Corporate Training

How to help employees transfer trained skills into work practice

How to help employees transfer trained skills into work practice

Employer Rewards and Expectations

Mónica Hamori from the Spanish business school IE (Instituto de Empresa) conducted a study to understand how organizational support from a company influences the learning outcomes of employees in massive open online courses (MOOCs) and their application in work practice. The study highlights the importance of corporate support for online learning, which not only improves learning outcomes but also facilitates the effective transfer of acquired knowledge to the workplace. Understanding this connection can help companies optimize their training programs and enhance employee competencies. Research shows that self-paced massive open courses (MOOCs) are directly linked to the professional tasks and goals individuals face at work. Employees learn to improve their performance and career advancement, as well as to acquire necessary skills and certifications that can help them find a new job. Employers, in turn, may not always be aware that their employees are taking courses online or at universities. However, some companies choose to actively support this process by selecting and funding specific courses for their employees and allocating time for learning within their work schedules. This creates opportunities for professional development and employee upgrading, which ultimately benefits the organization.

The question arises: does company support help employees apply acquired skills to their current jobs, rather than using them to seek new opportunities at other organizations?

Monica Hamori identifies two main types of support that employers can provide their employees. The first type of support includes material resources, such as funding for training, health insurance, and other benefits that help employees develop their professional skills and ensure their well-being. The second type of support involves emotional and psychological support, including creating a comfortable working environment, flexible work schedules, and motivational programs. These two aspects are key to developing a positive corporate culture and increasing productivity.

  • Incentive measures include reimbursement of the cost of courses purchased by employees, as well as the allocation of work time for training;
  • Expectation-enhancing measures - when the employer recommends that employees take certain courses and includes their results in these courses in their performance assessments.

The researcher formulated three key hypotheses. These hypotheses serve as the basis for further analysis and research in this area. Each of them is aimed at studying different aspects of the topic under consideration, which will allow for a deeper understanding of the subject of the study and its significance.

  • Both types of support improve employee performance in courses and their completion rate.
  • Both types of support motivate employees to use what they have learned in their current workplace.
  • Incentives reduce the motivation to apply learning results to finding a new job and reduce the likelihood that an employee will actively take action in this direction after the course.

In her study, Monica Hamori conducted a series of surveys among students taking one or more of 16 online marketing courses on the IE Business School platform. She also analyzed data on the students' learning outcomes. A total of 1,496 people participated in the survey during the course, and 443 respondents provided their responses after completing the courses. This study provides a deeper understanding of the impact of online education on the career development and professional skills of students.

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Her hypotheses were only partially confirmed, but in the process The study yielded unexpected discoveries. These results may have a significant impact on further study of this topic and open up new avenues for research.

Learning Content

A study conducted by a team of scientists from Utrecht University of Applied Sciences and the University of Amsterdam in the Netherlands focused on the links between learning content and motivation to apply acquired knowledge. This study analyzed the importance of learning content in developing sustainable motivation in students. The results showed that educational content plays a key role in activating interest and the desire to apply what they have learned in practice. These findings may help develop more effective educational programs aimed at increasing student motivation.

Research shows that the same factors, such as internal beliefs and social support, can have different effects on the development of soft and hard skills. This is due to the unique characteristics of each type of skill. Understanding these differences is important for creating effective training and development programs that address both technical and soft skills.

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Soft skills are easier Soft skills are easier to apply than hard ones, as adults already have significant experience in communication, self-regulation, and teamwork. In contrast, mastering new professional and specialized skills can be a more complex process. Soft skills, such as teamwork, adaptability, and effective communication, are in demand in various fields and help achieve professional success. Their development can significantly improve competitiveness in the labor market.

Established habits can make it difficult to adopt new soft skill practices. In contrast, hard skills are technical and professional skills that typically do not require retraining or behavioral changes. Learning and practicing hard skills makes it easier to track and evaluate personal progress, making the process more understandable and measurable than developing soft skills.

To test their hypotheses, the researchers applied a unified model of motivation known as the Unified Model of Task-Specific Motivation (UMTM). This approach integrates key elements of modern motivation theories, including Deci and Ryan's self-determination theory, Atkinson and Eccles's expectancy-value theory, Bandura's social cognitive theory, Ajzen and Fishbein's theory of planned behavior, Krapp's interest theory, and Csikszentmihalyi's flow theory. Using UMTM allows for a deeper understanding of motivation mechanisms in the context of specific tasks and contributes to the development of effective strategies for increasing productivity and job satisfaction.

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Academic Motivation: Scientific Theories and Their Explanations

Academic motivation plays a key role in the learning process. It determines how actively and effectively students perceive knowledge and participate in the educational process. Scientific theories offer various explanations of motivation based on psychological and pedagogical research.

One of the main theories is self-determination theory, which focuses on intrinsic and extrinsic motivation. Intrinsic motivation arises from an interest in learning and the desire to develop, while extrinsic motivation is associated with rewards and grades. Research shows that students with high intrinsic motivation achieve better results and are more persistent in learning.

Another important theory is expectancy-value theory, according to which motivation depends on the expectation of success and the significance of the outcome. If a learner believes that their efforts will lead to a positive outcome, and the outcome itself is valuable to them, then motivation will be high.

Cognitive-metacognitive theories also emphasize the importance of self-awareness and learning strategies. Learners who are aware of their strengths and weaknesses can more effectively manage their learning process and increase their motivation.

Thus, understanding academic motivation through the lens of scientific theories allows us to develop more effective teaching strategies that contribute to increased student interest and engagement.

At the center of the UMTM model are two key aspects of motivation: emotional and cognitive. The emotional aspect is associated with the enjoyment of the process of completing a task, while the cognitive aspect reflects the value of the outcome that a person expects to receive. These aspects demonstrate the attractiveness of the task for the individual. Importantly, they function as two relatively independent scales. This means that both positive and negative factors are considered simultaneously. For example, a task may offer significant rewards but also require significant effort or resources to complete. Therefore, a comprehensive analysis of motivation requires considering both aspects, allowing for a deeper understanding of what drives a person to achieve goals.

The model includes personal and contextual factors that enhance both emotional and cognitive aspects. Personal factors include self-efficacy and autonomy, while contextual factors encompass social support and social norms. These elements play a key role in shaping behavior and decision-making, and their interaction contributes to a deeper understanding of individual motivation and psychology.

This multidimensional model, according to its authors, demonstrates a person's readiness to perform certain actions, such as applying learning results to professional work. The model provides a better understanding of the factors influencing the transfer of knowledge and skills to real-world work settings.

Dutch researchers conducted a study using data from educational institutions in Amsterdam that offer training for police and judicial officers. A wide range of training topics was available, including police vehicle driving, judicial decision-making, improving work concentration, and managing organizational change. The researchers examined training programs of various formats and durations, including face-to-face and online sessions that combined lectures, practical assignments, and group and individual exercises.

Two main criteria were used in selecting the educational programs: first, that officers learned one specific skill, and second, that they were given the opportunity to apply this skill in the workplace within six weeks of completing the training. During the final sessions, participants were administered a questionnaire to assess the components of the UMTM. As a result, 1,122 people responded to the survey, and analysis of the collected data yielded interesting results.