Average Likert scale scores

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Empirical findings


This section is to present the findings from the interviews displaying different figures to be able to show the results. The findings are focusing on the participants involvement in student associations and their main impressions and takeaways. In addition, how they believe their involvement in a stu-dent association contributed to personal growth and how employable they became. We asked the participants on their recruitment experience and how they outlined their involvement in an associa-tion as well as how the recruiter emphasized different experiences. Through the interviews we could narrow down different aspects about their experience in a student association and what they said related to literature about employability. In appendix 3 we have provided you with the inter-view questions, however, it is important to remember it was semi-structured interviews which means that more questions have potentially been added in the interviews depending on the re-sponses. The first step was to identify categories that was discussed the most during the interviews. Different categories have been created through the transcriptions. The categories that occurred is the result of the overall emphasis on involvement in student associations and experience. Appendix 9 pro-vides graphs for each interview, showing the different categories. The identified categories were; learning, developed soft skills, leadership, time management, communication, delegate, find a job, creative, hours spent in student association, soft skills, experience, networking. However, the order of the categories is not a reflection of its frequency. We have displayed a table showing the main category from each interview. The table illustrates the parts of the interviews that was the most dis-cussed and can indicate the perceptions of the interviewees. However, this do not set the tone or importance from the interview when it comes to the main takeaways. This is strictly to illustrate the most discussed category from each respondent.

Table 2. Main categories from interviews.

Interview 1         Leadership
Interview 2         Experience
Interview 3         Experience
Interview 4         Soft skills
Interview 5         Learning
Interview 6         Experience

Furthermore, to get an overview from the interviews we have displayed a shortened extract from the excel document with word frequency from all six interviews. It helps indicate the accurate and narrow findings from the interviews. Word, length, count, weighted percentage and similar words are provided in the table. Nevertheless, minor adjustments have been done in the development of the word frequency table, we censured minor hollow words to avoid explanatory and “talking-words” and our own questions and comments from the word count. However, with just minor adjustments we still identified words that aligned with the takeaways/categories from the interview and did therefore not adjust the word frequency table any further. As a result, relatively low percentages are shown in the table. Positive, experience and involved were the three most used words in different the interviews. All participants considered their participation as something positive and something that included them in different social groups which to them was a personal gain by combining project work with posi-tive and fun aspects. P2“I had a lot of ideas, over time you get more experience” The positivity was firmly connected with the per-sonal gains, in relation to the networking and social scenery that took place. Networking was one of the main categories from the transcripts and p4“It gave me contacts, we were able to write our thesis with a company through contacts through the association” P6“I could use my experience from xxxx as well as learning from my mistakes” the self-reflection and learning opportunity was evident for all the participants. The more we discussed the more topics was cov-ered by the interviews, both communication and relationships building, P2“I like to build relation-ships”, P1“Important to listen first to everyone so everyone can speak their mind, and open communication is im-portant”. Communication and problem-solving in the different projects of student associations was something most interviews agreed they had experienced and depending on your role in association communication became vital. Personal growth was also linked to both experience and the positive takeaways from involvement in student associations, P5” You can challenge yourself”, as learning experience student associations could challenge the participants to grow themselves, both in terms of skills and other personal attributes: P4“Did contribute to knowledge and insights”, P1“I learned a lot about myself specially how to handle people and how to start working in a project environment”. One of the main takeaways from the interview is how the participants talked about experience, and to get hands-on experience by being involved in a student association. Since student associations takes place at university, theoretical experience is provided and among our interviewees it was evi-dent how important they considered projects within the associations were, in order to gain experi-ences beside part-time jobs and education, P2“Important to be a part of committees to get other knowledge more practical knowledge than just theoretical”. However, no parallels were drawn or linked between aca-demical learnings and the project learnings from student associations, the interviewees did not state they used theory from school, besides finding interests within different subjects and therefore par-ticipating in a student association. We consider it important to highlight the respondent’s emphasis on getting hands-on experience by being a part of a student associations, since they indicated that the experience itself gave them the opportunity to develop certain skills. P5“To get hands on experi-ence” P6“Experience I can apply on real life cases” P3“Being able to be hands-on” P1“Feeling proud to have ac-complished something” The experience as such which the respondents discussed was related to both personal opinions on how to spend your time at university as well as having fun and meeting new people. These aspects were the main reasons and motivation why the participants would recommend new students to be involved in a student association. The importance for us to know why and if the respondents would recommend new students to be involved in an association is to see if there were more reasons and motivation behind one’s involvement than the participants themselves know, P2“I wanted a learning experience and needed something practical since the program I attended did not have any internships”. As stated in the beginning of the thesis, we hope to help new students navigate their time at university along with maximizing their time at university which is why it is important to see if the interviewees would recommend being involved, since we are exploring the topic of perceived employability and what can lead up towards that,P5“I think that it is s a really good experience, the planning part and the parts afterwards when you look at everything you have done was this good was this bad how to do it better next time and then you have been a part of the whole process that is something is really good”. The majority of the reasons and motivations behind getting involved laid within internal beliefs of the social spectra that student as-sociations can provide, the potential to network as well as the experience as such. Within the term experience, we can find soft skills and learning, which was two major categories covered in the interviews, see table 4.1, P4“Leadership experience”, leadership, which also is one of the main categories are connected with both experience and learning as well as soft skills, P1“I think that there need to be two kinds of leaders within a team to balance out, if the manager would not have been strict, I would have had to be stricter.” Leadership could be considered a skill, and was discussed throughout all inter-viewees, reflection about how the interviewees themselves would be as a leader as well as how they had perceived leader within student association, P2“The leaders now were very focused on the goals. It’s good to see different perspectives”. Another important takeaway from the interviews is how all the participants in one way or another discussed how through their involvement in an association felt responsibility for the operations. Most comments about responsibility was in regard to how the participants felt obligated to perform in another way compared to their studies which enabled them to perform at their best at most times. Being responsible for others performance or having the obligation to complete something when other people are depending on it was what was emphasized and the underlying meaning; reli-ability. P6“With money comes responsibility, we had to create a brand, we had to look professional, we could not look like a group of students” P4“It takes time to realize you have responsibility” The category hours aim to determine the time spent on student associations, P3“It really depends on the role you have in the project and when it was, up and down with how much time”, it was important to locate how and why the participants spent the time they did on their involvement. In addition to how much time was spent other activities, school and more. The importance lays within how student as-sociations could have affected the students’ studies, both in a positive or a negative way and there-fore affected the overall experience of their involvement.


Firstly, in order for us to display the findings from our survey, we want to clarify matters that has affected the overall graphs and tables. As stated, we decided to use a CFA to apply on our survey and when using a CFA there are certain restrictions and guidelines one needs to follow. Since our aim was to reach a participant level between 200-300 and ended up with 75, this complicated the process of applying CFA on our research. Of the 75 participants we could use 56 to our CFA due to the criteria that a participant had have graduated and have been a part of an association, see ap-pendix 1. However, since this was the chosen method for our research, to complete a survey and apply CFA, we decided to stay on track with the plan and execute it, with reservation of its limita-tions and pitfalls due to the low participation level. It is important to be able to show reasons for what other equivalent models there are compared to the one chosen in a CFA, though it will be dif-ficult to follow that step we have created a simple CFA model. Since we developed a simple CFA model there are likely few equivalent models that explain the relationships in our data. The low participation level could have been avoided if there would not have existed a time re-striction and the choice of a CFA was implemented due to previous researcher’s method of re-search and their results. Although we were aware of the time restriction, we applied methods to en-able us to get enough answers to the survey by creating multiple plans how do distribute the survey and how often we could and would send it out. Through transparency of our findings and open dis-cussion of the results we decided to still include the CFA and explained throughout the display of findings from the survey.


Below you will find our model for the CFA that we have used for our thesis, the aim of the CFA is to test if factors that are hard to measure on their own. They can be measured with questions that are categorized together to measure the factor. The factors we measured are “Soft skills” (SS) and “Perceived employability” (PE) and we measured them with the rectangles SS1, SS2, SS5, and PE3, PE4, PE5 respectively. Under the model you can find the questions that belonged to each rectangle and were used in our survey to measure the factors. The double-sided arrow connecting the factors show if there is a correlation between them and we found one at 0,07, this was not statistically sig-nificant. our survey did accurately measure our factors and the questions in the model had the best factor loadings. The SS factor was mostly measured by creativity, initiative taking and leadership skills, which overall indicates that those were the skills most participants obtained or developed through-out their involvement. Furthermore, the questions that measured PE was possessing desired skills and abilities, feeling confident in job interviews and that their experience and skills are sufficient for any relevant job. The model observed above is one of four models for the factors listed in the data collection. How-ever, this model was chosen because it had the best factor loadings and model fit to our data. Addi-tionally, it had the best alignment with the interviews and our theoretical framework. See appendix 11 for the other models, which also follow the simple CFA model, these did not have acceptable model fit and are therefore not included in our display of the empirical findings from the survey.

Table 4

Table 4 shows how well the questions measure the factors SS and PE as in the model above where the same numbers are displayed by the arrows going from the factors to the questions. Additionally, you can see the standard errors (SE) that explain if our data has a spread similar to the entire popu-lation, given that the value is low like ours. We report both the standardized and unstandardized factor loadings, however focus on the standardized estimates as they can be interpreted without having to keep the scale of the questions in mind. Since other researchers may use a different num-bered Likert scale we chose to focus on standardized estimates for easier comparison (Easterby-Smith et al. 2015). These factor loadings show the effect of soft skills and perceived employability respectively from the questions listed above. A benchmark for factor loadings of > 0,7 is to be con-sidered good (Kline, 2007).

Table 5

In table 5 we present model fit statistics which tells you if the model used for our thesis fit the data from our survey that were tested in our research. The first three rows combined shows the results for a model chi square score, where the first row is the chi square statistic, the second is degrees of freedom and then p-value. It tests the exact fit hypothesis of our model and if you accept the hy-pothesis, as we do due to a p-value of >0,05, it indicates that the chosen model has a good fit with the data. Next, we present the GFI test and as the value gets closer to 1 it indicates best fit, and our score of 0,939 shows it has a good fit. The CFI test compares our model’s hypothetical improve-ments in fit to a baseline model and the value should be ≥0,9, with our value we can determine our model to be better than a baseline- model. Lastly, Our RMEA tests show whether our model is too complex, a value of ≤0,5 indicates good fit. As shown in our RMEA score is 0,87 and exceeds 0,5 indicating that our model is too complex to explain the data, this can be related to the low level of participation.

Table 6

In table 6 we present the Cronbach’s Alpha for the questions used to measure each factor. The results show how related the questions are to each other and is expected to be high since they are supposed to be categorized together. Scores >0,8 are considered high. This shows that our questions would have been suitable to use as a measurement tool if the participation level was higher.

Average Likert scale scores

As seen in appendix 8, the survey is categorized into five matrixes. In appendix 10 you can find five graphs showing the different average distribution results from the survey, the answers are from 1-7, with 1 being strongly disagree and 7, strongly agree. Down below is a display of a table showing the average Likert scale score per category. This table is to provide the reader will full transparency of the findings. Four out of five categories equaled agree in terms of getting a result with 5,5 or above on the scale. Which can be an indication that the participations of the survey did see a relationship between their involvement in a student association and the five categories. As stated, the different categories forming the matrixes is a result of previous literature about perceived employability and student as-sociations as well as the results from the interviews. The total average is 5,4 which represents “slightly agrees”. However, networking, soft skills, responsibility and perceived employability scores closer to 6, representing “agree”. As indicated, time management was the lowest scored category, the result would suggest that out of the five categories, time management was not the most relevant one. In addition to that, the partici-pants balanced school: their grades, and student associations. Contrary, networking was the cate-gory with the highest average score, 5,7, representing it as the category which what the participants took as their main positive takeaway from their involvement.

1 Introduction
1.1 Introduction to the topic
1.2 Background
1.3 Problem
1.4 Purpose
1.5 Aspiration
1.6 Definitions
1.7 Delimitations
2 Theoretical framework
2.1 Introduction of theoretical framework
3 Methodology
3.1 Research philosophy
3.2 Research approach
3.3 Research design
3.4 Research method
3.5 Data collection
3.6 Data analysis tool
3.7 Time horizon
3.8 Trustworthiness
3.9 Ethics
4 Empirical findings
4.1 Interviews
4.2 Survey
5 Analysis
5.1 Analysis of the interviews
5.2 Analysis of the survey
5.3 Analysis of the interviews and survey joint together
6 Discussion
7 Conclusion
7.1 Contributions
7.2 Limitations
7.3 Suggestions for future research

Are there factors affecting perceived employability of graduates that has been involved in student associations?

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