































   Advancements in Agricultural Development 
  Volume 6, Issue 2, 2025 
  agdevresearch.org 

 

1. Suzanna Windon, Associate Professor, Pennsylvania State University, 386 Shortlidge Rd. University Park, PA, 16802, 

sxk75@psu.edu,  https://orcid.org/0000-0002-9103-5123  
2. Carolyn Henzi, PhD Candidate, Pennsylvania State University, 386 Shortlidge Rd. University Park, PA, 16802, 

cmh704@psu.edu,  https://orcid.org/0009-0008-3330-017X 
3. Claudia Schmidt, Associate Professor, Pennsylvania State University, Armsby Building, University Park, 16802, 

czs786@psu.edu,  https://orcid.org/0000-0002-8597-7288 
 

56 

 

Farmers’ Motivation for Learning and Developing New Skills 
 

S. Windon1, C. Henzi2, C. Schmidt3 
 

 
Article History 
Received: October 31, 2024 
Accepted: May 15, 2025 
Published: June 13, 2025 
 
 
Keywords 
farmers; job motivation; motivation 
for learning and developing new skills; 
self-leadership competencies;  
SDG 4: Quality Education 
  

Abstract 
This study utilized an online survey to examine the relationships between 
farmers' self-leadership skills, job motivation, and motivation for learning 
and developing new skills. A self-selected, chain-referral sampling 
strategy, a convenience sampling, was employed, resulting in 59 
responses. The results show statistically significant positive associations 
among the variables. Farmers’ motivation for learning and development 
was moderately associated with job motivation (r = .34, p ≤ .05) and self-
leadership (r = .40, p ≤ .05). A stronger association was found between 
job motivation and self-leadership (r = .59, p ≤ .05). These findings suggest 
that higher motivation is linked to stronger self-leadership competencies 
among farmers. Chi-square analysis indicated a significant association 
between motivation for learning and gender (χ² = 67.31, p ≤ .05), with no 
significant associations found for age, educational level, employment 
status, tenure in farming, farm size, land ownership, or number of 
agricultural commodities produced. The findings suggest that extension 
services should enhance farmers’ motivation for continuous learning and 
skill development through targeted educational interventions. These 
insights should guide future research and practical initiatives, ensuring 
farmers have the necessary skills and support to succeed in an ever-
changing agricultural environment. 

 

mailto:sxk75@psu.edu
https://orcid.org/0000-0002-9103-5123
mailto:cmh704@psu.edu
https://orcid.org/0009-0008-3330-017X
mailto:czs786@psu.edu
https://orcid.org/0000-0002-8597-7288


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Introduction and Problem Statement 
 

This paper contributes to the advancement of agricultural development by providing new 
insights into the factors influencing farmers’ job motivation, self-leadership competencies, and 
motivation for learning and developing new skills, offering practical implications for improving 
agricultural practices and supporting sustainable development. Farmers’ motivation and 
willingness to learn and develop new skills are crucial to adapting to global challenges that 
agriculture faces due to the COVID-19 pandemic, climate change, and a growing population 
(United Nations, n.d.). Implementing improved practices, technologies, and business 
management strategies enables farmers to increase their production yield and sustain 
economically viable agriculture (National Institute of Food and Agriculture, n.d.). Agricultural 
producers desire to be successful, increase their profit, remain competitive, and improve their 
quality of life (Bhatta et al., 2019; Franz et al., 2009). This desire leads farmers to participate in 
educational programming that spans diverse topics across different formats and lengths (Franz 
et al., 2010), mainly when these programs are need-focused (Westbrook et al., 2009). Silvert et 
al. (2022) wrote that agricultural extension enhances the livelihoods of rural individuals and 
communities by building capacity and connecting them to information, technologies, and 
marketing opportunities. Previous literature suggested that extension professionals and 
outreach educators increase farmers’ participation and engagement in extension programs that 
help them learn and develop new skills and foster job motivation (Mills et al., 2018). Limited 
studies examined the relationship between farmers’ self-leadership skills, job motivation, and 
motivation for learning and development. The present study hypothesized that an individual’s 
self-leadership skills, job motivation, and motivation for learning and developing new skills are 
positively correlated. 
 

Theoretical and Conceptual Framework 
 
We propose an integrative framework combining leading theories to explore the relationships 
among self-leadership, job motivation, motivation for learning and development, and 
demographic variables. This approach views learning outcomes as indicators of goal-directed 
behavior. Motivation allows individuals to initiate actions (Hiriyappa, 2008 p. 1)or sustain 
behaviors in particular situations. Research indicates that farmers are highly motivated to learn 
and integrate new skills into their work (Bhatta et al., 2019; Franz et al., 2009). 
 
Self-Leadership 
Self-leadership involves influencing oneself to foster the self-motivation and self-direction 
required for effectiveness (Manz, 1986; Manz & Sims, 1991). It is a continuous process of self-
discovery and behavioral regulation, utilizing strategies to boost self-efficacy, manage actions, 
and pursue meaningful goals (Manz & Neck, 2006). Bandura’s (1991) self-regulation theory 
emphasizes self-observation, judgment, and reaction, aiding individuals in setting realistic goals 
and reinforcing positive behaviors. Self-determination theory (SDT) links motivation to personal 
growth and self-regulation (Deci & Ryan, 2012). Bryant and Kazan (2012) identify four pillars of 

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self-leadership: defining values, reflecting on motivation, planning, and building productive 
habits, which promote purposeful, goal-oriented behavior. 
 
Job Motivation 
Job motivation encompasses forces that drive work-related behavior, both intrinsic and 
extrinsic (Pinder, 2008). Herzberg’s two-factor theory (Herzberg et al., 1959) distinguishes 
between factors causing satisfaction (e.g., achievement) and dissatisfaction (e.g., salary). 
According to Robinson et al. (2003), the most substantial sources of farmers’ satisfaction are 
pride of ownership, making a satisfactory income, self-respect by doing a worthwhile job, 
meeting a challenge, enjoyment of work tasks, and ensuring a future income. Vroom’s 
expectancy theory (1964) links motivation to the belief that effort leads to meaningful rewards. 
Alderfer’s ERG theory (1969) categorizes needs into existence, relatedness, and growth, 
forming a continuum influencing satisfaction. These frameworks highlight how self-leadership 
competencies enhance intrinsic motivation, reduce reliance on external direction, and improve 
work performance (Manz, 2015; Stewart et al., 2019). McCombs (1991) mentions the 
relationship between the willingness to learn and motivation itself, stating that a motivated 
person is a lifelong learner, and a lifelong learner is a motivated person. Hence, farmers’ 
motivation to learn is essential to acquiring new skills, enabling them to be competitive. Manz 
(1986) highlights that self-leadership involves managing tasks with low intrinsic motivation 
through self-imposed strategies and leveraging the inherent motivational value of tasks, 
suggesting a strong relationship between self-leadership and intrinsic motivation in fostering 
more engaged and effective behaviors in organizations. 
 
Motivation for Learning and Development 
Farmers’ motivation to learn stems from intrinsic and extrinsic factors and values. Intrinsic 
motivators include personal satisfaction, curiosity, and self-fulfillment (Deci & Ryan, 1985). 
These factors and values are reflected in Bergevoet et al. (2004), where Dutch dairy farmers 
ranked higher in enjoying farm work, working with animals, and producing a good and safe 
product, rather than the goal of achieving maximum income. For farmers, intrinsic motivators 
and values might involve improving production outcomes or engaging with innovative practices 
(Mills et al., 2018). Lunneryd and Öhlmér (2009) and Willock et al. (1999) sustain that Farmers’ 
values affect their decision-making, shaping how farmers process and pay attention to 
information and forecast consequences, which all precede and successively direct their choices. 
Muri et al. (2020) and Hansen and Greve (2014) highlight that farmers are primarily intrinsically 
oriented and motivated; they emphasize the importance of individual characteristics and non-
monetary benefits in improving farmers’ wellbeing, valuing the nature of work, independence, 
and performance. Franz et al. (2009) reported that farmers from the United States Southeast 
region prefer the following learning formats: hands-on activities (99%), demonstrations (96%), 
and farm visits (94%), followed by field days, discussions, and one-on-one sessions. Farmers 
indicated that they do not prefer game-related activities, comics, role-playing, or radio. 
However, this perception might have changed given recent advances in game-based learning 
(Klit et al., 2018). Extrinsic motivators, such as financial rewards or job security, drive decisions 
to participate in learning programs with clear, practical benefits like profitability or efficiency 
gains (Franz et al., 2009; Ryan & Deci, 2020). Lunneryd and Öhlmér (2009) state that values 

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related to high profitability positively affect how farmers collect and process information in 
their decision-making to engage in learning and innovation. Öhlmér (1998) found that the 
nature of farmers’ values affects their problem detection and searching for options. The 
research underscores the importance of tailoring educational programs to address intrinsic and 
extrinsic motivations to meet farmers’ immediate needs and long-term growth. 
 
Adult Learning Theory 
Andragogy, the study of adult learning, posits that adults learn best when the material is 
relevant, practical, and aligned with their motivations (Knowles, 1980; Knowles et al., 1998). 
Adults are self-directed learners who use personal experiences as resources and focus on 
problem-solving. In agricultural education, effective programs resonate with farmers’ practical 
needs (Franz et al., 2010). High self-leadership skills further reduce the need for external 
motivation, emphasizing intrinsic rewards and self-management (Lovelace et al., 2007; Neck & 
Houghton, 2006). 
 
Relationship Between Motivation and Demographics 
Demographics significantly influence farmers’ motivation to learn and adopt new skills. 
Knowledge and skills are critical for integrating new agricultural practices (Kanyi et al., 2017). 
Gender, age, education, and farm size shape motivation and participation in educational 
programs. For instance, Narine et al. (2019) found that age and technology literacy impact 
farmers’ use of modern tools. Sarie et al. (2023) demonstrated a positive association between 
demographics and the adoption of innovative practices. Meece et al. (2009) indicated that 
gender influences motivation for professional development, with males generally more 
motivated in competitive settings, while females show stronger intrinsic motivation in 
collaborative environments. Recognizing these differences can improve the design and 
effectiveness of professional development opportunities in education. Understanding these 
factors is essential for designing effective outreach programs and fostering sustainable 
agricultural development. 
 

Purpose 
 
This descriptive-associational study assessed Pennsylvania farmers’ self-leadership, job 
motivation, and motivation for learning and developing new skills. Moreover, this study 
determined the relationship between farmers’ motivation for learning and developing new 
skills and farmers’ demographics. The following three research objectives guided this study: (a) 
Describe farmers’ self-leadership competencies, job motivation, and motivation for learning 
and developing new skills; (b) Describe the relationship between farmers’ self-leadership 
competencies, job motivation, and motivation for learning and developing new skills, and (c) 
Describe the relationship between farmers’ motivation for learning and development and 
selected demographic variables.  
 
 
 

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Methods 
 
This study is an offshoot of a more comprehensive study (Windon & Robotham, 2021) approved 
by the Institutional Review Board. The study targeted self-identified Pennsylvania farmers, with 
a sample (n = 59) selected using a self-selected and chain-referral convenience sampling 
approach (Fricker, 2008). Data was collected via an open web page survey, with recruitment 
supported by agriculture-related organizations in Pennsylvania in 2020. Recruitment utilized 
the Penn State Extension website, an online magazine press release, a newspaper, Farm Bureau 
County websites, and the Penn State Extension Facebook page. After excluding incomplete 
responses, the final dataset included 59 out of 91 surveys. A panel of seven experts (including 
educators, administrators, academic faculty, and a graduate student) assessed the survey 
instrument for face and content validity. A pilot study conducted during a three-day agriculture-
related event verified the scale’s reliability. Nonresponse bias was evaluated by comparing 
early (first 25) and late (last 25) respondents based on submission time. A t-test showed no 
significant nonresponse bias (Lindner et al., 2001; Miller & Smith, 1983), confirming that the 
sample represents the study population (see Table 1). However, caution is advised as the 
sample was not randomly selected, limiting generalizability to all Pennsylvania farmers. 
 
Instrumentation  
The research instrument comprised three scales to measure self-leadership competencies, 
motivation for learning and developing new skills, and job motivation. The Self-Leadership 
Competencies Scale included 11 items measured on a five-point Likert scale ranging from 1 
(strongly disagree) to 5 (strongly agree), with a Cronbach’s alpha of .74. Example items were: “I 
easily prioritize tasks during my busy season on the farm.” These scale items were adapted 
from Benge et al. (2011), Bruce and Anderson (2012), Conklin et al. (2002), and others. The 
Motivation for Learning and Developing New Skills Scale was adapted from Llinares-Insa et al. 
(2018). The scale consists of two items using a five-point Likert scale with a Cronbach’s alpha of 
.70. Sample items included: “I like to learn new things about my work, even if it is about small 
details.” Lastly, the Job Motivation Scale contained three items, measured on a five-point Likert 
scale, achieving a Cronbach’s alpha of .82. Example items were: “I take pride in doing my job as 
well as I can.” The scale is derived from Vithessonthi and Schwaninger (2008). 
 
A five-point Likert-type scale was used to collect data for this study, following the guidelines 
outlined by Lindner and Lindner (2024). The true limits of the response categories were defined 
as follows: Strongly Agree = 5.00–4.51, Agree = 4.50–3.51, Neither Agree nor Disagree = 3.50–
2.51, Disagree = 2.50–1.51, and Strongly Disagree = 1.50–1.00. The alpha level for statistical 
significance was set a priori at .05 (Lindner & Lindner, 2024). 
 
We treated independent and dependent variables as interval data. Spearman association 
analysis examined relationships between variables, while chi-squared analysis explored the link 
between farmers’ motivation for learning and their demographics. The questionnaire included 
eight demographic variables represented in Table 1.  
 

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Table 1 
Descriptive Statistics of Farmers’ Demographics  

Items n Frequency Percent 
Gender 54  100.0 
     Male  38 70.4 
     Female  14 25.9 
     I prefer not to say   2 3.7 
Age 55  100.0 
     Under 25  6 10.9 
     25-34  13 23.6 
     35-44  7 12.7 
     45-54  8  14.5 
     55-59  4 7.3 
     60+  17 30.9 
Education level 53  100.0 
     High school  13 24.5 
     Associate’s or Technical Certificate  13 24.5 
     Bachelor’s  21 39.6 
     Graduate degree  6 11.3 
Tenure in farming 55 100 100.0 
     <5 years  12 21.8 
     5-9 Years  10 18.2 
     10-14 Years  8 14.5 
     15-19 Years  3 5.5 
     20-24 Years  4 7.3 
     25+  18 32.7 
Employment status 52  100.0 
     Full-time farm  20 38.5 
     Part-time farm/Seasonal work  9  17.3 
     Work off farm full-time.  16  30.8 
     Work off-farm part-time  6 11.5 
     Work off-farm seasonal  1 1.9 
Farm size 53  100.0 
     Under 5 Acres  3 5.7 
      6-10 Acres  6 11.3 
     11-40 Acres  8 15.1 
     41-60 Acres  3 5.7 
     61-80 Acres  3 5.7 
     81-150 Acres  7 13.2 
     151-250 Acres  8 15.1 
     251-400 Acres  5 9.4 
     Over 400 Acres  10 18.9 
Number of Ag commodities 52  100.0 
     One  9 17.3 
     Two  14 26.9 
     Three  7 13.5 
     Four or more  22 42.3 
Ownership of land 53  100.0 
     Owned land  44 83.0 
     Rented land  9 17.0 

 

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Findings 
 
The first objective of this study was to assess farmers’ self-leadership competencies, job 
motivation, and motivation to learn and develop new skills. The overall mean score for self-
leadership competencies was 3.93 (SD = .49, n = 61), as shown in Table 2. This score falls within 
the Agree range, indicating that farmers moderately agreed on the importance of self-
leadership skills and demonstrated a reasonable level of proficiency. The relatively low 
standard deviation suggests moderate consistency in responses, meaning that most 
participants shared similar perceptions of their self-leadership abilities. Specifically, participants 
indicated greater needs in areas such as balancing work and personal life during peak farming 
seasons, managing stress, making timely decisions, and prioritizing tasks effectively. On the 
other hand, farmers reported higher proficiency in applying their personal values at work, 
working independently, maintaining self-confidence, and achieving business goals. 
 
Table 2 
Farmers’ Self-Leadership Competencies 

Items 
Strongly 

disagree, (%) 
Disagree, 

(%) 

Neither 
agreed or 
disagree, 

(%) 
Agree, 

(%) 

Strongly 
agree, 

(%) M SD 
I can balance my 

professional and 
personal life. 

3(5.0) 14(23.3) 15(25.0) 25(41.7) 3(5.0) 3.18 1.02 

I can manage my 
stress effectively. 

1(1.7) 10(16.9) 17(28.8) 28(47.5) 3(5.0) 3.39 .89 

I can make decisions 
quickly. 

0(0) 8(13.6) 14(23.7) 24(40.7) 13(22.0) 3.71 .98 

I can prioritize tasks.  1(1.7) 2(3.4) 14(23.7) 32(54.2) 10(16.9) 3.82 .82 
I can achieve my 

work-related 
goals. 

0(0) 0(0) 12(20.3) 35(59.3) 12(20.4) 4.02 .64 

I feel self-confident.  1(1.7) 3(5.0) 3(5.0) 30(50.0) 23(38.3) 4.17 .87 
I do my work 

independently. 
0(0) 1(1.7) 1(1.7) 19(32.2) 38(64.4) 4.59 .62 

I apply a set of values 
in the workplace. 

0(0) 0(0) 3(5.0) 18(30.0) 39(65.0) 4.60 .589 

Note. The farmers’ self-leadership scale was measured using a 5-point Likert scale: Strongly Agree = 
5-4.51, Agree = 4.5 -3.51, Neither Agree nor Disagree = 3.5-2.51, Disagree = 2.5-1.51, Strongly 
Disagree = 1.5-1. 

 
The overall mean score for farmers' job motivation was 4.72 (SD = .42, n = 59), as presented in 
Table 3. This score falls within the Strongly Agree range, indicating that farmers expressed high 
job motivation. The higher score suggests that, on average, farmers felt highly motivated in 

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their work, with many reporting a sense of personal satisfaction, pride in their roles, and a 
proactive approach to improving their job performance. The relatively low standard deviation 
of .42 further reinforces this interpretation, as it indicates that the responses were closely 
clustered around the mean, reflecting a strong consensus and consistency in job motivation 
among the participants. Overall, these findings suggest that job motivation is uniformly high 
across the group of surveyed farmers. 
 
Table 3 
Farmers’ Job Motivation 

Items 

Strongly 
disagree 

(%) 
Disagree 

(%) 

Neither 
agreed 

or 
disagree, 

(%) 
Agree 

(%) 

Strongly 
agree 

(%) M SD 
I think of ways of 

doing my job 
effectively. 

0(0) 0(0) 2(3.4) 20(33.9) 37(62.7) 4.59 .56 

I take pride in doing 
my job as well as I 
can. 

0(0) 0(0) 1(1.7) 11(18.6) 47(79.7) 4.78 .46 

I feel a sense of 
personal 
satisfaction when 
I do my job well. 

0(0) 0(0) 1(1.7) 11(18.6) 47(79.7) 4.78 .46 

Note. The farmers’ job motivation scale was measured using a 5-point Likert scale: Strongly 
Agree = 5-4.51, Agree = 4.5 -3.51, Neither Agree nor Disagree = 3.5-2.51, Disagree = 2.5-1.51, 
Strongly Disagree = 1.5-1. 

 
The overall mean score was 4.33 (SD = 0.54, n = 59), as shown in Table 4. This score falls within 
the Agree range, indicating that farmers expressed a high level of motivation to learn and 
develop new skills. The standard deviation suggests a moderate level of variability in responses, 
implying that while most participants were motivated, some variation in perceived motivation 
levels existed within the group.  
 
  

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Table 4  
Farmers’ Motivation for Learning and Developing New Skills 

Items 

Strongly 
disagree 

(%) 
Disagree 

(%) 

Neither 
agreed or 
disagree, 

(%) 
Agree 

(%) 

Strongly 
agree 

(%) M SD 
I view changes as an 

opportunity to learn 
and not as a 
difficulty. 

0(0) 1(1.7) 10(16.9) 30(50.8) 18(30.5) 4.19 .54 

I like to learn new things 
about my work, even 
if it is about minor 
details. 

0(0) 0(0) 1(1.7) 24(40.7) 34(57.6) 4.56 .53 

Note. The farmers’ motivation for learning and development scale was measured using a 5-point 
Likert scale: Strongly Agree = 5-4.51, Agree = 4.5 -3.51, Neither Agree nor Disagree = 3.5-2.51, 
Disagree = 2.5-1.51, Strongly Disagree = 1.5-1. 

 
The second research objective was to describe the relationship between farmers’ self-
leadership, job motivation, and motivation for learning and developing new skills. Table 5 
presents Spearman’s correlation among farmers’ motivation for learning and development, job 
motivation, and self-leadership. The results indicate a statistically significant positive 
association between the variables. Specifically, there is a moderate positive association 
between farmers’ motivation for learning and development and job motivation (r = .34, p ≤ 
.05), suggesting that farmers motivated to develop new skills are also more likely to exhibit high 
job motivation. Additionally, a moderate to strong positive association was found between 
farmers’ motivation for learning and development and self-leadership (r = .40, p ≤ .05), as well 
as between farmers’ job motivation and self-leadership (r = .59, p ≤ .05). These findings suggest 
that farmers with higher motivation for learning and development and those with higher job 
motivation tend also to exhibit stronger self-leadership competencies. 
 
Table 5 
Spearman’s Intercorrelation among Farmers’ Motivation for Learning and Development, Job 
Motivation, and Self-leadership. 

Items 
Farmers’ motivation for 

learning and development 
Farmers’ job 
motivation 

Farmers self-
leadership 

Farmers’ motivation for 
learning and development. 

1   

Farmers’ job motivation. .339* 1  
Farmers’ self-leadership. .403* .592* 1 
Note. *Statistical significance was determined using an alpha level of .05 

 

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The third research objective aimed to assess the association between farmers’ motivation for 
learning and development and various demographic variables. A chi-square analysis was 
conducted to examine these associations, with statistical significance set at p ≤ .05. The study 
revealed that gender was the only demographic variable significantly associated with farmers’ 
motivation for learning and development (χ² = 67.311, df = 42, p = .0108). In contrast, no 
significant associations were found between farmers’ motivation for learning and development 
and other demographic factors such as age, educational level, employment status, tenure in 
farming, farm size, land ownership, and the number of agricultural commodities produced. For 
these variables, p-values were greater than .05, indicating no significant relationships with 
motivation for learning and development. 
 
Table 6 
Chi-square Analysis on Association between Overall Farmers’ Motivation for Learning and 
Development and Selected Demographic Variables. 
Demographic factors Valid cases χ2 df p 
Gender  54 67.31 42 .01 
Age 55 101.29 105 .58 
Educational level  53 65.24 60 .30 
Employment status  52 81.67 80 .43 
Tenure in farming 55 123.99 105 .10 
Farm size 53 153.23 160 .64 
Land ownership 53 15.13 20 .78 
Number of agricultural commodities 

farmers produce 
53 61.07 60 .44 

 
Conclusions, Discussion, and Recommendations 

 
This study explores the relationship between farmers’ motivation for learning and developing 
new skills, self-leadership competencies, and job motivation within Pennsylvania. This study's 
findings align with existing literature, showing that autonomy and intrinsic motivation are 
deeply interconnected, supporting the self-determination theory (Deci & Ryan, 2012) and the 
theoretical alignment with adult learning theory (Knowles et al., 1998), where purposeful, self-
directed individuals are most likely to sustain lifelong learning behaviors. 
 
In this study, farmers demonstrate strong self-leadership skills such as goal setting, self-
confidence, adherence to values, and independent work, supported by the literature (Bryant & 
Kazan, 2012; Hansen & Greve, 2014; Muri et al., 2020; Neck & Manz, 2012). However, 
challenges persist in balancing personal and professional life during peak seasons, particularly 
in stress management, decision-making, and task prioritization; this points to potential risks of 
burnout and other mental health issues during peak farming seasons. Leadership educators and 
human resources practitioners should incorporate modular training based on stress 
management, work-life balance, decision-making, and prioritization strategies (e.g., 
mindfulness-based farming practices, digital time management tools) into Extension programs 

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curricula to address these needs. As Bryant and Kazan (2012) suggest in their four pillars of the 
self-leadership model, incorporating values, reflection, planning, and habits promotes 
purposeful, goal-oriented behavior. Practitioners should incorporate peer-led reflection tools in 
programming that might promote farmers’ goal setting and alignment with core values, as well 
as peer mentoring strategies where seasoned farmers reflect on real-life prioritization and 
decision-making approaches to model adaptive leadership for less experienced peers. By 
enhancing self-leadership skills, farmers can improve personal and professional outcomes 
through greater self-efficacy (Neck & Manz, 2012). The study confirms high job motivation 
among farmers, who take pride in their work and seek effectiveness in their roles. High job 
motivation suggests identity-based occupational commitment, where farmers derive intrinsic 
satisfaction beyond financial gain (Bergevoet et al., 2004; Hansen & Greve, 2014; Muri et al., 
2020). 
 
These findings support Muri et al.'s (2020) study, which identified a positive association 
between farmers’ job satisfaction and motivation. Farmers in Pennsylvania are also strongly 
motivated to learn and develop new skills, perceiving change as an opportunity for growth. 
Strong motivation to learn reflects active engagement in professional development, aligning 
with adult learning theories that emphasize self-direction and intrinsic interest (Knowles, 1980; 
Knowles et al., 1998). These findings align with McCombs’ (1991) assertion that motivated 
individuals are lifelong learners. Furthermore, the study found a positive relationship between 
farmers’ motivation to develop new skills and self-leadership competencies, supporting Bryant 
and Kazan’s (2012) four-pillars self-leadership model. According to Manz (1986), effective self-
leadership enables individuals to manage both inherently motivating and less appealing tasks, 
fostering overall productivity. 
 
In this study, gender was the only demographic variable significantly associated with motivation 
for learning and development. The positive association between farmers’ motivation for 
learning and development, job motivation, and self-leadership further suggests that these 
aspects of motivation are interconnected. These findings highlight the importance of gender in 
shaping farmers' motivations for skill development while underscoring the broader role that 
motivation and self-leadership play in driving farmer success. Furthermore, the lack of 
associations with demographics, except gender, might suggest that motivation is shaped more 
by psychosocial roles and responsibilities than by structural or economic factors, supporting the 
findings of Meece et al. (2009). Thus, incorporating qualitative follow-up studies would help to 
understand the nature of gender differences in motivation for learning and development. 
 
This study is subject to certain limitations. An open survey link utilizing an anonymous response 
format restricts the ability of researchers to track participants and engage in a more detailed 
discussion of the included variables. Moreover, it is challenging to confirm that all respondents 
were exclusively farmers. Another limitation is that the results cannot be generalized to the 
entire population of farmers in Pennsylvania or beyond; they merely represent the participants 
in this study. Additionally, this study found a disproportionate gender distribution of farmers, 
which may impact the study outcomes and interpretation. Gender was the only significant 
association between farmers’ motivation for learning and development and demographics. This 

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finding must be interpreted cautiously, but it opens the possibility of reflecting on cultural 
roles, access issues, or time availability. Despite these limitations, this research underscores the 
significant association among farmers’ self-leadership, job motivation, and motivation for 
learning and developing new skills. 
 
Future studies should explore how demand-driven innovation adoption in agriculture impacts 
farmers’ motivation and learning behaviors. Extension educators should incorporate 
motivational analysis as a common practice in design extension programming. Need-based, 
learner-centered approaches guided by Knowles’ (1980) adult learning theory can be reinforced 
by pre-program diagnostic tools to understand farmers’ dominant motivational drivers, 
whether intrinsic (e.g., innovation) or extrinsic (e.g., profitability). 
 
Silvert et al. (2022) highlighted the importance of addressing gender norms to expand women’s 
access to social capital and learning opportunities. Given the strong gender link, future research 
should prioritize participatory and intersectional studies to design responsive strategies for 
different farmer subgroups. Data-driven decisions can improve gender equity and increase 
program uptake. 
 
Extension programs should strengthen curricula by incorporating self-leadership concepts and 
theories into leadership development training to fill a theoretical and practical gap. 
Incorporating behavioral self-regulation models, such as Bandura’s self-regulation (1991) and 
Bryant and Kazan’s four-pillar model (2012), into extension programming would boost farmers’ 
motivation and skill acquisition but also empower farmers to pursue change proactively. Franz 
et al. (2009) emphasize that farmers prefer hands-on activities, demonstrations, farm visits, 
field days, and discussions. Although game-based learning was historically underutilized, recent 
advancements (Klit et al., 2018) suggest potential for broader acceptance. Gender also 
influences motivation for learning and developing new skills. Meece et al. (2009) note that 
historically, gender norms restricted women’s educational and professional opportunities, 
though significant progress has been made in recent decades. Extension programs should 
continue offering targeted support to foster farmers’ learning and professional growth, 
ensuring their resilience and success in an evolving agricultural landscape. 
 
Summarizing, enhancing agricultural practices, and boosting motivation among farmers 
requires a comprehensive approach that considers both personal and professional aspects of 
farming. The findings from this study suggest that strategies should prioritize comprehensive 
skill development programs aimed at improving job satisfaction, fostering self-leadership, and 
addressing the specific challenges farmers face, particularly around work-life balance and stress 
management. Incorporating gender-sensitive strategies and encouraging a culture of proactive 
learning can help farmers improve their motivation and productivity and ultimately contribute 
to more sustainable farming practices. These insights should guide future research and practical 
initiatives, ensuring farmers have the necessary skills and support to succeed in an ever-
changing agricultural environment. 
 
 

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Acknowledgments 
 
Funding Information: This research was funded by the College of Agricultural Sciences at The 
Pennsylvania State University. 
 
Previous Dissemination: Portions of this research were presented at the 2024 National 
AgrAbility Training Workshop in Atlanta, GA, as a poster presentation and as a distinguished 
research paper at the 2022 American Association for Agricultural Education Annual Conference, 
AAAE, Oklahoma City, OK, and as a poster at the 2022 Association for International Agricultural 
and Extension Education Annual Conference, AIAEE, Thessaloniki, Greece. 
 
Artificial Intelligence: Grammar and style support was provided using Grammarly app which 
incorporates Open AI’s ChatGPT (version GPT-4), which assisted in enhancing the overall clarity 
and flow of the manuscript. All final content was reviewed and approved by the authors to 
maintain accuracy and integrity. 
 
Author Contribution Statement: S. Windon –formulation of overarching research goals, design 
of methodology, validation, quantitative data collection and analysis, writing of manuscript 
including revisions and final publication draft. C. Henzi - writing the literature review of the 
manuscript, including revisions, and editing. C. Schmidt –conceptualization, writing the 
literature review, revision of the manuscript, and editing. 
 

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