Hubbry Logo
Training and developmentTraining and developmentMain
Open search
Training and development
Community hub
Training and development
logo
7 pages, 0 posts
0 subscribers
Be the first to start a discussion here.
Be the first to start a discussion here.
Training and development
Training and development
Training and development
View on Wikipedia
from Wikipedia

Training and development involves improving the effectiveness of organizations and the individuals and teams within them.[1] Training may be viewed as being related to immediate changes in effectiveness via organized instruction, while development is related to the progress of longer-term organizational and employee goals. While training and development technically have differing definitions, the terms are often used interchangeably. Training and development have historically been topics within adult education and applied psychology, but have within the last two decades become closely associated with human resources management, talent management, human resources development, instructional design, human factors, and knowledge management.[1]

Skills training has taken on varying organizational forms across industrialized economies.[2] Germany has an elaborate vocational training system, whereas the United States and the United Kingdom are considered to generally have weak ones.[2]

History

[edit]

Aspects of training and development have been linked to ancient civilizations around the world.[3] Early training-related articles appeared in journals marketed to enslavers in the Antebellum South[4] and training approaches and philosophies were discussed extensively by Booker T. Washington.[5] Early academic publishing related to training included a 1918 article in the Journal of Applied Psychology, which explored an undergraduate curriculum designed for applied psychologists.[6]

By the 1960s and 70s, the field began developing theories and conducting theory-based research since it was historically rooted in trial-and-error intervention research,[6] and new training methods were developed, such as the use of computers, television, case studies, and role playing.[6][7] The scope of training and development also expanded to include cross-cultural training, a focus on the development of the individual employee, and the use of new organization development literature to frame training programs.[7]

The 1980s focused on how employees received and implemented training programs, and encouraged the collection of data for evaluation purposes, particularly management training programs.[8] The development piece of training and development became increasingly popular in the 90s, with employees more frequently being influenced by the concept of lifelong learning.[9] It was in this decade that research revealing the impact and importance of fostering a training and development-positive culture was first conducted.[9]

The 21st century brought more research in topics such as team-training, such as cross-training, which emphasizes training in coworkers' responsibilities.[10]

Training practice and methods

[edit]

Training and development encompass three main activities: training, education, and development.[11][12][13] Differing levels and types of development may be used depending on the roles of employees in an organisation.[14]

The "stakeholders" in training and development are categorized into several classes. The sponsors of training and development are senior managers, and line managers are responsible for coaching, resources, and performance. The clients of training and development are business planners, while the participants are those who undergo the processes. The facilitators are human resource management staff and the providers are specialists in the field. Each of these groups has its own agenda and motivations, which sometimes conflict with the others'.[15]

Since the 2000s, training has become more trainee-focused, which allows those being trained more flexibility and active learning opportunities.[16] These active learning techniques include exploratory/discovery learning,[17] error management training,[18] guided exploration,[19] and mastery training.[16] Typical projects in the field include executive and supervisory/management development, new employee orientation, professional skills training, technical/job training, customer-service training, sales-and-marketing training, and health-and-safety training. Training is particularly critical in high-reliability organizations, which rely on high safety standards to prevent catastrophic damage to employees, equipment, or the environment (e.g., nuclear power plants and operating rooms).[20]

The instructional systems design approach (often referred to as the ADDIE model) is often used for designing learning programs and used for instructional design, or the process of designing, developing, and delivering learning content. There are 5 phases in the ADDIE model:[21]

  1. Needs assessment: problem identification. training needs analysis, determination of audience determined, identification of stakeholder's needs and required resources
  2. Program design: mapping of learning intervention/implementation outline and evaluation methods
  3. Program development: delivery method, production of learning outcomes, quality evaluation of learning outcome, development of communication strategy, required technology, and assessment and evaluation tools
  4. Training delivery and implementation: participation in side-programs, training delivery, learning participation, and evaluation of business
  5. Evaluation of training: formal evaluation, including the evaluation of learning and potential points of improvement

Many different training methods exist today, including both on- and off-the-job methods.[22] Other training methods may include:

  • Apprenticeship training: training in which a worker entering the skilled trades is given thorough instruction and experience both on and off the job in the practical and theoretical aspects of the work[23]
  • Co-operative programs and internship programs: training programs that combine practical, on-the-job experience with formal education, and are usually offered at colleges and universities[24]
  • Classroom instruction: information is presented in lectures, demonstrations, films, and videotapes or through computer instruction[24]
  • Self-directed learning: individuals work at their own pace during programmed instruction, which may include books, manuals, or computers that break down subject-matter content into highly organized logical sequences that demand a continuous response on the trainee's part.[25] It often includes the use of a computer and online resources.[26]
  • Audiovisual: methods used to teach the skills and procedures required for a number of jobs through audiovisual means[25]
  • Simulation: used when it is not practical or safe to train people on the actual equipment or within the actual work environment[25]

There is significant importance in training as it prepares employees for higher job responsibilities, shows employees they are valued, improves IT and computer processes, and tests the efficiency of new performance management systems. However, some[who?] believe training wastes time and money because, in certain cases, real life experience may be better than education, and organizations want to spend less, not more.[27]

Seminar training method

In the 1940s, Professor Reginald Revans introduced action learning development model, whereby training managers bring together organizational teams to improve organizational performance. According to Revans, the learning formula is: Learning (L) = Traditional Training Program (P) + Questioning (Q) to create development insights. In addition to traditional training methods (P), organizational questioning (Q) enables each employee to reflect on past experiences, the write down new insights to guide future actions to improve on the job performance and collective organizational performance. Action-learning based training models have become popular among many training managers and chief learning officers (CLOs).[28].

Training in the Public Sector

[edit]

Training and development in the public sector are essential for cultivating a competent, motivated, and ethically grounded workforce. These initiatives support skill acquisition, reinforce public service values, and enhance employee engagement. Research has examined how developmental interventions influence Public Service Motivation (PSM), facilitate training transfer, and improve work engagement across various public organizations.

Public Service Motivation (PSM) and Training

[edit]

PSM refers to prosocial and altruistic values that drive individuals to serve the public interest. It is a key predictor of job satisfaction, performance, and ethical behavior among public employees. In competitive civil service systems, recruitment may attract candidates motivated by extrinsic rewards, potentially crowding out intrinsic public service values, a phenomenon known as adverse selection.

A study by Chen, Hsieh, and Chen (2019) evaluated a five-week onboarding program for new civil servants in Taiwan. The training led to statistically significant improvements in public service-related knowledge and attitudes, including a stronger perception of public service as a means to help others and contribute positively to society. However, PSM itself showed minimal short-term change, suggesting that deeply held values are less responsive to brief interventions. The study found that perceived usefulness of training was strongly associated with attitude change and, in some cases, modest increases in PSM. A positive attitude toward public service work mediated the relationship between training usefulness and PSM, indicating that training can indirectly influence motivation by shaping how employees perceive their roles.[29]

Training Transfer and Implementation

[edit]

Beyond initial learning, public sector organizations often face challenges in ensuring that acquired skills are applied in the workplace. Quratulain et al. (2019) examined factors influencing training implementation among public employees in Pakistan, using Social Cognitive Theory. The study identified two key predictors: self-efficacy beliefs (confidence in one’s ability to apply learned skills) and training instrumentality beliefs (perception that training leads to tangible rewards or career advancement). Organizational climate moderated these relationships. A flexible work environment enhanced the impact of self-efficacy on implementation, while performance feedback strengthened the effect of instrumentality beliefs. These findings highlight the importance of supportive conditions in promoting training transfer.[30]

Training Access and Work Engagement
[edit]

Access to training opportunities is also linked to employee engagement. Hassett (2022) studied the U.S. federal workforce and found that perceived access to training was positively correlated with higher levels of work engagement. Employees with access to development opportunities had engagement scores approximately 15 percentage points higher than those without. The study applied High-Performance Work Systems (HPWS) and Job Demands-Resources (JD-R) theory to explain how training serves as a resource that buffers job demands and enhances motivation.[31]

Yu and Lee (2021) added a gender equity lens, showing that mentorship improves reporting of discrimination and career development among women in public organizations.[32]

Meta Analytic and Evidence on Training Effectiveness
[edit]

Recent meta-analytic reviews have reinforced the effectiveness of training programs in public sector contexts. A rapid evidence review commissioned by the UK government found that management training programs are generally effective at improving organizational outcomes, especially when training is facilitated in person, adapted to context, and includes feedback and practice-based components.[33] Another meta-analysis by the Inter-American Development Bank synthesized over 400 estimates and concluded that managerial training programs have positive effects on productivity, management practices, and firm survival, particularly when tailored to specific sectors and delivered by local organizations.[34]

Implications for public sector
[edit]

These findings offer practical guidance for public sector human resource management:

  • Strategic Training Design: Programs should be perceived as relevant and impactful to foster positive attitudes and indirectly support PSM.
  • Supportive Climate: Flexible environments and robust feedback systems promote training transfer.
  • Linking Training to Rewards: Clear connections between training and career outcomes enhance motivation and implementation.
  • Equitable Access: Providing widespread access to training opportunities improves engagement and reduces disparities.
  • Long-Term Development: Sustained interventions are necessary to cultivate intrinsic public service values beyond initial training.

Training and development in the public sector are not only tools for skill enhancement but also mechanisms for reinforcing public service values and improving organizational effectiveness.[35]

Public sector training and career development opportunities for women

Although there have been efforts from federal agencies to encourage employees to denounce discriminatory behaviour and display anti-discrimination legislation, research demonstrates that women opt to avoid making a formal report. Studies illustrate that women in law enforcement experience sexual harassment as a form of discriminatory behaviour, which includes asking for intimate acts, verbal and physical misconduct, impacting women’s employment around work performance, and creating an unsafe environment.[36]

Relationship between mentorship and workplace discrimination

Mentorship is one of the factors that influences the reporting of workplace discrimination among women. Considering that mentors must comply with employment rules relating to sexual abuse, mentors should encourage mentees to denounce discrimination and retaliation. The ‘No Fear Act 2002’ motivates employees to report inappropriate behaviour. In addition, the Federal Government demands annual training for agencies to inform workers of the prohibition of discriminatory behaviours and retaliation.[37]

It is essential to have policies regarding discriminatory employment because women in male-dominated fields are not willing to report discrimination, worried about revenge or frustrated about not seeing results from past cases. Therefore, it is confirmed that women who have opposite gender mentors disclose discrimination. Occupations like law enforcement posit an aggressive, masculine culture that suppresses female officers, and women who speak out against this structure are at risk of losing training and promotion opportunities.[38]

The initiative by the United Nations (2014), ‘HeForShe’, creates awareness about gender inequity and invites men to solidarise with women and cultivate change among communities to achieve a more equal workplace. Additionally, ‘MeToo’ and ‘Time’s Up’ campaigns motivate women to tell personal stories around sexual harassment, promoting change and creating awareness. Overall, it is suggested that public organisations designate female mentors from external companies. In the event of fiscal constraints, public sector agencies must expand the requirements of the ‘No Fear Act of 2002’ and establish an anti-discrimination training programme to address the situation.[39]

The token status factor prevents minorities’ career development

The status perspective of tokenism states that people belonging to low-ranking levels experience token negative effects, encountering barriers to rise to senior positions (glass ceiling). On the other hand, individuals who are part of higher categories and are involved in female-dominated fields experience positive token effects, such as rapid career advancement and promotion opportunities (glass escalator). Therefore, women in token positions face a climate of gender inequality that negatively affects their work commitments. The connection among token status, gender inequity, and work commitment impacts women’s career aspirations.[40]

Research shows that men pursue alpha career patterns (linear, career focus), in contrast, women seek a beta career pattern (aligned with family values, flexible and balanced). According to stereotype threat theory, women are likely to be judged based on negative stereotypes in relation to their skills and performance at their jobs. Hence, they experience impostor syndrome and tend to lower their career goals.[41]

Gender and equal opportunities

In general, public sector organisations attract more female than male employees. Most of these companies perpetuate gender, which means they provide career, economic, training, and development opportunities primarily for men; hence, men hold control of resources and are the decision-makers. In gendered organisations, women feel the need to prove themselves to be taken seriously.[42]

Incivility experienced by women and people of colour is known as ‘Modern discrimination’, which is subtler than more obvious offences like discrimination legislation or breaches of workplace policies. Talking condescendingly, not replying to emails, avoiding eye contact, or publicly embarrassing a woman are examples of incivility. Certain studies (e.g., Smith et al., 2021) confirm the existence of incivility towards women and women of colour, while others do not. In the US military, the rates of incivility towards African American women are high. Conversely, white women and non-Hispanic women face more incivility than Hispanic women in the public sector. The findings of Smith et al. (2021) suggest that Hispanic women report fewer harmful incidents because they develop strategies to avoid contact with offenders, tolerate the behaviour as the consequences might be frightening, or believe their efforts could be pointless.[43]

Human rights protection for women in New Zealand

In 2018, Jackie Blue -the Employment Opportunities Commissioner- attended the Committee on the Elimination of Discrimination against Women (CEDAW) in Geneva. Jackie’s mission was to present how the New Zealand Government protect women’s rights. It is also an opportunity to identify what issues around human rights women face, including violence against women, labour inequity, pay inequity, inequality in leadership roles, workplace sexual harassment and worker exploitation. This results in a long discussion where government representatives respond, and the committee provides recommendations to address the issues. Subsequently, non-governmental institutions and the Human Rights Commission are responsible for guaranteeing the effectiveness of recommendations to benefit NZ women.[44]

Needs assessments

[edit]

Needs assessments, especially when the training is being conducted on a large-scale, are frequently conducted in order to gauge what needs to be trained, how it should be trained, and how extensively.[45] Needs assessments in the training and development context often reveal employee and management-specific skills to develop (e.g., for new employees), organizational-wide problems to address (e.g., performance issues), adaptations needed to suit changing environments (e.g., new technology), or employee development needs (e.g., career planning). The needs assessment can predict the degree of effectiveness of training and development programs and how closely the needs were met, the execution of the training (i.e., how effective the trainer was), and trainee characteristics (e.g., motivation, cognitive abilities).[46] Training effectiveness is typically done on an individual or team-level, with few studies investigating the impacts on organizations.[1]

Principles

[edit]

Aik and Tway (2006) estimated that only 20–30% of training given to employees are used within the next month.[47] To mitigate the issue, they recommended some general principles to follow to increase the employees' desire to take part in the program. These include:

  • improving self-efficacy, which increases the learner's personal belief that they can fully comprehend the teachings[47]
  • maintaining a positive attitude, as an uncooperative attitude towards learning could hinder the individual's capability to grasp the knowledge being provided[47]
  • increasing competence, which is the ability for an individual to make good decisions efficiently[47]
  • providing external motivators, such as a reward for the completion of the training or an extrinsic goal to follow[47]

Motivation

[edit]

Motivation is an internal process that influences an employee's behavior and willingness to achieve organizational goals.[48] Creating a motivational environment within an organization can help employees achieve their highest level of productivity,[47] and can create an engaged workforce that enhances individual and organizational performance.[49] The model for motivation is represented by motivators separated into two different categories:

  • Intrinsic factors, which represent the internal factors of an individual, such as the difficulty of work[clarify], achievement recognition, responsibility, opportunity for meaningful work, involvement in decision making, and importance within the organization[49]
  • Extrinsic factors, which are factors external to the individual, such as job security, salary, benefits, work conditions, and vacations[49]
Training and development conference

Both intrinsic and extrinsic motivators associate with employee performance in the workplace. A company's techniques to motivate employees may change over time depending on the current dynamics of the workplace.[49]

Feedback

[edit]

Traditional constructive feedback, also known as weakness-based feedback, can often be viewed as malicious from the employees' perspective. When interpreted negatively, employees lose motivation on the job, affecting their production level.[50]

Reinforcement is another principle of employee training and development. Studies have shown that reinforcement directly influences employee learning, which is highly correlated with performance after training. Reinforcement-based training emphasizes the importance of communication between managers and trainees in the workplace. The more the training environment can be a positive, nurturing experience, the faster attendees are apt to learn.[51]


Retention

The training paradox represents the tension between training and development. Accord to human capital theory and monopsony theory, investment in employee portable training and development increases employee value to their current organisation, whilst also increasing value to other employers.[52][53] The expansion of access to online resources has enhanced individuals’ awareness of employment opportunities. Within the public sector, moving to another agency can be interpreted as beneficial as the employees’ knowledge, skills and abilities remain in a position that supports the delivery of public services. Using German employer and employee longitudinal survey data, Dietz and Zwick established that training has a positive effect on retention as it increases human capital and turnover.[54] Using German employer and employee longitudinal survey data, Dietz and Zwick established that training has a positive effect on retention as it increases human capital and turnover.[54] The research found that the negative effects of training were exacerbated when the training was credible, particularly when provided and certified by external institutions.[54] They determined that the decline in retention of portable human capital occurs regardless of its visibility and visible training that is not portable can still lead to reduced retention.[54] Other research has found well-intentioned values-driven training can lead to a negative retention effect if the psychological demands training creates are not managed.[55] A survey found that training that increases public servant’s awareness of systematic causes of poverty may improve service delivery, but without measures to address the associated emotional demands, training may contribute to burnout and higher turnover rates.[55]

Benefits

[edit]

The benefits of the training and development of employees include:

  • increased productivity and performance in the workplace[1]
  • uniformity of work processes
  • skills and team development[1][56][57]
  • reduced supervision and wastage
  • a decrease in safety-related accidents[57]
  • improved organizational structure, designs and morale
  • better knowledge of policies and organization's goals
  • improved customer valuation[58]
  • Enhancements in public service motivation among public employees[59]

However, training and development may lead to adverse outcomes if it is not strategic and goal-oriented.[60] Additionally, there is a lack of consensus on the long-term outcomes of training investments;[61] and in the public sector, managers often hold conservative views about the effectiveness of training.[59]

Research suggests that training and development measures may improve employee’s perceptions towards their employer.[31] Research shows learning and development activities are vital for professionalism and quality of workers in the public sector.[62]

Training and development activities affect variables that directly relate to individual and team performance including innovation, technical skills and self-management skills,[63][64][65] as well as variables that are indirectly related to performance including communication and empowerment.[63][64][65] At the organisational level, the benefits may include increased productivity and effectiveness as well as indirect outcomes like enhanced social capital and strengthened reputation.[63][64][65] Some also claim that the value of training and development has the potential to generate value for society.[63]

Barriers and access to training

[edit]

Training and development are crucial to organizational performance, employee career advancement and engagement.[66]

Disparities in training can be caused by several factors, including societal norms and cultural biases that significantly impact the distribution of training opportunities. Stereotypes and implicit biases can undermine the confidence and performance of minority groups to seek out training, affecting their career development.[67]

The impact of excluding or limiting a person's access to training and development opportunities can affect both the individual and the organization.

  • Disparities in training opportunities can adversely affect individuals from underrepresented groups, leading to slower career progression, reduced employee engagement, and limited professional growth.[66] Individuals may experience lower self-esteem and decreased motivation due to perceived or actual access to development opportunities. For example, if a leadership training program does not have minority representation, individuals may lack the confidence to "break the glass ceiling" and seek out the opportunity for themselves.[68]
  • When training opportunities are not equitably distributed, organizations may have reduced diversity in leadership and decision-making, which may stifle innovation and hinder organizational performance. Failure to address these disparities can lead to higher turnover rates and lower employee morale.[69]

Management teams that are not diverse can be self-replicating as senior leaders' demographic characteristics significantly impact the types of programs, policies and practices implemented in the organisation – i.e., there are more likely to be diversity programs if the management team is also diverse.[70]

To address these disparities, organizations can implement diversity policies, provide bias training, and establish mentorship programs to support underrepresented groups. These may include:

  • Implementing inclusive policies for addressing disparities: organizations should establish diversity and inclusion programs that specifically target training and development opportunities for underrepresented groups, which should focus on opportunities for future managers at the bottom of the hierarchy, as advancement to lower-level and middle-level positions is crucial for promotion to upper-level management.[71] These policies can help ensure employees have equal access to career advancement resources and can increase the implementation of mechanisms for reporting discrimination or advancement barriers.[72] Some efforts to support diversity and exclusion commitments in workplaces may be enshrined in law, such as the New Zealand Public Service Act 2020.[73]
  • Developing mentorship and sponsorship programs: these programs can support underrepresented groups by providing them with guidance, networking opportunities, and advocacy within the organisation. Creating supportive networks for minority and gender groups can provide safe spaces for people identifying as minorities to develop programs that are suited to them and to provide a united voice to report ongoing discrimination.[67]
  • Using data to track and address disparities in training opportunities: this may include censuses[74] or regular pulse surveys or records of learning that are linked to a person's self-identified attributes.

The current political climate in the United States has intensified debates around Diversity, Equity, and Inclusion (DEI) programs, leading to both challenges and shifts in corporate strategies. Increased political polarization, new state-level legislation, and public scrutiny have caused some companies to scale back or reframe DEI initiatives to avoid legal risks or reputational backlash. At the same time, many organizations remain committed to fostering inclusive workplaces, but are increasingly positioning DEI efforts under broader umbrellas like "talent development," "belonging," or "workplace culture" to navigate the evolving landscape. Overall, the environment has made DEI efforts more complex, requiring companies to be both strategic and resilient in advancing inclusive practices.

Occupation

The Occupational Information Network cites training and development specialists as having a bright outlook, meaning that the occupation will grow rapidly or have several job openings in the next few years. Related professions include training and development managers, (chief) learning officers, industrial-organizational psychologists, and organization development consultants. Training and development specialists are equipped with the tools to conduct needs analyses, build training programs to suit the organization's needs by using various training techniques, create training materials, and execute and guide training programs.[75]

Costs associated with training

[edit]

Multiple publications on training and development in the public sector highlight its significance in equipping employees to meet evolving skill and competency demands, as well as adapting to public sector reforms.[76][77] Public sector training policies are affected by efficiency measures and cost-cutting initiatives.[78][79] The implication of such may include cutbacks in training budgets and fewer time spent on training.[65][79] The OECD highlights a contrast between these budget cuts and sustainable competition strategies.[79] Some organisations remain uncertain about the overall return of investment of training programmes. A study noted that there is little consensus on how to assess training effectiveness at the level of individual employees.[80]

Mentorship

[edit]

Mentorship is a developmental relationship in which a more experienced individual (the mentor) provides guidance, support, and knowledge to a less experienced individual (the mentee) to foster their personal and professional growth.[81] Within training and development, mentorship is recognised as a complementary approach to formal instruction, offering sustained, relationship-based learning tailored to the mentee’s goals and the organisational context.[82]

Mentorship can be formal, structured through organisational programmes with defined objectives and matching processes, or informal, arising organically through workplace relationships.[83] Formal programmes often include scheduled meetings, goal-setting, and progressive reviews, while informal mentorship may be more flexible and driven by the mentee’s immediate needs.[84]

Conceptual Foundations

[edit]

Researchers argue that despite the widespread use of mentorship in organisational settings, the concept has suffered from definitional ambiguity and inconsistent theoretical framing.[85] They propose a unified definition of mentoring as “a process for the informal transmission of knowledge, social capital, and psychosocial support perceived by the recipient as relevant to work, career, or professional development.”[83] This definition emphasises the mentee’s perception of value, the informal nature of knowledge transfer, and the broader social and emotional dimension of mentoring. Additionally, it differentiates mentoring from related concepts such as coaching, advising, and role modelling.[86]

Benefits

[edit]

Mentorship has been associated with numerous benefits for not only individuals and organisations. It facilitates the transfer of knowledge, especially in complex or tacit areas, helping organisations preserve and share vital information.[87] Mentorship also supports career development by providing mentees with access to networks, challenging assignments, and advancement opportunities.[88] Moreover, mentees often report higher job satisfaction and greater commitment to their employers, which enhances employee engagement and retention.[87] Leadership development is another key benefit, as mentorship nurtures skills such as emotional intelligence, strategic thinking and effective communication.

Targeted mentorship programmes can promote diversity and inclusion by enabling underrepresented groups to access career pathways and leadership roles.[89] Mentorship can play a crucial role in transmitting social capital, including access to informal networks, social norms, and reputational benefits that are difficult to attain through formal training.[83]

Mentorship Programme Design

[edit]

For formalised mentorship programmes, effective mentorship will typically involve several key elements. First, a matching process, pairing mentors and mentees based on their goals, skills, and compatibility, to foster productive relationships.[88] Mentors also require preparation, often through training in active listening, delivering effective feedback, and cultural awareness.[90] Clear objectives are set from the start, including shared expectations, confidentiality agreements, and measurable goals to guide the mentoring relationship.[83] Regular evaluation, using tools like surveys, interviews, or performance metrics, can be used to assess the programme's impact and drive continuous improvement.[88] These mentorship programmes are often integrated into leadership pipelines, graduate development schemes, or professional associations, ensuring that mentoring supports the broader organisational development goals.

Challenges

[edit]

Common challenges for both formalised and informal mentorship methods include mismatched expectations, time constraints, and insufficient organisational support. Without clear objectives and accountability, mentorship relationships may lose momentum. Additionally, poorly designed programmes risk reinforcing existing inequities if access to mentors is uneven across the workforce.[91]

See also

References

[edit]

Further reading

[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Training and development

View on Grokipedia
from Grokipedia

Training and development refers to the organized activities undertaken by organizations to enhance employees' , thereby improving job performance and preparing individuals for future roles. emphasizes acquiring specific competencies for current positions through methods like workshops and on-the-job instruction, while development targets broader career advancement via mentoring, , and initiatives. These programs are foundational to , with empirical evidence linking them to higher productivity, better retention, and organizational adaptability. Studies show that investments in employee foster a learning culture that facilitates knowledge exchange and performance gains, though outcomes depend on program design and implementation. Key challenges include ensuring effective transfer of learned skills to the , measuring amid rising costs, and addressing barriers like time constraints from increased workloads and hybrid arrangements. Despite these hurdles, robust training and development remain critical for sustaining competitive edges in dynamic labor markets.

Historical Evolution

Pre-Industrial and Early Industrial Practices

In pre-industrial societies, skill acquisition predominantly occurred through informal family-based transmission and formal apprenticeships, ensuring the perpetuation of craft knowledge across generations. Children, often starting as young as age 7 or 8, assisted relatives in agricultural or artisanal tasks, gradually mastering techniques through and hands-on practice under parental ; this method relied on direct emulation rather than structured instruction, with familial ties providing the primary social and economic framework for learning. Formal apprenticeships supplemented this, originating in ancient civilizations like and where craft training maintained specialized labor pools, and becoming institutionalized in medieval via guilds that bound youths—typically males aged 10 to 14—for periods of 5 to 9 years to a master . Medieval craft in , emerging around the , standardized to foster transferable skills and regulate , requiring apprentices to live with masters, perform menial tasks initially, and progress through stages of competency demonstrated by producing a "" for guild approval. controlled entry by verifying apprentices' free status (excluding serfs) and limiting numbers to preserve levels and quality, while masters provided lodging, food, and moral oversight in exchange for unpaid labor; this system, dominant until the , emphasized transfer essential for complex trades like , blacksmithing, and , though it often exploited young trainees with harsh discipline and limited mobility. By the 1700s in , contracts included premiums paid by families to masters, reflecting the perceived value of skill acquisition amid rising demand for specialized labor. The advent of the in late-18th-century Britain disrupted these practices, as factories shifted production from skilled artisanal workshops to machine-based operations requiring minimal prior expertise, with training reduced to rudimentary on-the-job instruction for semiskilled tasks. Early mills, such as those pioneered by in the 1770s, employed pauper children from workhouses as apprentices under the 1760s parish apprenticeship system, where they learned machine operation through repetitive labor lasting 12-16 hours daily, but without the guild-enforced progression or quality safeguards, leading to high rates—exemplified by documented cases of limb loss from unguarded machinery—and rapid obsolescence as technological changes outpaced worker . This approach, where machinery embodied much of the expertise, prioritized output over comprehensive development, resulting in workforce instability; by the 1830s, parliamentary inquiries revealed apprentices enduring physical abuse and inadequate instruction, prompting limited reforms like the 1802 Health and Morals of Apprentices Act, which mandated and reduced hours but failed to institutionalize systematic training.

20th Century Formalization and Expansion

The formalization of training and development in the early stemmed from Frederick Winslow Taylor's principles of , outlined in his 1911 work, which advocated scientifically selecting workers, standardizing tasks through time-motion studies, and providing systematic instruction to replace informal methods with efficient, measurable training processes. This approach expanded with the establishment of in-house training schools, such as those at National Cash Register Company around 1900 and in 1913, which institutionalized vestibule training—simulated on-the-job practice—to accelerate skill acquisition amid rapid industrialization. World War II catalyzed significant expansion, as labor shortages necessitated rapid upskilling of millions; the U.S. government's (TWI) program, launched in 1940, delivered standardized modules on job instruction, methods improvement, and relations, certifying over 1.6 million supervisors and workers across 16,500 plants by war's end. TWI's structured, problem-solving framework influenced postwar practices, emphasizing hands-on coaching and immediate application to boost without relying on prior experience. Postwar professionalization advanced through the founding of the American Society for Training Directors (ASTD) in 1943, initially from a committee, which grew to standardize curricula, certify trainers, and publish resources like its 1945 newsletter, fostering a dedicated field amid economic booms and the GI Bill's push for workforce education. Concurrently, Donald Kirkpatrick's 1959 four-level evaluation model—assessing reaction, learning, behavior, and results—provided empirical tools to measure training efficacy, shifting from anecdotal to data-driven validation. The latter half of the century saw further expansion via (OD), rooted in Lewin's 1940s and T-group , which integrated psychological insights to address and in corporations. By the 1960s-1970s, OD programs proliferated in firms like General Electric's Crotonville leadership center (established 1956), emphasizing and competency models, while federal mandates post-1964 spurred compliance training, though empirical evidence on long-term behavioral impact remained mixed per Kirkpatrick's higher levels. ASTD's evolution into a global body by the reflected training's integration into human resource strategies, with U.S. corporate spending surpassing $50 billion annually by 1990, driven by technological shifts and quality initiatives like .

Post-2000 Digital Transformation

The advent of widespread and advancements in web technologies in the early enabled the shift from instructor-led to digital platforms in corporate settings, allowing scalable delivery of modules. By 2002, open-source learning management systems (LMS) like emerged, facilitating centralized content management, tracking, and assessment for employee development programs. This period marked the of e-learning due to declining hardware costs and the proliferation of , reducing barriers for organizations to implement online over traditional classroom methods. Adoption accelerated throughout the with the integration of mobile devices, enabling via apps and responsive platforms, which supported just-in-time training amid trends. By 2025, platforms dominated corporate training, with 93% adoption rates reported among organizations, driven by their ability to deliver personalized content at lower costs—up to 50-70% savings compared to in-person sessions. Approximately 98% of corporations had implemented or planned online learning, reflecting empirical evidence of higher retention rates (up to 60% for e-learning versus 8-10% for lectures). Emerging technologies further transformed delivery: (VR) and (AR) simulations, gaining traction post-2015, improved skill acquisition in high-risk fields like and healthcare by providing immersive, hazard-free practice, with studies showing 75% faster learning curves and 90% knowledge retention. (AI), integrated since the late 2010s, enabled adaptive algorithms that tailor content to individual performance data, enhancing engagement and outcomes through real-time feedback. elements, such as badges and leaderboards, boosted completion rates by 50% in some programs by leveraging behavioral . The from 2020 onward catalyzed hybrid models, compelling 77% of organizations to pivot to fully digital , which persisted due to proven and data-driven ROI metrics like reduced expenses and measurable skill uplift via . Despite these gains, challenges persist, including digital divides in access and the need for robust cybersecurity in LMS platforms, underscoring the causal link between technological infrastructure and effective . Overall, post-2000 digital shifts have prioritized and measurability, with peer-reviewed analyses confirming superior long-term transfer of to workplace over pre-digital eras.

Core Principles

Adult Learning Fundamentals

Adult learning, distinct from child , emphasizes principles tailored to mature learners' autonomy, accumulated experiences, and practical orientations, as formalized in Malcolm Knowles' theory introduced in the and refined through the 1980s. assumes adults enter education with a self-directed mindset, viewing themselves as responsible for their learning rather than dependent on instructors, which contrasts with children's typical reliance on external direction. This framework prioritizes learner involvement in planning, execution, and evaluation to align with adults' internal motivations and real-world applicability. Knowles identified five core assumptions underlying adult learning:
  • Self-concept: Adults develop a preference for self-direction as they mature, resisting directive teaching methods that treat them as passive recipients.
  • Experience: Adults accumulate a reservoir of life experiences that serve as foundational resources for new learning, enabling them to integrate concepts through reflection and application rather than rote memorization.
  • Readiness to learn: Learning readiness is driven by the need to address immediate life tasks or role transitions, such as career advancements, rather than deferred future benefits.
  • Orientation to learning: Adults favor problem-centered approaches focused on solving real-life issues over content-centered, abstract subject matter.
  • Motivation to learn: Internal factors, like personal growth or job relevance, predominate over external incentives such as grades or compliance.
A sixth principle, the need to know the "why" behind learning, was later emphasized, underscoring adults' demand for clear rationale before committing effort. These principles inform by advocating experiential methods, such as case studies and simulations, that leverage prior knowledge and promote immediate applicability. Empirical validation of remains inconclusive despite its widespread adoption; studies over four decades show variable , with critiques noting insufficient differentiation from general learning processes applicable across ages and potential overemphasis on untested assumptions. For instance, meta-analyses indicate that while self-directed elements enhance , outcomes depend more on contextual factors like trainer facilitation than inherent traits alone. In contexts, evidence supports integrating these fundamentals with evidence-based techniques, such as for retention (e.g., adults recall 80% more with over massed sessions), to maximize transfer to .

Motivation and Reinforcement Mechanisms

Motivation in training and development refers to the internal and external factors driving participants to engage with, absorb, and apply learned material, with empirical studies indicating that higher trainee correlates with improved knowledge retention rates of up to 75% compared to unmotivated groups. posits that intrinsic motivation—fueled by autonomy, competence, and relatedness—enhances learning outcomes more sustainably than extrinsic factors alone, as evidenced by interventions increasing autonomous motivation by 20-30% and subsequent performance in workplace tasks. In contrast, suggests that trainees exert effort when they anticipate that performance leads to valued rewards, supported by field studies showing that clear links between training effort and career advancement boost participation rates by 15-25%. Reinforcement mechanisms, rooted in principles, strengthen desired learning behaviors through contingent rewards or feedback, with positive —such as immediate praise or —proving more effective than in sustaining acquisition. A of programs across settings found that well-designed rewards elevate by an average of 22%, with effects amplified in training contexts where vouchers or bonuses for mastery increased completion rates by 40% in vocational programs. Feedback serves as a key reinforcer, with meta-analytic evidence from 607 effect sizes demonstrating that targeted feedback interventions improve overall (Cohen's d = 0.41), particularly when it specifies actionable improvements rather than vague evaluations. Empirical data underscores the interplay between and : programs combining intrinsic motivators with extrinsic reinforcements, such as goal-setting paired with progress-based incentives, yield retention improvements of 50% over six months post-training, as measured in . However, over-reliance on extrinsic rewards can undermine intrinsic if perceived as controlling, with longitudinal research showing a 10-15% drop in voluntary when incentives overshadow personal relevance. Effective programs thus integrate variable-ratio schedules, akin to those in behavioral experiments, to maintain without , evidenced by sustained gains in job-skills where intermittent rewards outperformed fixed schedules. These mechanisms collectively enhance transfer of to workplace application, with reinforced programs reporting 30% higher on-the-job metrics than non-reinforced counterparts.

Feedback and Iterative Improvement

Feedback mechanisms in training and development provide trainees with specific, timely information on their performance relative to objectives, enabling adjustments in behavior and skill application. Research indicates that effective feedback, when delivered constructively, enhances adult learners' ability to identify errors, refine techniques, and achieve educational goals, with studies showing improvements in task performance and self-efficacy following targeted input. Formative feedback, occurring during training, supports real-time corrections, while summative feedback post-training informs long-term retention; empirical data from workplace settings demonstrate that combining both types correlates with higher knowledge transfer rates, as measured by pre- and post-assessments showing gains of 15-25% in skill proficiency. Iterative improvement integrates feedback into cyclical processes, such as frameworks, where program designers collect participant evaluations, performance metrics, and behavioral outcomes to diagnose deficiencies and revise content or delivery methods. For instance, a in workforce development programs applied two cycles of staff-designed feedback-driven adjustments, resulting in statistically significant increases in participant rates by 10-12% compared to baseline iterations. This approach counters static training designs by incorporating causal evidence from outcomes—e.g., low application rates signaling irrelevant content—leading to targeted enhancements like modular adaptations or sessions. Organizations employing such loops report sustained program , with longitudinal analyses revealing reduced skill decay over 6-12 months post-training. Challenges in implementation include feedback overload or , where vague or infrequent input yields mixed results; meta-reviews of feedback studies note that only 30-40% of interventions consistently boost without motivational backlash, underscoring the need for evidence-based delivery, such as peer-reviewed protocols emphasizing specificity over volume. Despite these hurdles, rigorous application of feedback loops fosters measurable gains in organizational metrics, including a 2020 linking iterative refinements to 8-15% improvements in employee output variance. Prioritizing empirical validation over anecdotal success ensures causal , avoiding overreliance on self-reported satisfaction that often inflates perceived without behavioral change.

Training Methods and Practices

Needs Assessment and Program Design

Needs assessment in training and development involves systematically identifying discrepancies between employees' current capabilities and the required for organizational performance objectives. This process determines whether is the appropriate intervention or if other solutions, such as process redesign or , are needed, thereby preventing inefficient resource expenditure on irrelevant programs. Empirical studies demonstrate that rigorous correlates positively with enhanced employee skills acquisition and overall , as it aligns interventions with verifiable performance gaps rather than assumptions. Common methods for conducting needs assessment include organizational analysis to evaluate strategic goals, task analysis to break down job requirements, and individual analysis to assess personal competencies through tools like surveys, interviews, performance data reviews, and observations. The Hennessy-Hicks Training Needs Analysis questionnaire, validated and endorsed by the World Health Organization, is among the most utilized instruments globally, facilitating quantitative scoring of perceived and actual needs across clinical and managerial domains. In the ADDIE instructional design framework—widely applied since its formalization in the 1970s by Florida State University for U.S. military training—the analysis phase specifies learner characteristics, environmental constraints, and delivery options, ensuring subsequent phases address root causes of underperformance. Research indicates that skipping or inadequately performing this phase leads to training programs with diminished transfer to job tasks, as evidenced by meta-analyses showing higher return on investment when needs are empirically validated upfront. Program design follows directly from needs assessment outputs, translating identified gaps into structured learning objectives, content sequences, and delivery modalities tailored to adult learners' experiential backgrounds and job contexts. Within the ADDIE model, the design phase produces detailed blueprints including measurable objectives aligned with Bloom's taxonomy levels (e.g., knowledge recall to skill application), assessment strategies for formative and summative evaluation, and material outlines that prioritize causal links between training elements and performance outcomes. Effective designs incorporate principles such as specificity in objectives—e.g., "trainees will demonstrate 90% accuracy in data entry within 30 seconds"—to enable objective measurement, drawing from evidence that vague goals reduce program efficacy by up to 40% in controlled studies. Iterative prototyping and stakeholder input during design mitigate risks of misalignment, with longitudinal data from organizational implementations showing designed programs yield 15-20% greater skill retention compared to ad-hoc approaches.
Key Steps in Needs Assessment and Program DesignDescription
Identify performance gapsAnalyze current vs. required competencies using data from metrics like error rates or productivity logs.
Select assessment toolsEmploy validated instruments such as TNA questionnaires for scalable, reliable data collection.
Define learning objectivesCraft specific, measurable goals based on gaps, e.g., targeting causal deficiencies in task execution.
Outline content and methodsSequence materials logically, selecting formats (e.g., simulations for skill-based needs) informed by learner analysis.
Plan evaluation integrationEmbed metrics from design outset to verify causal impact on performance post-implementation.
This integrated approach ensures training investments are grounded in evidence rather than , with studies confirming that organizations employing formal and design frameworks achieve statistically significant improvements in employee performance metrics, such as a 12-18% uplift in task proficiency.

Traditional Delivery Approaches

Traditional delivery approaches in training and development primarily include instructor-led sessions, (OJT), and structured workshops, which emphasize face-to-face interaction and direct to impart skills and knowledge. These methods, prevalent before the digital era, rely on human facilitators to deliver content through lectures, demonstrations, and group activities, fostering immediate clarification of concepts and . training, in particular, involves groups gathering in dedicated spaces where trainers use verbal explanations, visual aids, and interactive exercises to cover theoretical material, often lasting from hours to several days. On-the-job training integrates learning directly into workplace tasks, with novices shadowing or assisting seasoned employees to acquire practical competencies through observation and hands-on practice. Empirical studies indicate that structured OJT can outperform approaches in boosting trainees' to learn and overall , particularly for task-specific skills, as it minimizes the gap between instruction and application. For instance, research comparing the two found higher learning outcomes in OJT groups due to contextual relevance, though it requires capable mentors to avoid inefficiencies. Workshops and seminars extend classroom principles by incorporating , case studies, and discussions to simulate real-world scenarios, enabling participants to practice decision-making under guidance. Effectiveness data from comparative analyses show traditional methods like these achieve knowledge retention rates of 20-30% immediately post-training, declining without reinforcement, underscoring the need for follow-up despite their strengths in social reinforcement and adaptability. However, these approaches often face limits, as they demand and can incur higher logistical costs compared to modern alternatives, with evidence suggesting equivalent or inferior long-term transfer to job performance in some skill domains without supplementary .

Contemporary Digital and Hybrid Methods

Contemporary digital methods in training and development encompass online learning platforms, learning management systems (LMS), and adaptive technologies that deliver scalable, on-demand content. E-learning, facilitated by platforms such as and for Business, allows employees to access modular courses via mobile devices or desktops, with modules averaging 5-10 minutes to align with fragmented work schedules. Adoption surged post-2020, with 68% of organizations reporting increased use of digital tools for skill development by 2023, driven by cost efficiencies—digital training costs up to 60% less than in-person sessions while reaching global workforces. Artificial intelligence (AI) has integrated deeply into these methods, enabling paths through algorithms that analyze user data to recommend content, predict skill gaps, and provide real-time feedback. In 2025, AI-driven systems like adaptive LMS platforms adjust difficulty levels dynamically, improving retention by tailoring to individual paces; for instance, generative AI automates , reducing development time by 50-70% for custom modules. Peer-reviewed analyses indicate AI-enhanced e-learning boosts engagement, with completion rates rising 20-30% compared to static online courses, though effectiveness depends on and algorithmic transparency to avoid biases in recommendations. Immersive technologies, including (VR) and (AR), simulate high-risk or complex scenarios for hands-on practice without physical resources. Corporate adoption reached 39% of enterprises by 2023, with the VR training market valued at USD 9.1 billion that year and projected to grow at 40% annually through 2025, particularly in and healthcare for procedural training. Studies show VR yields 75% retention after six months versus 10% for traditional lectures, attributed to experiential encoding, though hardware costs and limit scalability in smaller firms. Hybrid methods combine digital and in-person elements, such as blended learning where online modules precede facilitated workshops, fostering deeper application. A 2023 meta-analysis of 50+ studies found blended approaches superior to pure classroom instruction, with effect sizes of 0.35-0.50 on knowledge acquisition and behavioral change, outperforming fully online formats in interactive domains. By 2025, 70% of L&D programs incorporate hybrid designs, leveraging tools like Zoom-integrated VR for remote collaboration, though success hinges on robust internet infrastructure and deliberate sequencing to mitigate digital divides in access. Empirical data from corporate implementations reveal hybrid models enhance transfer to workplace tasks by 25%, as synchronous elements reinforce asynchronous digital prep.

Evaluation and ROI

Measurement Frameworks and Metrics

The Kirkpatrick Model, introduced by in 1959, provides a hierarchical framework for assessing effectiveness across four levels, progressing from immediate participant feedback to long-term organizational outcomes. Level 1 measures reaction, capturing trainees' satisfaction and perceived relevance through surveys immediately post-, with metrics such as completion rates and qualitative feedback scores typically aiming for at least 80% positive responses. Level 2 evaluates learning via pre- and post- assessments, quantifying knowledge or skill acquisition, often using tests where gains of 10-20% are considered indicative of basic efficacy. Level 3 assesses , examining on-the-job application through observations or supervisor reports, with success benchmarks including sustained changes in 50% or more of participants within 3-6 months. Level 4 focuses on results, linking to broader impacts like productivity increases or cost reductions, tracked via key performance indicators (KPIs) such as error rate reductions by 15-25% or revenue uplifts attributable to trained staff. Extending Kirkpatrick's approach, the Phillips ROI Model, developed by Jack Phillips in the 1990s, incorporates a fifth level to calculate financial (ROI), addressing the need to isolate training's net economic value amid variables. This level applies the formula ROI = [(Program Benefits - Program Costs) / Program Costs] × 100, where benefits are monetized outcomes from Level 4 (e.g., $50,000 in annual gains from a $10,000 program yielding 400% ROI), adjusted for attribution via control groups or to mitigate overestimation. Phillips emphasizes conservative estimates, converting only Level 3 and 4 data to dollars while excluding intangible benefits like improvements unless quantified separately. Empirical applications, such as those in U.S. federal agencies, report average training ROIs of 15-20% when rigorously isolating effects, though critics note challenges in causal attribution due to external factors like market shifts. Additional metrics complement these frameworks, including from digital platforms (e.g., completion rates >90%, quiz scores >75%) and organizational KPIs like employee retention improvements of 5-10% post-training or reduced turnover costs estimated at $5,000-15,000 per retained employee. The (SHRM) advocates integrating balanced scorecards with leading indicators (e.g., skill certification pass rates) and lagging indicators (e.g., on behavioral change), ensuring metrics align with baseline needs assessments to avoid vanity measures like unchecked satisfaction scores. Validity relies on mixed methods—quantitative data triangulated with qualitative insights—and longitudinal tracking, as short-term gains often decay without reinforcement, with studies showing 70% knowledge retention at 6 months under optimal conditions.
Framework LevelKey MetricsTypical BenchmarksData Collection Methods
Kirkpatrick Level 1: ReactionSatisfaction scores, engagement ratings≥80% positivePost-session surveys
Kirkpatrick Level 2: LearningPre/post test deltas, skill demonstrations10-20% knowledge gainAssessments, simulations
Kirkpatrick Level 3: BehaviorApplication frequency, supervisor evaluations≥50% on-job transferObservations, interviews
Kirkpatrick Level 4: Results metrics, cost savings15-25% improvement in KPIsPerformance records, financial audits
Phillips Level 5: ROINet monetary benefits/costs ratio≥10-15% returnMonetized Level 4 data, control comparisons

Empirical Evidence on Effectiveness

A of 115 experimental and quasi-experimental studies on training effectiveness in organizations found that training programs yield an average of d = 0.63 on outcomes and d = 0.51 on skill-based outcomes immediately post-training, with design features such as practice and feedback enhancing these effects by up to 0.20 standard deviations. Transfer of training to job performance, however, shows more variable results, with a of 89 studies reporting near-zero transfer (r = 0.05) without supportive factors like or work environment support, though these moderators can increase transfer by 0.10-0.30 in . At the organizational level, a 2025 meta-analysis of 42 studies linked higher training investment to improved firm performance metrics, including a corrected of ρ = 0.22 with and ρ = 0.18 with financial outcomes, particularly in contexts with strong transfer climates. Empirical evaluations using the Kirkpatrick model reveal consistently high satisfaction and learning gains (Level 1 and 2 effects averaging 80-90% positive response rates across hundreds of programs), but behavior change (Level 3) occurs in only 20-40% of cases without mechanisms, and results-level impacts (Level 4) on ROI are documented in fewer than 10% of studies due to methodological challenges like isolating training causality. Field studies provide causal evidence: A quasi-experimental of European Social Fund training grants in (2010-2014) showed recipient firms experienced 2.5% higher productivity growth compared to non-recipients, equivalent to €1,200 per trained employee annually, with effects persisting up to two years post-. Similarly, longitudinal data from over 1,000 U.S. firms indicated that a one-standard-deviation increase in hours correlated with 0.20 standard deviations higher innovative performance, though direct ROI calculations averaged 150-250% only for targeted programs like with pre-post controls. These findings hold after controlling for , but generalizability is limited by over-reliance on self-reported data in many corporate evaluations, which inflate perceived effectiveness by 15-20% relative to objective metrics.
Study TypeKey MetricAverage Effect Size/ROIModerators Enhancing Effectiveness
Knowledge/Skills Acquisition (Arthur et al., 2003)Post-training outcomesd = 0.51-0.63Practice fidelity, error-based learning
Training Transfer (Blume et al., 2010)On-job applicationr = 0.05-0.33, supervisor support
Organizational Performance (Jiang et al., 2025)Productivity/Financialρ = 0.18-0.22Organizational , rigor
ROI Case Studies (e.g., ESF Grants)Economic return150-250%Targeted , follow-up
Despite positive aggregate effects, evidence highlights null or negative outcomes in 20-30% of programs lacking alignment with job demands, underscoring that effectiveness hinges on causal pathways like deliberate practice rather than volume of training alone. Peer-reviewed sources consistently outperform industry reports in rigor, as the latter often derive from vendor-funded evaluations prone to .

Common Failures in Assessment

One prevalent failure in training assessment involves overreliance on Level 1 reaction surveys, which measure participant satisfaction but exhibit weak correlations with actual learning outcomes, behavioral changes, or organizational results, often leading evaluators to overestimate program success without verifying deeper impacts. Another common error is the absence of baseline measurements or control groups, making it impossible to attribute post-training improvements to the intervention rather than external factors such as market shifts or individual maturation, as evidenced by persistent challenges in isolating training effects in corporate settings. Assessments frequently neglect long-term follow-up, focusing instead on immediate post-training metrics that decay over time due to lack of , with studies showing that without sustained measurement beyond 3-6 months, true transfer to job performance remains unverified. Self-reported data introduces biases, including social desirability and recall inaccuracies, where participants overstate skill acquisition; empirical reviews indicate that such measures correlate poorly with objective tests or observed behaviors, undermining validity. In ROI calculations, a key pitfall is failing to account for opportunity costs and variables, resulting in inflated returns; for instance, Phillips' extension of Kirkpatrick's model highlights that without rigorous isolation of training's contribution—often via econometric methods—claimed ROIs exceeding 100% lack causal substantiation. Stakeholder misalignment exacerbates failures, as programs designed without upfront agreement on key performance indicators lead to subjective interpretations and disputes over , with reports from practitioners noting this as a primary reason for abandoned evaluations. Small sample sizes and non-representative participants further compromise generalizability, as seen in meta-analyses where underpowered studies yield unreliable effect sizes, particularly for Level 4 outcomes. These shortcomings persist partly due to resource constraints and methodological complexity, with surveys of L&D professionals revealing that only 37% routinely attempt Level 4 evaluations, prioritizing easier metrics despite their limited .

Benefits and Impacts

Organizational Performance Gains

Meta-analyses of empirical studies consistently demonstrate a positive association between employee investments and key organizational indicators, including , profitability, and overall firm . For instance, a 2020 synthesizing data from multiple studies across various contexts found that exhibits a direct positive relationship with organizational , with standardized effect sizes indicating practical significance, and no meaningful distinction in outcomes between and perceived . Similarly, a 2023 reported a significant effect of on work , with aggregated results from primary studies showing improvements attributable to enhanced employee capabilities rather than mere participation. These findings hold across sectors, though effect magnitudes vary by industry, with stronger impacts observed in knowledge-intensive fields where skill application directly influences output. Firm-level further substantiates these gains, revealing that correlates with increases that exceed adjustments, allowing firms to capture net benefits through higher value-added per employee. A study using Japanese data from 2009 to 2018 estimated that intensity positively predicts , controlling for firm size, age, and capital inputs, with supported by instrumental variable approaches addressing selection biases. In developing economies, such as , econometric analyses of firm surveys link expenditures to measurable uplifts, often on the order of 5-10% per additional hour per worker, mediated by reduced errors and faster task completion. Sponsored also fosters outputs through formal programs, informal learning, and self-study, which build creative problem-solving skills; catalysts include unstructured environments promoting ideation, while barriers such as time-limited structured courses can constrain innovative application among trainees. This is evidenced by filings and improvements in trained workforces, contributing to long-term competitive advantages. Return on investment calculations from rigorous case evaluations reinforce these patterns, though variability underscores the importance of alignment with organizational needs. One analysis of a manager development program reported a % ROI, derived from quantified gains in team and reduced turnover costs following behavioral changes post-training. Broader literature reviews confirm that when training targets strategic gaps—such as technical skills or —firms achieve profitability margins 10-20% above non-training peers, with inferred from longitudinal designs isolating training shocks from factors like market conditions. However, these gains are contingent on post-training application and measurement fidelity, as untargeted programs yield .

Individual Skill and Career Advancement

Training and development programs enable individuals to acquire specialized knowledge and competencies, directly enhancing their technical and for improved job performance. indicates that participation in such programs correlates with higher at the individual level, as workers apply learned techniques to daily tasks, reducing errors and increasing efficiency. For instance, formal , supplemented by informal methods and self-study, boosts employees' and technical students' ability to generate innovative suggestions and solutions, particularly in unstructured learning settings that catalyze creativity through autonomy and iterative feedback, though barriers like prescriptive curricula may limit exploration; this demonstrates value to employers and facilitates career progression. Longitudinal studies reveal sustained career benefits from targeted , including elevated employment stability and potential. In a 33-year analysis of economically disadvantaged U.S. , job skills participants experienced 42.6% to 57.9% higher odds of compared to those receiving only basic services, with gains reaching 69.6% in some years, such as a $10,764 increase (64%) in the first year. Systematic reviews further confirm that continuing positively influences work participation and retention, with trained individuals showing retention rates of 67% versus 56% for non-participants, and reduced turnover intentions. These outcomes stem from skill enhancement signaling competence to supervisors, facilitating promotions—formal recipients are more likely to advance internally based on personnel analyses. However, the magnitude of advancement depends on design and transfer ; poorly structured programs may yield minimal long-term gains due to limited application in real-world settings. High-quality, job-relevant , particularly in emerging fields like digital tools, equips individuals for role expansions or lateral moves, mitigating obsolescence risks in dynamic labor markets. Overall, rigorous evaluations underscore 's role in causal pathways to progression, provided it aligns with personal goals and organizational needs.

Criticisms and Controversies

Evidence of Ineffectiveness and Resource Waste

Numerous empirical studies indicate that a substantial portion of corporate expenditures yields minimal or no lasting impact on employee or organizational outcomes. In the , companies allocated approximately $162 billion to training programs in 2012, yet research suggests only about 10% of such initiatives effectively translate into improved workplace behaviors or results, primarily due to insufficient attention to organizational readiness and barriers to application rather than flaws in content delivery. Globally, annual spending on learning and development exceeds $130 billion, with assessments determining that merely 25% of these programs demonstrably enhance , highlighting systemic inefficiencies in and . A core mechanism underlying this waste is the limited transfer of learned skills to on-the-job application. A of 89 studies encompassing predictive factors such as characteristics, intervention design, and work environment characteristics revealed that while immediate learning occurs, post-training transfer—defined as the and of skills in novel contexts—remains modest, with work environment support and to transfer emerging as stronger predictors than individual traits or program features alone. Earlier foundational work by Baldwin and Ford, updated through subsequent reviews, similarly underscores that reactions and gains correlate weakly with behavioral transfer or performance results, implying that much training knowledge dissipates without reinforcement, leading to resource dissipation on non-applicable content. For instance, without addressing contextual constraints like supervisory support or opportunity to practice, training investments fail to yield causal improvements in , as evidenced by persistent gaps between attendance and measurable output changes. Specific domains amplify these concerns, particularly mandatory , which a multidisciplinary of over 100 studies identifies as frequently counterproductive. Such programs often produce short-term self-reported attitude shifts that fade within months, with no sustained behavioral or systemic effects on diversity metrics like minority representation; moreover, coercive formats can provoke backlash, increasing intergroup tension or even reducing marginalized group advancement. Meta-analyses corroborate this, showing negligible impacts on implicit biases or equity, diverting billions toward interventions that, at best, serve symbolic purposes without causal efficacy. Even in management training, where meta-analytic evidence documents positive but attenuated effects—such as a standardized mean difference of 0.18 in management practices and modest productivity gains—limitations persist, including inefficacy of brief programs under one month and weak links between skill acquisition and firm-level profits, underscoring opportunity costs when resources are not targeted at scalable, reinforced interventions. These patterns reflect broader causal realities: training isolated from accountability mechanisms or root organizational dysfunctions constitutes sunk costs, as exemplified by cases where multimillion-dollar safety programs preceded unchanged accident rates due to unaddressed cultural or procedural gaps.

Misattribution of Problems to Training Deficits

In organizational contexts, performance deficiencies are frequently ascribed to insufficient despite that many stem from non-trainable factors, including motivational shortfalls, resource inadequacies, or mismatches in employee selection and job expectations. This diagnostic oversight occurs when managers bypass systematic , opting for as a default intervention perceived as straightforward and politically neutral. Such misattribution persists because training programs offer measurable activities and short-term visibility, diverting attention from deeper causal chains like structures or impediments. The Mager and Pipe performance analysis model, outlined in their 1979 book Analyzing Performance Problems, provides a flowchart-based framework to counteract this by sequentially evaluating whether observed gaps arise from lack of or knowledge—amenable to —or from barriers like unclear expectations, insufficient feedback, or environmental constraints requiring alternative remedies such as process redesign or compensation adjustments. The model explicitly warns against presuming as the , noting that applying it to motivationally driven issues yields negligible results since acquired skills remain unused without corresponding drive. Updated editions, including the 1997 revision, reinforce this through case examples demonstrating how conflating causes leads to ineffective . Richard Swanson's performance diagnosis model extends this logic by categorizing shortfalls into individual aptitudes, organizational support, and environmental influences, insisting on empirical verification before deeming any a deficit. Applied in needs assessments, it reveals that presumed skill gaps often mask systemic failures, such as inadequate tools or supervisory practices, rendering futile. For example, in analyses like those for fire and emergency services, up to half of identified "training needs" trace to non-training origins, including policy ambiguities or equipment limitations, as confirmed through structured audits conducted under federal guidelines in the early 2000s. This pattern of misdiagnosis contributes to broader inefficiencies, as evidenced in human performance technology reviews showing that undiagnosed non-training causes correlate with poor skill transfer rates post-training, often below 20% in uncontrolled environments where root factors persist. Organizations repeating this cycle erode trust in development initiatives, channeling funds into recurrent programs without addressing causal realism, such as aligning rewards with desired behaviors or refining hiring criteria to match innate capabilities. Peer-reviewed syntheses in the field emphasize that rigorous pre-intervention audits, as advocated by these models, avert such waste by prioritizing interventions matched to verified etiologies.

Ideological Biases in Program Design

Training programs in organizational development frequently incorporate elements derived from progressive ideological frameworks, such as diversity, equity, and inclusion (DEI) initiatives that presuppose widespread unconscious biases favoring dominant groups and requiring interventions to achieve proportional representation. These designs often prioritize equity outcomes—defined as equal results across demographic categories—over merit-based skill acquisition, drawing from academic theories that emphasize structural oppression rather than individual agency or behavioral incentives. For instance, unconscious bias training, a staple in many corporate programs since the 2010s, assumes implicit prejudices are ubiquitous and malleable through awareness exercises, yet this premise stems from contested Implicit Association Test (IAT) methodologies whose predictive validity for real-world discrimination remains weak, with correlations to behavior often below 0.1 in meta-analyses. Empirical evaluations reveal that such ideologically driven designs frequently fail to deliver intended behavioral changes and can exacerbate divisions. A 2016 analysis of 830 mandatory sessions found they provoked backlash, increasing resistance to diversity efforts among participants, particularly white males who perceived the programs as accusatory. Similarly, a of 426 studies on bias interventions reported only weak short-term reductions in unconscious , with no sustained impact on explicit attitudes or actions, and some programs heightening intergroup tensions by activating . Researchers attribute this to a design flaw where trainings frame as an inherent moral failing of certain groups, fostering defensiveness rather than , as evidenced by post-training increases in controlled experiments. The prevalence of these biases in program design reflects broader institutional influences, including left-leaning orientations in academia and consulting firms that supply content, where surveys indicate over 80% of social psychologists self-identify as liberal, potentially skewing toward narratives of systemic disadvantage while underemphasizing cultural or motivational factors in gaps. This has led to programs that overlook evidence-based alternatives, such as voluntary skill-focused mentoring, which yield better retention and productivity outcomes without ideological overlay. Critics, including organizational scholars, argue that mandatory ideological components misattribute disparities to rather than testable causes like differences or hiring selectivity, resulting in toward performative rather than causal interventions. In response to these shortcomings, some organizations have shifted toward evidence-centric redesigns, but persistent of flawed models underscores how ideological priors—often insulated from rigorous falsification—compromise program efficacy, diverting funds from apolitical development strategies proven to enhance competence and cohesion.

Barriers to Implementation

Economic and Resource Constraints

Economic constraints on training and development programs primarily arise from high direct costs, including instructor fees, materials, venue rentals, and technology infrastructure, which can exceed thousands of dollars per participant for intensive sessions. In the United States, average corporate spending per learner fell to $774 in 2024, down from $954 the previous year, reflecting broader budget pressures amid economic uncertainty. Large organizations allocated an average of $1,689 per employee, compared to $826 for midsize firms and just $392 for small businesses, highlighting how scale influences affordability. Indirect costs further exacerbate limitations, as employee time diverted from productive work imposes opportunity costs estimated at 20-50% of during training periods, depending on role seniority. Overall U.S. training expenditures declined 3.7% to $98 billion in 2024, with for training staff dropping 4% to $60.6 billion, driven by hiring freezes and reduced hours rather than program elimination. In the , employer spending on has fallen 20% over the past decade, with larger firms cutting 35% and entities 38%, often prioritizing short-term survival over long-term skill building. Resource scarcity compounds these issues, particularly in small and medium enterprises lacking dedicated human resources departments or internal expertise, leading to reliance on external vendors that inflate expenses. Common barriers include inadequate staffing for program delivery and logistical challenges like venue availability, which deter implementation even when budgets permit. During economic downturns, training budgets are frequently the first to face cuts, as evidenced by anticipated reductions cited by 63% of learning leaders in 2024 surveys, despite evidence that such reductions correlate with persistent skills gaps and lower workforce adaptability. These constraints result in subdued participation rates, with only 45% of U.S. employees engaging in formal skill-building activities in 2024, perpetuating underinvestment that hinders organizational competitiveness. While cost-benefit analyses often reveal positive returns from targeted training—such as improved productivity outweighing expenditures in high-ROI programs—immediate fiscal pressures lead decision-makers to defer investments, favoring ad-hoc or self-directed learning over structured initiatives.

Organizational and Cultural Resistance

Organizational resistance to training and development programs often stems from leadership's skepticism regarding return on investment, with executives prioritizing short-term financial metrics over long-term capability building. A 2023 analysis of corporate training challenges identifies limited budgets and difficulties in measuring program impacts as primary barriers, leading organizations to deprioritize investments when quantifiable outcomes like productivity gains are hard to isolate from other variables. This hesitation is compounded by fears of employee turnover post-training, where employers anticipate that enhanced skills enable workers to seek higher-paying opportunities elsewhere, a concern echoed in workforce development discussions as a "brain drain" risk. Empirical data supports partial rationality in this resistance, as studies show only 10-15% of training content typically transfers to on-the-job application, undermining claims of universal efficacy. Cultural factors exacerbate resistance by embedding norms that undervalue continuous learning, particularly in hierarchical structures where development threatens established power dynamics. In organizations with rigid cultures, initiatives face pushback from managers who perceive them as disruptive to workflows or as unnecessary for already proficient staff, with experienced employees often dismissing programs as irrelevant or redundant. This cultural inertia manifests as overt or subtle opposition, such as non-participation or minimal effort, rooted in perceptions of as time-wasting amid pressing operational demands; for instance, extended session durations that interrupt productivity contribute to widespread employee disengagement. Broader resistance to change, including , arises from psychological factors like of incompetence exposure or loss of control, where entrenched practices reinforce aversion to unless models commitment through active involvement. Overcoming such resistance requires aligning programs with organizational priorities, yet persistent cultural mismatches—such as a lack of or real-world applicability—perpetuate cycles of underutilization, with poorly designed training reinforcing doubts about its value. In high-inertia environments, this can result in training being viewed as a compliance exercise rather than a strategic tool, limiting potential benefits like the documented 10-15% uplift from effective implementations. Ultimately, cultural resistance reflects causal realities of mismatched incentives, where without demonstrable, immediate , organizations rationally conserve resources amid evidence of frequent program failures.

Recent and Emerging Developments

AI and Technology Integration

The integration of (AI) into training and development has accelerated since 2023, enabling platforms that tailor content to individual learner needs based on performance data and preferences. By 2025, generative AI tools facilitate rapid course creation and personalization at scale, reducing development time from weeks to hours while incorporating real-time feedback loops. This shift addresses traditional one-size-fits-all models, which empirical studies show yield lower retention rates compared to customized approaches. Adoption rates reflect widespread experimentation, with Docebo reporting a surge from 5% to 95% of companies testing AI in learning and development (L&D) functions over 2024 alone. McKinsey's 2025 analysis indicates nearly all organizations invest in AI workplace tools, though only 1% claim maturity, highlighting implementation gaps such as insufficient and mismatches. Employees receiving AI-specific training report 76% higher efficiency gains from the technology versus 56% for those without, per Melbourne Business School findings, underscoring causal links between targeted upskilling and productivity. Key applications include AI-driven analytics for identifying skill gaps via predictive modeling, which a 2024 ResearchGate study links to 20-30% improvements in training ROI through precise resource allocation. Learning management systems (LMS) enhanced by AI automate assessments and provide micro-learning modules integrated into workflows, as seen in platforms like those from , where onboarding times decreased by up to 40% in pilot programs. Complementary technologies, such as (VR) simulations powered by AI algorithms, enable immersive scenario-based training; for instance, firms reported 75% faster acquisition in hazard recognition tasks using VR-AI hybrids in 2024 trials. Despite benefits, causal evidence reveals limitations: AI systems can perpetuate biases from training datasets, reducing effectiveness in diverse workforces unless mitigated by oversight, as noted in a 2025 ResearchGate review. Privacy concerns under regulations like GDPR have slowed full deployment, with only 72% of enterprises integrating AI into operations by mid-2025 due to hurdles. Emerging developments focus on hybrid models combining AI with facilitation to enhance retention, with SHRM projecting 50% of L&D programs to embed AI seamlessly into daily tasks by 2026.

Adaptation to Skills Gaps and Remote Work

The proliferation of following the , with approximately 40% of U.S. workers in fully or partially remote arrangements as of , has intensified skills gaps in digital fluency, collaboration tools, and self-management, necessitating targeted adaptations in programs. Organizations have responded by prioritizing upskilling in areas like AI integration and virtual communication, as remote setups demand higher proficiency in asynchronous tools and intercultural skills to mitigate isolation and productivity losses. According to the World Economic Forum's Future of Jobs Report 2025, skill gaps represent the primary barrier to , with over 39% of core skills expected to change by 2030, prompting a shift toward scalable digital to address these mismatches in remote environments. Training adaptations have emphasized e-learning platforms and micro-credentials for flexible, on-demand access suited to distributed teams, enabling employees to bridge gaps without disrupting remote workflows. McKinsey's 2025 analysis highlights that digital upskilling, once confined to IT roles, now extends organization-wide to foster adaptability, with surveys indicating that 34% of workers changed jobs between 2020 and 2024 partly due to skill obsolescence in evolving remote contexts. Deloitte's 2025 Human Capital Trends report underscores the "experience gap," where remote work erodes traditional mentorship, advocating for AI-assisted simulations and peer networks to accelerate practical skill acquisition in areas like data analytics and cybersecurity. These methods have shown efficacy in closing gaps, as evidenced by a 49% increase in frontline training participation leading to higher engagement scores in hybrid models. Emerging developments include hybrid skill-building ecosystems that combine virtual reality for immersive remote simulations with predictive analytics to identify gaps proactively, particularly as remote digital jobs are projected to grow 25% to 92 million globally by 2030. However, challenges persist, including reduced informal learning opportunities in remote settings, which Deloitte notes exacerbates entry-level experience deficits amid rapid digital transformation. Empirical data from McKinsey's 2021-2025 surveys reveal that successful programs integrate social-emotional training—such as resilience and virtual etiquette—with technical upskilling, yielding measurable productivity gains in remote cohorts. This causal focus on verifiable outcomes over generic interventions ensures training aligns with causal drivers of remote performance, rather than assuming uniform applicability across demographics or roles. Recent adaptations also incorporate innovative systems to generate innovation through training, such as hackathons, in-company courses, and campus events, which catalyze creative outputs by balancing structured tasks with unstructured exploration, overcoming barriers like motivational deficits or institutional rigidity for trainees and students. University hackathons, as hosted by Cornell University and Florida State University, exemplify systems where participants develop novel solutions leading to patents and ventures via collaborative ideation. Effective partnerships, including triple helix models uniting academia, industry, and government, enhance these efforts through technology transfers and licensing, with evidence from frameworks like those from the Wilson Center showing accelerated commercialization of training-derived innovations.

References

  1. https://www.td.org/talent-development-glossary-terms/what-is-employee-training-and-development
  2. https://ecampusontario.pressbooks.pub/humanresourcesmgmt/chapter/6-1-employee-training-and-development/
  3. https://www.allvoices.co/glossary/training-and-development
  4. https://www.aihr.com/blog/learning-and-development/
  5. https://pmc.ncbi.nlm.nih.gov/articles/PMC10796978/
  6. https://www.researchgate.net/publication/332537797_The_Importance_of_Training_and_Development_in_Employee_Performance_and_Evaluation
  7. https://pmc.ncbi.nlm.nih.gov/articles/PMC4282068/
  8. https://www.tandfonline.com/doi/full/10.1080/1359432X.2024.2319082
  9. https://sloanreview.mit.edu/article/its-time-to-face-the-three-challenges-of-learning/
  10. https://etheses.whiterose.ac.uk/1565/1/uk_bl_ethos_507656.pdf
  11. https://www.emerald.com/er/article/45/7/27/43550/Advance-employee-development-to-increase
  12. https://us.sagepub.com/sites/default/files/upm-binaries/43187_2_The_Organization_of_Work_in_Preindustrial_Times.pdf
  13. https://www.engr.psu.edu/mtah/essays/workers_lives.htm
  14. https://faculty.wcas.northwestern.edu/mdo738/research/delaCroix_Doepke_Mokyr_0317.pdf
  15. https://thekeep.eiu.edu/cgi/viewcontent.cgi?article=1016&context=plan_b
  16. https://moodle.adaptland.it/pluginfile.php/53711/mod_data/content/172105/epstein1998.pdf
  17. https://cepr.org/voxeu/columns/more-family-matters-apprenticeship-and-rise-europe
  18. https://www.sciencedirect.com/science/article/abs/pii/S001449831300003X
  19. https://www.britannica.com/money/history-of-the-organization-of-work/Organization-of-work-in-the-industrial-age
  20. http://www.historyisnowmagazine.com/blog/2024/3/28/impact-of-the-industrial-revolution-on-education-from-factories-to-classrooms
  21. https://factoryworkingconditions.com/history/working-conditions-during-the-industrial-revolution/
  22. https://nationalhumanitiescenter.org/pds/gilded/progress/text3/taylor.pdf
  23. https://www.allencomm.com/2016/04/history-training-development-infographic/
  24. https://www.lean.org/lexicon-terms/training-within-industry-twi/
  25. https://tmep.cis.tennessee.edu/node/378
  26. https://www.td.org/content/td-magazine/looking-back-at-70-years-of-astd
  27. https://www.devlinpeck.com/content/kirkpatrick-model-evaluation
  28. https://emergentchange.net/wp-content/uploads/2017/03/the-past-present-and-future-od.pdf
  29. https://digitalcommons.unl.edu/context/cehsedadfacpub/article/1015/viewcontent/Torraco_ADHR_2016_Early_history.pdf
  30. https://www.talentlms.com/ebook/elearning/history-of-elearning
  31. https://www.dokeos.com/brief-history-elearning/
  32. https://www.walkme.com/blog/evolution-employee-training/
  33. https://finance.yahoo.com/news/corporate-training-market-outlook-report-080500710.html
  34. https://www.ispringsolutions.com/blog/elearning-statistics
  35. https://www.devlinpeck.com/content/elearning-statistics
  36. https://www.mdpi.com/2076-3417/15/10/5424
  37. https://www.sciencedirect.com/science/article/abs/pii/S0747563221004489
  38. https://www.scnsoft.com/blog/digital-transformation-of-employee-training-development
  39. https://www.hr-brew.com/stories/2024/03/25/hr-101-let-s-discuss-the-evolution-of-corporate-learning
  40. https://www.researchgate.net/publication/377967797_FUTURE-PROOFING_THE_WORKFORCE_TRAINING_AND_DEVELOPMENT_IN_THE_DIGITAL_AGE
  41. https://biomedres.us/pdfs/BJSTR.MS.ID.008732.pdf
  42. https://www.researchgate.net/publication/385739930_The_role_of_virtual_reality_in_employee_training_and_development_Mediating_role_of_engagement_and_immersion_moderating_role_of_organizational_culture
  43. https://onlinelibrary.wiley.com/doi/full/10.1002/ace.20546
  44. https://pmc.ncbi.nlm.nih.gov/articles/PMC11008574/
  45. https://files.eric.ed.gov/fulltext/EJ1386100.pdf
  46. https://pmc.ncbi.nlm.nih.gov/articles/PMC4005174/
  47. https://www.researchgate.net/publication/261798593_Motivation_in_training_and_development
  48. https://pmc.ncbi.nlm.nih.gov/articles/PMC12292508/
  49. https://www.cipd.org/globalassets/media/knowledge/knowledge-hub/evidence-reviews/work-motivation-scientific-summary_tcm18-89562.pdf
  50. https://www.scirp.org/journal/paperinformation?paperid=41885
  51. https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1937-8327.2003.tb00287.x
  52. https://pmc.ncbi.nlm.nih.gov/articles/PMC5560428/
  53. https://www.researchgate.net/publication/232458848_The_Effects_of_Feedback_Interventions_on_Performance_A_Historical_Review_a_Meta-Analysis_and_a_Preliminary_Feedback_Intervention_Theory
  54. https://gsehd.gwu.edu/sites/g/files/zaxdzs4166/files/2023-11/barriers-motivation-behavior-performance-workplace.pdf
  55. https://pmc.ncbi.nlm.nih.gov/articles/PMC5113774/
  56. https://pmc.ncbi.nlm.nih.gov/articles/PMC9090977/
  57. https://elearningindustry.com/forgetting-is-failing-reinforcement-learning-workplace-learning-that-doesnt-fade-away
  58. https://pubmed.ncbi.nlm.nih.gov/8793652/
  59. https://www.researchgate.net/publication/323830482_The_Importance_of_Feedback_System_in_Training_Programmes_An_Empirical_Investigation
  60. https://journals.sagepub.com/doi/10.1177/21582440231185523
  61. https://journals.sagepub.com/doi/abs/10.1177/0193841X20923199
  62. https://www.managementconcepts.com/resource/from-feedback-to-action-building-a-continuous-improvement-process-for-training-programs/
  63. https://pmc.ncbi.nlm.nih.gov/articles/PMC7304587/
  64. https://scholarworks.indianapolis.iu.edu/bitstreams/14ae3037-dd1e-4a30-9612-97d55767da74/download
  65. https://olj.onlinelearningconsortium.org/index.php/olj/article/download/810/253/0
  66. https://www.opm.gov/policy-data-oversight/training-and-development/planning-evaluating/
  67. https://www.cdc.gov/training-development/php/about/assess-training-needs-conducting-needs-analysis.html
  68. https://www.emerald.com/jwam/article/17/1/82/1247378/Effects-of-training-needs-assessment-in-enhancing
  69. https://malque.pub/ojs/index.php/mr/article/view/11353
  70. https://pmc.ncbi.nlm.nih.gov/articles/PMC8167940/
  71. https://bmcmededuc.biomedcentral.com/articles/10.1186/s12909-021-02748-y
  72. https://www.uwb.edu/it/addie
  73. https://www.researchgate.net/publication/362910402_Effect_of_Training_Needs_Assessment_on_Employee_Performance_A_Review_Perspective
  74. https://www.aihr.com/blog/addie-model/
  75. https://elearningindustry.com/getting-know-addie-analysis
  76. https://www.td.org/content/newsletter/all-about-addie
  77. https://journals.sagepub.com/doi/10.1177/0258042X251343717
  78. https://www.researchgate.net/publication/287944022_Training_Needs_Assessment_A_Must_for_Developing_an_Effective_Training_Program
  79. https://www.arlo.co/blog/training-delivery-methods
  80. https://flearningstudio.com/types-of-training-delivery-methods/
  81. https://whatfix.com/blog/employee-training-methods/
  82. https://via.library.depaul.edu/cgi/viewcontent.cgi?article=1477&context=csh_etd
  83. https://www.researchgate.net/publication/283788084_Comparison_of_the_influences_of_structured_on-the-job_training_and_classroom_training_approaches_on_trainees%27_motivation_to_learn
  84. https://stacks.cdc.gov/view/cdc/5187/cdc_5187_DS1.pdf
  85. https://digitalcommons.andrews.edu/dissertations/178/
  86. https://research.com/careers/training-industry-statistics
  87. https://www.docebo.com/learning-network/blog/learning-development-trends/
  88. https://www.shrm.org/topics-tools/flagships/ai-hi/the-future-of-learning---development--adapting-to-an-ai-powered-
  89. https://pixovr.com/vr-training-statistics/
  90. https://www.takeaway-reality.com/post/vr-training-and-vr-education-statistics-2024
  91. https://www.sciencedirect.com/science/article/pii/S2666557323000204
  92. https://www.cypherlearning.com/blog/business/learning-and-development-trends-2024
  93. https://pmc.ncbi.nlm.nih.gov/articles/PMC12467614/
  94. https://www.kirkpatrickpartners.com/the-kirkpatrick-model/
  95. https://educationaltechnology.net/kirkpatrick-model-four-levels-learning-evaluation/
  96. https://trainingindustry.com/wiki/measurement-and-analytics/the-kirkpatrick-model/
  97. https://whatfix.com/blog/phillips-roi-model/
  98. https://roiinstitute.net/
  99. https://www.opm.gov/policy-data-oversight/training-and-development/reference-materials/training_evaluation.pdf
  100. https://www.cdc.gov/training-development/php/about/evaluate-training-measuring-effectiveness.html
  101. https://www.shrm.org/labs/resources/measuring-the-roi-of-your-training-initiatives
  102. https://psycnet.apa.org/record/2003-03332-006
  103. https://www.researchgate.net/publication/235975809_Transfer_of_Training_A_Meta-Analytic_Review
  104. https://journals.sagepub.com/doi/abs/10.1177/01492063251327588
  105. https://www.researchgate.net/publication/369972325_Kirkpatrick_Model_and_Training_Effectiveness_A_Meta-Analysis_1982_To_2021
  106. https://www.sciencedirect.com/science/article/abs/pii/S0927537121000919
  107. https://files.eric.ed.gov/fulltext/EJ909874.pdf
  108. https://hbr.org/2023/10/evaluating-roi-on-your-companys-learning-and-development-initiatives
  109. https://www.worklearning.com/2018/11/03/common-mistakes-in-workplace-learning-evaluation/
  110. https://www.forbes.com/sites/kevinkruse/2023/05/17/the-problem-with-lds-beloved-kirkpatrick-model-and-what-to-do-about-it/
  111. https://www.kirkpatrickpartners.com/wp-content/uploads/2024/04/evaluation-blunders-and-missteps-to-avoid-td-magazine-november-2016.pdf
  112. https://www.elcosh.org/record/document/1561/d000132.PDF
  113. https://learninguncut.global/learning-evaluation-avoid-kirkpatrick-traps/
  114. https://www.linkedin.com/advice/1/what-some-common-pitfalls-mistakes-avoid-when-13e
  115. https://www.roiinstitute.net/wp-content/uploads/2018/03/Measuring-ROI-The-ProcessCurrent-Issues-and-Trends.pdf
  116. https://cognota.com/blog/why-its-so-hard-to-measure-roi-in-training-and-development/
  117. https://www.peoplematters.in/article/employee-skilling/avoid-these-crucial-evaluation-mistakes-while-using-the-kirkpatrick-model-19195
  118. https://files.eric.ed.gov/fulltext/EJ1291600.pdf
  119. https://www.hrdive.com/news/learning-training-value-unclear-better-ROI/700001/
  120. https://www.learnupon.com/blog/measure-training-roi/
  121. https://onlinelibrary.wiley.com/doi/abs/10.1111/1748-8583.12284
  122. https://www.researchgate.net/publication/372147390_Meta_Analysis_of_the_Influence_of_Training_on_Work_Productivity
  123. https://napier-repository.worktribe.com/OutputFile/2498843
  124. https://www.sciencedirect.com/science/article/abs/pii/S0889158321000290
  125. https://ijbssnet.com/journals/Vol_11_No_2_February_2020/2.pdf
  126. https://wol.iza.org/uploads/articles/548/pdfs/who-benefits-from-firm-sponsored-training.pdf
  127. https://trainingindustry.com/articles/measurement-and-analytics/measuring-the-roi-of-manager-training-a-case-study/
  128. https://www.researchgate.net/publication/259080013_The_relationship_between_training_and_firm_performance_A_literature_review
  129. https://www.researchgate.net/publication/356328944_The_Impact_of_Training_on_Productivity_and_Wages_Firm_Level_Evidence
  130. https://link.springer.com/article/10.1007/BF03396858
  131. https://pmc.ncbi.nlm.nih.gov/articles/PMC10372812/
  132. https://pmc.ncbi.nlm.nih.gov/articles/PMC10647344/
  133. https://www.forbes.com/sites/hbsworkingknowledge/2016/07/25/companies-waste-billions-of-dollars-on-ineffective-corporate-training/
  134. https://www.businesswire.com/news/home/20200709005535/en/Employers-Wasting-Billions-on-the-Wrong-Training
  135. https://journals.sagepub.com/doi/10.1177/0149206309352880
  136. https://psycnet.apa.org/record/2010-12525-011
  137. https://pmc.ncbi.nlm.nih.gov/articles/PMC8919430/
  138. https://publications.iadb.org/publications/english/document/The-Effectiveness-of-Management-Training-Programs-A-Meta-Analytic-Review.pdf
  139. https://resources.careered.com/LCMSFileSharePreview/Resources/AdobePDF/2270384.pdf
  140. https://www.amazon.com/Analyzing-Performance-Problems-Really-Wanna-How/dp/1879618176
  141. https://hptmanualaaly.weebly.com/mager-and-pipes-model.html
  142. https://www.igi-global.com/viewtitle.aspx?TitleId=49074
  143. https://apps.usfa.fema.gov/ax/sm/sm_0389.pdf
  144. https://epdf.pub/handbook-of-improving-performance-in-the-workplace-the-handbook-of-selecting-and.html
  145. https://pmc.ncbi.nlm.nih.gov/articles/PMC10120861/
  146. https://www.scientificamerican.com/article/the-problem-with-implicit-bias-training/
  147. https://www.psychologytoday.com/us/blog/your-brain-at-work/201706/is-your-companys-diversity-training-making-you-more-biased
  148. https://scholar.harvard.edu/files/dobbin/files/an2018.pdf
  149. https://ocpathink.org/post/independent-journalism/study-finds-dei-training-increases-prejudice
  150. https://musaalgharbi.com/2020/09/16/diversity-important-related-training-terrible/
  151. https://www.realclearscience.com/articles/2020/12/05/research_shows_diversity_training_is_typically_ineffective_652014.html
  152. https://hbr.org/2024/06/research-the-most-common-dei-practices-actually-undermine-diversity
  153. https://www.bbc.com/worklife/article/20210326-the-complicated-battle-over-unconscious-bias-training
  154. https://trainingmag.com/2024-training-industry-report/
  155. https://learnexperts.ai/blog/how-much-do-companies-spend-on-training-per-employee/
  156. https://hrdailyadvisor.com/2024/08/21/how-much-are-companies-spending-on-employee-training-in-the-us/
  157. https://www.lingio.com/blog/cost-of-training-employees
  158. https://neweconomics.org/2024/03/employers-spending-a-fifth-less-on-employee-training-than-a-decade-ago
  159. https://www.getadministrate.com/resources/guides/learning-and-development-trends-report-2024/
  160. https://pmc.ncbi.nlm.nih.gov/articles/PMC8267230/
  161. https://elearningindustry.com/employee-training-statistics-trends-and-data
  162. https://www.gallup.com/workplace/692642/addressing-barriers-blocking-employee-development.aspx
  163. https://trainingindustry.com/articles/strategy-alignment-and-planning/why-cutting-ld-in-economic-uncertainty-is-a-costly-mistake/
  164. https://www.scirp.org/journal/paperinformation?paperid=127999
  165. https://doi.org/10.4236/ojbm.2023.115137
  166. https://www.linkedin.com/pulse/workforce-hermeneutical-paradox-why-employers-invest-dr-fred-1r43c
  167. https://doi.org/10.1177/1534484307303035
  168. https://doi.org/10.1037/0021-9010.88.2.234
  169. https://pmc.ncbi.nlm.nih.gov/articles/PMC8365138/
  170. https://www.yourthoughtpartner.com/blog/resistance-to-change-in-the-workplace
  171. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work
  172. https://www.researchgate.net/publication/378347256_Application_of_Artificial_Intelligence_in_Employee_Training_and_Development
  173. https://mbs.edu/faculty-and-research/trust-and-ai/key-findings-on-ai-at-work-and-in-education
  174. https://www.workhuman.com/blog/ai-for-training-and-development/
  175. https://www.sciencedirect.com/science/article/pii/S2667096824000776
  176. https://www.researchgate.net/publication/389649987_The_Future_of_AI_in_Corporate_Training_Opportunities_and_Challenges
  177. https://www.linkedin.com/pulse/ai-adoption-corporate-training-benefits-challenges-aristeksystems-4vrge
  178. https://www.linkedin.com/posts/carinakohli_flexiblework-futureofwork-leadership-activity-7361291529006518272-aBuI
  179. https://www.weforum.org/stories/2022/03/remote-work-intercultural-skills/
  180. https://www.weforum.org/publications/the-future-of-jobs-report-2025/in-full/3-skills-outlook/
  181. https://www.skillsoft.com/blog/wef-skill-gaps-are-the-biggest-barrier-to-transformation
  182. https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/we-are-all-techies-now-digital-skill-building-for-the-future
  183. https://digital-skills-jobs.europa.eu/en/latest/news/new-mckinsey-co-report-sheds-light-willingness-change-jobs-and-upskill
  184. https://www.deloitte.com/us/en/insights/focus/human-capital-trends/2025/closing-the-experience-gap-through-talent-development.html
  185. https://reports.weforum.org/docs/WEF_Empowering_Frontlines_2025.pdf
  186. https://www.weforum.org/stories/2024/01/remote-global-digital-jobs-whitepaper/
  187. https://www.fm-magazine.com/news/2025/may/experience-gap-when-digital-transformation-outpaces-training/
  188. https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/building-workforce-skills-at-scale-to-thrive-during-and-after-the-covid-19-crisis
  189. https://www.mckinsey.com/industries/public-sector/our-insights/the-upskilling-imperative-required-at-scale-for-the-future-of-work
  190. https://hack.cornell.edu/
  191. https://www.eng.fsu.edu/hackathon
  192. https://www.wilsoncenter.org/publication/triple-helix-approach-innovation
Add your contribution
Related Hubs
User Avatar
No comments yet.