A Profile of Soft Skills for MTUN University Students
Sarala Thulasi Palpanadanl*, Ros Eliana Ahmad Zuki2, Azhari Mariani3, Mazlan Aris4
1 Center for Language Studies, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia
2 Institut Pendidikan Guru Kampus Temenggong Ibrahim, Johor, Malaysia
3 SMK Dato’ Ali Haji Ahmad, Pontian, Johor, Malaysia
4 Institut Pendidikan Guru Kampus Raja Melewar, Negeri Sembilan, Malaysia
*Corresponding Author: [email protected] Accepted: 15 August 2021 | Published: 1 September 2021
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Abstract: Nowadays, soft skills, such as critical thinking and problem solving are being accentuated among university students as a process of preparing them for job markets.
However, the mastery of soft skills is not easily tangible as compared to the hard skills. In this case, an instrument such as a profile is needed to measure the extent of soft skills mastery levels among the students. Thus, a pilot study was conducted to validate and determine the reliability of the self-developed profile. A quantitative method was employed where 119 final year university students who had enrolled in an English course at a Malaysian Technical University Network (MTUN) had participated. The data were analysed based on the Fleiss Kappa and Rasch Model approach. Three experts were consulted for the validity of the instrument (profile). The results showed that all the evaluators gave a very good level of agreement, k=0.95 (>0.80) based on the value of kappa. In addition, the responses from the students were analysed and the Cronbach's Alpha value obtained was high (0.990). In addition, the examination of the functionality of the competency constructed item competency was studied.
It was found that respondent reliability was 0.96 (high) and the item reliability value was 0.68 (acceptable). Only two items with the outfit values of MNSQ beyond the range of 0.6 - 1.4 were dropped. Therefore, the study affirmed that the profile was valid and reliable, and could be used to measure the university students’ soft skill abilities in terms of critical thinking skills and problem solving skills. This profile also can be useful for other educational settings and courses.
Keywords: soft skills, university students, critical thinking, problem solving, profile
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1. Introduction
Mastering English as a second language has been an all-time challenge to both educators and learners. This is because English, being a global language has been used profoundly in every aspects of life, let alone in academic settings. While most learners are grappling with the basic command of the language, educators are also looking into improvising the quality of education for subjects taught in English. Thus, besides the hard skills that learners study in academic institutions such as universities, soft skills are also emphasized so that the graduates produced are versatile and ready for employability in terms of knowledge and skills (Majid, et al., 2012;
Greenberg & Nilssen, 2015). Among the soft skills which are commonly emphasized in cognitivism include the problem-solving skills and critical thinking skills. The graduates from universities will be more prepared to undergo the job seeking processes including job searching and application as well as the preparation involved for interviews The knowledge cultivated while undergoing studies in the universities may prepare the students with sufficient soft skills so that they can utilize it during the interview session which would land them the jobs they
look for. Meanwhile, a good grasp of soft skills also will be very useful for students once they enter workplace in terms of possessing good communication ability while conversing with their peers, superiors or customers while at work.
The importance of soft skills has been emphasized in the module produced by the Higher Education Department, Ministry of Malaysia (MOE, 2006) and further emphasized in the Malaysian Blueprint 2013-2025 (MOE, 2013). Thus, besides technical skills, graduates from technical universities are also expected to equip themselves with good interpersonal characteristics including soft skills that would be useful in various communication domains even in leaderships and consultations. Apart from the competency in language usage, being well-informed in soft skills also helps in shaping the humanistic aspect of the students which is crucial in maintaining the harmony of the organization while improving their performance at the respective places. Thus, soft skills are vital for university students to equip themselves before beginning to look for their favourite occupations. These skills are also included in the English language subjects such as English for Occupational Purposes, taught in technical universities which would be very useful for the university students especially the final year undergraduates as they will be entering job market soon upon graduation.
2. Literature Review
Nowadays, tremendous attention is given to the quality of education at schools, colleges and universities. The products of our local institution including university graduates are expected to be well prepared for employability in terms of hard and soft skill equally. Therefore, incorporating soft skills in the education and pedagogy has become a crucial matter and educators need to deliberately emphasize the skills while conducting lessons to ensure students master them. However, the mastery of soft skills such as critical thinking and problem solving which are vital in managing tasks at workplace are not easily tangible as the hard skills. Thus, more attention needs to be given in incorporating these skills into the teaching and learning processes.
2.1 The importance of Critical Thinking and Problem Solving Skills
Critical thinking is one of the elements of soft skills involving high-level thinking skills (Bailin, 2002), which is a form of evaluation process that requires evidence in drawing conclusions and considering alternative explanations (Fani, 2011). Some researchers argue that critical thinking aims to produce interpretation, analysis, evaluation, inference, explanations of evidence, concept, methodology, criterion, and contextual considerations as the basis for evaluations (Zhou et. al, 2013). Critical thinking should be the core of learning because it makes a person creative and innovative to be able to solve various problems of daily life in a more complex way. Therefore, the application of critical thinking skills is very important as the preparation for a very challenging world of education in the current era.
Some scholars claim that university education is where the intervention activities would take place that could enhance students’ critical thinking skills (Warburton,2008). Therefore, educational institutions should help to improve the ability of the students to think critically (Innabi and ElSheikh, 2011). Therefore, the critical thinking skills of university students need to be enhanced so that they are prepared to face the global challenges. Besides, it becomes an obligation for educators, nowadays, to educate university students to enhance their critical thinking skills so that they can apply the skills in their daily lives more meaningfully. Previous studies also suggest that learning critical thinking skills is important in promoting 21st century’s needs (Fine and Desmond, 2015; Hamlin and Wisneski, 2012). In addition, educators
should be able to identify if the university students are capable enough of mastering the critical thinking skills in the courses they teach (Facione, 2011; Paul and Elder, 2006). Therefore, an instrument such as profile is necessary to be established at university level to be used to determine the students’ mastery level of soft skills taught in the respected courses.
Problem solving skill is one of the domains of Cognitive (Bailin, 2002) which is very important for the university students to master to be applied effectively in their future endeavours including educational and workplace settings as well as for life. Apparently, problem solving skill is mainly crucial for students when they are about begin a new section of life upon graduation (Krulik and Rudnick, 1996). Thus, this skill need to be cultivated from a very early stage of schooling years among the learners (Saygili, 2017) by teachers or lecturers need to provide suitable tasks to students to guide them with this skill while teaching (Soifer, 2013;
Taylor, 2015) which is also essential to develop their critical thinking (Kem, 2016). Thus, educators should allocate platforms for students to practise addressing the problems assigned to them. This because problem-solving skill is rather complex in terms of its practicality (Saygili, 2017).
Nowadays, university students are expected to possess sufficient knowledge of soft skills in order to solve the problems that they might encounter at university while studying and at workplace once they are employed. Possessing good grasp of soft skills would help them find reasonable solutions for the challenges that they might face in future as various problems require various skills to be dealt with. Besides, it is important to provide enough time for university students to work on tougher problems but if they cannot, they should be given simpler problems to solve so that they are able justify them accordingly (London, 1993). Hence, it is vital to teach problem solving skills to students mainly for university students so that they are able to perform well in academic tasks and real-life circumstances. Furthermore, the development of a soft skill profile that includes the elements of soft skills is seen as very relevant and important to identify the mastery level of the relevant elements of soft skills among the university students. Thus, this pilot study was conducted with the objectives to validate the self-developed profile (instrument) and to determine the reliability of items of the being studied.
2.2 Methodology
A pilot study was conducted to test the validity and reliability of the instrument before being given to the respondents in the actual study (Borg and Gall, 1983). In addition, a pilot study can be conducted in the form of a small scale research in preparation of the actual study (Polite et al., 2001). Thus, any shortcomings, weaknesses or incomplete information of the instrument such as sentence structure, appropriateness of terminology and accuracy of meaning can be identified in advance for improvement based on the result of the pilot study analysis. Pilot study also serves in reviewing instructions and test items in questionnaires, and to estimate the response time periods (Lim, 2007; Bond and Fox, 2007). According to Cohen and Swerdlik (2002), the best item selection could be obtained from the analysis of a pilot study. As a result, the quality of the items of an instrument items could be improved in actual study. Hence, the researchers of this research conducted a pilot study on 119 university students from a technical university in Malaysia using a profile instrument. Wolf (1997) suggested, 30 to 50 individuals are suitable for a pilot study. Linacre (2005) suggested that a minimum of 30 people for a pilot study stage is sufficient. Therefore, the number of respondents involved in the study is suitable to provide significant results to achieve the objectives of the study. Meanwhile, the characteristics of the sample tested in the pilot study should have similarities with the study
population (Mohd Majid, 2005). So, this study selected the respondents (university students) who have the similar characteristics of the respondents (university students) in the actual study.
3. Discussion and Conclusion
The Fleiss Kappa analysis was used for the purpose of instrument (profile) validity. The analysis was conducted based on the results of three (3) experts’ review of the instrument.
Meanwhile, in order to determine the reliability of the instrument, Winsteps Version 3.69 software was used to analyze the quantitative data of the pilot study. In this section, the researchers conducted an examination of the functionality of the items according to the study construct from four (4) aspects, namely: (i) testing the person and item reliability and separation index; (ii) detect the polarity of the item by measuring the construct based on the Point Measure Correlation (PTMEA CORR) value; (iii) test the item fit; and (iv) determine the dependent items based on standardized residual correlation values.
3.1 Profile Validity
Table 1 shows the percentage of agreement for each item evaluated by the three evaluators (experts).
Table 1: Fleiss Kappa Analysis Project ID: 1
Project Title: Fleiss Kappa Analysis Expert No.: 3
Item No.: 40
Elements: % Ag Kappa
1.Critical thinking 91.7 0.907
2.Problem solving 93.35 0.953
Overall interrater reliability: 92.525%
Overall value of Kappa: 0.95 (k)
Based on Table 1, the percentage of agreement for each element exceeds 80% and the overall agreement percentage is 92.525%. The values of kappa, k for the both elements (critical thinking and problem solving) exceeded 0.80, which indicated very good level of agreement.
Overall, the kappa value for both the soft skill elements was k = 0.95. The findings indicated that all three evaluators provided very good level of agreement as the value of kappa, k exceeded 0.80. Thus, these results confirmed the validity of the profile (instrument) that was developed and thus, can be used in actual study.
3.2 Profile Reliability
3.2.1 Person and Item Reliability
In order to enable research instruments to be used in the research, McMillan and Schumacher (1984), stated that the acceptable Alpha-Cronbach values should range from 0.70 to 0.90. Meanwhile, Bond and Fox (2007) stated the Alpha -Cronbach value for acceptable reliability should be within the range of 0.71 to 0.99 (71% - 99%). Table 2 shows the range of Alpha-Cronbach scores and the reliability interpretations of this study obtained from the data analysis.
Table 2: Interpretation for Alpha-Cronbach Score
Alpha-Cronbach Score Reliability
0.90 - 1.00 Very good and effective with a high level of consistency 0.71 - 0.89 Good and acceptable
0.6 - 0.70 Acceptable
< 0.60 The item needs to be review
< 0.50 Items need to be dropped
The respondent reliability index explained that the ability of respondents answering different sets for measuring the same construct was consistent. The item reliability index, on the other hand, refers to the similarity in terms of item difficulty compared to other samples that have equivalent abilities (Wright and Masters, 1982). Thus, the reliability of the items and respondents indicated the extent to which the items are compatible based on Rasch model. Meanwhile, according to Linacre (2005), the separation index above 2.0 is considered good. The respondent separation index indicates the number of strata of the respondent’s ability to provide perceptions identified in the sample group measured by two (2) standard errors. It refers to the differences of individuals or groups based on the level of ability in the measured variables. The item separation index refers to the number of item difficulty strata of two (2) standard errors obtained from the test used which indicates the item difficulty level.
Figure 1: Person Reliability Separation Index
Based on Figure 1, the Alpha-Cronbach value obtained for the study is 0.99 which shows a very good result. The value of person reliability was also high (0.96). In addition, the value of separation index obtained was also high (4.84) which shows that there are five (5) strata of ability levels identified in the sample group.
Figure 2: Item Reliability
Figure 2 indicates the results of item reliability. The value item reliability obtained for the study was 0.68, which indicates that the reliability value is acceptable. Thus, the items can be used to measure usability of the variables of the study.
3.2.2 Polarity Item
Item polarity obtained by identifying the Point Measure Correlation (PTMEA CORR) can detect construct validity at earlier stage of the study (Bond and Fox, 2007). According to Linacre (2010), a positive value for PTMEA CORR can verify the item’s ability to measure the construct to be measured. In contrast, the PTMEA CORR value which is zero or negative means there are items that need to be repaired or dropped. That is, in measuring constructs, items do not move in parallel with other items. In other words, there is discrepancy between the interweaving responses of items or respondents with constructs. Thus, the pilot study analysis report could detect the item polarity of this instrument. Based on the results there was no negative values detected in the PTMEA CORR values. The smallest value was 0.75 which showed that the items move in parallel with other items and were able to measure what should be measured.
3.2.3 Item Fit
Item fit is important in determining the suitability of an item measuring a construct. In order to determine the appropriateness of the items in measuring the constructs, an examination of the data being studied should be performed. Usually in Rasch analysis reports, the statistics used are known as chi-square ratios called, infit and outfit mean square (MNSQ). The MNSQ index of infit and outfit is always referenced for item matching checks. The index is involved in each observation performed but each index has a different weighting value. Yet to determine the matching of items measuring a construct, attention to the MNSQ outfit index should take precedence over the MNSQ infit.
Based on Bond and Fox (2007), the accepted index value for the Likert scale (polytomous data) is in the range of 0.6 - 1.4 while for multiple options (dichotomous data) is in the range of 0.7 - 1.3. The standard value of Z (Zstd) which is a t-test for testing the hypothesis of matching the data with the model is also important in determining the matching of items. Items are said to be easy to predict if the value of Zstd is less than 0.00 and difficult to predict if the value exceeds 0.00. A Zstd value of 0.00 is the most expected value in a study. In general, the acceptable Zstd values should be within the range of ± 2.00. However, Linacre (2007) explained that the Zstd index can be ignored if the MNSQ value is accepted. Based on the results obtained from the analysis in this study, two (2) items were detected to have MNSQ outfit values out of the range of 0.6 - 1.4 namely items I0030 (0.53) and I0019 (0.5). Through this diagnosis, both the items had to be dropped from the list of items provided in the profile.
3.2.4 Standardized Residual Correlations
Based on Rasch analysis, which is able to identify if an item is leaning against another item or not. According to Linacre (2010), the correlation values between items exceeding 0.7 indicate that the items are interdependent and not singular in nature where Linacre suggests selecting only one item for measurement purpose with reference to the MNSQ value. If such cases occur, the items with an MNSQ value approaching 1.00 need to be retained to produce a good instrument. However, this pilot study analysis results showed that there were no overlapping items as the correlation between the two competency items was < 0.7. This means that there were no similarities in the characteristics among the items as they did not share the same dimensions, or the items did not share more than half of the random variance.
Table 3: Summary of Items Functionality Examination
Elements Remaining Item Dropped Item
Critical thinking 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20
19 Problem Solving 21, 22, 23, 24, 25, 26, 27, 28, 29, 31,
32, 33, 34, 35, 36, 37, 38, 39,40
30
Table 3 shows the summary of items functionality examination. Based on the analysis highlighted in Table 3, the analysis of the pilot study found that two (2) items had to be dropped for not meeting the requirements of the analysis of the profile items. This means that 38 out of 40 items in the profile were identified as suitable to be used in the actual study. Thus, majority of the items were reliable to be maintained in the profile to be used in the actual study.
In conclusion, the two objectives of the study were achieved. Firstly, the profile (instrument) was validated by the three experts who confirmed the profile with a high validation value (k = 0.95). Secondly, the items were found to reliable to measure the two elements (critical thinking and problem solving) of soft skills using the profile developed. Only two items had to be removed from the profile to achieve the best outcome in measuring the university students’
ability in the related soft skills. These findings indicate that all three evaluators gave a very good level of agreement because the value of kappa, k exceeded 0.80. Therefore, based on the findings, the items are reliable and the profile with high validity instrument can be used to measure the university students’ soft skill ability by referring to the critical thinking skills and problem solving skills. The procedure followed is believed to produce an instrument which is hoped to help university educators to obtain reliable feedback regarding the mastery of soft skills among the university students so that improvement can be done if necessary. This profile also can be replicated and useful for other educational settings and courses.
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DOI: http://dx.doi.org/10.4236/ce.2013.412A1006
