1. Introduction
Internship programs have an important role in the future career of business and administration students. They are preparing undergraduates and master students for entry-level jobs and may suggest the real potential of a future job candidate. Universities have been using internships to provide business students with practical experience, while offering a variety of benefits to employers: candidates adapted to working environment with better communication skills, wider problem-solving skills, and improved team working [
1]. International research states that the overall perceived value and attitude towards these programs is positive [
2,
3,
4,
5]. There is a significant growth of students’ involvement in real business and an obvious engagement of companies towards future potential employees. Still, research states that students’ expectations before taking an internship may not match their experiences after experiencing one [
1]. Although there is a variety of internship opportunities in for-profit businesses, non-profit organizations and public administration structures, the quality of these programs is shaped by all the actors involved in the process. Despite the potential benefits, the internship shortcomings are related to a lack of careful planning, adequate supervision, uniform requirements, and application of theory [
6].
In the last decade, business universities in Romania have been placing an increasing emphasis on student internship programs. As business teachers we have been involved in several tutoring activities and we identified different challenges, mostly related to the quality of internships. Our paper aims at identifying and analyzing the main factors which influence the quality of an internship program from students’ perspective. We chose the students’ point of view as they are the main beneficiaries of these practical experiences. The objective of our paper neither consist in creating a ranking of the aforementioned resulting factors nor in establishing to what extent they might influence the quality of an internship program, but in the interpretation of the resulting clusters of variables (factors). By acknowledging the factors which positively influence the quality of an internship from students’ perspective, third parties receive important suggestions about how they could better organize internships. Furthermore, they understand what to focus on while developing such programs in order to meet students’ expectations and needs for professional development. Some studies [
7] concluded that internships not only educate students, but may also educate educators to understand what is important for different industries.
This paper’s findings and analysis are based on a survey conducted on undergraduate and master students of the Bucharest University of Economic Studies (BUES). The framework of the research and analysis work extends mainly over the time period 2015–2018.The analysis is conducted by applying a quantitative method–factor analysis. Factor analysis is a clustering method for variables as well as a dimension reduction method. As a clustering method, factor analysis tries to identify coherent subsets within a large set of variables based on covariance and correlation analysis. The items within a subset—which are called ‘factor’ and ‘results’ from running the factor analysis—should be strongly correlated between each other, while the resulting factors are relatively independent of one another [
8]. As a dimension reduction method, factor analysis tries to cut down a large number of variables with similar meanings contained usually in a questionnaire to a smaller number of variables, called factors, which could be used in further statistical analyses. The underlying items should converge to the same concept which is reflected by the denomination of the factor.
In Romania, there are no studies addressing the factors influencing the quality of internships. Students’/academic staff’s/employers’ perceptions and considerations about factors contributing to the quality of the internships programs were not investigated and examined. This paper provides an analysis about the main factors which Romanian business and administration students consider relevant for the quality assurance of internships programs. The conclusions of this work may be used as valuable inputs for management/business schools/universities to improve the quality and relevance of their internships programs to better address the students’ expectations. The conclusions of this paper are targeting the business and administration students in Romania; the results obtained could be further used for cross-country and/or cross-study field and comparative studies.
The paper commences with some introductory considerations on the importance of internships programs for students’ future careers and research methods used. The paper continues with the literature review (in
Section 2), focusing on internships contribution to experiential learning and main factors influencing the quality of internships. The literature review is followed by the presentation of the research assumptions in
Section 3.
Section 3 also contains a detailed presentation of the research methods and materials, including the sample selection, data collection and analysis and the validity tests. In
Section 4, the main findings of our survey are presented and students’ perception on factors influencing the quality of internships are discussed. The paper concludes (in
Section 6) with the authors’ recommendations for the development of quality internships for business and administration students.
Section 6 also presents the limitations of the study and further research work.
3. Materials and Methods
3.1. Research Assumptions
The research goal consists in the identification of the main predictors of quality of internship programs from students’ perspective. The research assumptions we made are in line with the opinion of European Quality Charter on Internships and Apprenticeships and other studies that emphasize the fact that students appreciate that learning outcomes and KSAs (knowledge, skills, and abilities) are improved through practice [
3,
10]. When asked to evaluate such a program, the acquirement of practical skills is essential both for students and for academia [
2,
5,
11]. The way an internship is organized and coordinated through mentorship was intensively debated in various studies that identified specific predictors of the quality of internships like: structural and curricular issues, grading systems and quality of the coordinator, host organization practices and policies, quality of resources and procedures [
30,
31,
32]. We also put the research assumptions in relation with different studies analyzing millennials that underline their great emphasis on practical learning, workplace relationships, interesting work, clear opportunities, and guidance [
43,
44].
Starting from the aforementioned goal and based on evidence from the scientific literature detailed in the previous sections as well as on the educated guess of the authors, the following assumptions can be inferred:
- A1:
The acquirement of new practical skills is a significant predictor of quality internships.
- A2:
The way an internship is organized is a significant predictor of quality internships.
- A3:
The mentorship offered within the organization is a significant predictor of quality internships.
- A4:
The academic supervision within the faculty is a significant predictor of quality internships.
- A5:
The relations with the colleagues within the host organization is a significant predictor of quality internships.
3.2. Materials and Methods
We conducted a questionnaire based survey among undergraduate and master student population enrolled in business and administration university education programs at BUES, the most representative university in Romania in the economic and business field: it has 12 faculties offering the opportunity to study in different languages (Romanian, English, German, French) for over 21,000 students who may choose over 22 Bachelor’s Programs, 88 Master Programs, and 10 research areas for PhD studies. All educational programs offered business and economics areas, such as: finance, management, business administration, economics, international business, business law, public administration, tourism and hospitality management, accounting, informatics and cybernetics, etc. This is the reason for which we have considered BUES the most representative university for business and administration education in Romania and decided to conduct the survey at this university. Further similar studies can be conducted in other universities from Romania and results can be presented in a comparative way. However, as a starting point, we considered it appropriate to conduct the study in one of the biggest public higher education institution from this field.
The aim of this survey was to identify the quality predictors of internship programs from students’ point of view. The questionnaires were distributed during 2015 to BUES students from bachelor and master programs from all faculties, at the end of their internships programs; data analysis and interpretation were developed during 2016–2018. The questionnaire’s items (depicted in the next sections) were partially inspired from other similar studies on internships and were adapted to the peculiarities of the country and its economic university education system. Before launching the survey, a focus group, which brought together various experts and stakeholders from the education field as well as students (HR practitioners, academics, students, employers, etc.), was organized. The purpose of this focus group was to confer a broader perspective on the analyzed topic, namely quality of internship programs. Following the discussions and debates within the focus group, the existing items, provided by the authors in form of an initial questionnaire, were further improved and developed and new items resulted. A draft version of the questionnaire was tested during a pilot phase on 30 persons at the end of 2014 before the final version of the questionnaire was developed and distributed.
The items used for factor analysis in the present paper were formulated on a five-point Likert scale, which assesses the degree respondents agree or disagree with the statement as follows: 5—strongly agree; 4—agree; 3—neither agree nor disagree; 2—disagree; 1—strongly disagree. We opted for the Likert scale due to its multiple advantages: one the one hand, it has a high versatility and it is one of the most frequently used scale in surveys. Therefore, respondents are familiar with it and it is easy understandable for them. On the other hand, responses obtained are quantifiable, simple to code, and can be easily used in further quantitative data analysis. Due to the fact that all items are measured on the same scale, different operations with these items can be conducted. There are different Likert scales: the three-point, the five-point, and the seven-point Likert scale. The main drawback of the three-point Likert scale consists in the fact that many respondents that are not decided or want to simplify their decision-making process opt for the neutral answer, namely 2. The seven-point Likert scale can be also confusing due to the many options it offers. The most commonly used Likert scale is the five-point one. It encourages respondents to use all the five possible answers and it is also highly versatile.
In order to increase the accessibility for the respondents and consequently to maximize the response rate, we used different means of communication with the target group. Therefore, the questionnaire was distributed both on paper and in electronic format on a platform especially created for this purpose. 458 valid answers were collected and the obtained raw data was processed using various statistical methods such as the factor analysis presented in this paper.
The questionnaire design highlights four main parts: the first part contains demographic questions about respondents (see
Table 2), while the second part attempts to characterize the internship program from different perspectives (such as field of activity of the organization, payment of the internship, timeframe, how the internship program was found, etc.). The third section represents the core of the questionnaire and its items represent the basis for the factor analysis depicted in the following sections of this paper. The items of the questionnaire refer to different aspects of internship programs which influence their quality, such as: content of the tasks assigned to interns, relationship between the internship and the field of study, capacity of applying theoretical knowledge acquired at the university in practice, relationship with the coordinators from the organization and from the university, relationship with colleagues within the enterprise, infrastructure at the internship, access to training and development programs, organization of the internship at faculty and company level, induction period, evaluation of the acquired knowledge within the organization and university. The fourth component of the questionnaire contains open questions which offer respondents the opportunity to mention and detail positive and negative aspects of the internship and suggest improvement measures.
The demographic profile of participants was outlined by means of frequency analysis as depicted in
Table 2.
As resulting from the data above, over 75% of the participants are female, while just 24% are male. This outcome is not surprising, as it is well known that feminine student population prevails in the field of economic studies in Romania. According to the data, the overwhelming majority of the participating students (95%) are between 21 and 25 years old and the remaining 5% belong to the following categories: 2% are under 20 years old, 2% are between 26 and 30 years old and 1% are between 31 and 40 years old. Of the total number of participants, 82% are Bachelor students, while 15% are attending a Professional Master Program, and 3% a Research Master Program. The results of this category are directly related to the results regarding respondents’ age.
The main field of study of the participating students is Public Administration Management (40.39%) followed by Agribusiness (15.72%), Business Administration (8.95%) and Management (8.29%). The less represented areas are Finance (7.86%), Accounting (6.76%) and Human Resources Management (4.36%).
It could be observed that a large part of the respondents is conducting the internship in public institutions: 37% in public institutions at national level and 2% in public institutions at international level. This result is connected with the fact that many respondents study Public Administration and they are inclined to follow a career path in the same sector. On the second place we find SMEs (25%) followed by multinational companies (14%). 7% of the respondents opted for an internship in a NGO and a small part for an internship in a university (5%) or in its own company (1%). The analysis of the answers of those who ticked the option “Other organization, namely...” reveals that the most common other organizations were political institutions or parties at local or national level as well as local and regional public institutions.
4. Research Results
Related to the methodological procedures there are some major logical steps that were taken: based mainly on the literature review there were formulated some research assumptions (certain factors were expected to influence the quality of internship programs). The questionnaire was developed, refined, distributed, and the answers collected. We applied the factor analysis to the questionnaire’s items in order to see which factors which impact on the quality of internship programs would result. When dealing with factor analysis several decisions regarding data analysis techniques were made. We analyzed the assumptions made in the context of the resulting factors. Consequently, based on the resulting factors we established the main directions which might lead to quality improvement of the internship programs.
The final form of the questionnaire is a result of the focus group. Data obtained through the survey was analyzed using factor analysis and other statistics. Factor analysis is frequently used in social sciences, when researchers aim at measuring and quantifying complex and abstract phenomena and dimensions. Factor analysis clusters items which lead to a common idea or concept [
45]. We can state that this is also the case for the current research: we aim at assessing the quality of the internship programs from students’ perspective, a vast phenomenon which is difficult to be reduced to some quantitative factors. There are many facets of quality of internship programs. If these are not properly grouped in larger thematic clusters (in our case the factors resulting from factor analysis), stakeholders might lose focus and no clear overview of the fields of action can be provided. Therefore, taking into account the topic of the present paper, we consider the research method factor analysis suitable for the purpose of the paper: stakeholders of internship programs (e.g., universities, organizations, students, etc.) need to know which are the major dimensions they should concentrate on to improve the quality of internship programs. The factor analysis leads the readers exactly to the aforementioned dimensions. Thus, it is much easier to develop policies, programs, and measures aimed at raising the quality of internship programs, when one deals with structured information, which offers the ‘big picture’ of the field.
Factor analysis could be also considered the equivalent of cluster analysis (which tries to identify typologies of respondents) for items. In order to identify the key factors which determine the quality of an internship program, there have been formulated 25 items which were introduced in the questionnaire depicted in the above sections. We employed exploratory factor analysis to extract the dimensions/factors which influence the quality of internship program and toward which the 25 items converge. Through factor analysis we aimed at quantifying the contribution of each item to each of the resulting factors. This is possible by means of the factor loading. Using the equation from below, it can be assessed the contribution of each item to each of the resulting factors
One important issue within the factor analysis refers to the number of items which should be considered when defining a factor. Each item makes a contribution to each factor, but for some factors this contribution is very small and therefore not relevant. A reasonable expectation is to obtain a much smaller number of factors than the number of items, which can deliver a better overview of the topic discussed. The main task of the researcher consists in selecting those items which are significant for a factor and should be taken into account when defining it and based on this selection to infer the latent variable, in our case, the FIQs. One possibility consists in setting a priori a fix number of factors before running the analysis or leaving this option open. In the second case, in the literature are mentioned several decision criteria on the number of factors such as eigenvalue, scree plot, or fixed % of variance explained [
8]. In the present paper, we used the eigenvalue criterion (eigenvalue larger than 1) considering the fact that, if the eigenvalue is big, then that item has an important contribution to the underlying factor.
Mainly, there are two types of rotation: the orthogonal and the oblique one. The case of oblique rotation is more complex and correlation between factors is admitted. The statistical technique used in the present research is varimax orthogonal rotation, as it aims at maximizing the dispersion of factor loading within each factor. Also, by loading less items highly into each factor, the resulting clusters of factors are easier to understand and interpret.
As previously mentioned, extraction was based on eigenvalues greater than 1 and each of the 25 items was selected just for the factor, for which the factor loading was the greatest. Out of the 25 items, five have eigenvalues larger than 1 and therefore we the five selected factors (FIQs). As exhibited in the
Table 3 the cumulative total variance explained is 63.267%, which is in line with other researches in the field of social sciences.
As presented in
Table 4, all factor loadings retained for analysis are greater than 0.4, the minimum value recommended by specialists. At a sample size of more than 300 respondents (which is also our case) the minimum value recommended is even smaller [
46]. The five extracted factors and their corresponding items are presented in
Table 4. In order to deliver a better overview of the resulting factors and the underlying items, the coefficients (factor loadings) are sorted by size, small coefficients are suppressed and there are displayed just the biggest coefficients for each factor.
Data from
Table 4 should be interpreted as following: the fact that item 1 to item 9 belong to factor 1 means that they are (strongly) positively correlated with each other and only poorly with the items belonging to other factors. This means that if one person scores, for example, ‘5’ at Item 1, it is likely that the same person has a similar score at Item 2 and so on.
The results of the test Kaiser–Meyer–Olkin (KMO) are presented in
Table 5 and deliver information about the adequacy of the sample. The minimum recommended value for KMO is 0.5 and the obtained value of 0.93 could be considered as very high. The results of the Bartlett’s Test of sphericity are significant (Sig. = 0.000). This indicates that matrix R differs from the unit matrix (case in which correlations between items would have been 0, which means that between the items selected there is no correlation and therefore it is unlikely that they converge to a common idea, namely to a certain FQI). Consequently, the factor analysis can be run [
47].
After analyzing within the research team the results presented in
Table 4, the five resulted factors were interpreted as following: Factor 1—job arrangements; Factor 2—mentorship and employability benefits; Factor 3—learning content; Factor 4—academic supervision; Factor 5—bureaucracy and accessibility.
As depicted in the previous section of literature review these factors are in line with the outcomes of similar studies conducted in other countries and fields.
The items associated with Factor 1 cover aspects related to the organization of an internships which are approached from different perspectives: feedback received by students for their activity, tasks assigned, schedule, infrastructure and materials provided, workload, integration within organizational landscape. Considering the abovementioned issues, Factor 1 was called “job arrangements”. The items contained in Factor 2 focus on relations developed at working place, in particular with internships supervisor assigned by the host organization and, with other colleagues, development of communication skills, team activities, relevance of skills acquired for future employments and career. Accordingly, “mentorship and employability benefits” was considered a proper denomination for Factor 2. The items composing Factor 3 refer to the job content, the relation between knowledge acquired at faculty and tasks assigned at work place, the use of theoretical knowledge to real work experience. Therefore Factor 3 was called “learning content”. Factor 4 was called “academic supervision”; it refers to the relation between interns and the academic supervisor of the internship from the university, the internship assessment, grading system, and academic credits, academic bureaucracy, and documents. Factor 5 was called “bureaucracy and accessibility” and it covers items related to physical accessibility to the working place, logistics, documents flow and formalities, academic and employer internal bureaucracy.
Once the five factors have been identified, it was computed the Cronbach’s Alpha coefficient for each factor, in order to confirm the internal consistency of the scale. Cronbach’s Alpha index indicates if the underlying items reflect the factor that they actually measure and it is commonly used to check the consistency of the scale. In other words, the Cronbach’s Alpha coefficient ascertains if the scale is consistent and reliable and the measured construct (in our case each of the five FQIs) is unidimensional (the scale measures just one single latent variable). The values of Cronbach’s Alpha index rank between 0 and 1 and in the ideal case they are close to 1. In social sciences, there are many debates related to the minimum accepted value, but many scientists agree on the fact that 0.6 should be the minimum accepted value. Cronbach’s Alpha might vary according to the underlying number of items: the greater the number of items, the higher the probability that Cronbach’s Alpha has a larger value. From this reason in the case of factors which contain a small number of items, the values of Cronbach’s Alpha coefficient are usually smaller [
48]. In the following table are displayed the values of Cronbach’s Alpha for each of the five factors. It is also computed the Cronbach’s Alpha in the case of the elimination of each underlying item and it results smaller values in all cases of deletion. Therefore, it is not recommended to remove any of the items.
From
Table 6 it results that the value of Cronbach’s Alpha for the first four factors lies significantly above the recommended value: Factor 1—job arrangements (0.909), Factor 2—mentorship and employability benefits (0.846), Factor 3—learning content (0.82), Factor 4—academic supervision (0.847). For the fifth factor, bureaucracy and accessibility, Cronbach’s Alpha value is smaller, namely 0.40. This result can be explained also by the fact that this factor relies on only two items. No further statistics in case of the removal of an item are presented, as they would be irrelevant in this case: a factor has to rely on a minimum of two items.
Considering the resulting factors depicted above, we can state the A2 and A4 are fully confirmed (see Factor 1—job arrangements and Factor 4—academic supervision which refer exactly to the predictors stated in A2 and A4). On the other hand, we can state that A1 is just partially confirmed as items related to new practical skills are embedded in Factor 2 and Factor 3, but they do not lead to an independent factor. The same can be stated about A3 and A5, as items related to A3 are embedded in Factor 2 and items related to A5 can be identified in Factor 2. However, they do not meet the prerequisites to form independent factors. Therefore, two of the assumptions are fully confirmed and the other three just partially.
5. Discussion
Our research reveals students’ perception about 5 key factors influencing the quality of internships: Factor 1—job arrangements, Factor 2—mentorship and employability benefits; Factor 3—learning content, Factor 4—academic supervision, Factor 5—bureaucracy and accessibility, as described above. The survey provides good insights for companies and universities about the development of quality internship programs in the Romanian context.
The survey confirms that the benefits students associate to the experiential or work-based learning internships influence their perception about the quality of these programs. This also attests previous studies’ findings, which show that the quality of internships is positively correlated with their content and learning outcomes, the contribution of the internships to employability [
37,
49], as well as with the management and supervision of internships.
The findings also indicate that the quality of internships depends on the design of the programs, as indicated by Factor 1—job arrangements. The survey reveals that students value: organizational arrangement, in particular, the feedback received; the tasks assigned; the workload and activity schedule; infrastructure and materials provided; and integration within organizational landscape. Programs that are poorly administered can also have undesired impacts [
37]. The survey confirms the findings of previous studies, in particular related to: the content of the work and workload [
4,
40]; engagement in the company activities [
38], in particular students’ integration and cooperation with other employees [
40]; and received recognition and acknowledgement for their work [
4,
40]. Our research revealed that students are associating the good management of internships with clear definition of tasks and objectives and continuous feedback. Therefore, good internships have to include proper monitoring and assessment procedures [
32]. The quality of internships is also associated with the acknowledgement and received recognition [
4,
40] expressed directly (positive feedback and evaluation from supervisor, other employees or managers) or indirectly (usefulness of their work, the equal treatment of interns and employees). The items covering feedback are connecting Factor 1—job Arrangements with Factor 2—mentorship and employability benefits, emphasizing the role of the internship supervisor.
Findings related to Factor 2—mentorship and employability benefits reveal that surveyed students associate quality internships with their contribution to the development of professional knowledge and increased employability, in particular with the development of transferable and work-related skills such as team work, time management, and communication skills. Furthermore, the results of the survey confirm that Romanian business students, similar to social work students [
42,
49] assess the value of internships according to their contribution to the development of soft skills, critical for their employability. Unlike social work students, Romanian business students did not mention critical thinking as a relevant skill for their future employability. The research also confirms the importance of mentorship [
4,
5,
29,
40] and of the relationship between mentors and students. Thus, the quality of mentoring is considered by Romanian students a predictor for the quality of internships, since it contributes to their further professional development and maximization of learning outcomes.
Factor 3—learning content, is associated with the following items: job content, the relation between the tasks assigned and the educational level of interns, the correlation between theoretical knowledge acquired at faculty and tasks assigned at work place. The survey indicates that students correlate the quality of internships with positive learning outcomes resulted from performing specific tasks. Unlike other studies [
13,
37], students did not refer to learning methods deployed by supervisor or to the industry related training provided during internship program. This may indicate that they consider less relevant how knowledge and skills are delivered. What was important for them was the relevance of acquired knowledge and skills for their academic background and professional career. The students endorse the content of the experiential learning and work experience provided by internships as important contributors to their university education and learning.
Academic supervision (Factor 4) is also considered part of the quality of internship programs. These results, along with findings related to Factor 3—learning content, indicate that students perceive internships as work-based learning programs endorsing and complementing academic curricula. The academic supervision was also identified as quality factor for internship programs by students from other fields: sport students [
50] and hospitality students [
5]. Unlike these students, Romanian students limited academic supervision mainly to the support provided for managing and solving bureaucratic issues. The counseling skills of the academic supervisor were not considered highly relevant.
Other items considered important for the quality and attractiveness of an internship program are related to bureaucracy and accessibility to internship workplace. These specific items were clustered under Factor 5—bureaucracy and accessibility. Accessibility of the physical location, defined in terms of proximity to university or to their homes, was previously identified as factor influencing the preference of engineering, sciences, business, management, and sport students [
37] for a certain internship. Romanian students complained about bureaucratic burden associated to their internship programs. Since bureaucracy was not identified as quality factor for internships in previous research, one could conclude that this factor is specific to our university and is negatively affecting the quality of Romanian internships. Further improvements in the governance of internship programs—the simplification of administrative procedures and documents—have to be considered by the management of the university.
Compared with other previous studies [
5,
31], Romanian students did not mention financial remuneration of internships among the factors influencing the attractiveness and the quality of internships. This is not surprising because financial compensation of interns is not common in Romania as internships are in general mandatory in our academic curriculum.
On the one hand, analyzing Factors 1, 2, and 4 we can conclude that, based on students’ perception, internships should have clearly stated educational objectives. Within this context, academic supervision should play an important role when designing and managing internship programs. On the other hand, analyzing specific items from Factor 1 (internship workload) and Factor 3 (job content) we can conclude that the workplace supervisor (mentioned in Factor 2) also plays an important role when delivering relevant learning content and developing skills. Within this context, the workplace supervisor also has administrative responsibilities.
The five factors identified through factor analysis may be considered predictors of quality internships. In depth analysis of the items contained by each factor reveals areas in which improvement is needed at university level. Firstly, the effectiveness of academic supervision needs to be improved.
Our findings confirm that the quality of internship programs for business and administration students depends on clear educational objectives, development of specific academic-business partnerships, internship management, and assessment procedures [
6,
30,
51].
6. Conclusions
Business schools and universities are asked to respond to the pressure to make their curricula more relevant and to prepare students to be active contributors to business development and management immediately after graduation. Business university education should generate knowledge to equip its future graduates with ability to manage organizations [
52]. To this end, the development of quality internships programs for business university students could make the academic curricula more relevant for industry needs and narrow the students’ knowledge gap being defined as the “difference between what students know and what students can actually do” [
52].
Based on the findings of this paper, students, academics and industry are key contributors for quality internships. Interaction between industry and university becomes critical for the development of quality internships for business university students. According to our findings, from business and administration students, cooperation between university and industry is essential for quality internships. University–industry cooperation should address the learning objectives as well as the organization, evaluation, and assessment procedures.
Universities are formally responsible for designing the internship programs. It is through internships that university students experience work-based learning and put theory into practice. Internships programs supplement the coursework and should contribute to the development of students’ job-related skills, professional knowledge, and increased future employability. The academic curricula for business university students should be oriented towards students’ employability; thus, internship programs should give to the students the possibility to reduce the existing gap between what a student knows (theoretical knowledge acquired during academic classes) and what a student can do (capability to make use of the knowledge at future employment). From the student’s perspective, curricula for internships should give them the opportunity to close the knowing-gap [
52]. To this end, university management should actively involve the industry representatives in the design of internship programs. The industry contribution should be reflected in both the definition of the learning objectives and internships’ curricular issues design, as well as the interns’ evaluation and assessments procedures. Therefore, industry should provide inputs to university management about the industry specific work content, knowledge, and skills required to be used in designing the mandatory academic objectives and learning content of internships program to ensure their relevance for students’ future employability goals.
Industry is providing placements for interns. Host organizations from industry should meet specific criteria for quality internships organization and management. Host organizations are responsible for creating a learning supporting environment, for the workload and tasks assignment to interns, for on the job training and involvement in day to day activities of the organization, performance assessment, and for providing quality feedback to interns during their internships. Host organization mentorship is essential for quality internships. To this end, industry should ensure well-trained mentors are present who capable of understanding the learning objectives, creating collaborative working environments to support the learning objectives of the internship programs, and providing quality feedback. Mentors in host organizations are responsible for the monitoring of the students at workplace and for delivering periodical analysis of their progress reports to academic supervisors. Provision of quality feedback to students during internships is essential for interns’ learning performance and development of relevant skills related to employability. Feedback provided should be based on specific assessments and evaluation procedures during the internships. Therefore student monitoring performed by mentors at the interns’ workplaces should provide relevant inputs for in the job interns’ performances and to evaluate their progress by reference to the expected learning outcomes. Assessment and evaluation procedures of internships should accommodate both academic objectives and employers’ specific objectives; therefore university–industry cooperation becomes critical. Based on our findings, academic and mentors’ supervision and evaluation of interns should be formative, focusing on learning outcomes, compliance of the academic curriculum with learning contents, and development of interns’ capability to implement theoretical knowledge in practice. Academic supervisors and mentors in host organizations should permanently cooperate for the improvement of internship programs; interns should also be part of this process. Periodic meetings between academic supervisors and students, between academic supervisors and workplace supervisors, and between all university supervisors are highly recommended for quality internships development.
When referring to the quality of internship programs, most definitions refer to the relevance of the interns’ learning experience for academic instructional goals and employability objectives. Therefore, we focused on the students’ perception as they are the main beneficiaries of these work-based learning programs. Based on these considerations, in our opinion, it is essential that students’ perception to be considered by both university management and industry representatives for developing quality internships programs. Our paper summarizes the business and administration students’ perceptions about factors influencing the quality of internships programs. Our study is useful for any business and administration school to deliver quality internships which are consistent with students’ needs and employability expectations. Our findings are also useful inputs for employers for the delivery of quality internships for business and administration students: at the workplace, interns should benefit from good mentorship and a proper work-based learning environment to support them to close the knowing gap.
The study conducted has its limitations and further research is necessary in order to have an overall view. One of the main limitations of the present survey refers to the structure of the sample, which consists in students from BUES. Secondly, the perception on quality internships is assessed only from students’ perspective without considering other stakeholders’ opinions (e.g., employers, academia). Further research is expected to be conducted so that resulting outcomes could be compared with current students’ perspective. The final aim consists in identifying common areas to build upon for internships success. Recommendations for further studies refer also to the extension of the sample to other fields and regions of Romania. In this case, comparative analyses between different fields of study and activity as well as between regions could be conducted. Consequently, a better methodology for internship programs could be developed at university level and also a best practice guide at national level.