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Training design may not be as important as impacting an employee’s perception of the training. Many might wonder whether the effectiveness of training occurs because of some placebo effect (positive expectation) or nocebo effect (negative expectation) or if the training legitimately does what it was designed to do. The expectancy theory posits that individuals are motivated by their expectations of an outcome and the amount of effort it takes to accomplish that outcome (Muchinsky, 2012). This theory may provide a solution for organizations who want a simple training methodology that is backed by well-researched data. This theory could demonstrate that the content of training may not be as important as the employees’ expectations. While expectancy theory represents one method of motivating and training employees—and is by no means the only method—it may be the foot in the door that organizations need to get their employees moving in the right direction. It could run ancillary to any training program an organization chooses.


The Problem


Many trainers are ill-equipped to handle training analysis and design, but with help from trained professionals, they could still accomplish their goals. Industrial and organizational (I/O) psychologists might provide valuable insights to trainers. These professionals could help organizations sift through mountains of information to find well-researched data to support their training initiatives, or they could help trainers design programs that are good enough and are perceived as valuable by employees.


The Questions


The unknowns are whether expectancy theory can improve an organizations training programs and if I/O psychologists can contribute to the success of an organization in this area. It might be best to begin answering these questions by looking at the challenges organizations face when it comes to motivation and training. Additionally, one should give a homogenous view to the origins of expectancy theory and its place in the world of training. Factors like age, relationships, and perceptions about training might also impact its effectiveness.


Literature Review


The degree in which the knowledge that was shared in training leads to improved job performance is known as learning transfer (Jayakumar & Sulthan, 2014). This is a primary step to the success of any training program. Without transfer, nothing will change. To test this concept, Jayakumar and Sulthan used a census survey with 475 participants to determine employee perceptions on training. The results showed that for training to be effective it needs to help employees develop skills, it must transfer knowledge, and it needs to provide a method for ongoing support (Jayakumar & Sulthan, 2014). The results of this study yielded a high Cronbach alpha, which indicates that the results were very reliable, or in other words, consistent. Additionally, the results were valid when accounting for inter correlation, meaning that the survey measured what it was supposed to measure and that skills, knowledge transfer, and support were prevalent throughout the study.


Relevance and Effectiveness


Muchinsky (2012) claims that transfer is facilitated by an individual’s motivation to sustain a new behavior. Renta-Davids, Jiménez-González, Fandos-Garrido, and González-Soto (2014) found through 447 self-reported surveys given at two distinct intervals that transfer can only occur when training is relevant and effective. A step-by-step regression analysis and Cronbach’s alpha indicate these results to be both reliable and valid. The reason this analysis method is important is because it can test different variables to determine which ones had a mediating effect on transfer of learning (Renta-Daivids et al., 2014). Renta-Davids et al. found that the more relevant and effective the training is, the more transfer occurred. In other words, it does not help to train employees on information or processes they will not use.


Age


Age can also impact training effectiveness. Zwick (2015) suggests that older employees are expected to perform at the same levels as their younger peers. However, many older employees do not have the same goals as younger employees. When it comes to career development, earnings, flexibility, adoption of new skills, and job security, older employees may not take an interest (Zwick, 2015). It may be best to design training to accommodate employees at every level in the organization.


Participation


Training is no good without participation; both from managers and employees. Jayakumar and Sulthan (2014) demonstrate in their research that an employee’s perception of the training can impact whether he or she participates. Perception is not the only variable that affects participation. If managers do not see training as valuable, their employees are likely to see the training in a similar light (Franca & Pahor, 2012). Unfortunately, when this occurs, participation suffers. Leaders carry a strong influence over their peers. If employees believe they have a good relationship with their managers, that their job is secure, and if they know their leader’s expectations, this will influence whether an employee participates in training (Afsar, Shahjehan, & Rehman, 2010). More importantly, the leader/employee relationship affects transfer (the whole purpose for the training) because of the reinforcement, recognition, credit, and support the leader gives (Afsar, Shahjehan, & Rehman, 2010).


Expectancy Theory


Transfer and participation are important, but one must not forget content. Content needs to be relevant to be effective (Renta-Davids et al., 2014). These factors are precisely why expectancy theory fits into training as a strong motivator. When leaders understand this theory, they may be more inclined to pay attention to it. Additionally, they might be more willing to design training programs with expectancy in mind. Humans develop expectancies about the outcomes of their behaviors and consequently behave in a manner that is likely to create the desired outcome (Oliver, 1974). Employees are motivated by job outcomes (e.g. pay, promotions, recognition, accomplishments, and etc.) (Muchinsky, 2012). Instrumentality (Perceived degree of connections between performance and outcome), valence (one’s feelings), expectancy (the perceived connections), and force (the amount of effort needed) seemed to all be contributors to an individual’s motivation (Muchinsky, 2012).


Valence. If employees are not emotionally attached to the outcomes or do not anticipate satisfaction from their behaviors, they may be less likely to perform (Muchinsky, 2012). This is something trainers should keep in mind when designing a training program. If the employees’ attitudes toward training are negative, the training may never get off the ground.


The costs of expectancy. Modern researchers suggest that there is a hidden cost to expectancy theory. Flake, Barron, Hulleman, McCoach, and Welsh (2015), used focus groups to gather student’s perceptions of the cost of expectancy. Eight judges (experts in the field) analyzed the data to ensure it was relevant to cost dimensions; the higher the agreement, the more likely the content had validity. Flake et al. found that when exploratory factor analysis (used to measure the relationship between a set of variables) was contrasted with confirmatory factor analysis (used to test that what the researcher believes to be true is consistent with the results of a study), individuals expressed task effort, outside effort, loss of valued alternatives, and emotional costs. Flake et al. suggest that people express these costs in terms of too much or too hard and other similar phrases. This was in line with their assumptions that expectancy theory’s emotional costs are expressed in terms of value or weight.


Intrinsic motivation. Another factor of expectancy theory is the impact it has on one’s intrinsic motivation. Hsu, Shinnar, and Powell (2014) took a sample of 433 usable surveys from entrepreneurial undergraduates. The surveys covered 33 subtopics of entrepreneurship and expectancy and were designed to measure self-efficacy and intention. Hsu, Shinnar and Powell found that expectancy, instrumentality, and valence precede motivation. In essence, if one expects to a high degree that his or her behaviors will produce a desired outcome, and his or her feelings are in alignment with those predictions, he or she will be intrinsically motivated to pursue it (Hsu, Shinnar, & Powell, 2014).


Theoretical Framework and Recommendations


Training is only as effective as it is perceived (Jayakumar & Sulthan, 2014). For transfer to occur, the content needs to be relevant and effective (Renta-Davids et al., 2014). Additionally, trainers need to keep an individual’s age and other variables in mind when designing a training program (Zwick, 2015). When it comes to expectancy, trainers can use outcomes (i.e. rewards, recognition, etc.) to motivate employees to apply the training (Muchinsky, 2012). Extrinsically, these could act as incentives to drive employees. However, trainers need to keep intrinsic motivation in mind and demonstrate to employees the instrumentality, valence, and expectancy they could use to be internally driven (Hsu et al., 2014).

Implementing ideas from Franca and Pahor’s (2012) study, managers and leaders need to find value in the training and the outcomes it creates before presenting it to their employees. Perhaps this is where I/O psychologists can help. I/O psychologists can assist in finding information that is relevant to the organization and work closely with trainers to implement the training in an effective manner. After all, the goal is transfer of learning.


Discussion


Training effectiveness may not be as important as the employees’ perceptions and expectations. I/O psychologists can help organizations make the best choices for their teams and design programs that create anticipated satisfaction among employees. Research suggests that relevant and effective information transfers. Additionally, training needs to help employees develop new skills and provide them with ongoing support. Otherwise, transfer may not stick. Leaders impact the degree of transfer and the motivation of their employees. If employees feel they have a strong relationship with their leaders, they may be more inclined to practice or implement what is taught. Not all employees learn the same way or have the same drives. Trainers should keep this in mind and make adaptations for age and other variables.


When employees have high instrumentality, expectation, and valence, they will be more intrinsically motivated and will be more likely to be self-driven. Trainers can use incentives and recognition to help employees become more motivated. Extrinsic and intrinsic motivators can be designed with expectancy in mind. Organizations that work with I/O psychologists, value their training, have strong valence (the feeling of anticipated satisfaction), expect a return on their efforts, and test for transfer will have a higher probability of success than those who do not. If they keep employee differences in mind and build strong relationships, they will be more inclined to see employee’s expectations strengthen and transfer will occur.



References


Afsar, B., Shahjehan, A., & Rehman, Z. U. (2010). Leader’s influences on training effectiveness. Annales Universitatis Apulensis : Series Oeconomica, 12(2), 597-607. Retrieved from http://search.proquest.com/docview/856208500?accountid=458


Flake, J., Barron, K., Hulleman, C., McCoach, B., & Welsh, M. (2015). Measuring cost: The forgotten component of expectancy-value theory. Contemporary Educational Psychology, 41(1), 232-244. doi:10.1016/j.cedpsych.2015.03.002


Franca, V., & Pahor, M. (2012). Influence of management attitudes on the implementation of employee participation. Economic and Industrial Democracy, 35(1), 115-142. doi:10.1177/0143831X12464070


Hsu, D. K., Shinnar, R. S., & Powell, B. C. (2014). Expectancy theory and entrepreneurial motivation: A longitudinal examination of the role of entrepreneurship education. Journal of Business and Entrepreneurship, 26(1), 121-140. Retrieved from http://search.proquest.com/docview/1635000526?accountid=458


Jayakumar, G. S., & Sulthan, A. (2014). Modelling: Employee perception on training and development. SCMS Journal of Indian Management, 11(2), 57-70. Retrieved from http://search.proquest.com/docview/1543741421?accountid=458


Muchinsky, P. M. (2012). Psychology Applied to Work (10th ed.). Summerfield, NC: Hypergraphic Press, Inc..


Oliver, R. L. (1974). Expectancy theory predictions of salesmen's performance. Journal of Marketing Research, 11(3), 243-253. doi:10.2307/3151139


Renta-Davids, A., Jiménez-González, J., Fandos-Garrido, M., & González-Soto, A. (2014). Transfer of learning: Motivation, training design and learning-conducive work effects. European Journal of Training and Development, 38(8), 728 - 744. doi:http://dx.doi.org/10.1108/EJTD-03-2014-0026


Zwick, T. (2015). Training older employees: What is effective? International Journal of Manpower, 36(2), 136-150. doi:http://dx.doi.org/10.1108/IJM-09-2012-0138

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