On the impact of industrial placements in professional master education: an empirical study

Introduction: Despite the rapid expansion of China's Professional Master of Engineering (PME) programs, empirical research specifically investigating industrial placements within this context remains scarce. This study aims to address this significant gap in the literature.

Methods: A mixed-methods approach was employed, focusing on Mechanical Engineering PME students. Data were collected through surveys from 133 participants and analyzed using descriptive statistics and thematic analysis.

Results: Analyses revealed moderate to high levels of satisfaction. Communication and time management were identified as key skill gains. Students expressed strong demand for expanded internship opportunities, clearer university support, and stronger company commitment regarding mentorship, compensation, and working conditions. Hypothesis testing showed no significant differences in satisfaction across gender, year of study, program type, or career plans (all p > 0.05), though interpretation is cautioned due to limited statistical power from unbalanced sample sizes.

Discussion: These findings provide new insights into the understudied context of PME industrial placements in China and highlight practical directions for enhancing university-industry collaboration. The absence of demographic differences contrasts with international evidence and suggests preliminary signs of equitable benefits. Further research with larger, multi-institutional, and longitudinal samples is needed to validate and extend these conclusions.

Introduction

Since the introduction of the full-time professional master's degree as a separate track from academic master's programs 16 years ago, China has conferred over 4 million professional master's degrees across disciplines such as engineering, medicine, management, economics, and the arts. The proportion of professional master's degrees among all master's qualifications rose markedly from 35% in 2012 to 58% by 2021 (Ministry of Education, 2024). Notably, the Professional Master of Engineering (PME) has emerged as the most commonly awarded degree type within this category, accounting for more than one-third of all professional master's degrees.

The PME in China—typically a 2- to 3-year program—prioritizes practical skills and industry-oriented training (Ministry of Education, 2009), in contrast to the Academic Master of Engineering (AME), which emphasizes theoretical and research-based learning. Industrial placements or internships, often lasting 6 months to a year in full-time industry roles, are a central component of the PME curriculum (Mandilaras, 2004; Han et al., 2022). Unlike the shorter, predominantly 1-year master's programs in the UK and much of Europe, China's postgraduate system combines extended coursework with practice- or research-based training. Furthermore, many institutions impose publication requirements for AME students. This dual-track structure enables China's master's education to offer both practice- and research-oriented pathways, aligning with diverse industry and academic needs (Bao et al., 2018).

While China's Academic Master of Engineering system is relatively well-established, the Professional Master of Engineering remains in the early stages of development (Song and Huang, 2012; Han et al., 2022). Industrial placements—intended to bridge academic learning with real-world application—are a core component of PME programs. While the benefits of such placements are well documented in Western STEM education (Lock et al., 2009; Yi and Tang, 2023), studies in Asian contexts, particularly China, remain limited and often anecdotal (Chan et al., 2015). Moreover, international research has documented significant variation in internship experiences across demographic groups, including gender and academic background differences (Nogueira et al., 2021; Ge et al., 2025), though it remains unclear whether similar patterns exist within China's standardized PME framework. In particular, there is a lack of empirical evidence on how these experiences shape students' skill development, career preparedness, and overall satisfaction within China's evolving professional education landscape.

Specifically, mechanical engineering, as a core STEM discipline, is frequently cited for its disconnect between academic instruction and industry expectations (Brunhaver et al., 2017). This gap highlights the importance of experiential learning for PME students in mechanically related fields. Yet, few studies have examined how industrial placements affect educational outcomes in China, where PME programs face unique institutional, pedagogical, and cultural challenges (Peng et al., 2016; Han et al., 2022).

This study addresses these gaps by investigating the role of industrial placements in PME education within Mechanical Engineering disciplines in China. Adopting a mixed-methods approach, we surveyed a diverse cohort of PME students using a semi-structured questionnaire. Quantitative analysis assessed satisfaction levels and key influencing factors, while qualitative thematic coding of open-ended responses provided deeper insights into student experiences. Additionally, we tested whether demographic differences in internship satisfaction exist among Chinese PME students, as documented in international contexts.

Our findings indicate that while students generally report moderate satisfaction with their placement experiences (mean = 6.24 on a 9-point scale, SD = 1.73), the most valued outcomes are improvements in soft skills such as communication and time management. Contrary to international findings, no significant demographic differences were observed in internship satisfaction across gender, year of study, program type, or career plans, though power analysis suggests caution in interpretation due to unbalanced sample sizes. Quantitative analysis identifies research relevance and career alignment as key predictors of satisfaction. Thematic analysis reveals students' overwhelming demand for increased internship opportunities (20.7% of university-related and 18.9% of company-related responses), with complementary expectations for stakeholder roles: universities focusing on access and information provision, while companies emphasize quality mentorship and meaningful project involvement.

The main contributions of this study are summarized as follows:

• We provide empirical evidence on PME students' placement experiences and outcomes in China—a context largely underrepresented in the existing literature.

• We identify key institutional and industrial factors that influence student satisfaction and skill development during placements, revealing complementary stakeholder roles in internship support.

• We introduce a thematic network analysis that illustrates the interconnected responsibilities of universities and companies in enhancing PME training effectiveness.

• We offer practical recommendations for strengthening university-industry collaboration in the design and delivery of PME internships, based on students' specific expectations and priorities.

• We examine demographic differences in internship experiences within the Chinese PME context, providing preliminary evidence for equitable internship benefits across diverse student populations.

The rest of this paper is structured as follows. Section 2 reviews the work related to professional master's education and industrial placements. Section 3 describes the research design and methods used for data collection and analysis. Section 4 details the results. Section 5 discusses the implications of the findings for educational policy and practice. Finally, section 6 concludes the study and describes future work.

Literature review

This section reviews prior research on industrial placements in engineering education, focusing on their effects on student outcomes, the dynamics of university-industry collaboration, and the development of PME education in China. Based on this review, we develop hypotheses to guide the empirical investigation of student experiences and stakeholder expectations.

Employability and career preparedness

A growing body of literature highlights the benefits of industrial placements in enhancing engineering students' employability through the development of both technical and soft skills. Winberg et al. (2020) emphasized that industry-linked experiences embedded in curricula can foster competencies such as communication, teamwork, and project management—skills critical for transitioning into professional roles. However, they also highlighted variability in placement quality, pointing to the importance of structured support and meaningful engagement. Indeed, placement quality, rather than duration or structure alone, appears to be a stronger predictor of positive outcomes. Smith et al. (2019) found that well-supervised placements with substantive tasks significantly improved students' perceived employability. Similarly, Tennant et al. (2018) reported that even short placements can enhance professional identity when well-mentored.

International studies further stress the importance of support mechanisms such as pre-placement training and mentorship. Dumas Reyssier and Chaker (2024), for example, showed that social integration enhances career preparedness during overseas internships. Nonetheless, concerns remain about self-selection bias—where more capable or proactive students are likelier to secure placements—raising issues of equity and generalisability (Hu et al., 2017; Jones et al., 2017; Arsenis and Flores, 2024). Notably, several studies have documented significant differences in internship satisfaction and outcomes across demographic groups, including gender, academic background, and career orientation (Nogueira et al., 2021; Ge et al., 2025), suggesting that internship benefits may not be uniformly distributed across all student populations.

Academic impact and curriculum integration

The academic outcomes of industrial placements are inconclusive. Several studies report academic benefits when internships are well-aligned with curricular objectives. For instance, Ceschin et al. (2017) found that internship experience enhanced performance in design-focused modules, while Binder et al. (2015) observed that curriculum-integrated placements improved academic engagement overall. However, other studies highlight potential downsides. Caviggioli (2024) observed a modest decline in academic performance among internship participants in Italian engineering programs, attributing this to time and cognitive load conflicts. Ngonda et al. (2022) reported similar challenges in South Africa, where students cited inadequate mentorship and poor coordination as barriers to learning. These findings underscore the need for structured collaboration between universities and industry to ensure internships are pedagogically coherent and effectively support academic learning.

The theoretical foundation for understanding these varied outcomes lies in experiential learning theory. Kolb (1984)'s experiential learning cycle emphasizes that learning occurs through the transformation of experience via reflection and abstract conceptualization. In the context of industrial placements, this suggests that students must actively reflect on their practical experiences and connect them to theoretical knowledge for meaningful learning to occur. When placements lack structured reflection opportunities or clear connections to academic content, the learning potential may be diminished. Furthermore, situated learning theory (Lave and Wenger, 1991) posits that learning is most effective when it occurs in authentic contexts where knowledge is applied. Industrial placements provide such authentic contexts, but their effectiveness depends on students' ability to participate as legitimate peripheral participants in communities of practice, requiring appropriate mentorship and gradual integration into professional activities.

PME education and industrial integration in China

China's PME programs have rapidly expanded in recent years as part of national efforts to cultivate practice-ready engineers. Recent policy developments have further emphasized this commitment. In 2022, the China's Ministry of Education and State-owned Assets Supervision and Administration Commission established 18 National Institutes of Excellent Engineers, followed by 14 additional institutions in 2023, specifically targeting enhanced university-industry collaboration in professional engineering master's and doctoral degree programs (Ministry of Education, 2022). These initiatives reflect China's strategic focus on training graduate-level science and engineering talents through deepened industry-education integration.

As industrial placements are increasingly central to PME curricula, research attention has turned to their implementation and effectiveness. Jin et al. (2020) identified structural challenges, including weak university-industry coordination, ambiguous internship objectives, and insufficient supervision–issues that limit the developmental value of placements despite policy support. Chen and Gan (2021) evaluated the Internship Promotion Program (IPP) in Zhejiang and found improvements in students' soft skills and employability, though the study emphasized the need for stronger stakeholder collaboration. Similarly, Zhang and Chen (2023) noted that students valued enterprise-based training but felt that internships lacked adequate integration with academic learning, calling for dual-supervisor systems and curricular reform.

More recent research has begun to explore the application of advanced pedagogical approaches in Chinese engineering education. Studies on project-based learning in electronic engineering programs have demonstrated the benefits of interdisciplinary, experiential approaches that connect theoretical knowledge with real-world problem-solving (Fan et al., 2022). Additionally, research on STEAM education implementation has highlighted the importance of community engagement and contextual learning experiences that bridge academic and practical domains (Lau, 2025). These developments align with broader trends toward experiential and situated learning approaches in Chinese higher education.

Despite these contributions, few empirical studies foreground PME students' subjective experiences of placements. This remains a critical gap, especially as internships become compulsory across PME programs. Understanding how students perceive institutional and corporate support—particularly in terms of access, communication, mentorship, and academic alignment—is essential for improving internship quality and informing evidence-based policy and practice in China's evolving professional education system. Furthermore, given the documented demographic differences in internship experiences in international contexts, there is a need to investigate whether similar patterns exist among Chinese PME students, particularly considering the standardized structure of these programs and recent policy emphasis on equitable access.

Toward ecosystemic approaches

Recent studies increasingly advocates for ecosystemic perspectives in educational design (Bronfenbrenner, 1979; Cooper and Upton, 1990), recognizing that student outcomes are shaped by interactions between multiple stakeholders and systems. In the context of PME placements, this approach calls for coordinated action from universities, companies, and policymakers. This ecosystemic view is consistent with both experiential and situated learning theories, which emphasize the importance of environmental context and social interaction in learning processes. Kolb's theory (Kolb, 1984) highlights how the learning environment must provide opportunities for concrete experience, reflection, conceptualization, and active experimentation, while situated learning theory emphasizes the role of communities of practice and authentic participation in professional settings.

The integration of these theoretical perspectives with ecosystemic approaches suggests that effective industrial placements require coordinated efforts from multiple stakeholders to create environments that support both experiential learning cycles and legitimate peripheral participation in professional communities. This theoretical foundation informs our understanding of why students might have different expectations for universities vs. companies, and how these expectations might reflect complementary roles in supporting student learning and professional development.

Building on this view, this study investigates how PME students perceive institutional and industrial support throughout their placements. Through thematic and co-occurrence analysis of open-ended survey responses, the study offers practical insights into how key actors within the placement ecosystem can better align efforts to deliver meaningful, practice-oriented learning experiences. Additionally, given the established literature documenting demographic differences in internship experiences, this study tests the hypothesis that significant differences exist in internship satisfaction among student groups defined by gender, year of study, master's program, and career plans within the Chinese PME context.

Materials and methods

This section details the methodology adopted for this study, including data collection, preprocessing, and analysis.

Mixed-methods research design

This study adopted a mixed-methods research design (Tashakkori and Teddlie, 2010; Creswell and Clark, 2017), integrating both quantitative and qualitative approaches to gain a comprehensive understanding of PME students' experiences with industrial placements in China. This approach is particularly well-suited to exploring complex educational phenomena, as it facilitates the collection of both standardized, measurable data and in-depth, contextual insights. The implementation of the research design is illustrated in Figure 1, which outlines three main stages: data collection, data preprocessing, and data analysis. In the final stage, statistical techniques were applied to quantitative data, while qualitative data were examined through thematic analysis, in accordance with the nature of each dataset.

Figure 1

Figure 1. Illustration of the process of the mixed methods methodology adopted in this study.

A survey-based approach was chosen for its efficiency in reaching a large sample and its suitability for capturing attitudes, experiences, and perceptions within a limited timeframe (Dillman et al., 2014). Data were collected using semi-structured questionnaires, which combined closed-ended questions for statistical analysis with open-ended items to elicit nuanced student perspectives This format allows for flexibility while ensuring consistency across responses (Bryman, 2016).

Data collection

Questionnaire design

The questionnaire was semi-structured, which was developed based on prior literature on the benefits of internships in higher education (Knouse and Fontenot, 2008), with specific adaptations to reflect the PME context in China. It comprised three main sections: 1) demographic information: including gender, year of study, and academic background; 2) internship experience and satisfaction: measured using structured Likert-scale items; 3) open-ended questions: designed to elicit qualitative insights on perceived challenges, learning outcomes, and the role of institutional and industrial support. To ensure clarity, relevance, and appropriate length, the questionnaire was pilot-tested with five PME students. Revisions were made based on their feedback to enhance readability and content validity.

Participants

The target population comprised students either currently enrolled in or recently graduated from PME programs in mechanical engineering, intelligent manufacturing, and related fields. Participants were recruited from a provincial university in central China, specifically from its College of Mechanical Engineering. To ensure accessibility, the questionnaire was administered in Chinese, the participants' mother tongue.

Administration procedure

Data collection was conducted over a 4-week period during the late Fall semester of the 2024–2025 academic year. The survey was hosted on the online platform Wenjuanxing¹ and distributed electronically via university mailing lists and WeChat groups commonly used by master's students. Participation was entirely voluntary, and informed consent was obtained from all respondents in accordance with ethical standards for research involving human participants (Babbie, 2020). Respondents were assured of anonymity, confidentiality, and their right to withdraw from the study at any time without consequence. A total of 152 responses were received. After a data cleaning process to remove incomplete or inconsistent entries, 133 valid responses were retained for analysis.

Data preprocessing and analysis

All open-ended responses in Chinese were translated into English to facilitate analysis. Qualitative data were translated using an automated module integrating Google Translate with the Natural Language Toolkit (NLTK)², while quantitative data were manually translated by the authors to ensure accuracy and consistency.

Quantitative data, including Likert-scale items, were analyzed using descriptive statistics (means, standard deviations, frequency distributions) and inferential statistics where appropriate. In particular, analysis of variance (ANOVA) was employed to examine how internship experiences varied across groups with different demographic characteristics, academic backgrounds, and future career plans. Qualitative data were analyzed using thematic analysis, following the six-phase framework outlined by Braun and Clarke (2006). Two researchers independently coded the responses to enhance inter-coder reliability, and any discrepancies were resolved through discussion and consensus.

Results

This section details the analysis of the 133 valid survey responses described previously, including respondents' demographic characteristics, qualitative and quantitative findings that studies all-around aspects of internships.

Profile of respondents

This section presents the demographic profile of the 133 PME student respondents, encompassing gender, academic stage, disciplinary background, and career aspirations (Figure 2). The sample composition provides insight into the characteristics of students engaging with internship programs within engineering education contexts.

Figure 2

Figure 2. Profile of the survey respondents. (a) Gender. (b) Years of study. (c) Enrolled master programs. (d) Future career plan.

The respondent pool was predominantly male (n = 114, 85.7%), with females comprising 14.3% (n = 19). This distribution reflects persistent gender imbalances characteristic of engineering disciplines, particularly in mechanical and manufacturing engineering fields (Engineering UK, 2022). Participants represented various stages of their PME studies, with second- and final-year students accounting for the largest proportions (33.8% and 34.6%, respectively), followed by first-year students (25.6%) and recent graduates (6.0%). The inclusion of recent graduates provides valuable post-program perspectives on internship outcomes and career transitions.

Regarding disciplinary enrolment, students were distributed across five PME specializations. Mechanical Engineering represented the largest group (n = 78, 58.6%), followed by Intelligent Manufacturing (18.8%), Mechatronics Engineering (11.3%), Measurement and Control (6.0%), and Industrial Engineering (5.3%). This distribution encompasses both traditional and contemporary engineering domains, reflecting the breadth of modern PME curricula.

Career aspirations aligned strongly with PME program objectives, as the majority of students (n = 100, 74.6%) intended to pursue industry careers, demonstrating the practical orientation of these programs. Academic career plans were reported by 14.2% of respondents, while 9.7% planned hybrid roles combining industry and research elements. Only one student (0.7%) indicated an alternative career path. These findings underscore the workforce development emphasis inherent in PME program design and the alignment between student expectations and program goals.

While this sample would provides valuable insights, several limitations affect representativeness. The single-institution design limits generalizability, the pronounced gender imbalance constrains analytical precision, and voluntary participation may introduce self-selection bias. Future research should employ multi-institutional sampling across different university tiers, stratified sampling with minimum 30 participants per subgroup, geographic diversification across China's regions, and longitudinal designs to enhance external validity and provide more robust evidence for policy recommendations.

Descriptive analysis

This section presents a comprehensive analysis of students' internship experiences, covering their industry placement profiles, overall satisfaction, influencing factors, and motivations and barriers to participation. Before presenting these findings, we first established the measurement quality of our survey instruments. Internal consistency analysis using Cronbach's alpha confirmed that all multi-item scales demonstrated adequate to excellent reliability: Overall Evaluation (α= 0.82, 3 items), Satisfaction Factors (α= 0.89, 8 items), Skills Development (α= 0.85, 5 items), and Institutional Support (α= 0.76, 3 items). All coefficients exceeded the 0.70 threshold recommended for research applications (Nunnally and Bernstein, 1994), validating the use of composite scale scores in the analyses that follow.

Internship experience profile and overall evaluation

Students completed internships across diverse organizational contexts, with private enterprises hosting the majority (60.9%), followed by state-owned enterprises (18.8%) and other organizations (9.8%), while startups and foreign companies represented smaller proportions (6.0% and < 5%, respectively) as shown in Figure 3. This distribution reflects the dominant role of private sector engagement in PME internship programs while providing exposure to various organizational models.

Figure 3

Figure 3. Proportional distribution of company types where students completed internships and their future participation intentions. Company categories representing less than 5% of the total are shown in the legend for readability.

The value of these diverse experiences is underscored by students' overwhelming endorsement: 91.7% indicated willingness to participate in internships again if given the opportunity, with only 6.0% expressing uncertainty. This strong support translates into correspondingly positive evaluations across multiple dimensions, as illustrated in Figure 4.

The comprehensive assessment reveals moderate to high satisfaction levels, with primary metrics averaging 6.2 on a 9-point scale. Skills development patterns show particular strength in soft skills, with communication and teamwork achieving the highest rating (mean = 6.65), followed by time management and stress handling (mean = 6.59). Professional skills application scored lowest (mean = 6.28), suggesting a focus area for program enhancement. Among satisfaction factors, colleague collaboration received the most positive evaluation (mean = 6.53), while salary and benefits scored lowest (mean = 5.76), indicating that interpersonal relationships and work environment outweigh financial considerations in shaping overall satisfaction.

Figure 4

Figure 4. Illustration of the overall evaluation of internship experiences. (a) General satisfaction. (b) Skills development. (c) Satisfaction factors.

Determinants of internship satisfaction and participation

The correlation analysis in Table 1 reveals that alignment factors most strongly predict overall satisfaction. Research relevance (r = 0.785, r² = 0.616) and company-career match (r = 0.773, r² = 0.598) emerged as the dominant predictors, emphasizing the critical importance of congruence between internship content and students' academic or professional trajectories. While salary and benefits, city environment, and company culture also demonstrated substantial correlations (r>0.74, r²>0.5), a notable pattern emerged: colleague collaboration, despite receiving the highest mean satisfaction rating (6.53), showed comparatively lower predictive power (r = 0.689, r² = 0.475). This suggests that while students value interpersonal relationships highly, structural alignment ultimately exerts greater influence on overall satisfaction.

Table 1

Table 1. Correlation between overall satisfaction and satisfaction factors, with top two correlated factors with light gray.

These correlation patterns align closely with students' stated motivations for pursuing internships, as illustrated in Figure 5a. The primary drivers center on professional development: understanding the professional environment (71.4%), accumulating work experience (45.1%), and expanding professional networks (23.3%). This career-focused orientation reinforces why alignment factors emerge as such strong predictors of satisfaction.

Figure 5

Figure 5. Identified factors influencing internship participation. (a) Motivations. (b) Barriers.

However, significant participation barriers persist. As illustrated in Figure 5b, time conflicts with academic responsibilities (39.1%) represent the most frequently cited obstacle, followed by difficulty finding suitable opportunities (34.6%) and inadequate compensation (21.8%). These findings suggest that enhanced academic-industry integration, improved matching mechanisms, and better financial support could substantially reduce barriers and encourage broader engagement. The contrast between strong career-development motivations and systemic participation barriers highlights the need for institutional reforms to better align internship programs with student needs and academic schedules.

Thematic analysis: support from university and company

In addition to the descriptive statistical analyses presented in earlier sections, qualitative methods were employed to examine students' responses to open-ended survey questions regarding the support provided by universities and companies during internships.

Specifically, thematic analysis (Attride-Stirling, 2001; Braun and Clarke, 2006)—a widely used qualitative approach—was applied to identify key areas where institutional and corporate stakeholders could improve the industrial placement experience. The analysis was conducted following Braun and Clarke's (2006) six-phase framework: (1) familiarization with data, (2) generating initial codes, (3) searching for themes, (4) reviewing themes, (5) defining and naming themes, and (6) producing the report. All responses were systematically coded using open coding techniques, with iterative refinement of themes through constant comparison. The coding process was facilitated using qualitative data analysis principles, with themes emerging inductively from the data rather than being predetermined. After excluding non-substantive responses (e.g., “none,” “no comment”), 111 valid responses were retained for analysis. These were systematically coded and organized into thematic categories, with some responses contributing to multiple themes. This analysis revealed five salient themes for each stakeholder group—universities and companies—reflecting students' perspectives on how the quality and relevance of internships could be enhanced through targeted support and improvements.

University support themes

Table 2 summarizes the five most prominent themes identified from students' qualitative feedback on how universities could better support industrial placements and internships, along with their frequencies and percentages.

Table 2

Table 2. Thematic analysis of university support for industrial placements and internships.

The most frequently cited theme was Increase Internship Opportunities and Connections (20.7%), reflecting students' strong desire for universities to take a more proactive role in establishing partnerships with industry. Representative comments included: “find some formal companies to cooperate with and provide appropriate salary,” “strengthen school-enterprise cooperation,” and “provide more internship platforms.” These responses underscore the critical role of institutional networks in facilitating access to relevant placements. The second most prevalent theme, Enhanced Information Sharing and Communication (10.8%), highlight students' concerns regarding adequacy and accessibility of internship-related information. Students specifically called for “more comprehensive information acquisition” and noted that “the information is more public, and it is better to have students directly communicate with the company leaders.” Others suggested to “add more channels to let students learn about relevant content.”

Other notable themes included Career Guidance and Curriculum Integration (8.1%), in which students recommended embedding internships within formal curricula and enhancing career advisory services, with one respondent noting the need to “include internship-related courses into professional training programs, such as career planning, internship guidance and other courses to help students understand the importance, process and precautions of internship in advance”; Event Organization (7.2%), with calls for more job fairs, company lectures, and site visits, as students suggested to “try to get more companies to attend school to hold lectures” and “organize more job fairs”; and Balance Academic Requirements and Practical Experience (6.3%), which pointed to the need to reduce academic workload to better accommodate hands-on industrial experience, with students emphasizing the need to “strengthen the management of balancing academic and practical practice” and arguing that “there is no need to ask everyone for high-level papers, and professional masters should be given the opportunity to go out for internships.”

Company support themes

As shown in Table 3, the most frequently cited theme was Increase Internship Positions and Opportunities (18.9%), with students consistently calling on companies to “open more internship positions/jobs,” “provide more internship opportunities,” and “expand cooperation projects.” This reflects a clear demand for increased access to industrial placements. The second most prominent theme, Improve Internship Quality and Mentorship (12.6%), highlights the importance students place on meaningful and guided experiences. Respondents specifically emphasized desires such as “a master takes some projects,” “let students participate in the project and lead them into it,” and “provide suitable positions and have a mentor system.” Students also called for companies to “schedule tasks related to high degree of professional matching during internship.”

Table 3

Table 3. Thematic analysis of company support for industrial placements and internships.

Other salient themes included Better Compensation and Work Conditions (10.8%), where students raised concerns about “salary/benefits,” “reasonable work hours,” and “treatment of interns”, with specific requests to “increase salary and benefits,” “can increase some salary and rest time; arrange labor overtime reasonably,” and provide “more benefits”; Enhanced Communication and Transparency (9.9%), which focused on the clarity of “job descriptions” and “recruitment information”, with students requesting companies to “better introduce or promote your own company's specific work, and put forward practical needs,” provide “more detailed and reliable recruitment information,” and ensure “the content of the job is more transparent”; and Tolerance and Support for Learning (8.1%), where students asked for greater “patience with new interns,” “career planning guidance,” and fewer “experience requirements.” Key quotes included requests for companies to give “interns more fault tolerance opportunities,” practice “bringing new ones with the old, and being a little patient,” and “don't ask for too much work experience.” Together, these themes suggest that while increasing the number of available placements remains a critical priority, students are equally attentive to the quality, fairness, and inclusiveness of their internship experiences.

Comparison of university and company themes

To enable a more nuanced comparison, thematic feedback on institutional and industrial support was visualized using a horizontal bar charts and heapmap, as shown in Figure 6. The thematic analysis reveals a strong and consistent demand from students for both universities and companies to expand internship opportunities, reflected by the high frequency of related themes (20.7% for universities and 18.9% for companies). Notably, complementary patterns also emerged; for instance, the university theme of Enhanced Information Sharing and Communication (10.8%) aligns closely with the company theme of Enhanced Communication and Transparency (9.9%), suggesting that students expect coordinated efforts in information dissemination.

Figure 6

Figure 6. Comparison of university and company by frequencies of theme and subthemes. (a) Comparison of theme frequencies between university and company support for internships. (b) Heatmap showing the frequency of sub-themes across university and company stakeholders.

Figure 6b presents a comparative breakdown of sub-theme frequencies regarding the roles of universities and companies in supporting internships. The findings highlight divergent expectations. For companies, the most frequently mentioned sub-themes was Open more internship positions (12 mentions), Provide more internship opportunities (5), and Increase salary/benefits (5), indicating that students prioritize access and fair compensation in corporate settings.

In contrast, expectations of universities centered on facilitation and institutional support. Dominant sub-themes included School-enterprise cooperation (7), Provide more information about internships (5), and Increase cooperation with companies (5), reflecting students' desire for universities to act as effective intermediaries. Academic support also emerged as important, with themes such as Reduce research burden and Include internship courses in curriculum (3 mentions each). For companies, practical support was expected through calls for Provide mentorship and Include students in real projects (4 mentions each).

In summary, the thematic comparison indicates that students rely on companies for meaningful, well-supported internship experiences, while they expect universities to enhance access, communication, and academic integration of internships.

Thematic network analysis

To further examine the relationship between university and company support, a thematic network was constructed from qualitative coding of open-ended survey responses. As shown in Figure 7, the network illustrates the interconnections between key themes, with node size indicating theme frequency and edge thickness reflecting the strength of co-occurrence-based associations.

Figure 7

Figure 7. Thematic network of university and company themes, with node size reflects frequency, edge thickness indicates co-occurrence strength.

The network reveals clear patterns of interconnectedness between university and company support themes. Key university themes—Increase Internship Opportunities, Enhanced Information Sharing, and Career Guidance and Curriculum Integration—were strongly associated with company themes such as Increase Internship Positions (18.9%) and Improve Quality and Mentorship (12.6%). These connections reflect students' emphasis on coordinated efforts between institutions and industry.

The strongest thematic associations (association weight ≥ 0.7) were observed between:

• Increase Internship Opportunities→Increase Internship Positions (0.9)

• Enhanced Information Sharing→Enhanced Communication and Transparency (0.8)

• Career Guidance and Curriculum Integration→Improve Quality and Mentorship (0.7)

These strong linkages demonstrate that students conceptualize effective internship support as inherently collaborative. The highest association (0.9) between opportunity creation themes suggests that students recognize the fundamental need for both universities and companies to address the access bottleneck simultaneously. The parallel connection between information sharing and communication transparency (0.8) indicates students' expectation for coordinated information flow across stakeholders.

Beyond these primary connections, moderate associations (weights 0.3–0.6) reveal secondary support mechanisms that students consider important. Institutional efforts—such as event organization and curriculum integration—were linked to company-based quality improvements, suggesting that students view university facilitation activities as complementary to, rather than separate from, company-delivered learning experiences. The associations between themes such as Balance Academic and Practical Experience and Tolerance and Support for Learning highlight the need for flexibility and pedagogical support in navigating internships.

Overall, the thematic network illustrates the interdependence of university and company efforts in delivering meaningful and equitable internship experiences, demonstrating that students naturally think in terms of integrated support systems rather than isolated interventions. This finding offers a strategic lens for designing coordinated support mechanisms across both domains.

Hypothesis testing on group differences

Building on the thematic analysis presented in the previous section, this section examines whether students' internship perceptions vary systematically across different demographic and academic characteristics. Prior studies have shown that students' perceptions of internships are not uniform—they vary significantly by gender, socioeconomic background, academic discipline, and other contextual factors (Nogueira et al., 2021; Ge et al., 2025).

Based on these findings, we formulated and tested the following hypothesis:

• H₀: There are no significant differences in internship satisfaction among student groups defined by gender, year of study, master's program, or career plans.

• H₁: Significant differences exist in internship satisfaction among student groups defined by gender, year of study, master's program, or career plans.

To test this hypothesis, one-way ANOVA was conducted to examine variations in internship satisfaction across four demographic and academic factors: gender, year of study, enrolled master's program, and intended career path. The analysis focused on three key dependent variables: overall satisfaction, alignment with expectations, and perceived helpfulness to graduate studies.

ANOVA results and group comparisons

Table 4 presents a comprehensive overview of the ANOVA results for all demographic and academic factors examined, while Table 5 shows the descriptive statistics for each group. The results provide strong support for the null hypothesis (H₀). Across all factors and dependent variables, no statistically significant differences were observed (all p > 0.05). The effect sizes were consistently small (η² < 0.03), indicating that demographic and academic characteristics account for less than 3% of the variance in internship satisfaction ratings.

Table 4

Table 4. Comprehensive one-way ANOVA results for group differences in internship perceptions.

Table 5

Table 5. Group means for overall satisfaction across demographic and academic factors.

While no significant differences emerged, several descriptive patterns are noteworthy. Third-year students reported the highest satisfaction (6.52), while second-year students reported the lowest (6.00). Students aspiring to academic careers showed higher satisfaction (6.68) compared to those pursuing industry careers (6.18). Among master's programs, Mechatronics Engineering students reported the highest satisfaction (6.33), while Industrial Engineering students reported the lowest (5.71). However, these patterns should be interpreted cautiously given the non-significant statistical tests and limitations discussed below.

Power analysis and statistical considerations

Given the consistently non-significant results across all ANOVA analyses, a post hoc power analysis was conducted to evaluate the statistical power of our tests and assess the risk of Type II errors. The power analysis followed (Cohen 2013) conventions, where Cohen's f effect size was calculated from observed eta-squared values using $f=\sqrt{\frac{{\eta }^2}{1-{\eta }^2}}$, then statistical power was computed using the F-distribution with observed effect sizes, actual sample sizes, and α = 0.05.

As shown in Table 4, the observed power ranged from 0.05 to 0.28 across all comparisons—substantially below the conventional 0.80 threshold recommended for adequate power. This inadequate statistical power was primarily attributed to two methodological limitations. First, several subgroups had markedly small sample sizes that severely limited the ability to detect meaningful differences, with Industrial Engineering (n = 7), Measurement and Control (n = 8), and the “Othe” career category (n = 1) falling well below the minimum recommended sample size of 30 per group for ANOVA analyses (Stevens et al., 2002). Second, substantial imbalances existed across groups, particularly the gender distribution (114 males vs. 19 females, representing 85.7% vs. 14.3%).

To achieve adequate power (0.80) for detecting medium effects (f = 0.25), prospective power analyses indicated that total sample sizes would need to range from 180 to 1,020 participants depending on the number of groups and expected effect size, with balanced group distributions being essential. The limited statistical power introduces several important considerations for result interpretation, including elevated risk of Type II errors and reduced stability of effect size estimates, particularly for groups with fewer than 15 participants.

Discussion of hypothesis testing results

The hypothesis testing results lead us to retain the null hypothesis (H₀) that there are no significant differences in internship satisfaction among student groups. This finding contrasts with prior research that has documented significant group differences in internship experiences (Nogueira et al., 2021; Ge et al., 2025). Several factors may explain these results, including methodological considerations such as limited statistical power due to unbalanced and modest sample sizes, contextual factors such as the focus on a relatively homogeneous population of professional master's students in mechanical engineering programs in China, and potential institutional factors reflecting successful efforts to promote equitable internship experiences.

Despite the non-significant statistical tests, the small observed effect sizes (η² < 0.03) suggest that any practical differences between groups are minimal. This finding offers encouraging preliminary evidence that internships may provide broadly comparable value across demographic and academic groups within this context. However, the limited statistical power necessitates cautious interpretation, and future studies with larger, more balanced samples would provide more definitive evidence regarding the presence or absence of group differences in internship perceptions. The current results should be viewed as promising initial findings that warrant confirmation through more robust methodological approaches.

Discussion and implications

This study investigated industrial placements among Professional Master's in Engineering (PME) students in China using a mixed-methods approach, offering insights into students' satisfaction, perceived skill development, and expectations of institutional and corporate support. The findings reveal both encouraging patterns and areas requiring coordinated improvement from universities and companies.

The results indicate generally positive placement experiences, with moderate to high satisfaction levels and strong endorsement of future participation. While soft skills such as communication and time management were rated more positively than technical skills, satisfaction was most strongly predicted by alignment between internship tasks and students' academic interests or career aspirations. This reinforces the importance of relevance and integration in work-based learning, as suggested by Kolb's experiential learning theory (Kolb, 1984), and highlights the value of real-world projects and mentorship, central to situated learning theory (Lave and Wenger, 1991).

The hypothesis testing revealed no statistically significant group differences across gender, academic stage, program type, or career plans. While this contrasts with prior research that has reported such variations (Jones et al., 2017), our post-hoc power analysis showed that this study might be underpowered to detect small-to-moderate effects due to unbalanced subgroup sizes (Cohen, 2013). However, the consistently small effect sizes (η² < 0.03) suggest minimal practical differences between groups, offering encouraging preliminary evidence for equitable internship benefits. Future research involving larger and more balanced samples in China's PME context is needed to more confidently assess these potential group differences.

The thematic analysis revealed students' overwhelming consensus for increased internship opportunities, with this theme comprising 20.7% of university-related and 18.9% of company-related responses. This universal demand indicates that access represents the primary constraint in the current internship ecosystem (Zhang and Chen, 2023). Complementary roles were also apparent: students expected universities to strengthen information dissemination (10.8%) and curricular integration (8.1%), while companies were asked to improve internship quality through mentorship (12.6%), clearer communication (9.9%), and inclusion in meaningful work. Thematic network analysis further illustrated the interconnectedness of these expectations, with strong associations between access, mentorship, and communication. These findings suggest that students view internship success not as the sole responsibility of either stakeholder but as a shared enterprise requiring coordination across institutional boundaries. Less frequent but important concerns included academic workload conflicts and compensation issues, mirroring structural tensions seen in other contexts (Caviggioli, 2024; Ngonda et al., 2022).

These insights yield several practical implications. For universities, priorities include expanding industry partnerships, improving communication systems, and aligning internship opportunities more closely with academic schedules and curricula. Companies, in turn, should offer structured mentorship programs, project-based roles that contribute to real business objectives, and transparent communication about internship expectations and learning outcomes. At the policy level, frameworks are needed to support quality assurance, incentivize company participation, and reduce financial barriers for students. These implications highlight how universities and companies can collaboratively enhance the impact of internships through coordinated, stakeholder-driven improvements that integrate academic learning with professional practice.

This study has limitations. The sample was drawn from a single provincial institution, limiting generalisability. The strong male majority reflects broader trends in engineering education but restricts gender-based analysis. Additionally, voluntary participation may introduce self-selection bias (Hu et al., 2017). Despite these constraints, the study offers timely and valuable insights into a largely understudied context—the impact of industrial placements in Asian master education.

In summary, this research highlights the multifaceted nature of industrial placements in PME education. While overall student perceptions are positive, the study underscores the need for coordinated, stakeholder-driven improvements that integrate academic learning with professional practice. By aligning placement structures with students' academic and career trajectories, universities, companies, and policymakers can collectively enhance the value and impact of PME industrial placements.

Conclusions and future work

This paper provides an empirical account of industrial placements in China's PME programs—an understudied context in the literature on experiential learning in postgraduate education. Through a mixed-methods approach, we examined student experiences and identified key factors—such as academic-workplace alignment and stakeholder collaboration—that shape placement effectiveness. Our findings demonstrate the multifaceted nature of successful placements, with alignment between academic interests and workplace activities emerging as particularly influential. The complementary roles identified for universities and companies illuminate the necessity of coordinated ecosystemic approaches (Bronfenbrenner, 1979; Cooper and Upton, 1990) to placement design and implementation. The absence of statistically significant group differences in satisfaction suggests a potential universality of internship benefits—contrasting with existing international studies that report demographic disparities—though this interpretation requires validation through larger-scale investigations with greater statistical power.

This study extends the work of Zhang and Chen (2023) and Chen and Gan (2021) by offering a more detailed account of stakeholder responsibilities within China's unique PME context. Moreover, the identified expectations align with Winberg et al. (2020)'s model of collaborative engineering education while highlighting priorities shaped by China's evolving professional education landscape. As PME education in China continues to expand, coordinated efforts between universities and industry will be essential to ensure that placements effectively advance students' academic and professional development.

Future research will build on these findings through multi-institutional and longitudinal designs, involving larger and more diverse student samples with balanced demographic representation to achieve adequate statistical power for detecting group differences and incorporating employer perspectives to capture the full placement ecosystem. We also plan to adopt intervention-based evaluations (Drew et al., 2007) to inform evidence-based strategies for strengthening PME-industry integration, particularly focusing on the specific interventions suggested by students such as enhanced mentorship programs and improved university-industry information systems.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The requirement of ethical approval was waived by Wuhan University of Science and Technology for the studies involving humans. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

LW: Writing – original draft, Project administration, Resources, Conceptualization, Writing – review & editing, Funding acquisition. LX: Formal analysis, Writing – review & editing, Writing – original draft, Resources, Visualization. YG: Data curation, Writing – review & editing, Supervision. ZZ: Resources, Supervision, Writing – review & editing. XX: Resources, Writing – review & editing, Supervision. ZW: Supervision, Writing – review & editing, Resources. FX: Resources, Writing – review & editing, Software.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This research was funded by the Hubei Provincial Higher Education Teaching Reform Research Projects (grant number: 2023247 and 2022232).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that Gen AI was used in the creation of this manuscript. We have used Generative AI to assist translation, data analysis and also help to improve the writing, including grammatical checking.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Footnotes

1. ^https://www.wjx.cn/

2. ^https://www.nltk.org/

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