rouiller & Goldstein, 1993; Tracey et al., 1995). The more leaders indicate that training is essential to the organization, the better the outcomes of training.
Choose the right tool and method for training
When developing a culture of ongoing training and learning, you must be realistic with your employee's time. Requesting all employees to sit through numerous classroom training on top of their busy and fluctuating schedules may not be the most feasible option. Instead, start taking advantage of what online learning platforms offer, including ease of use, learner autonomy, instant feedback, tracking, etc. This is not to say traditional training is never the way to go, as some training may be best suited for an in-person format but considering all of your available training options should be one of the first steps in implementing continuous learning.
Get leadership involved
Culture starts from the top and trickles down, so management needs to communicate their support for continuous learning activities and participation. The reward of promoting ongoing training is that training no longer fits into one box (such as training new employees); it can now be focused on what is essential to the development of each individual at each level, including management.
Reward learners
It may be beneficial, especially in the early stages of developing continuous training, to make the experience valuable, fun, and engaging in promoting adoption. There are many ways organizations can motivate self-directed learning, such as introducing gamification components into the learning environment. Consider awarding badges based on the completion of a task or learning activity. Use points to mark achievements and progress where learners can move through different levels based on the number of courses completed or events attended. Do something that conveys to your employees that learning is a top priority within the organization.
Provide autonomous options
Developing a continuous learning environment may seem challenging and time-consuming when starting. But promoting ongoing learning opportunities does not have to be managed on the organizational side solely. Some systems can easily be put into a portal containing job aids and knowledge repositories or databases that track learned and automatically recommend supplemental training. It is also possible to set up employee-led programs by establishing "communities of practice" where individuals of similar interests and job knowledge can interact virtually or in-person to answer questions and discuss challenging situations. Training is not always about knowing what was learned but should also prepare learners to understand where (and whom) they can go for help in the future.
Track and analyze results
Finally, track and analyze the results of any implemented training programs. By doing so, you can figure out what is working and what isn't. A massive downfall of the traditional training method is there is usually no follow-up or effort to track what was learned. And so, by actively working to do so, retention is no longer a guessing game but rather a thought-out and practiced methodology.
Here at Radiant Digital, we specialize in providing learning solutions to suit your organization's needs. We can help you develop training opportunities and implement change management strategies to promote a successful transition to a learning culture. Reach out to us today to see how we can help.
Citation:
Arthur, W., Jr., Bennett, W., Jr., Stanush, P. L., & McNelly, T. L. (1998). Factors that influence skill decay and retention: A quantitative review and analysis. Human Performance, 11(1), 57–101. https://doi.org/10.1207/s15327043hup1101_3
Salas, E., Tannenbaum, S. I., Kraiger, K., & Smith-Jentsch, K. A. (2012). The science of training and development in organizations: What matters in practice. Psychological science in the public interest, 13(2), 74–101. http://www.jstor.org/stable/23484697.
Statista Research Department (2020, December 15). U.S. Training Industry Expenditure 2020. Statista. Retrieved September 27, 2021, from https://www.statista.com/statistics/788521/training-expenditures-united-states/.
Going Beyond the Kirkpatrick Model: Rethinking Your Training Evaluation Strategy
Measuring training effectiveness is one of the many responsibilities for learning and development professionals and one of the many priorities for senior leadership in workplaces. According to Statista Research Department, every year, U.S businesses collectively invest more than $80 billion on training their employees, and global spending on training and development has increased by 400% in 11 years. This investment cost emphasizes the importance of measuring training effectiveness and business impact. Also, as organizations provide more training offerings to upskill and reskill their employees, learning, and development professionals are hungry for guidance on creating and demonstrating the value of training to their organizations. The Kirkpatrick model is no secret to effectively evaluating training programs; however, most professionals get stuck in implementing the model's levels 3 (behavior) and 4 (results). Thus, it is no wonder that learning and development professionals seek other methods or creative strategies to evaluate the success of training programs. This article will explore effective evaluation strategies in achieving levels 3 and 4 of the Kirkpatrick Model and discuss Brinkerhoff's Success Case Method as an alternative approach to evaluating training. Depending on your evaluation goals, one or more of these solutions could provide structure in evaluating training at your organization.
Learning and development professionals have embraced the Kirkpatrick model and continue to adopt it as the standard approach for evaluating training programs. The evaluation model dates back to 1959 when published in the Journal of the American Society of Training Directors that outlines techniques for evaluating training according to four levels of evaluation. The model's primary strength is that it is easy to understand and implement as the evaluation only includes four levels: reaction, learning, behavior, and results.
Kirkpatrick Model
Level 1
Level 1 evaluations (reaction) measure participants' overall response to the training program. This includes asking participants how good, engaging, and relevant the training content is to their jobs. Level 1 is considered simple and is typically achieved by implementing a formative evaluation in a survey immediately following training.
Level 2
Level 2 evaluations (learning) measure the increase in participants' knowledge due to the instruction during training. In level 2, it is common to assess learning using knowledge checks, discussion questions, role-play, simulations, and focus group interviews.
Level 3
Level 3 (behavior) aims to measure participants' on-the-job changes in behavior due to the instruction. This is essential because training alone will not yield enough organizational results to be viewed as successful. However, this level is also considered somewhat difficult to evaluate as it requires measurement of knowledge transfer (hyperlink previous article on knowledge transfer).
Level 4
Then lastly, there is Level 4 (results). Level 4 is the reason training is performed. Training's job is not complete until its contributions to business results can be demonstrated and acknowledged by stakeholders. Again, the majority of learning professionals struggle connecting training to performance and results for critical learning programs. When talking with other learning development professionals, the standard response to the difficulty in demonstrating learning results is the time required to measure and decide on a practical approach to capturing key performance indicators. Level 3 and 4 truly is the missing link in moving from learning to results so, what can organizations do to measure the impact of training behavior and the results.
Measuring Level 4 (Results) Strategies
One strategy organizations can implement in achieving desired results from training programs is to create leading indicators. Leading indicators provide personalized targets that all contribute to organizational outcomes. Consider leading indicators as little flags marching toward the finish line, which represents the desired corporate results. They also establish a connection between the performance of critical behaviors and the organization's highest-level impact. There are two distinct types of leading indicators, internal and external, which provide quantitative and qualitative data. Internal leading indicators arise from within the organization and are typically the first to appear. Internal leading indicators relate to production output, quality, sales, cost, safety, employee retention, or other critical outcomes for your department, group, or programs that contribute to Level 4 results. In addition to internal leading factors, external leading factors can be identified in measuring the success of a training program. For example, external leading factors relate to customer response, retention, and industry standards.
The benefit of identifying and leveraging leading indicators is they help keep your initiatives on track by serving as the last line of defense against possible failure at Level 4. In addition, monitoring leading indicators along the way give you time to identify barriers to success and apply the proper interventions before ultimate outcomes are jeopardized. Finally, leading indicators provide important data connecting training, on-the-job performance, and the highest-level result. The first step in evaluating leading indicators is to define which data you can borrow and which information you will build the tools to gather. For example, human resource metrics may already exist and can be linked to the training program/ initiative. If the data is not already available within the organization, it is crucial to define what tools to build to gather the data. Typical examples of tools that may need to be made are surveys and a structured question set for interviews and focus groups.
Alternative Approach to Kirkpatrick Model
Alternative to using the Kirkpatrick model in measuring training success, the Success Case Method (SCM) by Robert Brinkerhoff has gained much adoption across several industries. This method involves identifying the most and least successful individuals who participated in the training event. Once these individuals are identified, interviews and other ways, such as observation, can be conducted to understand the training's effects better. In comparison, the Kirkpatrick model seeks to uncover a program's results, while the SCM wants to discover how the program affected the most successful participants. One weakness of this model is that only small sample size (successful participants) is asked to provide feedback on the training program, which may omit valuable information and data that could have been collected if all participants were included in giving feedback. This evaluation method may be more beneficial for programs that aim to understand how participants are using the training content on the job, which may result in more qualitative data than quantitative metrics. Both evaluations have benefits and disadvantages in measuring training effectiveness, so the key is selecting the best approach for your training program or perhaps combing these two approaches.
Here at Radiant Digital, we enjoy collaborating with organizations in developing training effectiveness strategies. Partner with us and learn how we can support your learning development team.
The Influence of Training and Development Opportunities on Employee Retention
In the continuously changing workspace, recruiting and retaining top employees is more crucial than ever. According to the Bureau of Labor Statistics 2020 Job Openings and Labor Turnover Survey (JOLTS), the overall voluntary turnover rate from December 2019 to December 2020 was 19.9%. This rate has steadily increased over the last decade. As the turnover rate increases, the cost of employee turnover also reaches new heights. The Work Institute's 2017 Retention Report states that turnover can cost employers an average of 33% of an employee's annual salary due to recruiting, interviewing, onboarding, and initial training costs (Sears, 2017).
How are companies supposed to recruit the right personnel, and then what do companies need to encourage recruits to be long-term employees? The clear answer is increasing training and development opportunities for employees to decrease turnover intentions. According to the EXECU Search Group report from 2019, 86% of professionals said they would change jobs if offered more professional development opportunities. Also, the top reported reason employees gave for leaving their position was lack of career development opportunities, as shown in the graphic below from the Work Institute's 2017 Retention Report. This reason is nearly double the second most reported reason, lack of work-life balance.
Similar to turnover intentions, 43% of the variance in organization commitment can be explained by an organizational learning culture (Joo, 2010). When organizations offer growth and developmental opportunities, such as training and further education, employees feel their employment is valued, that their current and future abilities are trusted, and that the company wants to continue their development (Mustafa & Ali, 2019). This can be further explained through the basis of social exchange theory (Blau, 1964) which says when employees feel their organizations value them as essential resources and care about their professional and long-term development, they are more likely to be engaged and diligently work for the organization to fulfill the reciprocal relationship exchange (Raza, Ali, Naseem, Moeed, Ahmed, & Hamid, 2018).
Studies are ongoing concerning the availability of learning and development opportunities for employees and their influence on different workplace outcomes, including organizational commitment, well-being, employee engagement, job satisfaction, role performance, and turnover intentions. The following sections provide current research and statistics relating to the learning opportunities studies.
Employee Emotional Exhaustion
Emotional exhaustion is a chronic state of fatigue characterized by physical and mental depletion due to workplace demands and stressors. Related turnover intentions are the deliberate and conscious effort to leave an organization for other opportunities or personal/professional concerns (Raza et al., 2018). According to Proost, Ruysseveldt, and Dijke, learning opportunities positively affect knowledge and skill acquisition and provide opportunities for "skill utilization, job enhancement, and professional growth" (2012). In addition, these opportunities help employees realize their goals and "adequately manage the physiological and psychological demands they encounter in their jobs" (2012), which decreases emotional exhaustion and related turnover intentions.
Employee Expectations
Increasing learning opportunities also help reduce early-stage turnover due to unmet expectations about one's position. For example, the 2012 Proost, Ruysseveldt, and Dijke study report the relationship between unmet expectations and turnover intentions are stronger when learning opportunities are low (b = .21) (i.e., one standard deviation below the mean) and weaker when learning opportunities are high (b = .08) (i.e., one standard deviation above the norm). This clearly shows how increasing learning opportunities can decrease turnover intentions.
Employee Engagement
Learning opportunities can reduce negative workplace tendencies and increase employee performance/engagement and extra-role behaviors. Employee engagement is the state of mind held by positive and encouraged employees characterized by vigor, enthusiasm, dedication, and absorption (Eldor & Harpaz, 2016). Extra-role behaviors define exceptional employees—proactivity, knowledge sharing, creativity, and adaptivity (Eldor & Harpaz, 2016). In one study, 625 employees were surveyed on employee engagement, extra-role performance, job satisfaction, and perceived level of learning. The study found that the relationship between perceived learning climate and employee engagement was strong, positive, and significant (r = 0.52, p≤0.001), as were the relationships between employee engagement and all four performance variables: proactivity (r = 0.35, p≤0.001), knowledge sharing (r = 0.38, p≤0.001), creativity (r = 0.49, p≤0.001), and adaptivity (r = 0.44. p≤0.001) (Eldor & Harpaz, 2016). This data reveals that organizations promoting learning opportunities reduce turnover and increase employee engagement and performance—these benefit employee satisfaction with their position and the organization.
Job Satisfaction
Finally, learning opportunities show one of the most potent effects on overall employee job satisfaction. Job satisfaction is one of the critical determinants of turnover intentions. It can be described as the perception of one's job expectancies and job reality and whether those expectancies are being met. Research shows that employees who feel more satisfied within their position and organization are more likely to become engaged employees and display lower turnover intentions (Lin & Huang, 2020). In addition, organizations that prioritize learning and development found increased employee job satisfaction, productivity, and profitability (Egan, Yang, & Barlett, 2004). Several studies on this topic show conclusive results. One study tested different forms of learning against employee satisfaction and employee turnover intentions and found that all types of learning (individual learning (γ=0.41, p<0.001), collective learning (γ=0.42, p<0.05), organization-level understanding (γ=0.40, p<0.01), inter-organizational learning (γ=0.45, p<0.01), and exploration learning (γ=0.44, p<0.01)) correlated positively and significantly to employee satisfaction and correlated negatively and significantly to turnover intentions. This shows that learning opportunities, in any form, are highly valued by employees regarding job satisfaction and can reduce an employee's turnover intentions.
Desired Learning Opportunities
These studies show that learning and development opportunities should not be underestimated in the scope of organizational success, both in reducing turnover and the increase of positive employee behaviors. Beyond understanding that employees desire training and learning opportunities from their organizations, it is imperative to understand what topics they want. PayScale's 2019 Compensation Best Practices Report surveyed 38,000 respondents who were asked to indicate which professional development opportunities they enjoyed the most from their organization. Shown in the graphic below are the top seven categories of training and development from the survey. The principal learning opportunity wanted to be selected by 32% of respondents in management/leadership training. A close second, chosen by 30% of respondents, is professional certification. Additional training included in the top seven are technical skills (17%), teamwork and interpersonal skills (8%), employer-subsidized degree (7%), communications/public speaking (4%), and diversity and inclusion (2%).
Conclusion
Radiant Digital specializes in custom content creation to suit your unique organizational needs and to learn objectives if you're looking to increase your organization's learning and development opportunities. It can be hard to know exactly where to start when creating a learning-focused culture. Radiant can assist you in the design, development, and implementation of learning programs so you can achieve your highest organizational goals. Reach out to us today to see how we can help.
Citations
2019 Compensation Best Practices Report. PayScale. (n.d.). Retrieved from https://www.payscale.com/data/professional-development-employees-want.
Bureau of Labor Statistics, U.S. Department of Labor (2020). 2020 Job Openings and Labor Turnover Survey. Received from https://www.bls.gov/opub/mlr/2021/article/as-the-covid-19-pandemic-affects-the-nation-hires-and-turnover-reach-record-highs-in-2020.htm
Egan, T., Yang, B., & Bartlett, K. (2004). The effects of organizational learning culture and job satisfaction on motivation to transfer learning and turnover intention. Human Resource Development Quarterly, 15, 279-301.
Joo, B. (2010). Organizational commitment for knowledge workers: The roles of perceived organizational learning culture, leader-member exchange quality, and turnover intention. Human Resource Development Quarterly, 21. 69 - 85. 10.1002/hrdq.20031.
Lin, C. Y., & Huang, C. K. (2020). Employee turnover intentions and job performance from a planned change: The effects of an organizational learning culture and job satisfaction. International Journal of Manpower, 42. 409-423. 10.1108/IJM-08-2018-0281.
Mustafa, G., & Ali, N. (2019) Rewards, autonomous motivation, and turnover intention: Results from a non-Western cultural context, Cogent Business & Management, 6:1, 1676090, DOI: 10.1080/23311975.2019.1676090.
Proost, K., Ruysseveldt, J.,& Dijke, M. (2012) Coping with unmet expectations: Learning opportunities as a buffer against emotional exhaustion and turnover intentions, European Journal of Work and Organizational Psychology, 21:1, 7-27, DOI: 10.1080/1359432X.2010.526304.
Raza, B., Ali, M., Naseem, K., Moeed, A., Ahmed J., & Hamid M. (2018) Impact of trait mindfulness on job satisfaction and turnover intentions: Mediating role of work–family balance and moderating role of work–family conflict, Cogent Business & Management, 5:1, DOI: 10.1080/23311975.2018.1542943.
Sears, L. (2017) 2017 Retention Report. Received from https://cdn2.hubspot.net/hubfs/478187/2017%20Retention%20Report%20Campaign/Work%20Institute%202017%20-Retention%20Report.pdf
The employee experience will be critical to business success in 2019, according to New Hiring Outlook report by the EXECU: Search group. PR Newswire. (2019). Received from https://www.prnewswire.com/news-releases/the-employee-experience-will-be-critical-to-business-success-in-2019-according-to-new-hiring-outlook-report-by-the-execusearch-group-300773946.html.
Yu, H., Fang, L., & Ling, W. (2009) An empirical study on the construct and effective mechanism of organizational learning. Frontiers of Business Research in China, 3, 242–270. https://doi.org/10.1007/s11782-009-0013-3