Work–Study Conflict Stressors and Impacts: A Cross-Disciplinary Analysis of Built Environment Undergraduates

Abstract

With built environment (BE) programs emphasizing industry-based learning through cadetships and work-integrated experiences, students face significant stress in balancing studies and work. The research aims to investigate the relationship between specific stressors encountered by students in various BE disciplines and their subsequent impact on mental health and academic outcomes. An online survey of BE students across Australian universities examined academic and work stressors in architecture, engineering, construction management, property, and planning disciplines. ANOVA analysis compared their intensity, health impacts, and academic outcomes across the disciplines. The study found that academic stressors—self-expectations, test anxiety, and heavy workload—were consistent across BE disciplines. Work-related stressors, including time pressure and work–study balance, were also widespread, with architecture students particularly concerned about career relevance and workplace support. Mental health outcomes showed moderate anxiety and depression across all disciplines, but architecture students reported higher stress levels and greater academic impact. This research sheds light on systemic factors impacting BE students’ well-being and academic performance, emphasizing the need for targeted support. It advocates flexible teaching, enhanced work-integrated learning, and tailored mental health resources. Further study is needed to develop a causal model linking stressors to outcomes and to rethink BE education for better student support and career readiness.

1. Introduction

Many built environment (BE) degree programs, including those in Australian universities, strongly encourage students to work as cadets during their studies to ensure they are industry-ready by the time they graduate [1]. This approach bridges the gap between academic learning and real-world experience, providing students with a practical understanding of the architectural, engineering, and construction industry. As cadets, students rotate through various projects and roles, such as design, cost estimating, site coordination and supervision, and contract administration. This rotational experience is intended to give them a comprehensive, hands-on understanding of the industry, allowing them to develop diverse skills necessary to thrive in their future careers [2]. The hands-on experience gained through these cadetships is invaluable in building a strong foundation in the industry’s technical and managerial aspects. Employers often seek graduates with this kind of practical experience, as it reduces the learning curve when transitioning from the academic environment to the workplace.

While this industry-based learning model is beneficial for developing work-ready graduates, it also poses significant challenges to the well-being of built environment students [3]. The demands of working as a cadet, often alongside a full academic workload, can lead to high-stress levels and burnout. The pressure to excel in both work and educational settings can be overwhelming, particularly when students are expected to balance these responsibilities with personal commitments [4]. This intense workload can negatively impact students’ mental and physical health, leading to burnout and reduced motivation [5]. Moreover, the strain of juggling work and study can result in poor academic performance and, in some cases, even dropout [6]. Students may struggle to meet the demands of their course while also fulfilling the expectations of their cadetship or work. The dual burden can lead to feelings of inadequacy and frustration, eroding their academic confidence and engagement. Over time, this can contribute to declining academic performance as students become increasingly fatigued and dissatisfied. In more severe cases, cumulative stress may cause students to withdraw from their studies, resulting in higher dropout rates [7]. Recent reports from Australia claim that dropout rates of domestic university students from their bachelor’s degrees were at their highest in 2024 at 25% [8].

In recent years, there has been a growing focus on the difficulties faced by undergraduate students in managing both work and study responsibilities. Research on built environment students has primarily explored three major themes: burnout, mental health issues, and coping strategies. A substantial amount of research has examined the role of work–study pressures in contributing to burnout among BE students. For instance, Lingard et al. [9] analyzed the relationship between student employment and burnout, specifically within the context of property and construction programs in Australia. Their subsequent study expanded to compare burnout patterns among Hong Kong and Australian construction students. Similarly, Moore and Loosemore [10] examined burnout among construction undergraduates at a different university in Australia. Bakare et al. [11] examined burnout amongst undergraduates in building technology programs in Nigeria, whereas Jia [12] investigated the influence of burnout on dropout rates amongst architecture undergraduates in Hong Kong. Mental health issues, particularly depression, among BE students have also been increasingly investigated. Loosemore et al. [13] examined the occurrence of depressive symptoms among architectural, construction, and civil engineering undergraduates at an Australian university, alongside the availability of support services. Another area of interest is stress management, with Groen et al. [14] examining how construction students cope with stress and the role of resilience in managing academic demands. Turner et al. [15] carried out an international study analyzing student perspectives on resilience, well-being, and the key factors shaping their experiences across Australia, the United Kingdom, and the United States of America.

While research has focused on burnout, stress, and depression among BE undergraduates managing work–study conflicts, a significant gap exists in comprehensively understanding the diverse stressors they encounter and their impact on health, well-being, and academic performance. Furthermore, there is limited knowledge about how these stressors and their impacts differ across various BE disciplines. Therefore, this study aims to investigate the specific work–study conflict stressors faced by built environment (BE) undergraduate students across different courses and assess their varying impacts on students’ physical and mental health, as well as academic performance. This study’s aim is achieved by addressing the following research questions:

• What specific stressors do BE undergraduate students face when balancing work and study, and how do these stressors vary across different courses?
• How does the conflict between work and study affect the physical and mental health and academic performance of BE undergraduates, and how do these impacts vary across different courses?

The study provides insight into the systemic factors influencing BE students’ well-being and highlights the need for targeted support, including flexible teaching methods, enhanced work-integrated learning, and tailored mental health resources to mitigate work–study conflicts.

2. Theoretical Background

Many universities advocate for students to acquire hands-on industry experience alongside their studies, recognizing that it enhances employability by providing real-world insights and essential skills that complement university learning [16,17,18,19]. Despite these advantages, research signals a rising incidence of well-being concerns among university students, commonly associated with the challenges of balancing study and work commitments [20,21,22,23]. For instance, Zajac et al. [6] found that around 15% of undergraduates leave university in the first year, which raises concerns about student retention. This dropout rate increases to 25% among undergraduate students in Australia [8]. These difficulties are not limited to a particular field but span various disciplines such as nursing, health, architecture, construction, engineering, agriculture, education, and environmental sciences [9,11,12]. In the built environment sector, current research has pointed to various academic and work-related stressors that negatively affect students’ physical and mental health and academic progress, as discussed in the following sections.

2.1. Academic Stressors

The demanding nature of BE courses can impose considerable mental health challenges on students, contributing to stress, anxiety, and depression. Key factors contributing to this stress include the structured nature of the curriculum, exams, and the heavy academic workload. The inflexible course requirements often limit students’ ability to manage their academic responsibilities alongside personal commitments or extracurricular activities. The constant pressure of unnegotiable deadlines can lead to prolonged stress and anxiety.

Examinations, a central component of built environment programs, further intensify stress. The pressure to achieve high scores—critical for academic progression and future career opportunities—can lead to excessive worry and long study hours, often at the cost of students’ health and well-being [24]. Additionally, students frequently manage multiple assignments, projects, and presentations simultaneously, requiring substantial time and effort. The cumulative effect of these tasks can be overwhelming, often leading to burnout and exhaustion.

Some built environment programs utilize a flipped classroom approach, where students engage with course materials before attending class, allowing for more interactive in-class learning [25]. While this method has educational benefits, it can pose challenges if not supported with structured guidance, potentially leading to information overload and increased pressure to self-learn [26]. Furthermore, the competitive nature of built environment disciplines adds to student stress. Many students feel the need to maintain strong academic performance while also managing internships, part-time jobs, and extracurricular commitments, further straining their mental well-being.

In addition to external academic pressures, self-imposed stress, driven by personal expectations and self-perceptions, significantly contributes to heightened academic anxiety [27]. This indicates a strong connection between academic stress and the likelihood of experiencing mental health issues. The cumulative impact of these stressors can lead to an ongoing cycle of anxiety and exhaustion, ultimately undermining both students’ academic progress and well-being.

2.2. Work Stressors

Undergraduates employed in the AEC industry face significant work-related pressures. The industry is known for its demanding nature, with long hours, tight deadlines, and ever-changing work environments [28]. Juggling professional responsibilities with academic obligations forces students to manage multiple roles simultaneously, increasing their stress levels. The need to meet tight project deadlines while keeping up with coursework leaves limited rest time. Furthermore, the unstable feature of AEC work, such as frequent changes in schedules and locations, can disrupt study routines, making it harder to maintain academic progress [29]. Furthermore, the unpredictable nature of AEC work, including repeated schedule and location changes, can disrupt study routines, making it harder to maintain academic performance.

The demanding and fast-paced nature of construction jobs can intensify stress and anxiety, especially for undergraduates who are still honing confidence and professional competencies. The pressure to excel in a competitive, high-pressure industry may cause fear of failure and/or self-doubt. The sharp learning curve and the necessity to rapidly adjust to the workplace norm can be particularly overwhelming for students new to the industry. These work-related challenges, when combined with academic demands, can take a considerable toll on students’ mental health.

Managing academic responsibilities and work demands places a considerable strain on students. The cumulative effects of long working hours, strict deadlines, and high-pressure environments often lead to chronic fatigue, burnout, and a decline in academic performance [3]. These stressors not only affect students’ ability to succeed in their studies but also pose risks to their overall well-being.

It is posited that the increased demands of industrial jobs of built environment students create a perceived imbalance between academic and professional obligations, triggering a stress response. Students’ cognitive appraisals of these stressors, coupled with limited coping resources, are hypothesized to significantly impact their mental health and, subsequently, not only their health and well-being but also their academic performance. Specifically, it is theorized that the chronic stress experienced from managing competing work and study demands will lead to diminished cognitive function, increased anxiety, and reduced motivation, ultimately resulting in a measurable decline in academic outcomes.

2.3. Impact of Stressors on Health and Well-Being

The cumulative effects of academic, work, and personal stressors can result in physical health problems for students, often presenting as stress-related conditions that affect their general lives and well-being. Chronic stress disturbs typical physiological processes, contributing to various health concerns that may worsen without effective management [30]. Common stress-related health issues include sleep problems, musculoskeletal disorders, gastrointestinal problems, and a compromised immune system [31]. Additionally, chronic stress exposure can elevate the risk of mental health issues such as anxiety, depression, and more severe conditions. High stress can lead to mental health symptoms such as panic attacks, burnout, anxiety, substance abuse, self-harm, and suicidal thoughts [32,33,34,35]. If not adequately addressed, these well-being issues can severely affect academic progress and common functioning, potentially resulting in long-term psychological effects.

2.4. Impact of Stressors on Academic Performance

Kamardeen and Sunindijo [36] analyzed the connections between stressors, well-being symptoms, and academic performance among BE postgraduates. Their findings align with the stress-performance inverted U-curve theory, suggesting that moderate stress can enhance performance, whereas both low and high stress levels have detrimental effects. When students experience low levels of stress, they may struggle with motivation and engagement, corresponding to the left side of the curve, where performance declines due to a lack of challenge. On the other hand, high stress levels—especially those stemming from academic and work pressures—can lead to mental health issues such as anxiety and depression, ultimately reducing both performance and well-being.

While manageable levels of stress can drive motivation, chronic stress from academic workloads and professional responsibilities can result in burnout, anxiety, and depression, severely impacting academic outcomes [3,33]. The combined strain of coursework deadlines, demanding AEC industry roles, and personal challenges can push students beyond optimal stress levels, jeopardizing both their academic progress and overall well-being [5]. The cumulative burden of academic and work stressors often correlates with poorer academic performance, reflected in high failure and attrition rates as well as lower pass and completion rates [37]. Research indicates that well-being challenges such as stress, anxiety, attention difficulties, behavioral issues, and depression are strongly associated with reduced academic achievement [5].

2.5. Conceptual Framework

The conceptual framework presented in Figure 1 synthesizes key findings from the literature to guide the study’s aims. Building on this foundation, the study proposes the following hypotheses for empirical evaluation:

• The intensity of academic and work stressors confronting BE undergraduates varies depending on the course of study.
• The effects of work–study conflict on BE undergraduates’ health, well-being, and academic performance vary depending on their course of study.

3. Research Method

The study adopted a positivistic paradigm with a quantitative survey method for primary data collection. This philosophical perspective is deemed more appropriate because the study aimed to capture the experiences of a large body of built environment students enrolled in many universities and conduct comparative analyses. Several similar previous studies that investigated students’ well-being used the same methodology, for example, Turner et al. [15], Sunindijo and Kamardeen [38], and Loosemore et al. [13].

3.1. Survey Instrument

The study questionnaire was designed to gather data on the following aspects:

• Student course information and demographic details;
• Exposure to academic, work-related, and personal stressors;
• Physical health and well-being status;
• Impact of stressors on academic performance.

While course and demographic details were collected directly, responses to other questions were measured on a 5-point Likert scale (never, rarely, sometimes, often, and always). The survey questions were drawn from the comprehensive literature review presented earlier and the research instrument used by Kamardeen and Sunindijo [33,38].

3.2. Survey Administration and Participants

An online survey was administered to undergraduate Built Environment (BE) students across Australian universities from July to October 2024. Following approval from the author’s university Human Research Ethics Committee, universities were contacted to distribute the survey. Informed consent was obtained from all participants, and anonymity and confidentiality were strictly maintained. Altogether, 379 responses were collected, of which 253 were deemed valid for use. According to Louangrath [39], a sample size of 30 to 200 is generally considered adequate for social science studies that collect Likert scale responses. The number of valid responses in this study surpasses this minimum, providing a solid foundation for analysis.

Table 1. Participant details.

	Category	Frequency	Percent
Course	Architecture/design	41	16.2
	Construction management	120	47.4
	Engineering	31	12.3
	Property	17	6.7
	Planning	13	5.1
	Other	17	6.7
	Unspecified	14	5.5
Age	18–24	187	73.9
	25–34	43	17.0
	35–44	14	5.5
	45 and above	9	3.6
Sex	Male	106	41.9
	Female	144	56.9
	Non-binary/third gender	2	0.8
	Unspecified	1	0.4
Category	Domestic student	218	86.2
	International student	35	13.8
Study year	1st year	57	22.5
	Mid years	123	48.6
	Final year	73	28.9
Modules enrolled per semester	1	12	4.7
	2	36	14.2
	3	77	30.4
	4	121	47.8
	5 or more	7	2.8
Assignments submitted per module	1	6	2.4
	2	29	11.5
	3	133	52.6
	4 or more	85	33.6
Mode of study	Face-to-face	114	45.1
	Online	37	14.6
	Hybrid	102	40.3
Weekly work hours	0 h	30	11.9
	Up to 20 h	65	25.7
	20–30 h	60	23.7
	30–40 h	55	21.7
	More than 40 h	43	17.0
Tuition fee payment method	Scholarship	9	3.6
	Earn and pay	39	15.4
	Family support	33	13.0
	Study loan	159	62.8
	Pay from savings	13	5.1
Living expenses payment method	Scholarship	1	0.4
	Family support	88	34.8
	Pay from savings	17	6.7
	Earn and pay	147	58.1

outlines the participants’ course enrollment and socio-demographic details.

The participants were drawn from multiple universities across different states, ensuring diversity in geographic location, institution type, and program specialization (e.g., architecture, construction, urban planning). This enhances the sample’s representativeness. National enrollment statistics indicate that 10,374, 10,825, and 10,652 undergraduate students were enrolled in BE courses in Australia in 2021, 2022, and 2023, respectively [40]. Thus, the study’s sample represents approximately 2.5% of the total population. While some generalizability limitations exist, the sample size meets statistical requirements and provides meaningful insights into sector-wide trends.

Students from seven distinct courses participated in the survey: architecture/design, construction management, engineering, property, planning, project management, double degree, and unspecified. Due to the small sample sizes for project management and double degree participants, these groups were combined and reclassified as “other” in the data table. Nearly half of the respondents are studying construction management, underscoring the importance of examining each course group separately to avoid skewing the findings.

Nearly three-quarters of the participants are under the age of 24 and are likely employed in cadet, intern, or junior professional roles within the industry. The remaining participants are middle-aged or mature students, many of whom may hold full-time positions and have family responsibilities.

A higher proportion of female students participated in the survey, suggesting a positive trend in female enrollment in built environment programs. While this does not definitively indicate a female majority in these courses, it points to a potential increase in female representation in the industry in the near future.

The survey also saw a greater number of domestic students responding, although the proportion of international students was consistent with their usual representation in these programs at Australian universities.

Nearly half of the participants were in second or third year, while first-year and final-year students each represent approximately a quarter of the sample. Since built environment degrees typically span four years, this distribution reflects a fairly balanced representation across academic stages.

Academic load is assessed by the number of subjects and their corresponding assessment requirements. Around 50% of participants enroll in four subjects per semester, with nearly a third opting for three. A smaller proportion takes fewer subjects. In terms of assignments, more than half of the participants submit three per subject, while about one-third submit four or more, indicating that the majority maintain a full academic load. Most students attend classes either in person or in a hybrid format.

Weekly work hours vary, with a comparable number of students working up to 20, 20–30, or 30–40 h per week. A smaller group works 40 or more hours per week, likely balancing part-time studies with full-time work. Approximately two-thirds of participants depend on study loans to cover tuition fees, and a comparable proportion earn and pay their living expenses. About 15% of students work both to cover tuition and living costs, suggesting they likely work full-time while studying.

3.3. Data Preperation

The dataset was pre-processed for two purposes: re-coding Likert scale responses and handling missing values. To facilitate quantitative analyses, the Likert scales used in the survey were assigned numerical coding as follows: never = 1, rarely = 2, sometimes = 3, often = 4, and always = 5. The 253 valid responses were then reviewed, discovering random missing values in certain variables. Addressing missing data is crucial to avoid bias in the results. The expectation maximization (EM) method for data imputation was applied to treat missing data values in the dataset. Kang [41] claimed that both multiple imputation and expectation maximization methods are superior to other approaches for addressing missing data. The EM method was chosen for this study as this technique is directly available in SPSS Version 29.0 and easily implementable.

The internal consistency reliability of the Likert scale used in the questionnaire was assessed using Cronbach’s alpha, which evaluates the extent to which items within each construct consistently measure the same underlying concept. As shown in

Table 2. Internal consistency and reliability test.

Construct	Cronbach’s Alpha Value
Academic stressors	0.847
Work stressors	0.861
Personal stressors	0.819
Physical health impact	0.847
Well-being (DASS-8)	0.933
Impact on academic performance	0.781

, all alpha values exceeded the recommended threshold of 0.70, indicating strong reliability. This suggests that the scales effectively capture the intended constructs, ensuring the robustness of the questionnaire’s measurement framework.

Normality tests were conducted on the items under each construct using the Kolmogorov–Smirnov test, which was preferred over the Shapiro–Wilk test due to the sample size exceeding 50. The resulting p-values were all greater than 0.05, indicating that the dataset follows a normal distribution, thereby satisfying the assumptions of normality for subsequent statistical analyses.

3.4. Analysis Method

Various analytical techniques were applied to the pre-processed data to address the research questions as follows:

• Descriptive statistical analyses and ranking identified the primary academic and work stressors faced by BE undergraduates. These descriptive statistical summaries provide insights into the average trend and variability within the sample [42] and are, therefore, essential for understanding the data distribution related to stressors.
• ANOVA tests assessed how students’ experiences with stressors, health and well-being outcomes, and academic performance differ due to the course type. ANOVA is a powerful method for identifying statistically significant differences across multiple groups, providing deeper insights into subgroup dynamics within the sample [43]. It is particularly well suited for analyzing variations in stressors, psychological conditions, and academic performance based on student characteristics.

4. Findings

The study’s findings are presented here under appropriate headings.

4.1. Academic Stressors for BE Students

Table 3. ANOVA test results for academic stressors.

Academic Stressor	Overall		Course Comparison
			Architecture/ Design		Construction Management		Engineering		Property		Planning		Other		Unspecified		ANOVA Results
	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	F	p-Value
1. Self-expectations of high performance	4.13	0.943	4.20	0.980	3.98	1.029	4.06	0.727	4.18	0.883	4.46	0.877	4.53	0.514	4.43	0.852	1.580	0.153
2. Anxiety about underperforming in studies	3.94	1.033	4.17	1.046	3.70	1.074	3.94	0.998	4.35	0.786	4.15	0.899	4.18	0.883	4.29	0.914	2.457	0.025
3. High academic demands	3.74	0.961	3.93	0.959	3.58	0.967	3.74	0.893	3.94	0.899	3.69	1.109	4.06	0.748	3.93	1.141	1.331	0.244
4. Worried or anxious about tests/exams	3.55	1.173	3.59	1.072	3.38	1.237	3.68	0.979	4.29	0.920	3.69	1.032	3.35	1.412	3.93	1.072	2.059	0.059
5. Not enough time for academic work due to work or social activities	3.47	1.010	3.54	1.075	3.48	1.045	3.26	0.930	3.76	0.831	3.23	1.092	3.53	0.874	3.50	1.019	0.627	0.709
6. Problems when doing group assignments	3.31	1.084	3.12	1.053	3.38	1.132	3.03	1.048	3.76	0.970	3.15	0.801	3.24	1.091	3.55	1.083	1.317	0.250
7. Disappointment with current performance	3.11	1.218	3.22	1.275	2.95	1.215	3.06	1.237	3.59	0.939	3.00	1.291	3.18	1.185	3.64	1.216	1.326	0.246
8. Nervous about making class presentations for assignments	3.03	1.278	3.17	1.202	2.96	1.305	2.74	0.999	3.06	1.519	3.69	1.109	3.00	1.323	3.29	1.541	1.088	0.370
9. Challenges in finding suitable resources for learning/assignment	2.98	0.947	3.02	0.851	2.87	1.053	3.00	0.894	3.35	0.606	2.85	0.689	3.06	0.966	3.29	0.825	1.051	0.393
10. Difficulties in understanding assessment requirements	2.97	0.940	3.15	0.882	2.76	0.926	2.90	0.978	3.35	0.702	3.00	0.707	3.65	0.996	3.14	1.027	3.496	0.002
11. Difficulties in understanding subjects or pre-recorded lectures	2.92	0.924	2.83	0.738	2.83	0.938	3.16	1.036	3.35	0.931	2.69	0.947	2.82	0.951	3.14	0.864	1.532	0.168
12. Difficulties in adapting to new/different methods of learning	2.77	0.922	3.02	0.961	2.68	0.954	2.84	1.036	2.94	0.899	2.69	0.751	2.59	0.712	2.86	0.535	1.005	0.423
13. Inadequate support from lecturers to solve academic problems	2.68	1.114	2.54	1.227	2.58	1.081	2.87	1.258	3.35	1.222	2.46	0.660	3.06	0.748	2.50	1.019	1.965	0.071
14. Challenging administrative matters	2.67	1.244	2.41	1.204	2.71	1.191	2.52	1.208	3.06	1.345	2.77	1.363	2.76	1.393	2.79	1.528	0.709	0.643
15. Conflict with fellow students	1.98	0.929	1.88	0.842	1.97	0.978	1.99	0.991	2.00	1.000	1.85	0.689	2.35	0.862	1.93	0.829	0.590	0.738

depicts the outcomes of an ANOVA analysis conducted to examine the academic stressors experienced by built environment (BE) students in Australia. This analysis compares stressor experiences across students from different BE courses to determine if there are statistically significant differences. The hypotheses tested are as follows:

• Null Hypothesis (H₀): There are no statistically significant differences in academic stressor experiences among students enrolled in different BE courses.
• Alternative Hypothesis (H₁): There are statistically significant differences in academic stressor experiences among students enrolled in different BE courses.

If the ANOVA test results in a p-value less than the significance level (α = 0.05), the null hypothesis is rejected in favor of the alternative hypothesis. Otherwise, the null hypothesis is retained [43]. Based on the analysis, except for two academic stressors, others yielded p-values greater than 0.05 (see Table 3), indicating no significant differences across courses. The two exceptions are as follows:

• Difficulties in understanding assessment;
• Anxious about underperforming in studies.

These results suggest that the remaining 13 academic stressors are experienced with similar intensity across all seven courses. For the stressor “difficulties in understanding assessment”, construction management and engineering students conceded lower mean values than students in other courses. Similarly, construction management students had the lowest mean value for “anxious about underperforming in studies”. In contrast, property students recorded the highest mean values for these two stressors.

In the absence of significant differences in academic stressor experiences across courses, key academic stressors were identified based on their overall mean values to guide pedagogical strategies. Stressors with mean values exceeding 3.0—the midpoint on the Likert scale employed—were selected to reflect their intensity. Table 3 lists the academic stressors in descending order based on their overall mean values. Six academic stressors with mean values above this threshold were identified as follows:

• Self-expectation of high performance;
• Anxious about underperforming in studies;
• High academic demands;
• Anxious about tests/exams;
• Insufficient time for academic work due to work or social commitments;
• Challenges with group assignments.

Three of these stressors are internal to students (self-expectation, anxiety about performance, and test-related anxiety), while high academic demands and group work issues stem from course design, and insufficient time results from work–study conflicts. These stressors may interact, potentially reinforcing each other and collectively contributing to psychological distress.

4.2. Work Stressors for BE Students

Table 4. ANOVA test results for work stressors.

Work Stressors	Overall		Course Comparison
			Architecture/ Design		Construction Management		Engineering		Property		Planning		Other		Unspecified		ANOVA Results
	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	F	p-Value
1. Difficulties in balancing study and work demands	3.73	1.053	3.81	1.144	3.71	1.073	3.48	0.923	3.82	1.185	3.92	0.862	3.70	1.046	4.07	0.917	0.679	0.666
2. Study interferes with paid work	3.33	1.190	3.41	1.240	3.29	1.190	3.14	1.176	3.53	1.007	3.15	1.144	3.24	1.097	3.79	1.477	0.671	0.674
3. Excessive workload	3.22	1.145	3.33	1.151	3.30	1.142	3.05	1.083	3.29	1.105	2.92	1.188	2.92	1.234	3.07	1.269	0.657	0.685
4. High time pressure at work	3.09	1.237	2.89	1.311	3.30	1.200	2.97	1.278	2.65	1.222	2.92	1.038	2.85	1.248	3.07	1.328	1.324	0.247
5. Doubts that study may not contribute to career improvements	2.98	1.284	3.51	1.207	2.85	1.300	2.40	1.128	3.41	1.228	2.85	0.899	2.92	1.125	3.43	1.604	3.220	0.005
6. Doubts about finding a job after graduation	2.90	1.339	3.46	1.187	2.62	1.311	3.12	1.443	3.35	1.272	2.31	1.032	2.60	1.179	3.57	1.453	3.977	0.001
7. The tasks you perform do not match your skills (underuse of skills or over expectations)	2.70	1.131	2.70	1.145	2.69	1.197	2.70	1.154	2.71	0.849	1.87	0.812	3.06	0.899	3.21	0.975	1.972	0.070
8. Inflexible work schedule	2.51	1.259	2.41	1.247	2.75	1.279	2.41	1.257	2.00	1.000	1.92	0.954	1.77	0.842	3.00	1.468	3.197	0.005
9. Insufficient pay for the work you do	2.29	1.256	2.23	1.119	2.38	1.303	2.12	1.279	2.18	1.590	1.85	1.068	2.26	0.902	2.57	1.342	0.629	0.707
10. Job insecurity/uncertainty	2.21	1.156	2.44	1.226	2.16	1.149	2.24	1.239	1.94	0.899	2.08	1.038	1.91	0.935	2.64	1.393	1.006	0.422
11. The workplace does not appreciate/support university studies	2.18	1.233	2.41	1.118	2.23	1.287	1.98	1.215	1.82	0.728	1.69	1.032	1.60	0.875	3.00	1.617	2.767	0.013
12. Lack of knowledge or information to perform your work	2.05	1.029	1.82	0.878	2.18	1.109	1.92	1.140	2.24	0.831	2.08	0.760	2.06	1.029	1.71	0.825	1.114	0.355
13. Low support at work from peers and management	1.99	1.032	2.11	0.979	2.04	1.073	2.03	1.168	1.71	0.772	1.92	0.641	1.66	1.003	1.93	1.141	0.664	0.679
14. Poor relationship with supervisors/colleagues	1.85	0.975	1.95	0.913	1.83	0.926	1.93	1.261	1.47	0.624	2.00	0.913	1.46	0.614	2.21	1.424	1.402	0.214
15. Bullying and harassment at work	1.40	0.760	1.46	0.703	1.43	0.760	1.54	1.058	1.24	0.437	1.00	0.000	1.34	0.594	1.43	0.938	0.996	0.428

presents the ANOVA analysis results, examining work-related stressors faced by BE undergraduates in Australia, comparing stressor experiences across various BE courses to identify statistically significant differences. The survey assessed the prevalence of 15 work stressors, with results indicating no statistically significant differences for 11 of these stressors (p-values > 0.05). However, four work stressors showed significant variation among student groups, with p-values below 0.05. Specifically, construction management students reported “inflexible work schedule” as a higher stressor, while architecture students rated the following three stressors higher:

• Doubt about finding a job after graduation;
• Concerns that their studies may not contribute to career advancement;
• Lack of workplace appreciation or support for university studies.

Additionally, Table 4 lists the work stressors in descending order based on their overall mean values. Key work stressors were identified based on overall mean values. Stressors with mean values above 3.0—the average of the Likert scale applied—were considered significant due to their intensity. Four stressors exceeded this threshold:

• Difficulties in balancing study and work demands;
• Study interference with paid work;
• Excessive workload;
• High time pressure at work.

These stressors likely have interconnected dynamics, potentially reinforcing one another and collectively contributing to psychological distress. Conversely, stressors associated with interpersonal relationships at work, including low support from peers and management, poor relationships with supervisors or colleagues, and experiences of bullying and harassment, received lower ratings. This indicates that BE students generally experience supportive workplace environments in their cadet or intern roles.

4.3. Mental Well-Being of BE Students

The well-being of BE undergraduates was assessed by means of the DASS-8 scale [44], which encompasses eight markers—two for stress, three for anxiety, and three for depression—and also offers a severity ranking method for symptoms based on cumulative scores. The severity thresholds were adjusted to align the DASS-8 with the 5-point Likert scale deployed in this research (compared to the original 4-point scale, ranging from 0 to 3). The adjusted severity levels are shown in

Table 5. Well-being severity ranking.

Well-Being Symptom	Severity Levels and Rating Interval
	Normal	Moderate	Severe
Stress	1–3	4–6	7–10
Anxiety	1–5	6–10	11–15
Depression	1–5	6–10	11–15

.

Table 6. ANOVA test results for well-being.

Well-Being	Overall		Course Comparison
			Architecture/ Design		Construction Management		Engineering		Property		Planning		Other		Unspecified		Overall		ANOVA Results
	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	F	p-Value
1. Depression	8.35	3.399	8.93	3.416	7.67	3.323	8.41	3.586	9.38	3.068	9.54	3.205	8.68	3.206	9.64	3.692	8.35	3.399	1.917	0.079
2. Anxiety	8.31	3.435	9.11	3.325	8.02	3.601	7.42	2.998	8.51	2.974	9.77	3.140	8.14	3.530	9.14	3.505	8.31	3.435	1.423	0.206
3. Stress	6.72	2.143	7.13	1.700	6.49	2.320	6.13	1.783	6.82	2.205	8.15	1.573	6.50	2.159	7.64	2.134	6.72	2.143	2.397	0.029

presents the results of an ANOVA analysis that examines well-being among BE students in Australia, comparing perceived stress, anxiety, and depression across students in different BE courses to determine statistically significant differences. Results indicate no statistically significant differences in perceived anxiety and depression across courses, with p-values above 0.05 and mean values in the moderate intensity range (6–10). However, perceived stress shows a statistically significant variation among courses, with a p-value less than 0.05. Students enrolled in architecture/design and planning degrees report higher stress levels, categorized as severe, whereas students in other courses experience moderate stress levels.

4.4. Physical Health of BE Students

Table 7. ANOVA test results for health.

Health (Ranked as per Severity Intensity)	Overall		Course Comparison
			Architecture/ Design		Construction Management		Engineering		Property		Planning		Other		Unspecified		ANOVA Results
	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	F	p-Value
1. Feeling tired or having low energy	3.82	1.030	4.14	0.874	3.72	1.109	3.47	1.049	4.09	0.615	4.00	0.577	4.01	1.119	3.86	1.099	1.858	0.089
2. Trouble sleeping	3.30	1.185	3.54	1.271	3.26	1.225	3.14	1.221	3.21	0.734	3.69	1.032	2.82	1.283	3.64	0.745	1.329	0.245
3. Headaches	3.06	1.214	3.33	1.260	2.90	1.262	2.93	1.149	3.34	0.987	3.38	0.768	3.10	1.306	3.29	1.204	1.130	0.345
4. Back pain	2.94	1.228	2.94	1.162	2.87	1.283	2.99	1.273	3.20	0.991	3.00	1.528	3.07	1.029	2.93	1.207	0.239	0.963
5. Pain in your arms, legs or joints	2.56	1.128	2.67	1.273	2.65	1.184	2.31	0.966	2.41	0.938	2.46	1.127	2.64	0.994	2.29	0.914	0.646	0.693
6. Stomach or bowl problems	2.46	1.232	2.51	1.274	2.44	1.290	2.73	1.187	2.10	1.098	2.31	0.855	2.66	1.372	2.36	1.008	0.631	0.705
7. Dizziness	2.22	1.142	2.56	1.266	2.23	1.164	1.88	1.090	1.93	1.197	2.15	0.689	2.20	1.015	2.34	0.973	1.289	0.263
8. Chest pain or shortness of breath	2.01	1.054	2.19	1.170	2.04	1.121	1.94	0.958	1.53	0.628	2.08	1.115	1.91	0.790	2.07	0.917	0.852	0.531

presents an ANOVA analysis assessing potential differences in physical health effects arising from work–study conflict among BE students across various courses. With p-values above 0.05 for all surveyed health conditions, no significant differences in health effects were observed between student groups. The table organizes health conditions in descending order of their overall mean values. Conditions with mean values above 3.0 on the Likert scale were identified as more frequent, with three issues exceeding this threshold: feeling tired or having low energy, trouble sleeping, and headaches. Musculoskeletal pain scored closer to the midpoint. These conditions are likely linked to burnout and chronic stress.

4.5. Academic Performance of BE Students

Table 8. ANOVA test results for academic performance.

Academic Progress	Overall		Course Comparison
			Architecture/ Design		Construction Management		Engineering		Property		Planning		Other		Unspecified		ANOVA Results
	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	F	p-Value
1. Adverse impact on academic performance	3.84	0.978	4.21	1.027	3.83	0.953	3.45	1.036	4.02	0.735	3.46	1.05	3.76	0.941	4.03	0.846	2.39	0.029
2. Reduced attendance in scheduled learning activities	3.12	1.099	2.96	0.978	3.15	1.143	3.26	1.128	2.52	1.253	3.54	0.776	3.32	0.985	3.16	1.026	1.514	0.174
3. Intention to defer studies	2.57	1.246	2.88	1.202	2.48	1.23	2.4	1.275	2.37	1.276	2.31	1.182	2.64	1.265	3.23	1.31	1.473	0.188
4. Intention to discontinue studies	2.54	1.246	2.86	1.445	2.36	1.172	2.77	1.327	2.75	1.155	2.08	1.038	2.29	1.077	3.07	1.269	1.975	0.07

presents the ANOVA test results examining the effect of work–study conflict on the academic progress of BE students. A statistically significant variation was observed in the extent of the negative impact on academic performance across BE courses, indicated by a p-value below 0.05. Architecture students experience the greatest negative impact, while engineering students are the least affected. Conversely, p-values above 0.05 suggest no statistically significant differences across courses in the following adverse effects:

• Reduced attendance in scheduled learning activities;
• Intention to defer studies;
• Intention to quit studies.

The most common adverse effects, with overall mean values exceeding 3.0 on the Likert scale used in the study, are reduced academic performance and lower university attendance.

5. Discussion

5.1. Validation of Hypotheses

The study was guided by two hypotheses for empirical investigation:

• The intensity of academic and work stressors confronting built environment (BE) undergraduates varies depending on the course of study.
• The effects of work–study conflict on BE undergraduates’ health, well-being, and academic performance vary depending on their course of study.

Across different student cohorts, no significant differences were found in exposure to thirteen out of fifteen academic stressors. However, property students reported two stressors more prominently: difficulty in understanding assessments and anxiety about underperforming. Thus, the hypothesis that academic stressor experiences vary by course does not hold strongly, suggesting that all BE students, regardless of their course of study, can be considered as a single group regarding academic stressors. The similarities in academic stressors across disciplines could be attributed to several factors. Firstly, most academic programs follow similar structures involving exams, assignments, and deadlines, which generate comparable stressors for students. Additionally, common academic pressures like time management, workload, and performance expectations are universally experienced. Universities also provide standardized support services that address these stressors across disciplines. Lastly, regardless of the field, students tend to face high expectations to perform well, leading to shared stress experiences across all disciplines. Hence, pedagogical and student support strategies aimed at reducing work–study conflict should focus on the top-ranked academic stressors identified in this study: high self-expectations, anxiety about underperforming, demanding academic workloads, test/exam-related anxiety, limited time for academic work due to employment, and difficulties with group assignments. Similarly, no statistically significant differences were observed in exposure to eleven out of fifteen work stressors across different student cohorts. However, architecture students reported three specific stressors at higher levels: doubts about finding a job after graduation, concerns about the relevance of their studies to career advancement, and a perceived lack of workplace appreciation or support for their university studies. Embedding and effectively managing work-integrated learning programs within architecture courses may help address these concerns. Overall, the hypothesis that exposure to work stressors varies by course partially holds for architecture students but does not strongly apply to other student groups.

The hypothesis that well-being, health, and academic performance vary across courses presents some nuanced findings. No statistically significant differences in perceived anxiety and depression were observed across courses, but architecture and planning students reported higher levels of perceived stress, supporting the hypothesis only partially. In terms of health impacts, no significant differences were found between student groups, fully supporting the hypothesis. Notably, burnout-related health issues were reported by students across all built BE disciplines.

All BE students exhibited similar rates of reduced attendance, intentions to defer studies, and intentions to quit, indicating shared challenges in these areas. However, academic achievement due to work–study conflict did differ, with architecture students experiencing more severe negative impacts, suggesting that the hypothesis of varying academic performance across courses is not strongly supported. Consequently, strategies to improve retention and success may be generalized to benefit all BE students.

5.2. Comparison with Prior Research

Previous research has examined work–study conflict and well-being challenges within specific built environment (BE) disciplines, such as construction management and architecture, with some studies also including engineering. This study advances the field by examining a broader array of BE courses and focusing on a wide range of stressors affecting these students. While it corroborates many established findings, it also contributes critical new insights, particularly regarding stress, burnout, and the intersection of academic and work demands across disciplines.

Lingard et al. [9] identified high burnout rates among Australian construction and property students, noting that work commitments often compromise their university attendance. Additionally, Lingard et al. [9] compared Australian and Hong Kong construction students and found that, while both groups experienced high burnout, its sources differed: Australian students’ burnout was linked to work–study conflict, whereas Hong Kong students’ burnout related more to socio-economic pressures. The current study aligns with these findings, showing that BE students who work in the industry frequently miss classes due to high time demands and workloads. Furthermore, these students report notable burnout symptoms—low energy, sleeplessness, and headaches—resulting from overlapping work and academic pressures, such as high academic demands, insufficient time for studying, and the challenges of balancing dual responsibilities.

Contrasting earlier work, Jia [11] found that burnout among Hong Kong architecture students did not lead to dropout due to the perceived high cost of leaving but did result in lower academic commitment. In this study, however, moderate tendencies toward deferral and dropout were observed among BE students facing stress, anxiety, depression, and burnout driven by work–study conflicts. This suggests that, within the Australian context, such conflicts may more strongly impact students’ intentions to continue their studies.

Moore and Loosemore [10] reported that a substantial proportion of Australian construction students experience stress and burnout due to academic workload, financial pressures, and limited social support. Groen et al. [14] added that construction students experience stress linked not only to academic tasks but also to personal relationships, extracurricular involvement, and difficulties in applying knowledge. Similarly, Loosemore et al. [13] found a high prevalence of depression among students in architecture, construction, and civil engineering, with academic pressure being a significant contributing factor. The present study extends these findings across BE disciplines, revealing that students consistently experience moderate anxiety and depression and high levels of stress and burnout. Additionally, this study identifies a comprehensive set of stressors that contribute to these outcomes, including self-imposed performance expectations, fears of underperformance, high academic demands, test and exam anxiety, limited study time due to work, difficulties with group assignments, and significant time pressures within the workplace.

In conclusion, this study confirms much of the previous research but provides a more nuanced understanding of the complex stressors impacting BE students across multiple disciplines. By identifying common and course-specific challenges, it highlights the need for systemic, tailored strategies that address the pervasive work–study conflict affecting undergraduates’ health, well-being, and academic success. These findings underscore the importance of developing flexible pedagogical and support mechanisms that account for students’ diverse experiences while reinforcing resilience against the high demands of both academia and industry.

5.3. Practical Implications

The findings of this study offer several practical implications for improving BE students’ well-being, academic success, and career readiness. Below are some strategies that universities, educators, and industry stakeholders might consider implementing to create a supportive environment that enhances BE students’ academic, personal, and professional outcomes.

• Flexible academic scheduling: Given that many BE students face significant time pressures from work, universities could offer more flexible course scheduling options. Evening classes, online modules, and asynchronous learning options could make it easier for students to fulfill both their academic and work obligations without compromising one for the other. Flexible academic scheduling can be implemented without compromising rigor by adopting structured approaches, such as blended learning, flipped classrooms, and strategic course design, that balance workload distribution. Additionally, universities can integrate modular coursework, allowing students to complete components at different paces while maintaining assessment integrity. Strengthening industry–academic collaboration in work-integrated learning programs can also ensure that flexibility enhances, rather than undermines, educational quality.
• Academic workload and assessment adjustments: Educators might consider adjusting academic workloads and revising assessment formats to reduce student stress. For example, spreading assessments throughout the semester, offering flexible deadlines, or incorporating more group-based, applied projects aligned with real-world scenarios could help students manage their time more effectively and reduce burnout.
• Enhanced work-integrated learning programs: Embedding structured work-integrated learning (WIL) programs within BE curricula can provide students with industry experience while aligning with academic requirements. Architecture students, for example, could benefit from industry partnerships that recognize and support their dual roles as students and emerging professionals, potentially reducing concerns about career relevance and workplace appreciation.
• Integrated support services for work–study balance: Universities could establish or expand support services focused on helping students manage work–study conflicts. This could include workshops on time management, resilience and mindfulness training, peer support groups, and targeted counseling services to address the unique challenges of balancing academic and work demands. Furthermore, stress management and self-care skills could be embedded into the curriculum to help students build long-term resilience.
• Career support and industry alignment: Given architecture students’ concerns about post-graduation employment, universities could strengthen career support services that specifically address the needs of BE students. This may include career coaching, industry networking events, and portfolio development workshops. Additionally, fostering closer partnerships with industry can help ensure that course content remains relevant to evolving job market requirements, alleviating students’ concerns about career advancement.

6. Conclusions

This study offers critical insights into the complex dynamics of work–study conflict among BE students, particularly within Australian universities where industry-based learning is strongly promoted. While cadetships and work-integrated learning programs play a key role in equipping students with industry-relevant skills, they simultaneously introduce significant stressors pertaining to balancing academic and work demands and managing time effectively. These stressors heighten mental health risks for students, which in turn adversely affect academic outcomes.

Key findings highlight that academic and work-related stressors are broadly shared across BE disciplines, with high self-expectation, workload intensity, and time pressures emerging as primary challenges. However, discipline-specific differences, such as architecture students’ heightened concerns about career relevance and post-graduation employment, underline the need for tailored support. Moreover, the study underscores that these stressors collectively contribute to moderate to high levels of burnout, stress, anxiety, and reduced academic engagement, which align with prior research on student well-being challenges but provide a more comprehensive perspective across BE disciplines.

The practical implications outlined call for systemic responses to support BE students’ well-being and academic success. Universities and industry stakeholders should prioritize flexible academic scheduling, structured support services, mental health resources, and adaptive learning strategies to help students manage the dual demands of study and work. These findings advocate for educational reforms that prepare BE students for the professional world and foster resilience and a sustainable work–study balance. Addressing work–study conflicts with a strategic, student-centered approach will not only enhance BE students’ immediate well-being and academic success but also contribute to the cultivation of skilled, adaptable, and mentally resilient professionals ready to thrive in the architectural, engineering, and construction industries.

This study provides valuable insights into BE students’ stressor experiences, well-being, health, and academic performance across various courses. However, there is significant potential for future research to expand on these findings. This study primarily relies on self-reported survey data, which may introduce response biases such as social desirability or recall bias. Additionally, while the quantitative approach provides broad insights, the exclusion of qualitative data limits a deeper exploration of students’ lived experiences and coping mechanisms. Future research should incorporate mixed-method approaches, including interviews or focus groups, to capture richer, more nuanced perspectives. In addition, areas for further investigation include the following: (1) reimagining BE education and pedagogical approaches to reduce work–study conflict, with a focus on curriculum flexibility, work-integrated learning models, and support services tailored to student needs; and (2) developing a comprehensive causal model that links academic and work stressors to student well-being, health, and academic outcomes. This model could provide a clearer understanding of how these factors interact, potentially guiding targeted interventions to improve student experience and success.