Pa ge 1 Pa ge 14 7 American Journal of Human Psychology (AJHP) Trainers’ Characteristics and Trainees’ Motivational Orientation as Predictor of Transfer of Training John Lester Combong1*, Christhoffer Lelis1 Volume 3 Issue 1, Year 2025 ISSN: 2994-8878 (Online) DOI: https://doi.org/10.54536/ajhp.v3i1.5719 https://journals.e-palli.com/home/index.php/ajhp Article Information ABSTRACT Received: July 15, 2025 Accepted: August 18, 2025 Published: September 12, 2025 This study explored how the trainers’ characteristics and the trainees’ motivational orientation influenced the transfer of training among employees in the Financial Technology industry. This work is attached to Sustainable Development Goal (SDG) 8, concentrating on decent work and economic growth. Despite heavy investments in corporate trainings, many organizations struggle to convert training into on-the-job behavior; drawing on Self- Determination Theory, this study tested how trainer characteristics (interaction, attitude, competency) and trainees’ motivational orientation (intrinsic, extrinsic) jointly predict transfer of training among Philippine fintech sales agents using a correlational–predictive design with simple random sampling, validated instruments, and SPSS analyses (Pearson r; multiple regression). Descriptively, trainer characteristics (M = 3.61), motivational orientation (M = 3.66), and transfer (M = 3.67) were moderate. Trainer characteristics strongly correlated with transfer (r = .839, p < .001), as did motivational orientation (r = .906, p < .001); the regression model explained 81.3% of variance in transfer (R² = .813, p < .001), with motivational orientation exerting the larger standardized effect (β = .675, p < .001) compared with trainer characteristics (β = .278, p < .001). Findings extend transfer theory by quantifying the relative contribution of motivation vis-à-vis trainer qualities in a fintech context and offer actionable levers for industrial counseling practice: autonomy- supportive design, relevance framing, structured coaching and feedback, and recognition systems that strengthen internalization, thereby maximizing behavior change at work. Keywords Fintech Sales, Industrial Counseling, Motivational Orientation, Trainer Characteristics, Transfer of Training 1 School of Counseling and Psychology Graduate School, San Pedro College, Davao City, Philippines * Corresponding author’s e-mail: johnl_combong@spcdavao.edu.ph INTRODUCTION Industries consistently face difficulties with the effective transfer of training, which refers on how trainees translate and apply new skills and competencies in their actual work environments. While significant investment has gone into training initiatives, some companies still face problems with how these trainees integrate these skills into their daily professional roles, with only marginal observed improvements in workplace behavior and performance outcomes (Liu et al., 2024). This transfer problem is illustrated by empirical evidence, where knowledge is acquired during training sessions but not applied afterwards (Mehner et al., 2024; Alam et al., 2023). Even though many government and international agencies offer training in the Philippines, effective transfer of training remains a problem. Recent Studies by the PIDS or the Philippine Institute for Development Studies (2025) reveal systemic gaps preventing this. For example, they found that technical vocational education and training (TVET) programs increase participation in the labor market but not job quality or employment outcomes. Also, the World Bank (2018) found that only 3% of TVET participants had access to structured enterprise training, such as TESDA’s Dual Training System (DTS), with inconsistent supervision and monitoring. Local government units also conduct training without readiness assessments or post-training evaluations, which have a limited long-term impact. Training programs not tailored to job functions or industry demands are of limited utility. This is theoretically explained by models such as the Social Learning Theory (Bandura, 1986), which holds that effective skill transfer is mainly dependent on the observational learning and modeling provided by trainers, and the Self-Determination Theory (Ryan & Deci, 2017), which holds that intrinsic psychological needs drive trainee motivation to transfer skills. Empirical research identifies additional transfer problems caused by inadequate post- training support, low motivation of trainees, inadequate alignment of training content with workplace tasks, and low opportunities for practical skill application post- training (Zulkifly et al., 2021; Alam et al., 2023). The commitment of employees is vital to ensure transfer of training for the responsive achievement of organizational goals (Liu et al., 2024). Trainers’ characteristics, including interaction, attitude, and competency, are the attributes and behaviors of those who lead the training, playing a crucial role in translating learned concepts into practical skills (Ambu-Saidi et al., 2024; Lee, 2023; Mehner et al., 2024). Organizations face significant challenges in implementing effective training programs, so factors contributing to those challenges must be addressed (Lee, 2023). Trainees’ motivational orientation, as conceptualized by de Jong et al. (2022) pertains to the internal psychological states that drive an individual’s engagement with and commitment to the learning process (Liu et al., 2024). It encompasses intrinsic Pa ge 14 8 https://journals.e-palli.com/home/index.php/ajhp Am. J. Hum. Psychol. 3(1) 147-160, 2025 and extrinsic motivation (Casey et al., 2021). Engagement leads to learning and higher rates of transfer of training (Casey et al., 2021). Transfer of training, the dependent variable, represents the degree to which trainees effectively apply the knowledge, skills, and attitudes acquired during training to their actual job performance and contribute to organizational objectives (Sarfraz et al., 2021). Supervisor support, peer support, and opportunity to use learning correlate positively with transfer of training (Sarfraz et al., 2021). This study aims to examine how trainers’ characteristics and trainees’ motivation to transfer predict the effectiveness of transfer of training among sales agents at Company A, thereby filling a literature gap by providing empirical evidence on how these factors influence transfer of training. Specifically, the study seeks to describe trainers’ characteristics based on peer support, motivation to transfer, and perceived transfer of training; describe trainees’ motivational orientation based on intrinsic and extrinsic motivation; describe the level of transfer of training concerning trainees’ peer support, motivation to transfer, and perceived transfer of training; determine the relationships among trainers’ characteristics, motivational orientation, and transfer of training; and identify the influence of trainers’ characteristics and trainees’ motivational orientation on the transfer of training. Conversely, the study hypothesizes that there is no significant relationship between trainers’ characteristics and the transfer of training (H₀₁), no significant relationship between trainees’ motivational orientation and the transfer of training (H₀₂), and that trainers’ characteristics and trainees’ motivational orientation do not significantly predict the transfer of training (H₀₃). Globally, this study contributes to the growing body of literature on training effectiveness by emphasizing the dual importance of trainer attributes and motivational readiness in enhancing skill transfer. It reinforces theoretical models such as social learning theory and self-determination theory within the organizational training context. The study advances understanding of how internal and external motivational drivers and instructional quality converge to influence training success. Socially, the study addresses pressing needs in industries that rely heavily on knowledge- based performance and continuous upskilling, such as financial technology companies. Organizations can use the findings to optimize their training designs and improve employee outcomes. HR professionals, corporate and regional trainers, and training program developers may also benefit from actionable insights on how to elevate training efficiency. Lastly, this research offers a foundational reference for future researchers aiming to explore similar variables in other industries or cultural contexts. LITERATURE REVIEW Organizations and industries invest heavily in training, but a persistent “transfer problem” prevents translation of learned knowledge and skills into work practice, limiting performance improvements and return on investment (Summers, 2021; Mehner et al., 2024; Liu et al., 2024). Foundational work shows that initial learning can be solid, but retention and on-the-job application decay without reinforcement, as illustrated by learning and forgetting curves (Gautam & Basnet, 2020; Bisbey et al., 2021). This shortfall—fewer than 10% of training and development expenditures recouped by employers—signals systemic barriers spanning individual, instructional, and organizational domains (Summers, 2021; Ambu-Saidi et al., 2024). Constraints such as limited budgets, weak evaluations, and low participation impede effective transfer (Lee, 2023). Consequently, research has increasingly interrogated trainee dispositions, trainer characteristics, and work environment supports to explain when training applies (Alam et al., 2023; Liu et al., 2024). Even so, critical gaps remain: Studies have not adequately described how individual trainer characteristics - e.g., instructional technique, expertise, interpersonal skill - interact with a trainee’s on to transfer to shape downstream performance - in industrial counseling contexts (Kurniatun et al., 2021; Vaag et al., 2022). Emerging evidence on active retrieval and authentic, high-fidelity learning environments (including VR) offers promising tools to narrow the learning-application divide, yet their mechanisms vis-à-vis trainer behaviors and trainee motivation require elaboration (Kim, 2022; Linden et al., 2023; Sheldon et al., 2023; Harris et al., 2020; Radhakrishnan et al., 2022). Addressing these omissions, the present study examines how trainer characteristics and motivation to transfer jointly and differentially predict transfer of training in industrial counseling, thereby advancing practical strategies to heighten ROI and sustain performance improvements (Hussain et al., 2023; Yafi et al., 2021; Leuhery, 2024; Yimam, 2022; Ichdan, 2024; Aqel & Alkshali, 2022; Forner et al., 2020; Ajjawi et al., 2023). A consistent pattern in the literature links trainer characteristics to trainees’ motivation and, ultimately, to transfer outcomes. Trainers’ subject-matter mastery, instructional design competence, and interpersonal behaviors cultivate confidence, a supportive climate, and perceived relevance—conditions that energize motivation and encourage application of new skills (Hu et al., 2021). Like Bandura, modeling high-quality instructional behaviors (clarity, enthusiasm, engagement, competence) strengthens learning and subsequent work performance (Harris et al., 2020; Drew et al., 2020; Pedram et al., 2021). Complementarily, immersive simulations can extend these effects by offering realistic, low-risk practice with rapid feedback; when fidelity and immersion are high, transfer improves (Gawlik-Kobylińska et al., 2020; Renganayagalu et al., 2021; Drew et al., 2020; Xie et al., 2021). Meta-analytic and comparative evidence further indicates that VR can outperform or match traditional methods in shaping behavior, knowledge retention, and safety outcomes, provided skilled human facilitation remains in place (Nykänen et al., 2020; Kanade & Duffy, 2022; Onososen & Innocent, 2025; Markwell et al., 2023; Pedram et al., 2021). Pa ge 14 9 https://journals.e-palli.com/home/index.php/ajhp Am. J. Hum. Psychol. 3(1) 147-160, 2025 Motivation itself—shaped by both intrinsic and extrinsic factors—predicts whether trainees expend effort to apply learning, persist through obstacles, and generalize skills (Febriyarso & Ruslan, 2021; Li, 2023; Fajri et al., 2022; Ismael et al., 2021; Diwedi & Nema, 2023). However, time and resource constraints for post-training practice often blunt these effects and highlight the need to align trainer behaviors with environmental supports to maintain motivation after the classroom (Scorgie et al., 2023; Juliano & Liew, 2020). In sum, the literature substantiates pathways from trainer characteristics, motivation to transfer, and transfer of training, while pointing to contextual predictor and their correlation that can amplify or dampen these links (Liu et al., 2024). Social Learning Theory provides the study’s central lens: trainees learn by observing credible models, internalizing standards, and regulating performance through self- efficacy; thus, trainer behavior and learning context jointly condition skill acquisition and transfer (Manik et al., 2022; Xie et al., 2021). Its three dimensions of reciprocity - personal, behavioral, and environmental determinants - map directly to trainer qualities, trainee motivation, and workplace affordances and show how modeling, feedback, and supportive climates contribute to long-term application (Mash & Edwards, 2020; Lourenço et al., 2025; Fukamizu et al., 2021; Kumyoung et al., 2024; Rose et al., 2020). Self-Determination Theory (SDT) deepens this account by specifying that satisfaction of autonomy, competence, and relatedness needs fosters autonomous motivation— more persistent and transferable than behavior driven by external contingencies (Moll-Khosrawi et al., 2021; Forner et al., 2020; Vergara‐Morales & Valle, 2021; Shkoler & Kimura, 2020; Li et al., 2022; Gagné et al., 2022; Ellikkal & Rajamohan, 2024). Based on Expectancy Theory, supported by Goal-Setting Theory, trainees apply skills when they believe effort will produce performance and valued outcomes; Equity Theory argues fairness perceptions shape discretionary effort; and feedback focuses on specific, challenging goals as drivers of sustained application (Lokman et al., 2022; Valenzuela et al., 2024; Urhahne & Wijnia, 2023). Social cognitive mechanisms (notably self-efficacy) mediate observation– performance links (Kumyoung et al., 2024). Taken together, SLT explains how trainer modeling and instructional quality seed self-efficacy and observable performance standards; Expectancy, Equity, and Goal setting specify the cognitive–motivational appraisals that convert capability into effortful application; SDT clarifies why autonomy-supportive climates and competence feedback produce durable, self-endorsed transfer. This integrative scaffold aligns with industrial counseling settings, where nuanced facilitation, fair treatment, and structured practice opportunities are pivotal for turning learning into job performance (Ishida & Sekiyama, 2024; Urhahne & Wijnia, 2023; Bandhu et al., 2024; Fuente et al., 2022; Gustiani et al., 2022; Férriz-Valero et al., 2020; Szulawski et al., 2021; Yağar et al., 2025; Cullen & Oppenheimer, 2024; Gao et al., 2024; Smith & Wyness, 2024). To ensure tight alignment between constructs and their measurement, this study operationalizes each variable as follows: first, Trainers’ Characteristics (IV) are assessed using the Learning Environment Inventory adapted by Aziz et al. (2022), which captures interaction, attitude, and skill/competence as instructional qualities that condition transfer (Aziz et al., 2022; Kerins et al., 2021; Mathis, 2020; Ferdilan et al., 2021; Hu et al., 2021; Ismail et al., 2021; Nirtha et al., 2021; Ambarawati, 2020); second, Motivation to Transfer (MV/IV) is measured with instruments grounded in the Unified Model of Task- Specific Motivation that integrate self-efficacy, outcome expectations, and perceived relevance to gauge willingness and effort to apply skills (Yang et al., 2020; Mehner et al., 2024; Liu et al., 2024; Fitria et al., 2023; Toom et al., 2021; Pânişoară et al., 2020); and third, Transfer of Training (DV) is captured through a Modified Transfer of training Survey adapted from Salamon et al., focusing on the application of trained behaviors over time in real work settings, including environmental enablers and constraints (Summers, 2021; Burke-Smalley & Mendenhall, 2020; Alam et al., 2023; Stewart et al., 2020; Liu et al., 2024; Zulkifly, 2022). Consistent with these instruments, Trainers’ Characteristics are defined as the trainer’s expertise, pedagogical skill, communication, and professional demeanor that shape a conducive learning climate and model effective performance (Aziz et al., 2022; Kerins et al., 2021; Hu et al., 2021; Ismail et al., 2021; Nirtha et al., 2021); Motivation to Transfer denotes the trainee’s intention and sustained effort to apply newly acquired knowledge and skills, anchored in perceived utility, confidence, and supportive conditions (Gautam & Basnet, 2020; Pânişoară et al., 2020; Yang et al., 2020); and Transfer of Training refers to how much trained skills are used on the job. This shows up as changes in behavior, better performance, and perceived use of the skills (Summers, 2021; Zulkifly, 2022). At the indicator level, interaction signifies the extent to which the trainer elicits dialogue, facilitates participation, and provides responsive feedback to build engagement and understanding (Mathis, 2020); attitude captures the trainer’s professional disposition—enthusiasm, respect, and support—that shapes trainee receptivity and motivation (Ferdilan et al., 2021; Hu et al., 2021); and skill/ competence denotes the trainer’s mastery of content and pedagogy, coupled with consistent, exemplary conduct that clarifies performance standards (Ismail et al., 2021; Nirtha et al., 2021; Ambarawati, 2020). In parallel, personal study represents self-directed efforts to consolidate and extend learning beyond formal sessions through review and independent practice (Khiat & Vogel, 2022); reflective practice entails deliberate appraisal of application attempts, using feedback to adjust strategies and strengthen self-regulation (Adıgüzel et al., 2023); and structured practice indicates organization- supported, supervised opportunities that provide time, resources, and corrective input to embed skills (Snider Pa ge 15 0 https://journals.e-palli.com/home/index.php/ajhp Am. J. Hum. Psychol. 3(1) 147-160, 2025 et al., 2023). Finally, peer support encompasses coworker encouragement and assistance that reduce barriers and normalize the use of new behaviors at work (Alam et al., 2023; Stewart et al., 2020), whereas perceived transfer of training captures employees’ judgments of the extent and impact of applying trained skills, including efficiency and performance gains (Zulkifly, 2022). The literature points to a mutual benefit: trainers who demonstrate effective practices and create supportive environments boost motivation. This increase in motivation raises the chances of applying skills in real- world situations. After training, high-quality practice settings and support enhance these effects (Sarfraz et al., 2021; Chachar et al., 2022; Harris et al., 2020; Drew et al., 2020). By outlining specific constructs, tools, and indicators related to social learning theory and other motivational theories, this study aims to clarify how the qualities of trainers and motivation work together to aid transfer in industrial counseling. It also seeks to identify areas for practical improvement (Summers, 2021; Liu et al., 2024). MATERIALS AND METHODS This chapter outlines the methodological procedures employed in the study, including the research design, respondents, research locale, data-gathering instruments, data collection procedures, and ethical considerations. The goal is to ensure that the methodology aligns with the research objectives and is grounded in best practices for quantitative research. This study utilized a correlational-predictive quantitative design to investigate the relationship and predictive influence of trainers’ characteristics and task-specific motivational orientation to transfer on the actual transfer of training. A quantitative approach was deemed appropriate as the study aimed to measure and analyze numerical data using statistical techniques. The predictive nature of the research seeks to determine the extent to which independent variables (trainers’ characteristics and motivational orientation) can forecast the dependent variable (transfer of training), aligning with established practices in organizational psychology and industrial counseling (Burke & Hutchins, 2007; de Jong et al., 2022). The respondents of the study were sales agents and field staff of different fintech brands operating in the Philippines. These individuals represent the primary frontliners of the company’s digital consumer lending operations and have undergone formal training sessions aimed at enhancing customer engagement, compliance, and sales performance. Respondents shared common characteristics, such as active employment under Company A’s Philippine branch, exposure to company-led training programs, and performance-based job structures. The study employed a simple random sampling technique to eliminate selection bias and ensure a representative distribution of respondents. Following standard power analysis guidelines (Cohen, 1992), the minimum sample size was determined to achieve sufficient statistical power for correlation and regression analyses. To reflect the diversity of Company A’s operational units, the sample included both newly hired and tenured field agents across various deployment areas in the Philippines. This distribution allowed the study to capture a range of experiences in training and its subsequent transfer to real- world tasks. Respondents were required to have completed at least one formal training program and be actively working during the data collection process. Those on leave, probationary status without training experience, or those who failed to complete the post-training assessment were excluded. All respondents had the right to withdraw from participation at any point, in accordance with ethical research standards. Its strategic focus on the Philippine market, combined with its emphasis on sales performance, agent development, and digital lending makes it an ideal locale for studying training effectiveness. The organization’s rapid expansion and training investment efforts underscore the relevance of investigating how trainers’ characteristics and trainees’ motivation influence transfer of training in a high- performance, fintech-driven sales environment. Three research instruments were utilized in this study, each measuring a distinct construct relevant to the research objectives. The first instrument was the Learning Environment Inventory adapted from Aziz et al. (2022), which assessed Trainers’ characteristics. It was composed of three dimensions: Interaction (e.g., encouragement of participation), Attitude (e.g., trainer enthusiasm and support), and Competency (e.g., subject matter expertise and clarity). Each item in this instrument was rated using a 5-point Likert scale, ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). The second instrument used was based on the Unified Model of Task-Specific Motivation by de Jong et al. (2022), which measured the respondents’ motivational orientation. This instrument was grounded in Self- Determination Theory and included three components: Personal Study, Reflection on Practice, and Formal Training Engagement. Respondents evaluated their internal motivation and perceived value of the training using the same 5-point Likert scale. The third instrument was the Modified Transfer of training Survey, adapted from Salamon et al. (2022), which was designed to assess transfer of training. It focused on three dimensions: peer support, motivation to apply, and perceived transfer of skills. This survey aimed to capture both the behavioral intent and the actual application of newly learned knowledge and skills in the workplace after the training. The data –gathering process followed a systematic approach to ensure reliability and ethical compliance throughout the research. The process began with formal coordination by sending a letter to the Chief Executive Officer (CEO) and the Human Resources (HR) department of Company A. The letter detailed the study’s objectives, procedures, and ethical protocols. Upon approval, the researcher was granted access to the Pa ge 15 1 https://journals.e-palli.com/home/index.php/ajhp Am. J. Hum. Psychol. 3(1) 147-160, 2025 contact details of eligible respondents, specifically sales agents who had undergone relevant training sessions. A list of active sales agents, including their names, email addresses, and deployment locations, was provided by the HR department. From this list, a random sample was selected using a simple random sampling technique to ensure fairness and representativeness. The selected respondents were then contacted via email, where they received an informed consent form outlining their rights, including the voluntary nature of participation, the confidentiality of their responses, and the assurance that their involvement would bear no professional consequences. Once consent was obtained, the research instruments, composed of three standardized questionnaires, were administered electronically. These included tools measuring trainers’ characteristics, task-specific motivational operation, and transfer of training. Instructions were clearly outlined in the digital forms, and follow-up communications were made available to address questions or clarifications. The data collection period lasted for two weeks in August 2025, during which periodic reminders were sent to encourage timely submission of responses. All responses were compiled and exported from the digital platform into Microsoft Excel for initial screening and data cleaning. The final dataset was then transferred to SPSS version 26 for statistical analysis, where each response was coded and organized according to the study’s variable structure. The study employed both descriptive and inferential statistical techniques to analyze the collected data. Descriptive statistics such as mean, standard deviation, and frequency counts were computed to summarize the respondents’ demographic profile and describe the central tendencies and variability of their responses across the three main variables. To examine the relationships between variables, the Pearson Product-Moment Correlation Coefficient was used. This test measured the strength and direction of the relationships between trainers’ characteristics, task- specific motivational operation, and the actual transfer of training. Furthermore, to assess the predictive power of the independent variables, trainers’ characteristics and task-specific motivational operation, a multiple linear regression analysis was performed. This allowed the researcher to determine how much variance in the transfer of training could be explained by the two predictors. In addition, the reliability of each instrument and its subscales was tested using Cronbach’s Alpha. All scales used in the study achieved acceptable reliability scores, indicating that the items within each questionnaire consistently measured the intended constructs. Using RAOSOFT Sample Size Calculator, the sample size was determined as 400 respondents, applying a 95% confidence level and a 4.99% margin of error to ensure representative data. The formula used to calculate the sample size (n) is given by: n = N × Z2 × p × (1 − p)/(N − 1) × e2 + Z2 × p ×(1 − p) where: n = required sample size N = required sample size Z = Z-value (Z=1.96 for 95% confidence level) p = estimated proportion (typically 0.5 for maximum variability) e = margin of error (0.0499 or 4.99%) This research adhered strictly to ethical standards in conducting studies involving human respondents All potential respondents were informed about the nature and objectives of the study through a comprehensive informed consent process. Participation was entirely voluntary, and respondents were assured of their right to withdraw from the study at any point without any adverse consequences. The confidentiality and anonymity of participants were prioritized, with no personally identifiable information included in any stage of data analysis or presentation. Only aggregated data were reported. RESULTS AND DISCUSSIONS This chapter presents the data and the analysis of findings derived from respondents’ answers, addressing the objectives of the study regarding the relationship of trainers’ characteristics and trainees’ motivational orientation to the transfer of training among fintech employees. The overall mean for Trainers’ Characteristics was 3.61 (SD = 0.96), indicating a moderate level across respondents. Within the latent construct, Competency registered the highest mean (M = 3.68, SD = 0.99), followed by Attitude (M = 3.62, SD = 0.98) and Interaction (M = 3.53, SD = 0.99). The subscale standard deviations clustered around 0.98–0.99, suggesting comparable variability across indicators, while the relatively smaller overall SD reflects aggregation at the latent level. Taken together, the pattern implies moderately favourable perceptions of trainers, with slightly stronger views on competency than Table 1: Descriptive Statistics for Trainers’ Characteristics, Trainees’ Motivational Orientation and Transfer of Training Variables SD Mean Descriptive Level Trainers’ Characteristics 0.92 3.61 Moderate Interaction Attitude Competency Trainees’ Motivational Orientation 0.95 3.66 Moderate Intrinsic Motivation Pa ge 15 2 https://journals.e-palli.com/home/index.php/ajhp Am. J. Hum. Psychol. 3(1) 147-160, 2025 on interaction. Results indicate that external incentives may initially motivate trainees, but practical training requires a balanced approach with intrinsic and extrinsic motivators (Kashefian-Naeeini et al., 2024). Understanding how these motivating forces combine to design interventions to increase training efficacy and sustain skill application is important. (Don et al., 2022). Building intrinsic motivation is essential for encouraging deeper learning, better engagement, and effective skill transfer (Näsström et al., 2021). Hence, intrinsic motivation based on personal satisfaction and perceived value is linked to better learning outcomes, long-term behaviour change, and skill retention. (Rubio et al., 2023; Kessels et al., 2024; Li, 2022). On the other hand, while extrinsic motivation can spark initial interest, it often falls short for long-term behaviour change and can lead to shallow skill application (Li et al., 2022; Yusuf, 2021). Therefore, relying too much on extrinsic motivators can weaken intrinsic motivation, resulting in lower engagement and a lack of ongoing application once external rewards are gone (ALİSOY, 2023; Johansen et al., 2023). As a result, this leads to the need to create an environment of intrinsic motivation for long-term transfer of training and professional development within organizations.(Morris et al., 2022). These results indicate that despite acknowledged knowledge and skills of trainers, interpersonal and communication strategies are needed to improve for a better learning environment (Jelińska & Paradowski, 2021). Understanding trainer characteristics is critical. Effective trainers are key to successful organizational learning and employee development (Njuguna et al., 2021). Such perceptions need further analysis. Such data will help identify targeted training interventions to enhance trainer interaction skills/training effectiveness and speed learning transfer. The overall mean for Motivational Orientation was 3.66 (SD = 0.95), also at a moderate level. Among its components, Extrinsic motivation showed the higher mean (M = 3.71, SD = 1.00) relative to Intrinsic motivation (M = 3.61, SD = 0.94). Standard deviations for the indicators ranged from 0.94 to 1.00, indicating wider spread than the IV1 latent SD and suggesting more heterogeneous motivational profiles across individuals. The pattern points to slightly greater endorsement of extrinsic drivers compared to intrinsic ones. The overall mean for Transfer of training was 3.67 (SD = 0.95), indicating a moderate level. The highest indicator mean was Motivation to Transfer (M = 3.73, SD = 1.04), followed closely by Peer Support (M = 3.71, SD = 1.03), while Perceived Transfer of Training was comparatively lower (M = 3.57, SD = 0.94). Indicator-level SDs ranged from 0.94 to 1.04, reflecting moderate dispersion and suggesting meaningful individual differences in transfer- related experiences and perceptions. Overall, respondents reported moderate transfer with slightly stronger motivational readiness than perceived transfer outcomes. Such perceptions need further analysis. Such data will help identify targeted training interventions to enhance trainer interaction skills/training effectiveness and speed learning transfer. Therefore, this gap emphasizes the need to look into workplace factors that help or hinder skill application, as these factors are often ignored yet essential (Bhurtel & Bhattarai, 2023; Kerins et al., 2021). Data showed a huge gap: while trainees plan to use new skills, they fail to put them to work. This indicates an apparent disconnect between the intention to use skills and their actual application. (Liu et al., 2024). This analysis reflects the study’s primary objective of defining the link between key trainer qualities, trainee motivation, and the transfer of training across organizations. It also identifies areas for targeted improvements and employee growth. (Summers, 2021). Table 2 shows the correlation analysis revealed a strong positive relationship between Trainers’ Characteristics and Transfer of Training (r = 0.839, p < .001), indicating that higher perceptions of trainer quality, encompassing interaction, attitude, and competency are associated with greater transfer of training among trainees. Similarly, Trainees’ Motivational Orientation demonstrated a very strong positive correlation with Transfer of Training (r = 0.906, p < .001), suggesting that trainees with higher intrinsic and extrinsic motivation are more likely to apply training in the workplace. Extrinsic Motivation Transfer of Training 0.95 3.67 Moderate Peer Support Motivation to Transfer Perceived Transfer of Training Overall 0.88 3.65 Moderate Table 2: Influence of Trainers’ Characteristics and Trainees’ Motivational Orientation towards Transfer of Training Variables Transfer of Training Pearson's r p-value Interpretation Trainers’ Characteristics 0.839 < .001 Significant Trainees’ Motivational Orientation 0.906 < .001 Significant Pa ge 15 3 https://journals.e-palli.com/home/index.php/ajhp Am. J. Hum. Psychol. 3(1) 147-160, 2025 Both correlations were statistically significant at the 0.001 level, implying that the observed associations are highly unlikely to have occurred by chance. The coefficients indicate that both trainer-related and trainee-related factors contribute substantially to successful transfer of training, with motivational orientation showing a slightly stronger association. These findings indicate competent trainers are necessary, but trainees’ intrinsic motivation is more powerful and lasting for skill transfer to the workplace (Shen & Feng, 2024). Thus, organizations seeking to maximize training effectiveness should foster a motivated workforce and continuously recruit and retain good trainers. This combined attention to trainer quality and trainee motivation is critical to achieve maximum human capital development and organizational performance (Hussain et al., 2023). In addition, ongoing investment in training and development improves individual skills and directly contributes to organizational effectiveness and competitiveness in a dynamic market to ensure its existence and growth (Ismael et al., 2021; Radia & Ibtissem, 2021). This sustained investment ultimately enables employees to self-actualize by acquiring new knowledge and skill sets required to build a learning organization. (Li, 2023). Additionally, robust training evaluation, despite the inherent difficulties due to its often-qualitative benefits, is paramount for demonstrating the impact of such initiatives and critically informing the refinement of future programs (Urbancová et al., 2021). Thus a comprehensive training adequacy approach must include instrumental and non-instrumental dimensions such as motivation and self-esteem to enhance and sustain behaviour change (Shafei & Sameri, 2021). The trainer characteristics and trainee motivational orientation are significant predictors of an effective transfer of training, with trainee motivation is more linked and associated (McAnally & Hagger, 2024).This outcome demonstrates that organizations need to select top trainers and also develop motivational factors in their workforce to maximize training investment returns (Shirvani et al., 2024). Although there has been extensive academic study on transfer of training (Stumbrienė et al., 2023), Organisations remain challenged with ensuring that learned skills are implemented at work. This persistent difficulty indicates a large gap between theoretical understanding and practical application, and calls for a deeper analysis of factors underlying transfer success (Omar et al., 2022). Table 3 presents the regression analysis results examining the influence of Trainers’ Characteristics (TC) and Trainees’ Motivational Orientation (TMO) on Transfer of Training. The model was statistically significant, F= 367, p = .001, with a multiple correlation coefficient of R = 0.902 and R² = 0.813, indicating that approximately 81.3% of the variance in Transfer of Training was explained by the two predictors. Both predictors were statistically significant at the 0.001 level. TMO (B = 0.675, β = 0.675, t = 20.673, p < .001) had a stronger predictive effect compared to Table 3: Influence of Trainers’ Characteristics and Trainees’ Motivational Orientation towards Transfer of Training Predictor Estimate Stand. Estimate SE t p Interpretation Intercept 0.165 0.88 1.873 0.062 TC 0.287 0.278 0.034 8.498 < .001 Significant TMO 0.675 0.675 0.033 20.673 < .001 Significant R = 0.902 R2 = 0.813 F = 367 P = 0.001 TC (B = 0.287, β = 0.278, t = 8.498, p < .001). This suggests that trainees’ motivation—both intrinsic and extrinsic—exerts a greater influence on the likelihood of transferring learned skills to the workplace than trainer- related qualities, although both factors make meaningful contributions to predicting transfer outcomes. The intercept (B = 0.165, p = 0.062) was not statistically significant, indicating that when both predictors are at zero, the baseline level of Transfer of Training would not differ significantly from zero. Overall, the model demonstrates that enhancing both trainer quality and trainee motivation is essential for maximizing transfer of training, with trainee motivation having the larger impact. This finding is consistent with Self-Determination Theory (Deci & Ryan, 1985), which argues that intrinsic and extrinsic motivations are central for sustained behavioural application. Trainees who consider training personally relevant, career-enhancing, and rewarding internally and externally are more likely to seek opportunities to transfer learning. The item statements in the Appendix, such as “I am motivated to use what I learned to improve my job performance” and “I expect recognition for applying my training,” reflect these motivational drivers. Although TC had a negligible relative effect, its influence remains statistically significant. This supports Adult Learning Theory (Knowles, 1980) and transfer frameworks (Baldwin & Ford, 1988), which highlight the role of trainer competence, clarity, responsiveness, and real-world application examples in fostering an environment conducive to transfer. Appendix items regarding “clear explanations,” interactive discussions,” and “ constructive feedback” illustrate how effective trainer behaviors contribute to readiness and confidence in applying learned skills. These results suggest a dual-pronged approach for organizations: First, boost trainee motivation by integrating relevance framing, autonomy-supportive practices, career- linked incentives, and recognition programs into training Pa ge 15 4 https://journals.e-palli.com/home/index.php/ajhp Am. J. Hum. Psychol. 3(1) 147-160, 2025 initiatives. Also, trainer effectiveness can be enhanced through professional development that strengthens technical expertise and interpersonal engagement. Such results support earlier correlational studies showing robust positive associations between predictive factors and transfer of training. They also clarify that trainee motivational orientation dominates trainer characteristics when both are considered. This conclusion agrees with Self-Determination Theory, which holds that autonomously driven motivation based on intrinsic factors predicts sustained behavioural modification and practical skill application better than pure external influences (Chiu, 2022). Though trainer attributes help create a learning environment, the ultimate motivator for skill transfer is often the individual’s desire, commitment, and perceived utility of the acquired knowledge (Snider et al., 2023). Consequently, this suggests that while proficient training delivery is essential, actively cultivating intrinsic motivation through perceived competence, challenge, autonomy, impact, social relatedness, and meaningfulness is imperative for achieving lasting transfer of training (Swiatczak, 2021). Furthermore, autonomous motivation augmented by extrinsic drivers influences individuals to apply new skills, commitment, and persistence. For instance, motivational pathways outlined in Appendix - “desire to improve job performance”, “anticipation of recognition,” “personal interest in the subject matter” - are examples of such motivational pathways. Hence, these results suggest understanding and strategically applying motivational theories in training development and execution is critical to training efficacy and Long-Term skill transfer. (Shen & Feng, 2024). However, despite extensive academic inquiry, few organizations entirely use their training investments and fail to translate learned content into improved workplace performance. (Yimam, 2022). Given the high variance explained (R² = 0.813), these two predictors are powerful levers for driving transfer, and strategic investment in both areas is likely to yield substantial improvements in training ROI. CONCLUSIONS These descriptive results showed that respondents perceived trainers’ statistics and trainees’ orientation moderately. Most trainer-related attributes were competency, followed by attitude and interaction. The inferential findings demonstrated that both predictors- trainers’ characteristics and trainees’ motivation- were significantly and positively correlated with transfer of training, with motivational orientation exhibiting a slightly stronger relationship. These outcomes empirically support the study’s theoretical framework, particularly Sociocultural Theory (Bandura, 1986) and Self-Determination Theory (Ryan & Deci, 2017). All findings suggest that an integrated approach focusing on trainer quality and trainee motivation is essential for maximum transfer of training in organisational contexts. Based on the findings, it is recommended that industries, especially their human resource managers, training developers, and supervisors, strengthen trainer–trainee interaction by equipping trainers with advanced facilitation skills grounded in industrial counselling techniques such as active listening, empathic feedback, and motivational questioning. To deal with the lower ratings for intrinsic motivation, HR managers and training developers should include career counselling components to enable employees to match acquired skills with personal and professional goals while allowing autonomy and creativity in skill application. 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