How do vocational students evaluate vocational education internships – an evaluation scale development in China

Abstract

Purpose

This research aims to construct an Evaluation Scale for Vocational Education Internships (ESVEI) tailored to assess the vocational educational internship experiences from the perspectives of vocational students. It also seeks to investigate the influence of certain factors – such as gender, family background, educational attainment, chosen major and the duration of the internship – on the assessment of these internships.

Design/methodology/approach

In the development of ESVEI, a combination of methods was employed, including literature analysis, item refinement, exploratory factor analysis, confirmatory factor analysis, multiple group analysis and reliability analysis. A total of 1,114 vocational students who had finished their internships completed questionnaires formulated based on ESVEI.

Findings

A two-dimensional evaluation tool called the ESVEI, consisting of the “Internship Content Evaluation” (ICE) and “Internship Supervisor Evaluation” (ISE) with seven items, has been created. Based on this, the corresponding questionnaires’ results indicate that female respondents, those from urban areas and those in the medical and nursing fields generally rated their internships more favorably compared to their male, rural and engineering and manufacturing counterparts. Additionally, when the internships last less than six months, the longer the internship, the more favorable evaluations.

Research limitations/implications

Because of the limited number of respondents, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed evaluation scale further.

Practical implications

The scale developed in this study serves as a tangible instrument for assessing the vocational education internship experiences of vocational students. Furthermore, this analysis can provide valuable insights for identifying areas that require further growth and improvement based on the dimensions of internship content and the trainers involved.

Originality/value

This is one of the first studies to develop an evaluation scale for vocational education internships in China, which not only clarifies the evaluation dimensions of internships but also forms a tool for future research.

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Introduction

For years, school-enterprise collaboration has stood as a cornerstone of vocational education in various nations. Notably, in China, this partnership has gained legislative momentum. The recently promulgated Vocational Education Law explicitly mandates the prioritization and implementation of school-enterprise cooperation within vocational education (SCoPRC, 2022a). Further reinforcing this emphasis, in 2022, the “Opinions on Deepening Reform of Modern Vocational Education System Construction” posited that the key to progressing the modern vocational education reform lies in maintaining adherence to school-enterprise cooperation (SCoPRC, 2022b).

Given the significance of school-enterprise cooperation, it has been a critical focal point in academic research on vocational education. However, research in China on school-enterprise cooperation primarily focuses on policy design, incentive structures, implementation strategies, and safeguarding mechanisms, with considerably less emphasis on evaluating the status of this cooperation. For the holistic advancement and promotion of school-enterprise collaboration, it’s imperative to fathom their real-time status. To achieve such an understanding, a robust evaluation framework is indispensable.

Among the plethora of initiatives tailored to nurture school-enterprise cooperation, internships stand out as the most direct and common practice. Through internships, schools and employers can mutually benefit from shared resources. Empirical evidence underscores the pivotal role of internships in career orientation (Rauner, 2006). They not only augment students’ work productivity but also facilitate more effective hiring decisions for employers (Yang and Tian, 2014).

In this study, we spotlight vocational education internships as a representative example of school-enterprise cooperation. Aiming to enrich the research on the evaluation of such cooperation in China, on one side, we address the research problem of “how vocational students evaluate vocational education internships”. We endeavor to answer the specific sub-questions of “what aspects of the internship should be evaluated” and “what tools should be employed for evaluation” by devising a vocational education internships evaluation scale specifically for vocational students. On the other side, we apply this scale to support systematic evaluation of students’ experiences in internships. Based on the empirical results derived from our investigation, we put forth recommendations to refine and advance vocational education internships in China.

Literature review

Internship in vocational education

Multiple studies have shown the significant influence of internships. These studies have examined different facets, such as the association between internship experience and employee retention (Yang and Tian, 2014), as well as the cost-benefit analysis of internships for companies (Ran, 2016). In the realm of vocational education, internships also hold significant importance in fostering talent. Vocational education aims to develop occupational competence, which refers to an individual’s preparedness and capability to do complex tasks and appropriate actions in occupational, social, and personal contexts (KMK, 2021). More specifically, vocational education should equip students with specialized knowledge of work processes that are directly relevant to the requirements of a certain employment. Expertise that is immediately applicable to and often obtained inside the work process should encompass the entire work process (Fischer and Rauner, 2002). Acquiring expertise in work process knowledge cannot be accomplished solely through theoretical study or in settings that are not related to a specific context. Extensive research on competency has also highlighted a significant connection between acquiring competence, taking practical action, and unique work environments (Bergmann et al., 2000; Rauner, 2001; Straka and Macke, 2009). Therefore, offering internships during vocational educational studies is critical for the mastery of work process knowledge and the development of vocational competence.

The current research on internships in vocational education can be categorized into four groups. Firstly, research indicates the significance of internships in vocational education. Internships offer vocational students with valuable hands-on experience (Vukić et al., 2011). Furthermore, internships facilitate the acquisition of crucial professional competencies and enhance students’ readiness for their prospective vocations (Akomaning et al., 2011). Moreover, from the employer’s standpoint, internships can offer companies the opportunity to obtain part-time assistance and assess potential future employees (Wan et al., 2013).

Secondly, research investigates the efficient execution of internship programs. Research has determined that effective planning, supervision, and feedback from both the company and academic institution are essential for optimizing the advantages of internships (Aqli et al., 2019). Moreover, the establishment of successful internship programs necessitates proficient communication and cooperation between educational institutions and industry affiliates (Awasthy et al., 2020).

Thirdly, studies focus on the difficulties and barriers encountered during internships in vocational education. Despite notable accomplishments in internship programs, persistent issues include the absence of a well-defined internship system (Xu and Li, 2008), inadequate regulatory mechanisms (Wu, 2015), insufficient accountability among practicing teachers (Deng et al., 2015), and limited involvement from companies (Li, 2012).

Ultimately, research emphasizes devising solutions for the issues that arise during internships. Several studies suggest different approaches including restructuring the internship system (Du, 2010), strengthening the implementation process (Liu, 2010), developing an assessment framework (Yi, 2014), and creating a system for managing internship quality (Wang et al., 2013).

Evaluation of internships in vocational education

Prior studies in vocational education have primarily examined the significance, challenges, and possibilities of improving internships. Studies have indicated a correlation between the quality of vocational education and internships. Internships of high quality are essential for improving students’ employability, skills, and overall educational experience (Gamboa et al., 2013). However, there remains a dearth of research on evaluating internships using a comprehensive evaluation tool that addresses both formative and summative aspects of the internship experience.

An internship is an essential element of the curriculum in vocational education programs. For example, the Chinese vocational curriculum system consists of three primary elements: the public fundamental curriculum, professional curriculum, and practical curriculum. Internships, which are a vital part of the practical curriculum, play a critical role in Chinese vocational education. Therefore, within a more specific scope, the assessment of vocational education internships can be categorized under educational evaluation.

Since the 1940s, common education evaluation models such as Tyler’s objective-centered evaluation, Stake’s responsive evaluation, and Suffete’s CIPP Model (Context, Input, Process, Product) have emerged. According to evaluation strategies of existing models, like Tyler’s Model, some studies delineate the content of internship evaluations based on the internship’s objectives. Such studies emphasize the extent to which goals are met and the tangible benefits reaped from the internships. Related research has sought to measure the impact of internships on employability (Knous et al., 1999; Callanan and Benzing, 2004; Choe et al., 2023), job performance (Gault et al., 2010; Jung and Lee, 2016), career readiness (Jackson, 2018), and overall career trajectory and success (Brooks et al., 1995; Gault et al., 2000). These evaluation strategies often face criticism for placing too much emphasis on goals, which can lead to neglecting the individual requirements of students or the intricacies of other aspects in the educational process.

To address the criticisms of objective-centered evaluation, some research, guided by Stake’s Model, seeks to improve educational programs by actively involving stakeholders through direct communication and gathering their feedback. For example, a tool known as the Task Self-Efficacy Scale has been developed to assess individuals’ confidence in their ability to successfully accomplish tasks in 10 distinct professional areas (Lucas et al., 1997). Certain extension research endeavors to consider not only the input from relevant stakeholders but also the educational process. Fields such as nursing often delve into evaluation subjects such as the formation of an intern’s professional self-concept (Arthur, 1995) and their comprehension of profession-specific ideas (Jiang et al., 2006). Furthermore, various assessment approaches have been devised to examine internships by incorporating the perspectives of relevant stakeholders and considering the educational aspects that influence their outcomes. For example, the Work Experience Questionnaire, a tool that has been studied, has identified four criteria: clear goals, workplace assistance, university support, and general competencies. These factors are used to assess the internship experience of engineering students (Luk and Chan, 2020). In addition, the Internship Satisfaction Questionnaire, which focuses on undergraduates, has shown that feedback, autonomy, support from university supervisors, academic preparedness, flexible working hours, student self-initiatives, location, and variety of skills are crucial elements that contribute to internship satisfaction (Hussien and La, 2018).

To summarize, several studies have been conducted to create tools specifically designed for evaluating internships. However, there is a limited amount of research on the development of internship evaluation strategies and tools from the perspective of stakeholders in vocational education or the vocational educational process.

Inspired by Suffete’s CIPP Model, a thorough assessment considers not only the result and factors in process of the internship, but also the external aspects such as the work environment. Extensive research on effective internships emphasizes the need for comprehensive evaluations that include both formative and summative assessments across wider aspects: projects, programs, persons, products, institutions, and systems (Sweitzer and King, 2014). Zhang et al. (2016, pp. 93–96) proposed a comprehensive assessment approach. This approach suggests assessing the context of internships by considering policies, programs, and the level of collaboration between schools and businesses. It also involves evaluating the contributions of internships, such as the salary offered by companies, the positions available for internships, and the quality of supervisors. Additionally, it includes appraising the internships based on factors like attitudes, attendance, and specific performance. Lastly, it involves examining the outcomes of internships, such as honors and awards received, certificates obtained, and the rate of employment. However, these explorations mostly focus on theoretical aspects. The suggested evaluation content has not been properly examined and validated empirically. In addition, executing this all-encompassing strategy usually necessitates significant investments in terms of time, resources, efficient data management, and financial outlay (Scriven, 1991; Stufflebeam, 2003).

The dimension and measurement of internship in vocational education

Previous studies on internships have revealed two main findings. Firstly, there is insufficient research on internship evaluation within the broader context of internship research. Secondly, current internship evaluation studies predominantly employ summative evaluation methodologies that gauge the attainment of objectives. The formative evaluation of internships is not given enough emphasis and the formative evaluation in the vocational education field was not highlighted, which perhaps lacks the ability to accurately assign unsatisfactory outcomes. In addition, the comprehensive assessment has mostly limited to theoretical research, and the creation of appropriate evaluation techniques is frequently a lengthy and costly process.

This study aims to create an internship evaluation scale that consists of two evaluation dimensions for the interns. One dimension pertains to the Internship Content Evaluation (ICE), while the other dimension revolves around the Internship Supervisor Evaluation (ISE). The construction of such an internship evaluation scale is based on the Educational Triangle Model, which posits that an educational process comprises instructors, students, and educational content (Astolfi, 2008). This study considers internships as an educational process that involves interns, supervisors, and the content of the internship. The aim is to analyze the internship activities as a dynamic educational process that goes beyond just evaluating predetermined outcomes. It enables effective improvement and optimization in situations where assessments are inadequate, by enhancing teacher teams and optimizing content. In contrast, this strategy simplifies the complex and diverse elements of the CIPP model by giving priority to the central element of instruction, namely teachers and learning content. This aids in reducing the complexity of evaluation and improving the feasibility of assessing internships.

We have designed the initial questions for our evaluation scale by taking influence from existing instruments. The ICE dimension comprises seven items, which took inspiration from the Work Experience Questionnaire (Luk and Chan, 2020). On the other hand, the ISE dimension consists of five items, which were inspired by the Student Evaluation of Teachers Questionnaire (Oermann et al., 2018) and the Teaching Quality Assessment Indicators (Wu et al., 2021) (see Table 1).

For our scale, we utilized a 7-point Likert scale for participants’ responses, which ranged from “totally disagree” (1 point) to “strongly agree” (7 points). To compute the total internship evaluation score, one simply adds the scores from both dimensions. Consequently, higher agreement with the items indicates a more favorable evaluation.

Methodology

Participants

To validate the preliminary scale, we conducted a widespread questionnaire distribution to vocational students who had completed their internships. For the sampling procedure, we adopted a convenience sampling method to collect data. The researcher initially reached out to the vocational institutes via personal connections and the researcher’s workplace platform. Subsequently, a thorough online webinar was conducted to obtain consent from participants. It was stated explicitly to potential participants that their participation in the survey was voluntary and that they had the right to withdraw at any time without facing negative repercussions. 1,582 questionnaires were returned. Upon examination, we found that 467 surveys were deemed incomplete or poorly filled out. This included instances when respondents provided the same answer for all questions or completed the questionnaires in an unusually short time. Such responses would be regarded as invalid and be discarded. Consequently, we had 1,114 valid responses that were included in our subsequent analyses (see Table 2). The rate of valid questionnaires was 70.4%.

The respondent pool consisted of 41.2% males and 58.8% females. Geographically, rural respondents formed the majority, representing 62.3%, with urban respondents making up 37.7%, which aligned with the actual distribution of students’ family backgrounds, specifically, about 70% of vocational education students in China originated from rural regions (MoE, 2022). It’s notable that secondary vocational schools largely cater to further education, implying that their internships tend to be shorter and less important. On the other hand, most vocational universities, having been established after 2019, have a relatively smaller student body. Given these distinctions, our sampling was skewed toward students from vocational colleges. As for the fields in which these students undertook their internships: engineering and manufacturing attracted about 25%, the business sector accounted for around 40%, while medicine and nursing, as well as information technology (IT), held approximately 20 and 15%, respectively. In terms of internship duration, the majority engaged in long-term internships.

Statistical analysis

In the process of developing the ESVEI, the study’s data were randomly divided into two sample sets. The first sample set (N = 500) was subjected to exploratory factor analysis (EFA) to uncover the latent factor structure of the refined items, using IBM SPSS software version 26. We verified the data’s aptitude for factor analysis via the Kaiser–Meyer–Olkin (KMO) measure and Bartlett's test of sphericity.

Subsequently, to validate the extracted factor structure, confirmatory factor analysis (CFA) and validity analyses were performed on the second sample set (N = 614), using AMOS software version 24. To bolster the robustness of our scale and reduce the likelihood of sampling anomalies, we conducted a multi-group analysis (MGA) to assess the scale’s invariance across diverse groups, echoing the recommendations by Hoyle (1995, pp. 1–15).

Finally, to derive a comprehensive perspective on the status of vocational education internships in China across varied respondent demographics, we employed descriptive analysis, T-tests, and one-way ANOVA on the full sample (N = 1,114), relying on a questionnaire formulated from the ESVEI.

Results

Exploratory factor analysis

To ensure precise differentiation among the items in our scale, we undertook item refinement to eliminate redundancy. This was guided by two essential criteria. First, the corrected item-total correlation (CITC) should be at least 0.5. Second, the value of Cronbach’s $α$ after the deletion of a specific item should not exceed the Cronbach’s $α$ value of each dimension. As per these criteria, items A3, A5, A7, B4, and B5 were discarded, leaving seven items selected for the evaluation scale (see Table 3). Aside from its ability to improve the model fit, the reasons for removing these items also encompass their redundancy with other items and their ability to clarify reality. For example, item A1 demonstrates a notable degree of repetition with the content of item A3. Item A4 includes both A5 and A7, while B3 includes B4. The exclusion of B5 is based on two considerations. On the one hand, most vocational schools provide relevant guidance and advice related to career development during the early stages of study, helping students better understand their chosen field. On the other hand, with the widespread use of digital resources in education, it is easier for students to access career development information. As a result, the internship supervisor's ability to offer advice and guidance on career development is no longer a crucial factor in evaluating their performance. The Cronbach’s $α$ value of the entire scale was 0.924, while Cronbach’s $α$ values for IIC and IES were 0.875 and 0.945, respectively, all comfortably exceeding the minimum recommended threshold of 0.7 (Tavakol and Dennick, 2011). Further, Cronbach’s $α$ values for each dimension decreased when any specific item was removed. These results suggest that the refined scale exhibits commendable reliability and consistent internal consistency.

In this study, principal component analysis was employed to perform EFA on the scale. The analysis returned a KMO value of 0.894, which is above the acceptable threshold of 0.6 (Kaiser, 1974). Furthermore, Bartlett’s test of sphericity was significant (p $< 0.001$ ), indicating that the variables possess mutual factors, hence the scale is suitable for factor analysis. We predetermined the extraction of two factors, selecting components with absolute coefficient values above 0.5. The results illustrated that the factor loadings for each item were all above 0.6, and the two extracted factors accounted for 80.87% of the total variance. This consistency between the results of the factor analysis and the outcomes post-scale purification suggests that the overall explanatory power of the refined items is excellent.

Confirmatory factor analysis

The construction of the two-dimensional measurement model was guided by the preceding EFA’s results. The model fit was assessed using a variety of goodness-of-fit indices and recommended cut-off points. These indices included the $χ^{2} / d f$ (with a value between 1 to 3 being acceptable) (Carmines and McIver, 1981; Bollen, 1989), comparative fit index (CFI, with a value greater or equal to 0.90 being acceptable, and a value greater or equal to 0.95 being desirable) (Hu and Bentler, 1998), Tucker-Lewis index (TLI, with a similar scale to CFI) (Hu and Bentler, 1998), goodness of fit index (GFI, with a similar scale to CFI) (Jöreskog and Sörbom, 1996), and root mean square error of approximation (RMSEA, with a range of ≤0.05 indicating a good fit, ≤0.08 an acceptable fit) (Kline and Santor, 1999). The results for these indices were listed in the Table 4. These values suggest the satisfactory fit of our two-dimensional model, which fits better than the one-dimensional model (see Table 4). It provides evidence supporting the superiority of the two-factor model and confirms the structural assumptions of the two dimensions of internship assessment.

Additionally, to assess the reliability of the ESVEI, we computed both the composite reliability (CR) and the average variance extracted (AVE). For the ESVEI, the CR values for each dimension were 0.859 and 0.941, both surpassing the recommended minimum threshold of 0.7 (Fornell and Larcker, 1981). This implies that the overall measurement model demonstrates strong convergent validity. The calculated AVE for each dimension exceeded the benchmark value of 0.5 (Hair et al., 1998). This suggests not only that the variables within each dimension are highly related but also that the dimensions themselves are distinct, confirming their discriminant validity (see Table 5).

For the ICE and ISE dimensions, their Cronbach’s $α$ was 0.857 and 0.940, respectively. The overall ESVEI displayed a Cronbach’s $α$ value of 0.924. These results suggest that the ESVEI demonstrated commendable reliability, both in its subscales and the whole scale.

Discriminant validity

When constructing the ESVEI, it is important to assess the discriminant validity of internship assessment measures that have similar attributes. In a certain context, an internship is also a job. For the purpose of assessing discriminant validity, the Job Satisfaction Index (JSI) was chosen in this study, which is a comprehensive tool used to assess employee satisfaction with the internship job. To maintain the quality of questionnaire completion and prevent biased responses due to overfilling, the study adjusted, compressed, and screened the items of the original JSI scale to make them more relevant to the internship. The selection criterion consisted of two primary factors. To minimize the loss of components, the items in each dimension of the scale that had a better correlation with the total were selected first. Furthermore, items that have semantic phrases that closely resemble those of the ESVEI items are chosen, resulting in a final selection of five items. Results demonstrated strong discriminant validity between the newly constructed ESVEI scale and JSI (see Table 6).

Convergent validity

During the process of developing a new scale, it is crucial to evaluate if the items in the new scale have a substantial influence on the variables that are theoretically expected to have an impact (Walumbwa et al., 2008). Occupational identity encompasses the cognitive and affective aspects of employees’ attitudes and feelings towards their professions, careers, and organizations. It refers to the mental, self-identifying, and emotional perception of how individuals see the significance and significance of their job (Allen and Meyer, 1990). Research has shown that there is a substantial correlation between employees’ occupational identity and factors such as job tasks (Lin et al., 2013), favorable work environments and interpersonal interactions (Di, 2017), and assistance and direction from mentors (Chen et al., 2020). This study employed occupational identity as a correlational measure to investigate the influence of internship assessments on occupational identity. The Occupational Identity Scale created by Skorikov and Vondracek (2011, pp. 693–714) was utilized. The results indicate that the questions in the ESVEI were effective in accurately predicting the respondents’ occupational identity, demonstrating a favorable level of convergent validity (see Table 7).

Incremental validity

For newly developed measurement scales, in addition to considering its discriminant validity and convergent validity, it is usually necessary to test its incremental validity to examine the extent to which the measurement scale contributes to the validity scale (Judge et al., 2003). In this study, regression analysis was used to test whether the ESVEI had a better evaluation effect than the JSI. Model 1 showed that the JSI had a significant effect on occupational identity (β $=$ 0.837, p < 0.001). Model 2, with the addition of the ESVEI, showed that the internship evaluation had a significant effect on occupational identity (β $=$ 0.264, p $<$ 0.001) and the R² value was increased from 0.699 to 0.726. The data suggest that the ESVEI has a more favorable effect on the prediction of occupational identity compared with the JSI, which suggests that the ESVEI has better incremental validity by maintaining an additional amount of interpretation (see Table 8).

Multi-group analysis

Typically, ensuring measurement invariance is crucial when validating a scale across varied samples. Measurement invariance is often used for categorical variables such as gender, age, and educational level. Considering our respondents mainly with post-secondary education, in our research, the validity of the ESVEI was tested between different genders. Guided by the methodological framework of Tarhimi et al. (2015, pp. 14–29) and Wang et al. (2018, pp. 425–434), we embarked on a multi-group analysis (MGA) to check measurement invariance.

The preliminary step involved conducting a single-group confirmatory factor analysis (CFA) to establish a baseline model. This was followed by a multi-group CFA to evaluate the ESVEI’s measurement invariance between male and female respondents. To rigorously test for invariance, we constructed four models: the unconstrained model (M1), the measurement weights model (M2), the structural covariance model (M3), and the measurement residuals model (M4). These models scrutinized the equivalency of factor structures, factor loadings, factor covariances, and residuals of each observed variable across the groups. The findings from the single-group CFA indicated a well-fitted baseline model, substantiated by a $χ^{2} / d f$ value between 1 and 3, CFI and TLI values exceeding 0.9, and an RMSEA less than 0.08 (see Table 9).

The results of the MGCFA are presented in Table 10. Both the M2 and M3 yielded p-values greater than 0.05, which suggests invariance in terms of factor loadings and covariances across the different gender groups. Despite a p-value for the M4 falling below 0.05, it successfully demonstrated the constancy of residuals. This conclusion is supported by $∆$ TLI less than 0.05 and an $∆$ CFI less than 0.01 (Cheung and Rensvold, 2002). Drawing from these results, the ESVEI constructed in this research exhibits measurement invariance. This validates that no substantial disparities exist between the male and female samples.

Evaluation of vocational education internships in China with ESVEI

Utilizing the ESVEI, we collected data to assess the vocational education internships from the Chinese vocational students (see Tables 11 and 12). Regarding gender and background differences, a t-test revealed that female respondents from urban areas significantly rated internships higher compared to their male and rural counterparts. An analysis using one-way ANOVA revealed no significant variances in evaluations across different educational levels. However, differences emerged when examining respondents’ major fields. Specifically, participants who majored in medical and nursing assessed their internships more positively than those in engineering and manufacturing, business, and IT.

Further, internship evaluations among respondents with diverse internship duration varied significantly, particularly for internships shorter than six months. When the internship is up to six months, the longer the internship, the better the evaluation rating of the perceived internship experience.

Conclusion and discussion

Conclusions

This study developed and validated a comprehensive seven-item measure that includes both summative and formative aspects to evaluate the quality of internships as perceived by vocational students. Subsequent empirical analyses confirmed that the ESVEI is both reliable and valid. Therefore, this scale can serve as a practical instrument for thoroughly assessing the evaluation opinions of vocational students on vocational education internships. More precisely, the assessment of internship content by students can be accurately determined by considering factors such as the degree to which internship tasks align with the interns’ learning needs and expectations, the clarity of the internship content, the compatibility of internship resources, equipment, and facilities, and the level of difficulty presented by the internship tasks. Meanwhile, the assessment of an internship supervisor is made easier by considering variables such as the supervisor’s expertise and credentials, as well as their ability to teach and provide feedback.

The data collected by the newly developed ESVEI indicates that female respondents, individuals from urban areas, and those in the medical and nursing fields generally rated their internships more positively compared to their male, rural, and engineering and manufacturing counterparts. This finding is in line with previous studies. For instance, a study examining internship evaluations among undergraduate students in the field of engineering has produced comparable results, suggesting that male individuals demonstrate lower levels of overall satisfaction with their internships, specifically regarding payment and opportunities for professional networking (Chopra et al., 2020). In contrast, women exhibited more contentment with the support and working conditions provided by their employers. A study conducted by Burger et al. (2020) found that urban residents reflect more positive evaluations of various work experiences, including internships, due to higher satisfaction with life and stronger positive emotions. Several studies have found differences in how internships are evaluated by students in different academic disciplines. For instance, engineering students evaluate internships with particular emphasis on problem-solving skills and the acquisition of practical work experience, whereas in the fields of business and tourism management, student satisfaction with internships is directly correlated with career progression (Nogueira et al., 2021).

Moreover, our study has found that internships with a duration of less than six months generally receive higher evaluations as their length rises. This finding also supports the research conducted by Azmi et al. (2018, 2019), which found that a six-month duration is the optimal period for undergraduate engineering students to acquire both technical and non-technical abilities, as well as gain practical work experience.

Suggestions

Analysis results of internship evaluations within Chinese vocational education from the perspectives of students suggest the necessity of heightened attention towards certain groups that tend to express lower ratings, including males, interns from rural backgrounds, and those engaged in engineering and manufacturing fields. In addition, it advises that given the substantially different ratings of internship duration on its overall evaluation; it is recommended to adjust the length of the internship more precisely.

Contributions

The establishment of the ESVEI, aimed at assessing vocational students’ viewpoints on vocational education internships, has four primary advantages. This study aims to broaden the empirical research on internship evaluation by focusing primarily on vocational education and vocational students. Further, it introduces a novel assessment scale for evaluating vocational education internships, which can be a practical tool for future research in this field. Moreover, it assists researchers in gaining a preliminary comprehension of current opinions of students’ evaluation in vocational education internships by employing the scale. In addition, this scale highlights two crucial aspects for assessing vocational internships from various evaluation factors, which offer new avenues for future research. For example, a deeper investigation can be conducted to find out how the content of an internship or the supervision provided during the internship may impact job selection, occupational competence acquisition, and the enhancement of individual self-efficacy.

Limitations

This study presents some potential limitations. First, considering the vastness of China, our sample size remains relatively modest. Consequently, the outcomes might not comprehensively represent the perceptions of all Chinese vocational students. To validate these findings, it is recommended future research to expand the geographical coverage of the sample. Furthermore, education plays a crucial role in the process of social stratification and the selection of talent. Ultimately, students from various educational backgrounds need to find a suitable occupation. Thus, comprehensively, all forms of education can be considered as vocational education or various phases of vocational education. In this context, the internships required to be completed in the course of education are vocational internships. In other words, students participating in vocational internships are not exclusively restricted to students attending vocational schools. In theory, the ESVEI might also be utilized to evaluate internships for students from different educational backgrounds, including university students. Given that the data primarily came from vocational students and the analysis mainly focused on this group, it suggests validating the scale with other categories of respondents to explore the application scope and limitations of ESVEI in the future. Second, the formulation of the ESVEI predominantly hinges on the student’s perspective. To gain a more comprehensive insight into Chinese vocational education internships from vocational students’ perspectives, it would be beneficial for subsequent studies to further investigate the underlying factors contributing to the differences in students’ evaluations based on gender, family background, and major. This will facilitate a better comprehension of students’ assessments of vocational education internships. At last, this study has not addressed questions regarding the detailed impact of internship evaluations on internship satisfaction, and occupational identity, including the different influences of the two dimensions. Future research should aim to address these gaps and expand our understanding in this area.

Funding: The research is funded by the National Social Science Fund of China (BJA220255).

Table 1

Initial items of the ESVEI

Factor	Nr.	Item
ICE	A1	The tasks and content of the internship align with my learning needs and expectations
	A2	The descriptions of internship tasks and roles are explicit and well-defined
	A3	The content of the internship is directly related to my academic major
	A4	The internship provides necessary resources, equipment, and facilities
	A5	A reasonable stipend and benefits are offered during the internship
	A6	The internship furnishes challenging tasks
	A7	The internship ensures a safe working environment for the interns
ISE	B1	The internship supervisor exhibits substantial experience and qualifications in their field
	B2	The internship supervisor provides clear instructions and guidance on the tasks and workflow throughout the internship
	B3	Timely assistance was readily available from the internship supervisor
	B4	Feedback was provided by the internship supervisor in alignment with my performance
	B5	The internship supervisor was adept in offering guidance and advice related to career development

Note(s): ESVEI evaluation scale for vocational education internships, ICE internship content evaluation, ISE internship supervisor evaluation