The match between higher education skill supply and employers’ skill needs in Ethiopia

The match between higher education skill supply and employers’ skill needs in Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The match between higher education skill supply and employers’ skill needs in Ethiopia Asmera Teshome This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3845044/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The purpose of this study investigated the match between higher education skill supply and employers’ skill needs, with a special focus on engineering graduates in Ethiopia. Using an embedded mixed method design, the study analyzed both primary and secondary data on the match between higher education supply and employers needs for discipline-specific, technical, interpersonal, and generic skills. 275 research participants recruited from employees, employers, higher education instructors, and decision-makers took part in the study. The findings of the study revealed that higher learning institutes moderately equip graduates with discipline-specific skills, technical skills, interpersonal skills, and generic skills, while employers’ need for these skills is high. These indicate existence of a significant mismatch between higher education skill supply and employers’ needs, which was higher for technical and generic skills than interpersonal and discipline-specific academic skills. Such mismatch between higher education skill supply and employers’ skill needs negatively affect economic performance and social security through increasing rate of graduates’ unemployment. To mitigate such problems, higher learning institutes could conduct real employers’ needs assessments before preparing training curricula and need to update training styles and contents accordingly. The skills employees acquire at work, factors contributing to the mismatch between skill supply and employers’ needs, and impacts of skill mismatch could be future research areas. engineering graduates higher education institutes employers’ need skill match competences Introduction The need for a better understanding of graduates’ competence requirements is growing with the increasing demand for fresh graduates from employers (Pang, Wong, Leung, & Coombes, 2019). Academic degrees alone are becoming inadequate because employers need potential engineers with competencies and capabilities in generic skills to meet the demands of the globalization era and make their companies most competitive (Azmi, Kamin, & Noordin, 2018). Individuals’ success in transitioning to the labor market and performance in their working lives are closely linked to the process of acquiring these skills and competences. However, providing a standard curriculum to produce graduates with multi-skills and implicating the curriculum and factors supporting the career development of students are becoming challenges in higher education (Azmi et al., 2018). Education and training in developing countries, including Africa, fail to supply graduates who meet the existing labor market needs in soft skills such as innovation and creativity, communication skills, and entrepreneurship skills (Azmi et al., 2018; Wongnaa & Boachie, 2018). Graduates of higher education on the continent often lack knowledge about the realities of the existing labor market. Higher education institutions are lagging behind in equipping graduates with the necessary skills that would meet the needs of industries (Getahun et al., 2020).The gap between educational institutions’ output and labor market requirements has widened, resulting in a rising incidence and duration of graduate unemployment (Ibid). As a part of continental Africa, Ethiopia is not an exceptional country facing similar problems. In response to the dire needs for higher education in Ethiopia, the government has begun expanding both public and private higher learning institutes with relevant programs since the 1990s (Yibeltal, 2016). The country’s higher education landscape has shown significant change in terms of enrollment, expansion, and graduate mix programs (Reda & Gebre-Eyesus, 2018). Similarly, the number of public universities rose from two at the beginning of the 1990s to thirty-four, while the number of private higher education providers was about 100 in 2015 (Karorsa & Polka, 2015; MOE, 2015), and the number of public higher learning institutions rose to 46 in 2019. The total number of graduates in undergraduate programs from both private and government higher-learning institutions increased from 10,768 in 2005 to 102,890 in 2015. The number of engineering graduates has also increased drastically since the introduction of the 70:30 professional and program mix policy. Despite quantitative changes in terms of the number of higher education institutions and student enrollment, the issue of quality and relevance of higher education, a wider mismatch between the performance of higher education graduates and the need for the labor market (Olkaba & Tamene, 2017; Yibeltal, 2016), and the entry of a limited number of graduates into the labor market remain critical challenges in Ethiopia (Fenta, Asnakew, Debele, Nigatu & Muhaba, 2019; Reda & Gebre-Eyesus, 2018). The current higher education system in Ethiopia is not in line with opening ways for the graduates for future business and the foundation of their reasonable vocation (Fenta et al., 2019). Most graduates of higher education institutions are yet ill-equipped to meet the challenges of life and employment (Getahun, Mohammed, Mersha, & Deresse, 2020). Due to a lack of employability skills and competence among new higher education graduates, unemployment and underemployment remain critical challenges. Very little attention has been paid to the issue of graduate skills and employers’ needs in all ESDP I-V, PASDEP, Higher Education System Overhaul/HESO, Higher Education Proclamation No. 650/2009, the Education and Training Policy (ETP) of 1994, the Education Sector Strategy of 1994, Proclamation No. 351/2003, and the higher education policies and strategies of Ethiopia (Yibeltal, 2016). Local researchers (e.g., Fenta et al., 2019; Jote, 2017; Reda & Gebre-Eyesus, 2018; Yibeltal, 20016) conducted empirical studies on unemployment, graduate tracer studies, enhancing graduate employability, higher education, and the labor market rather than directly focusing on graduate skills and competencies acquired at higher learning institutes and required by employers. The findings of these studies indicate that graduate skills and competencies have become a serious problem in Ethiopia. They also claimed that wider gaps exist between employers’ expectations and graduates’ performance in terms of quality of work, productivity, and specific job-related knowledge, skills, and competencies. The studies used qualification mismatches as proxies for skill mismatches because of data limitations. Such a measure not only disregards specific skills required by jobs but also the type of education required, as it merely depends on the number of years of education. Understanding the skills and competencies that employers expect from graduates helps universities enhance graduates’ employability and prepare graduates to increase their competition in the job market (Fitriani & Ajayi, 2022). Studying the state and trend of labor market mismatch enables policymakers to take corrective action in the event of a high mismatch between the skills available in the economy and the skills required by the economy (Beyene & Teklesilassie, 2018). Although collecting and consolidating data on the skill needs of the economy is important for proper analysis of skill mismatch, there is a critical shortage of data on the types and levels of skills the economy requires in Ethiopia (Ibid.). The findings of this study are believed to fill some of the existing knowledge gaps on labor market skill needs and higher education skill supply to reduce the current boom in graduates’ unemployment in Ethiopia. It helps shed some light on the importance of frequent assessments of employers’ skill needs and considering their needs in designing higher education curricula. It assists national and international universities, students, employers, policymakers, and employability stakeholders to critically assess and identify skills demanded in the current dynamic technological era and the increasing internationalization of higher education and employment to design, implement, and evaluate policies that enhance their collaborative efforts. It encourages the development of national competence and skills policy frameworks based on stakeholders’ needs for the current growing intake and graduation rates in engineering disciplines in Ethiopian public universities that would help guide higher education and employers in tackling the challenges of matching graduate skills with employers’ skill needs. Thus, the purpose of this study was to assess the gap between the skill supply of higher education institutions and employers needing the same skills, with a special focus on engineering graduates of public higher education institutions in Ethiopia. Research questions The current study sought answers to the following research questions: Do the skills needed by employers match those acquired at higher education institutions? Are there statistically significant mean differences between higher education supply and employers needs for discipline-specific academic skills, technical skills, interpersonal skills, and generic skills? Do the skills needs of employers match the skills acquired at higher education institutions as perceived by employees, employers, and instructors? Are there statistically significant mean differences between higher education supply and employers needs for discipline-specific academic skills, technical skills, interpersonal skills, and generic skills as reported by employees, employers, and instructors? Review of related literature The role of higher education in skill development Higher education aims to prepare young people to become highly productive and successful in the labor market, provide employers with a choice of talent for their current and future operations, and prepare well-trained workforces that could meet employers’ requirements (Branine & Avramenko, 2015). The quality of knowledge generated within higher education institutions and its availability to the wider economy are becoming increasingly critical to national competitiveness, especially in developing countries (Ibid.).There has been a growing emphasis on the role of higher education institutions (HEIs) in enabling employability and graduate employment through the provision of courses, seminars, workshops, and industrial and practical training (Azmi et al., 2018; Rowe & Zegwaard, 2017). The employability of individuals primarily depends on the knowledge, skills, and attitudes they possess; the way they use those assets and present them to employers; and the context within which they seek work (Yibeltal, 2016). In this 21 st century knowledge era, higher education institutions are supposed to play a critical role in achieving both human resources and the overall social development of a nation by contributing to knowledge production through teaching, research, and the provision of community services (Azimi, Kamin, Noordin 2018). Higher education institutions should assist students in understanding how the lessons learned in school are associated with future career opportunities (Rowe, & Zegwaard, 2017). They are supposed to play a key role in national development through the intensification and diversification of programs that could produce a high-level technical work force within the context of national needs (Babalola, 2015). Thus, to meaningfully contribute to the socio-economic development of a country, higher education expansion must be aligned with market demand (Reda & Gebre-Eyesus, 2018). Materials and methods Research design The study employed a mixed-methods research design that involves both quantitative and qualitative sources of data for a complete understanding of the research problem (Creswell, 2014; Maarouf, 2019). A mixed-method approach has emerged from an integrated view of quantitative and qualitative research (Maarouf, 2019) and is acknowledged as the third methodological movement over the last two decades (Creswell, 2014). It helped in harmonizing the shortfalls of exclusively using a single method by triangulating or complementing one set of results with another to enhance the validity of inferences and the representativeness of the findings (Creswell, 2014; Gay, Mills, & Airasian, 2012). These complementary strengths and triangulation are the two main advantages that encouraged the researcher to employ a mixed-methods approach. Assessing both quantitative outcomes and qualitative processes in mixed research helped the researcher get a full understanding of a complex picture of social phenomena. The embedded type of mixed-methods design was employed in this particular study. Embedded design involves the simultaneous or sequential collection of both quantitative and qualitative data, where one form of data plays a supportive role for the other (Creswell, 2014). Qualitative data was collected to support and provide additional information for the quantitative data. Here, both forms of data were collected roughly at the same time. Both qualitative and quantitative data were merged, integrated, linked, and embedded. Study population Employees and employers who previously graduated in the civil, mechanical, and electrical engineering fields of study from Ethiopian public higher education institutions and are currently working in different economic sectors, as well as instructors of higher learning institutes took part in the study. A total of 275 research participants, comprising employees, employers, higher education instructors, and decision-makers, took part in the study. While 260 respondents (90 employees, 40 employers, and 130 higher education instructors) took part in filling out the study questionnaire, 15 individuals took part in key informant interviews. Employees who took part in filling out the study questionnaire were mainly former graduates of civil, electrical, and mechanical engineering disciplines and are currently working in different economic sectors. Employers were individuals who previously graduated in one of the three engineering disciplines mentioned above and are currently leading companies that are capable of employing engineering graduates (e.g., site supervisors of construction companies, human resource managers, personnel, team leaders, and production managers). Both employees and employers were recruited from construction bureaus, road authorities, and electric utilities of Addis Ababa City Administration and Oromia National Regional State, as well as private companies capable of employing large engineering graduates (Etete Construction, Sunshine Construction, and Belayab Motors). Similarly, instructors of civil engineering, electrical engineering, and mechanical engineering who took part in filling out the study questionnaire were recruited from Addis Ababa Science and Technology University, Adama Science and Technology University, Ambo University, and Jimma University. While employees and instructors were selected using simple random sampling techniques, employers were selected using purposive sampling techniques. The relative abundance of the instructors recruited to fill out the study questionnaire was partly due to the large role instructors’ play in curriculum development and implementation, equipping graduates with the necessary competencies, and their availability and willingness to take part in the study. In addition, 15 individuals, comprised of four college deans, one from each sample university, one policymaker and one expert from the Ministry of Education, one expert from the Ministry of Labor and Skills, two team leaders from each construction and road authority bureau of both Addis Ababa City Administration and Oromia National Regional States, one technical team leader from BelayAB Motors, and two construction supervisors from Etete and Sunshine construction companies, were purposefully selected and took part in key informant interviews. Data gathering tools The study employed two sets of self-developed questionnaires with the same content. The first set of the questionnaire was designed to ask the extent to which higher learning institutes equip engineering graduates with discipline-specific, technical, interpersonal, and generic skills. The second set of questionnaires was designed to assess the extent to which the engineering labor market requires these skills. The researchers reviewed engineering graduate employability skills developed by the Malaysian, Hong Kong, and Japan Ministries of Education, a tool to test the learning and employability framework developed by INCHER (International Centre of Higher Education Research) of the University of Kassel, Germany; CHEERS (Careers after Higher Education: European Research Study Projects), literature, and national policy documents to prepare study questionnaires. The questionnaires were designed in the form of a 5-point Likert scale (ranging from 1 replacing very low extent to 5 replacing very high extent). The questionnaire consisted of 34 items (10 items related to discipline-specific skills, 6 items related to technical skills, 6 items related to interpersonal skills, and 12 items related to generic skills). Each item was used to assess both levels of engineering graduates skill acquisition during study at higher learning institutes and labor market needs for the same skills after graduation. A pilot test was conducted on 25 employees, employers, and instructors prior to the commencement of actual data collection to check reliability and validity using the questionnaires. To ensure the reliability of the survey instruments, test-retest reliability has been conducted by administering the questionnaires to the same respondents at two different moments. The closer the findings of the retested survey are to those of the first test, the greater the reliability of the instrument. The validity of the instruments was checked using a thorough analysis by experts relevant to the fields. Several cognitive interviews (thinking aloud) were conducted with employees, employers, and instructors to improve the survey instruments. A few modifications were made to the questionnaire depending on the results of the pilot study. The questionnaire was administered and collected on a face-to-face basis by the researcher, with the facilitation of paid academic staff from each faculty of the sample universities. Of the 300 questionnaires dispatched to respondents, 260 were duly filled out and returned. Thus, the return rate of the questionnaire was 84 percent. Unstructured interview guides were prepared and utilized to collect qualitative data to substantiate the data gathered via questionnaires (quantitative data). Key informant interview participants were asked about the kinds of competences acquired by civil, electrical, and mechanical engineering students in higher education institutions and required by employers of graduates of the same departments, and whether competences acquired by graduates of the three departments match competences that the employers require for companies’ productivity. The researcher used Amharic language to ask interview guide questions. Each interview took an average of 40 minutes, during which a sound recorder was used to capture data. In addition to primary data collected using questionnaires and key informant interviews, the researcher reviewed some purposively selected policy and strategy documents, such as the Ethiopian Higher Education Road Map (2017), the Education Sector Development Program (1997–2017), the Higher Education Proclamation (2009), the Education Policy and its Implementation (2003), and the National Employment Policy and Strategy (2009). Data analysis methods Based on the recommendation of scholars (Cresswell, 2014), the researcher made every attempt to select the statistical procedures that were appropriate for the data analysis rather than merely following the approach used by some other scientists in their field. Both descriptive statistics like mean and standard deviation and inferential statistics like the paired sample t-test were employed to analyze quantitative data gathered using questionnaires. The mean is the most commonly used stable measure of central tendency. It is an arithmetic average of the scores. For the purpose of analysis, the five-point Likert scales were taken as interval data, and mean scores ranging from 1–1.8 represent skills not acquired or required at all; 1.8–1.60 represent skills acquired or required at a little extent; 2.61–3.4 represent skills acquired or required at a moderate level; 3.4–4.20 represent skills acquired at a high extent; and 4.21–5 represent skills acquired or required at a very high extent. Similarly, the standard deviation is the most frequently used index of variability and considers every score in its calculation. In this study, the value of standard deviations was used to compare the variability of higher education supply and employers needs for academic, technical, interpersonal, and generic skills. The smaller the value of the standard deviation, the closer the score around the mean and the less the variability of higher education skill supply and employers’ needs, while the highest standard deviation value indicates the existence of a wider gap between higher education skill supply and employers’ needs. A paired sample t-test was used to check whether or not there was a statistically significant mean difference between employees’, employers, and instructors’ responses related to higher education skill supply and labor market skill needs and if the difference was a real difference or a difference by chance using respondent categories (employee, employer, and instructor) as independent variables and acquired and required skills as dependent variables. In all inferential statistical tests employed to analyze quantitative data, a preselected probability level (test of significance) α= 05 was employed because such a confidence interval is often used by educational researchers (Gay et al., 2012). In conducting a test of significance, a test value with greater than α= 05 indicates existence of significant difference between comparison groups (real difference) while a test value less than α= 05 (preselected probability level) reflecting no statistically significant difference between comparison groups (any difference found is attributed to sampling error or chance). The researcher transcribed, translated and thematically coded data collected via key informant interviews and document reviews, and integrated, supported, substantiated, and checked the data gathered using questionnaires. Ethical considerations The data collection process commenced after clearance was guaranteed by the Addis Ababa University Department of Educational Planning and Management. Informed consent was obtained from all eligible respondents before distributing the questionnaire. While obtaining informed consent, the respondents were informed about the anonymity and confidentiality of their responses. Thus, confidentiality issues were properly addressed in all data collection processes Results 5.1 The match between higher education skill supply and employers or labor market needs The match between higher education skill supply and labor market skill needs was investigated in terms of graduates acquisition and employers and labor market requirements for such skills as discipline-specific academic skills, technical skills, interpersonal skills, and generic skills. Table 1: Mean difference between acquired and required skills Skill Mean of acquired skills Mean of required skills Mean difference Standard deviation Paired sample t-tests t df p Discipline specific academic skill 3.23 3.98 0.74 0.68 17.51 259 <0.01 Technical skill 3.31 4.16 0.85 0.75 18.19 259 <0.01 Interpersonal skill 3.37 4.11 0.74 0.71 16.68 259 <0.01 Generic skill 3.27 4.14 0.88 0.72 19.38 259 <0.01 Table 2: Comparisons of higher education skill supply and employers and labor market needs as reported by employees, employers, and instructors Type of skill Respondent Acquired and required skill N Mean SD Acquired and required skills mean difference Discipline specific skill Employee Acquired 90 3.14 0.44 0.53 Required 90 3.67 0.65 Employers Acquired 40 3.17 0.34 0.74 Required 40 3.91 0.49 Instructors Acquired 130 3.32 0.34 0.89 Required 130 4.21 0.56 Technical skill Employee Acquired 90 3.45 0.49 0.51 Required 90 3.96 0.70 Employers Acquired 40 3.35 0.47 0.92 Required 40 4.27 0.54 Instructors Acquired 130 3.19 0.39 1.07 Required 130 4.26 0.59 Interpersonal skill Employee Acquired 90 3.40 0.51 0.42 Required 90 3.82 0.59 Employers Acquired 40 3.44 0.44 0.76 Required 40 4.20 0.46 Instructors Acquired 130 3.34 0.49 0.95 Required 130 4.29 0.52 Generic skill Employee Acquired 90 3.35 0.50 0.65 Required 90 4.00 0.53 Employers Acquired 40 3.36 0.45 0.88 Required 40 4.24 0.47 Instructors Acquired 130 3.18 0.46 1.02 Required 130 4.20 0.59 Table 3: Paired sample t-test for overall acquired and required skills as reported by employee, employer and instructor Respondent type Pair Mean Mean difference S.D t df p Employee Required- 3.85 0.59 0.61 9.21 89 <0.01 Acquired 3.26 Employer Required- 4.13 0.85 0.50 10.69 39 <0.01 Acquired 3.28 Instructor Required- 4.24 0.99 0.58 19.32 129 <0.01 Acquired 3.26 Discipline specific academic skills Discipline-specific skills help graduates perform tasks in the 21st century and are more relevant to one’s career (Shivoro al., 2019). In this study, discipline-specific academic skill was measured in terms of 10 variables, including the foundation of engineering , manufacturing and construction, operation, measurement, and control technology, applying technical fields, planning, design, calculation, and construction, quality control and assurance, environmental safety, health, and security, applying knowledge of science and engineering principles, skill in a specific engineering discipline, and skill in application and practice. As seen in Table 1, higher learning institutes moderately equip graduates with discipline-specific skills, with a mean value of 3.23 lying between 2.61 and 3.4, while it is highly required in engineering graduate labor markets, with a mean value of 3.98 lying between 3.4 and 4.20. Compared to generic, interpersonal, and technical skills, the gap between higher education supply of discipline-specific skills and engineering labor market need for the same skill was narrowest (mean difference =0.74; SD = 0.68). The mean of required discipline specific academic skills was also higher than the mean of acquired academic skills. A paired sample t-test in Table 1 also confirms the existence of a statistically significant mean difference between acquired and required discipline specific skills (mean =0.74, SD =0.68, t = 17.51, p = 0.01) at the 0.05 level of confidence. As indicated in Table 2 attempts were made to identify the match of higher education skill supply and employers/ labor market needs based on the reports of employees, employers and instructors. Employees (mean = 3.14; SD = 0.44), employers (mean = 3.14; SD = 0.34), and instructors (mean = 3.32; SD = 0.34) reported that higher learning institutes moderately equip graduates with discipline specific skills. However, the requirement the same skills by employers and the labor market was high as reported by employees (mean = 3.67; SD = 0.65), employers (mean = 3.91; SD = 0.49), and instructors of higher learning institutes (mean = 4.21; SD = 0.56). When compared to employees (mean difference = 0.53) and employers (mean difference = 0.74), instructors reported that graduates acquire more discipline specific academic skills during studies at higher learning institutes, and employers and labor market needs for the same skill were very high. Yet, the report of the instructors (mean difference 0.89) revealed the existence of a significant mismatch between discipline specific academic skills acquired at higher learning institutes (mean = 3.32; SD = 0.34); and the requirements of the same skills by employers and the labor market (mean = 4.21; SD = 0.56). Technical skills Technical skills are among the employability skills required by most employers. Graduates acquisition of these skills indicates their proficiency to perform highly in a particular job (Fitriani & Ajayi, 2022). For the purpose of this study, computer skills, the skill of planning and organizing tasks, problem-solving skills, decision-making skills, professional skills, and the skill of seeking and developing opportunities were indicators used to measure technical skills. As shown in Table 1, graduates moderately acquire technical skills, with a mean value of 3.31 lying between 2.61 and 3.4. However, its requirement in the engineering labor market is high, with a mean value of 4.16 lying between 3.4 and 4.20. The gap between higher education supply of technical skills and engineering labor market need for the same skills was widest (mean difference =0.85; SD = 0.75) next to generic skills. A paired sample t-test result depicts a statistically significant mean difference between technical skills acquired at higher learning institutes and employers’ needs for the same skills (mean difference =0.85; SD = 0.75; t = 18.19; p =0.01) at a 0.05 level of confidence. The report of employers (mean = 3.35; SD = 0.47) and instructors (mean = 3.19; SD = 0.39) in Table 2 revealed that higher learning institutes moderately equip engineering graduates with technical skills, while employees (mean = 3.45; SD = 0.49) reported that higher learning institutes highly equip graduates with the same skill. While the report of employees revealed that technical skills (mean = 3.96; SD = 0.70) is highly required in the engineering labor market, employers (mean = 4.27; SD = 0.54) and instructors (mean = 4.26; SD = 0.59) confirmed that the employers and labor market's need for technical skill is very high. Therefore, the reports of employees (mean difference = 0.51), employers (mean difference = 0.92), and instructors (mean difference = 1.07) confirmed the existence of a mismatch between technical skills acquired at higher learning institutes and those required by the labor market among engineering graduates. The mean difference between technical skills acquired at higher learning institutes and those required by the graduate labor market was highest for instructors, followed by employers and employees. Interpersonal skills Interpersonal skills are the ability to work in a team and communicate and cooperate effectively with diverse colleagues and clients ( Velasco-Martínez & Tójar-Hurtado, 2018 ) . In this study, interpersonal skills were measured in terms of teamwork, client/stakeholder focus, working with people from different cultures, communication skills (both written and verbal), interpersonal skills, empathy, adaptability, and flexibility. The finding of this study reveals graduates moderately acquire interpersonal skills, with a mean value of 3.37 lying between 2.61 and 3.4, though the requirement the current Ethiopian engineering labor market is high, with a mean value of 4.11 lying between 3.4 and 4.20. The gap between higher education supply of interpersonal skills and engineering labor market need for the same skill was the third widest (mean difference =0.74; SD = 0.71), next to technical skills. The paired sample test in Table 1 confirms the prevalence of statistically significant mean differences between required interpersonal skills (mean =4.11) and acquired interpersonal skills (mean = 3.37), with a mean difference of 0.74, S.D. = 0.71, t = 16.68, p =0.01 at the 0.05 level of confidence. As depicted in Table 2, employees (mean = 3.4; SD = 0.51) and instructors (mean = 3.34; SD = 0.49) reported that interpersonal skill was moderately acquired at higher learning institutes, while employers (mean = 3.44; SD = 0.76) confirmed that higher learning institutes highly equip graduates of engineering disciplines with the same skill. For both employees (mean = 3.82; SD = 0.59) and employers (mean = 4.20; SD = 0.59), interpersonal skills were highly required by employers. Instructors (mean = 4.29; SD = 0.52), on their part, reported that the requirement for interpersonal skills in the engineering labor market was very high. Employees (mean difference = 0.42), employers (mean difference = 0.76), and instructors (mean difference = 0.95) hold different views about graduate acquisition of interpersonal skills and the requirement of the same skill in the engineering labor market. These indicate existence of mismatch between interpersonal skills acquired at higher learning institutes and employers or labor market needs for the same skill. Generic skills Scholars (e.g., Asai, Breda, Rain, Romanello, Sangnier, 2020; Green, 2016) argue that generic skills are general skills that could apply to a whole range of industries and are increasingly important in modern economies. In this study, creative thinking, willingness to learn, leadership skill, integrity, sense of responsibility, innovativeness, determination, loyalty to the institution and its objectives, ability to assert oneself, self-confidence, and sense of independence are observable indicators used to measure generic skills. The aggregate mean response in the above Table 1 confirms that generic skills (mean = 3.27) were moderately acquired during university studies, with mean values lying in between 2.6 and 3.4. Nevertheless, the need for generic skills in the Ethiopian engineering labor market was high, with a mean value of 4.14 lying between 3.4 and 4.20. The gap between higher education supply and engineering labor market need for generic skills was the widest (mean difference =0.88; SD = 0.72) of all skill types under scrutiny. A paired sample t-test result affirms evidence of a statistically significant mean difference between generic skills acquired at higher learning institutes and those required by employers or the labor market (mean difference = 0.87; SD = 0.72; t = 19.38; p=0.01) at a 0.05 level of confidence. As shown in Table 2, Employees (mean = 3.35; SD = 0.50) and employers (mean = 3.36; SD = 0.45) who took part in the study reported that higher learning institutes moderately equip graduates with generic skills, while the instructors affirmed that universities equip graduates with the same skills to a very high extent. With regard to employers and labor market needs, employees (mean = 4.00; SD = 0.53) and instructors (mean = 4.20; SD = 0.59) believed that generic skills were highly required in the engineering labor market. Interestingly, employers (mean = 4.24; SD = 0.47) reported that the needs for generic skills among employers and the labor market were very high. The reports of employees (mean difference = 0.65), employers (mean difference = 0.88), and instructors (mean difference = 1.02) confirmed the existence of wider gaps between generic skills acquired during studies at university and the requirements of generic skills in the engineering labor market. Paired sample t-tests were computed to test mean differences among employees, employers, and instructors in responding to levels of skills acquired at higher learning institutes and levels of labor market needs for the same skills. As seen in Table 3, there is a statistically significant mean difference between skills acquired at higher learning institutes and the mean requirement of the same skills in the labor market (p 0.01; α ≤ 0.05). The mean difference was highest for instructors (mean difference = 0.99 SD = 58; t = 19.32; df = 129; p = 0.01), followed by employers (mean difference = 0.85 SD = 0.50; t = 10.69; df = 39; p = 0.01), and the lowest difference among employees (mean difference = 0.59 SD = 0.561; t = 9.21; df = 89; p = 0.01). Thus, the mean responses of employees, employers, and instructors revealed the existence of a significant mismatch between the skills supplied by higher learning institutes and the skills required by employers in the Ethiopian context. Corroborating the above ideas, reports of key informant interviews and reviews of policy documents revealed that the recent higher learning institutes in Ethiopia give minimal attention to equipping learners with most aspects of discipline-specific, technical, interpersonal, and generic skills. Due to weak university-industry linkage, students’ exposure to the real world of work and the teaching of practitioners from industry remained inadequate, which results in a lack of technical and practical skills among engineering graduates. Higher learning institutes also marginalized strategies and tactics to prepare programs requiring intensive use of IT in teaching and learning tasks. The quality of education has shown a sharp decline; competences are not well identified in higher education curricula; the organization of modules is found to be weak; the teaching methods employed are highly dominated by the traditional lecture method; the world of work is not yet aware of the movement of HEIs towards competence-based curricula; and higher education institutions neglected the development of employability and other lifelong learning skills in graduates. However, there is increasing policy and strategic emphasis on producing qualified engineers and natural scientists capable of understanding and utilizing appropriate technologies in growing manufacturing and service providing enterprises; developing science and technology institutions to produce highly qualified technicians, engineers, and scientists in line with the demand of the national economy; modifying the balance of the enrollment of higher education in favor of the science and technology needs of the country and conducting practical training in cooperation and collaboration with industries; and enabling the establishment of a workforce in manufacturing and service-provider enterprises with the knowledge and skills necessary to learn, adapt, and utilize technology. Ethiopia has witnessed the implementation of a modular approach that requires changing the old knowledge-based curriculum to a contemporary competency-based type of curriculum. The competency-based curriculum emphasizes the identification of professional and vocational skills, job-specific skills, and transferable skills that higher education graduates may have after completing the curriculum. Discussion The study of Ethiopian higher education engineering graduates’ skill match in labor markets found that higher learning institutes moderately equip graduates with discipline-specific skills, while the need of the engineering graduate labor market for the same skills was high. Though the study by Wongnaa and Boachie (2018 ) underscores the importance of discipline-specific skills in the fields of science, technology, engineering, and math, the commitment of Ethiopian higher learning institutes to equip learners with discipline-specific skills was seemingly low. This might be due to the fact that countries differently value discipline specific skills and generic skills. For instance, most British and German employers want new graduates with good transferable skills rather than excellent academic grades, while French and Spanish employers prefer graduates with excellent academic qualifications over transferable skills (Branine & Avramenko, 2015). Higher learning institutes tend to equip students with indicators of discipline specific skills like skill in applying knowledge of science and engineering principles and skills in planning, designing, calculation, and construction over other aspects. Skill in applying knowledge of science and engineering, specific engineering discipline skill, work place safety, health, and security, the foundation of engineering, and operation, measurement, and control technology were highly required among employers than others. Supporting the idea, scholars (e.g., Shivoro et al., 2019) argued that discipline-specific skills are more relevant to one’s career and help graduates perform tasks in the 21 st century. Nevertheless, scholars (e.g., Fitriani & Ajayi, 2022) reported that academic institutions often fail to provide the right skillsets for graduates due to weak collaboration between universities, employers, and professional accreditation bodies. As discussed above, scholars argued that discipline-specific skills are crucial in hard science fields like engineering and technology, enable graduates to secure employment in their field of studies and receive higher wages, and help graduates perform tasks in the 21 st century. The findings of this study revealed that the need for discipline-specific skills in the engineering labor market was high while the supply of graduates with the same skills was low. The differences between scholars arguments and the findings of this study might be attributed to higher learning institutes’ negligence in considering the importance of such skills in engineering graduates labor markets, the declining quality of higher education with the current increasing enrollment and graduation rates, and the absence of assessment of employers’ skill needs by higher learning institutes in curriculum design, delivery, and evaluation. Such a mismatch between higher education discipline specific skill supply and employers needs results in a scarcity of well-qualified engineers capable of applying, testing, and improving existing engineering-related scientific theories and knowledge that fit the changing technological environment. It also increases the rate of graduate unemployment, and employers opt to recruit new employees from non-graduates and are exposed to the additional cost of training. The current emerging technologies require continuously updating and improving technical skills, which are very important for engineering (Azmi, Kamin, & Noordin, 2018). The findings of this study showed that graduates of higher learning institutes moderately acquire technical skills during university study, while the same skills are highly required in the engineering labor market. Next to generic skills, there was the widest gap between higher education supply and employers needs for technical skills. Employees, employers, and instructors have different views related to graduates’ acquisition and employers’ need for technical skills. According to the reports of employers and instructors, engineering graduates moderately acquire technical skills, while employees believe that higher learning institutes well equip graduates with the same skills. Employers and instructors believed that technical skills were highly required in the engineering graduate labor market. Concomitantly, local study by Siraye, Abebe, Melese, and Wale (2018) identified technical skills such as problem-solving skills, information technology skills, adapting to change, and risk-taking skills as the skills most demanded by employers and graduates acquisition of technical skills is an indication of their proficiency to perform highly in a particular job. Nevertheless, except for computer skills, in Ethiopia, little attention has been given to equipping graduates with aspects of technical skills like skill in planning and organizing tasks, problem-solving skills, appropriate decision-making skills, research skills, creative skills, the skill to learn, adapt, and utilize technology, professional skills, and skill in seeking and developing opportunities. Higher education graduates in Ethiopia lack technical and practical skills related to the work they are assigned to do and need close supervision to perform certain assigned tasks because of insufficient practical attachment during studies at higher learning institutes. Supporting the findings by Fitriani and Ajayi (2022), the finding of this study revealed that employers prefer and value graduates with high technical skills, including skill in manipulating computers, problem-solving skills, decision-making skills, and skill in organizing and planning tasks. However, the mismatch of higher education supply and employers need for technical skills indicate that higher learning institutes and employers are not closely working together in identification of technical skills demanded by the world of work and integrating in both curricular and extra-curricular activities. Despite its high requirement in the current Ethiopian engineering labor market, moderate attention was given to graduates’ interpersonal skills development. Employees, employers, and instructors holding different views about graduate acquisition of interpersonal skills and its requirement in the engineering graduate labor market indicate the existence of a mismatch between graduates’ acquisition of interpersonal skills and employers’ needs. Little attention has been given to the development of aspects of interpersonal skills such as the ability to focus on stakeholders’ or clients’ needs, empathy, working with people from different cultures, adaptability, and flexibility in the higher education curriculum. In contrast to the finding by Getahun et al. (2020), this study found that engineering graduates of Ethiopian higher learning institutes better develop the ability to work in teams and communication skills than other skills. The study by Ahmed, Philbin, and Cheema (2020) argued that communication skill, together with other skills, determines the success or failure of a given project and is a very important competency to be valued. Yet, graduates of Ethiopian higher learning institutes lack oral and written communication skills in English, a medium of instruction in higher learning institutions. Supporting the study by Collet and Hine (2015), teamwork, communication skills, the ability to work with people from different cultures, and empathy were components of interpersonal skills highly required by employers. Interpersonal skills such as communication skills, empathy, negotiation skills, and focusing on client needs are main requirements for any job and assist organizational success. Thus, higher learning institutes and employers properly identify interpersonal skills and integrate them into higher education curricular and extracurricular activities that positively contribute to engineering graduates’ and organizational success. Scholars (e.g., Asai, Breda, Rain, Romanello, & Sangnier, 2020; Green, 2016) argue that generic skills are general skills that could apply to a whole range of industries and are increasingly important in modern economies. The findings of this study showed that Ethiopian higher learning institutes moderately equip graduates with generic skills, while the need in the Ethiopian engineering labor market is very high. The gap between higher education supply and engineering labor market need for generic skills was the widest of all skill types under scrutiny indicating significant mismatch between generic skills acquired at higher learning institutes and employers’ needs. Though scholars argue that the employment and job qualities of graduates are primarily determined by generic skills acquired during university studies, higher learning institutes in Ethiopia highly neglected equipping students with generic skills such as creative thinking skills, leadership skills, integrity, innovativeness, determination, loyalty to institutions and objectives, the ability to assert oneself, self-confidence, and independence. This study showed that most graduates lack aspects of generic skills such as entrepreneurship skill, leadership skills, psychological, emotional, and social maturity, intellectual skills, accountability, readiness or motivation to learn new things; a feeling of belongingness; and life skills. In contrast, aspects of generic skills like willingness to learn, willingness to perform, commitment, and sense of responsibility are better acquired during the curricular and extracurricular activities of higher learning institutes. Yet scholars (e.g., Asai et al., 2020) revealed that individuals with stronger generic competences are more widely employed outside their own field of study and easily adapt to tasks and requirements with which they are not familiar. It has also been argued that the acquisition of general skills will translate into higher earnings in a competitive labor market (Asai, Breda, Rain, Romanello, & Sangnier, 2020). Thus, generic skills are core employability skills that are more or less equally required in all organizations and critical for graduate success in the labor market and organizational competitiveness. However, higher learning institutes in Ethiopia seemingly failed to identify these key employability skills to incorporate into curricular and extracurricular tasks in the current booming higher education enrollment, graduation, and unemployment rates. Such a mismatch between higher education skill supply and employers’ skill need is an indication of inefficiency in the labor market that can hinder productive capacities, which generate unemployment and underemployment, harm organizational productivity due to lower output per worker, inflate average labor costs, affect firm-level profitability, and affect the capacity of enterprises to innovate and adapt to changing market conditions. Conclusion T his study assessed the match between higher education skill supply and labor market skill needs, with a special focus on engineering graduates of public higher education institutions in Ethiopia. The findings of this study showed that higher learning institutes moderately equip graduates with discipline-specific academic skills, technical skills, interpersonal skills, and generic skills, while the need for these skills in the engineering graduate labor market is high. Compared to other skill types under scrutiny, the gap between higher education supply of discipline-specific academic skills and engineering labor market need for the same skill was narrowest. Next to generic skills, there is the widest gap between higher education supply and employers needs for technical skills. The gap between higher education supply of interpersonal skills and engineering labor market need for the same skill was the third widest, next to generic skills and technical skills. Employees, employers, and instructors have different views related to graduates’ acquisition and employers’ need for all types of skills under scrutiny. For instance, while employers and instructors believe that engineering graduates moderately acquire technical skills; employees believe that higher learning institutes well equip graduates with the same skill. Similarly, employers and instructors believe that technical skills are highly required in the engineering graduate labor market. These indicate existence of a significant mismatch between higher education's supply of the four types of skills and employers and the labor market's needs. The mismatch between higher education skill supply and employers skill needs has several impacts and implications for companies and organizations. Among other things, skill mismatch impacts workers or firms that are currently employing or looking to employ workers, compromises firms’ productivity, quality, and competitiveness, results in higher wages, increases recruitment costs, requires more investment in current personnel, results in market losses, implies a greater workload and pressure on current personnel, may result in lower company competitiveness, and prevents investments in and the development of knowledge-intensive and innovative industries, which hamper economic growth, competitiveness, and innovative capacity at the macroeconomic level. Despite having not impacted the primary outcomes of the paper, this study excluded skills employees acquire at work through experience and prospective graduates in sample selection, factors attributed to mismatch of higher education skill supply and employers’ skill needs. It didn’t employ sophisticated statistical techniques like factor and regression analysis in its data analysis. Thus, future research could consider all these limitations. Higher education institutes could also conduct real employers’ needs assessments before preparing training curricula for different fields of study and updating training styles and contents based on the needs of employers. References Ahmed, R., Philbin, S. P., & Cheema, F. E. A. (2021). Systematic literature review of project manager's leadership competencies. Engineering, Construction and Architectural Management , 28 (1), 1-30.https://doi:10.1108/ECAM-05-2019-0276. Asai, K., Breda, T., Rain,A., Romanello, L., & Sangnier, M. (2020). Education, skills and skill mismatch. A review and some new evidence based on the PIAAC survey. URL: https://shs.hal.science/halshs-02514746. Azmi, A. N., Kamin, Y., & Noordin, M. K. (2018). Competencies of engineering graduates: what are the employer’s expectations. International Journal of Engineering & Technology , 7 (2.29), 519-523. https://doi: 10.14419/ijet.v7i2.29.13811. Babalola, S. (2015).Strategies for improving the employability skills and life chances of youths in Nigeria. Current studies in comparative Education , 2 (1), 137-147. URL=https://api.semanticscholar.org/CorpusID:56331785. Beyene, B.M., & Teklesilassie, T.G. (2018). The State, Determinants, and Consequences of Skills Mismatch in the Ethiopian Labour Market. EDRI Working Paper 21. Addis Ababa: Ethiopian Development Research Institute. Branine, M., & Avramenko, A. (2015). A comparative analysis of graduate employment prospects in European labour markets: A study of graduate recruitment in four countries. Higher Education Quarterly , 69 (4), 342-365. https://doi: 10.1111/hequ.12076. Creswell, J. W. (2014). Research design: Qualitative, quantitative and mixed approaches. SAGE publication, Inc. Fenta, H. M., Asnakew, Z. S., Debele, P. K., Nigatu, S. T., & Muhaba, A. M. (2019). Analysis of supply side factors influencing employability of new graduates: A tracer study of Bahir Dar University graduates. Journal of Teaching and Learning for Graduate Employability, 10(2), 67-85. Fitriani, H., & Ajayi, S. (2022). Preparing Indonesian civil engineering graduates for the world of work. Industry and Higher Education , 36 (4), 471-487. https:// doi. 10.1177/09504222211046187. Gay, L.R., Mills, G.E. & Airasian, P.W. (2012) Educational Research: Competencies for Analysis and Application. 10th Edition, Pearson, Upper Saddle River. Getahun, M., & Mersha, D. (2020). Skill gap perceived between employers and accounting graduates in Ethiopia. Financial Studies , 24 (2 (88)), 65-90. http://hdl.handle.net/10419/231700. Green, F. (2016). Skills demand, training and skills mismatch: A review of key concepts, theory and evidence. Foresight, Government Office for Science . http://hdl.voced.edu.au/10707/422302. Jote, T. (2017). Exploring employment status and education–job match among engineering graduates in Ethiopia: policy implications. International Journal of African Higher Education , 4 (1), 42-65. https://doi.org/10.6017/ijahe.v4i1.10249. Karorsa, D. L., & Polka, W. S. (2015). The Equity-Quality Dilemma of Higher Education Expansion: A Goal-Oriented Planning Approach for Maintaining High Quality Standards in Ethiopia. Educational Planning , 22 (3), 19-35. Maarouf, H. (2019). Pragmatism as a supportive paradigm for the mixed research approach: Conceptualizing the ontological, epistemological, and axiological stances of pragmatism. International Business Research , 12 (9), 1-12. https://doi:10.5539/ibr.v12n9p1 Ministry of Education, MoE. (2015). Education statistics annual abstract. Addis Ababa. Olkaba, T., & Tamene, E. (2017). Bologna process and reality on the ground in Ethiopian higher education. Asian Journal of Educational Research , 5 (4), 43-51. ISSN 2311-6080. Păcurariu, G. (2019). The Integration of Higher Education Graduates on the Labor Market. European Review of Applied Sociology , 12 (19), 23-32. https://doi.org/10.1515/eras-2019-0008. Palmer, R. (2017). Jobs and skills mismatch in the informal economy. ILO.ISBN:978-92-2-131613. Pang, E., Wong, M., Leung, C. H., & Coombes, J. (2019). Competencies for fresh graduates’ success at work: Perspectives of employers. Industry and Higher Education , 33 (1), 55-65. https://doi.org/10.1177/0950422218792333. Reda, N. W., & Gebre-Eyesus, M. T. (2018). Graduate unemployment in Ethiopia: the ‘red flag’and its implications. International Journal of African Higher Education , 5 (1), 32-43. https://doi.org/10.6017/ijahe.v5i1.10967. Rowe, A. D., & Zegwaard, K. E. (2017). Developing graduate employability skills and attributes: Curriculum enhancement through work-integrated learning. Asia-Pacific Journal of Cooperative Education, Special Issue, 18 (2), 87-99. Shivoro, R. S., Shalyefu, R. K., & Kadhilaho, N. (2019). A critical analysis of universal literature on graduate employability. Journal for Studies in Humanities and Social Sciences , 6 (2), 248-268. Siraye, Z., Abebe, T., Melese, M., & Wale, T. (2018). A tracer study on employability of business and economics graduates at Bahir Dar University. International Journal of Higher Education and Sustainability , 2 (1), 45-63. https://doi: 10.1504/IJHES.2018.092406. Velasco-Martínez, L. & Tójar-Hurtado, J. (2018). Competency-Based Evaluation in Higher Education— Design and Use of Competence Rubrics by University Educators. International Education Studies; 11 (2), 118-132. https://doi:10.5539/ies.v11n2p118. Wongnaa, C. A., & Boachie, W. K. (2018). Perception and adoption of competency-based training by academics in Ghana. International journal of STEM education , 5 (1), 1-13. https://doi.org/10.1186/s40594-018-0148-x. Yibeltal, J. (2016). Higher education and labor market in Ethiopia: A tracer study of graduate employment in engineering from Addis Ababa and Bahir Dar Universities. Addis Ababa University, Addis Ababa, Ethiopia . URI: http://etd.aau.edu.et/handle/123456789/3799. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3845044","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":265854861,"identity":"48e1d366-d3cf-4680-9efb-4360b1073cff","order_by":0,"name":"Asmera Teshome","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0004-1722-6425","institution":"Addis Ababa","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Asmera","middleName":"","lastName":"Teshome","suffix":""}],"badges":[],"createdAt":"2024-01-08 09:49:40","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-3845044/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3845044/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49346101,"identity":"b848bc8d-654f-4555-9e21-7f28c51bef3f","added_by":"auto","created_at":"2024-01-09 04:48:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":244177,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3845044/v1/28560f86-8935-47f9-bd97-3eb7f0baec91.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eThe match between higher education skill supply and employers’ skill needs in Ethiopia\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe need for a better understanding of graduates\u0026rsquo; competence requirements is growing with the increasing demand for fresh graduates from employers (Pang, Wong, Leung, \u0026amp; Coombes, 2019). Academic degrees alone are becoming inadequate because employers need potential engineers with competencies and capabilities in generic skills to meet the demands of the globalization era and make their companies most competitive (Azmi, Kamin, \u0026amp; Noordin, 2018). Individuals\u0026rsquo; success in transitioning to the labor market and performance in their working lives are closely linked to the process of acquiring these skills and competences. However, providing a standard curriculum to produce graduates with multi-skills and implicating the curriculum and factors supporting the career development of students are becoming challenges in higher education (Azmi et al., 2018). Education and training in developing countries, including Africa, fail to supply graduates who meet the existing labor market needs in soft skills such as innovation and creativity, communication skills, and entrepreneurship skills (Azmi et al., 2018; Wongnaa \u0026amp; Boachie, 2018). Graduates of higher education on the continent often lack knowledge about the realities of the existing labor market. Higher education institutions are lagging behind in equipping graduates with the necessary skills that would meet the needs of industries (Getahun et al., 2020).The gap between educational institutions\u0026rsquo; output and labor market requirements has widened, resulting in a rising incidence and duration of graduate unemployment (Ibid). As a part of continental Africa, Ethiopia is not an exceptional country facing similar problems.\u003c/p\u003e\n\u003cp\u003eIn response to the dire needs for higher education in Ethiopia, the government has begun expanding both public and private higher learning institutes with relevant programs since the 1990s (Yibeltal, 2016). The country\u0026rsquo;s higher education landscape has shown significant change in terms of enrollment, expansion, and graduate mix programs (Reda \u0026amp; Gebre-Eyesus, 2018). Similarly, the number of public universities rose from two at the beginning of the 1990s to thirty-four, while the number of private higher education providers was about 100 in 2015 (Karorsa \u0026amp; Polka, 2015; MOE, 2015), and the number of public higher learning institutions rose to 46 in 2019. The total number of graduates in undergraduate programs from both private and government higher-learning institutions increased from 10,768 in 2005 to 102,890 in 2015. The number of engineering graduates has also increased drastically since the introduction of the 70:30 professional and program mix policy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite quantitative changes in terms of the number of higher education institutions and student enrollment, the issue of quality and relevance of higher education, a wider mismatch between the performance of higher education graduates and the need for the labor market (Olkaba \u0026amp; Tamene, 2017; Yibeltal, 2016), and the entry of a limited number of graduates into the labor market remain critical challenges in Ethiopia (Fenta, Asnakew, Debele, Nigatu \u0026amp; Muhaba, 2019; Reda \u0026amp; Gebre-Eyesus, 2018). The current higher education system in Ethiopia is not in line with opening ways for the graduates for future business and the foundation of their reasonable vocation (Fenta et al., 2019). Most graduates of higher education institutions are yet ill-equipped to meet the challenges of life and employment\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(Getahun, Mohammed, Mersha, \u0026amp; \u0026nbsp;Deresse, 2020). Due to a lack of employability skills and competence among new higher education graduates, unemployment and underemployment remain critical challenges. \u0026nbsp;Very little attention has been paid to the issue of graduate skills and employers\u0026rsquo; needs in all ESDP I-V, PASDEP, Higher Education System Overhaul/HESO, Higher Education Proclamation No. 650/2009, the Education and Training Policy (ETP) of 1994, the Education Sector Strategy of 1994, Proclamation No. 351/2003, and the higher education policies and strategies of Ethiopia (Yibeltal, 2016).\u003c/p\u003e\n\u003cp\u003eLocal researchers (e.g., Fenta et al., 2019; Jote, 2017; Reda \u0026amp; Gebre-Eyesus, 2018; Yibeltal, 20016) conducted empirical studies on unemployment, graduate tracer studies, enhancing graduate employability, higher education, and the labor market rather than directly focusing on graduate skills and competencies acquired at higher learning institutes and required by employers. The findings of these studies indicate that graduate skills and competencies have become a serious problem in Ethiopia. They also claimed that wider gaps exist between employers\u0026rsquo; expectations and graduates\u0026rsquo; performance in terms of quality of work, productivity, and specific job-related knowledge, skills, and competencies. The studies used qualification mismatches as proxies for skill mismatches because of data limitations. Such a measure not only disregards specific skills required by jobs but also the type of education required, as it merely depends on the number of years of education.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUnderstanding the skills and competencies that employers expect from graduates helps universities enhance graduates\u0026rsquo; employability and prepare graduates to increase their competition in the job market (Fitriani \u0026amp; Ajayi, 2022). \u0026nbsp;Studying the state and trend of labor market mismatch enables policymakers to take corrective action in the event of a high mismatch between the skills available in the economy and the skills required by the economy (Beyene \u0026amp; Teklesilassie, 2018). Although collecting and consolidating data on the skill needs of the economy is important for proper analysis of skill mismatch, there is a critical shortage of data on the types and levels of skills the economy requires in Ethiopia (Ibid.). The findings of this study are believed to fill some of the existing knowledge gaps on labor market skill needs and higher education skill supply to reduce the current boom in graduates\u0026rsquo; unemployment in Ethiopia. It helps shed some light on the importance of frequent assessments of employers\u0026rsquo; skill needs and considering their needs in designing higher education curricula. It assists national and international universities, students, employers, policymakers, and employability stakeholders to critically assess and identify skills demanded in the current dynamic technological era and the increasing internationalization of higher education and employment to design, implement, and evaluate policies that enhance their collaborative efforts. It encourages the development of national competence and skills policy frameworks based on stakeholders\u0026rsquo; needs for the current growing intake and graduation rates in engineering disciplines in Ethiopian public universities that would help guide higher education and employers in tackling the challenges of matching graduate skills with employers\u0026rsquo; skill needs.\u0026nbsp;Thus, the purpose of this study was to assess the gap between the skill supply of higher education institutions and employers needing the same skills, with a special focus on engineering graduates of public higher education institutions in Ethiopia.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch questions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe current study sought answers to the following research questions:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eDo the skills needed by employers match those acquired at higher education institutions?\u003c/li\u003e\n \u003cli\u003eAre there statistically significant mean differences between higher education supply and employers needs for discipline-specific academic skills, technical skills, interpersonal skills, and generic skills?\u003c/li\u003e\n \u003cli\u003eDo the skills needs of employers match the skills acquired at higher education institutions as perceived by employees, employers, and instructors?\u003c/li\u003e\n \u003cli\u003eAre there statistically significant mean differences between higher education supply and employers needs for discipline-specific academic skills, technical skills, interpersonal skills, and generic skills as reported by employees, employers, and instructors?\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Review of related literature","content":"\u003cp\u003e\u003cstrong\u003eThe role of higher education in skill development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHigher education aims to prepare young people to become highly productive and successful in the labor market, provide employers with a choice of talent for their current and future operations, and prepare well-trained workforces that could meet employers\u0026rsquo; requirements (Branine \u0026amp; Avramenko, 2015). The quality of knowledge generated within higher education institutions and its availability to the wider economy are becoming increasingly critical to national competitiveness, especially in developing countries (Ibid.).There has been a growing emphasis on the role of higher education institutions (HEIs) in enabling employability and graduate employment through the provision of courses, seminars, workshops, and industrial and practical training (Azmi et al., 2018; Rowe \u0026amp; Zegwaard, 2017). The employability of individuals primarily depends on the knowledge, skills, and attitudes they possess; the way they use those assets and present them to employers; and the context within which they seek work (Yibeltal, 2016). In this 21\u003csup\u003est\u003c/sup\u003e century knowledge era, higher education institutions are supposed to play a critical role in achieving both human resources and the overall social development of a nation by contributing to knowledge production through teaching, research, and the provision of community services (Azimi, Kamin, Noordin 2018). Higher education institutions should assist students in understanding how the lessons learned in school are associated with future career opportunities (Rowe, \u0026amp; Zegwaard, 2017). They are supposed to play a key role in national development through the intensification and diversification of programs that could produce a high-level technical work force within the context of national needs (Babalola, 2015). Thus, to meaningfully contribute to the socio-economic development of a country, higher education expansion must be aligned with market demand (Reda \u0026amp; Gebre-Eyesus, 2018).\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eResearch design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study employed a mixed-methods research design that involves both quantitative and qualitative sources of data for a complete understanding of the research problem (Creswell, 2014; Maarouf, 2019). A mixed-method approach has emerged from an integrated view of quantitative and qualitative research (Maarouf, 2019)\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eand is\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eacknowledged as the third methodological movement over the last two decades (Creswell, 2014). It helped in harmonizing the shortfalls of exclusively using a single method by triangulating or complementing one set of results with another to enhance the validity of inferences and the representativeness of the findings (Creswell, 2014; Gay, Mills, \u0026amp; Airasian, 2012). These complementary strengths and triangulation are the two main advantages that encouraged the researcher to employ a mixed-methods approach. Assessing both quantitative outcomes and qualitative processes in mixed research helped the researcher get a full understanding of a complex picture of social phenomena. The embedded type of mixed-methods design was employed in this particular study. Embedded design involves the simultaneous or sequential collection of both quantitative and qualitative data, where one form of data plays a supportive role for the other (Creswell, 2014). Qualitative data was collected to support and provide additional information for the quantitative data. Here, both forms of data were collected roughly at the same time. Both qualitative and quantitative data were merged, integrated, linked, and embedded.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEmployees and employers who previously graduated in the civil, mechanical, and electrical engineering fields of study from Ethiopian public higher education institutions and are currently working in different economic sectors, as well as instructors of higher learning institutes took part in the study. A total of 275 research participants, comprising employees, employers, higher education instructors, and decision-makers, took part in the study. While 260 respondents (90 employees, 40 employers, and 130 higher education instructors) took part in filling out the study questionnaire, 15 individuals took part in key informant interviews. Employees who took part in filling out the study questionnaire were mainly former graduates of civil, electrical, and mechanical engineering disciplines and are currently working in different economic sectors. Employers were individuals who previously graduated in one of the three engineering disciplines mentioned above and are currently leading companies that are capable of employing engineering graduates (e.g., site supervisors of construction companies, human resource managers, personnel, team leaders, and production managers).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBoth employees and employers were recruited from construction bureaus, road authorities, and electric utilities of Addis Ababa City Administration and Oromia National Regional State, as well as private companies capable of employing large engineering graduates (Etete Construction, Sunshine Construction, and Belayab Motors). Similarly, instructors of civil engineering, electrical engineering, and mechanical engineering who took part in filling out the study questionnaire were recruited from Addis Ababa Science and Technology University, Adama Science and Technology University, Ambo University, and Jimma University. While employees and instructors were selected using simple random sampling techniques, employers were selected using purposive sampling techniques. The relative abundance of the instructors recruited to fill out the study questionnaire was partly due to the large role instructors\u0026rsquo; play in curriculum development and implementation, equipping graduates with the necessary competencies, and their availability and willingness to take part in the study. In addition, 15 individuals, comprised of four college deans, one from each sample university, one policymaker and one expert from the Ministry of Education, one expert from the Ministry of Labor and Skills, two team leaders from each construction and road authority bureau of both Addis Ababa City Administration and Oromia National Regional States, one technical team leader from BelayAB Motors, and two construction supervisors from Etete and Sunshine construction companies, were purposefully selected and took part in key informant interviews.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData gathering tools\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study employed two sets of self-developed questionnaires with the same content. The first set of the questionnaire was designed to ask the extent to which higher learning institutes equip engineering graduates with discipline-specific, technical, interpersonal, and generic skills. The second set of questionnaires was designed to assess the extent to which the engineering labor market requires these skills. The researchers reviewed engineering graduate employability skills developed by the Malaysian, Hong Kong, and Japan Ministries of Education, a tool to test the learning and employability framework developed by INCHER (International Centre of Higher Education Research) of the University of Kassel, Germany; CHEERS (Careers after Higher Education: European Research Study Projects), literature, and national policy documents to prepare study questionnaires. The questionnaires were designed in the form of a 5-point Likert scale (ranging from 1 replacing very low extent to 5 replacing very high extent). The questionnaire consisted of 34 items (10 items related to discipline-specific skills, 6 items related to technical skills, 6 items related to interpersonal skills, and 12 items related to generic skills). Each item was used to assess both levels of engineering graduates skill acquisition during study at higher learning institutes and labor market needs for the same skills after graduation.\u003c/p\u003e\n\u003cp\u003eA pilot test was conducted on 25 employees, employers, and instructors prior to the commencement of actual data collection to check reliability and validity using the questionnaires. To ensure the reliability of the survey instruments, test-retest reliability has been conducted by administering the questionnaires to the same respondents at two different moments. The closer the findings of the retested survey are to those of the first test, the greater the reliability of the instrument. The validity of the instruments was checked using a thorough analysis by experts relevant to the fields. Several cognitive interviews (thinking aloud) were conducted with employees, employers, and instructors to improve the survey instruments. A few modifications were made to the questionnaire depending on the results of the pilot study. The questionnaire was administered and collected on a face-to-face basis by the researcher, with the facilitation of paid academic staff from each faculty of the sample universities. Of the 300 questionnaires dispatched to respondents, 260 were duly filled out and returned. Thus, the return rate of the questionnaire was 84 percent.\u003c/p\u003e\n\u003cp\u003eUnstructured interview guides were prepared and utilized to collect qualitative data to substantiate the data gathered via questionnaires (quantitative data). Key informant interview participants were asked about the kinds of competences acquired by civil, electrical, and mechanical engineering students in higher education institutions and required by employers of graduates of the same departments, and whether competences acquired by graduates of the three departments match competences that the employers require for companies\u0026rsquo; productivity. The researcher used Amharic language to ask interview guide questions. Each interview took an average of 40 minutes, during which a sound recorder was used to capture data. In addition to primary data collected using questionnaires and key informant interviews, the researcher reviewed some purposively selected policy and strategy documents, such as the Ethiopian Higher Education Road Map (2017), the Education Sector Development Program (1997\u0026ndash;2017), the Higher Education Proclamation (2009), the Education Policy and its Implementation (2003), and the National Employment Policy and Strategy (2009).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Data analysis methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the recommendation of scholars (Cresswell, 2014), the researcher made every attempt to select the statistical procedures that were appropriate for the data analysis rather than merely following the approach used by some other scientists in their field.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eBoth descriptive statistics like mean and standard deviation and inferential statistics like the paired sample t-test were\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eemployed to analyze quantitative data gathered using questionnaires. The mean is the most commonly used stable measure of central tendency. It is an arithmetic average of the scores. For the purpose of analysis, the five-point Likert scales were taken as interval data, and mean scores ranging from 1\u0026ndash;1.8 represent skills not acquired or required at all; 1.8\u0026ndash;1.60 represent skills acquired or required at a little extent; 2.61\u0026ndash;3.4 represent skills acquired or required at a moderate level; 3.4\u0026ndash;4.20 represent skills acquired at a high extent; and 4.21\u0026ndash;5 represent skills acquired or required at a very high extent. Similarly, the standard deviation is the most frequently used index of variability and considers every score in its calculation. In this study, the value of standard deviations was used to compare the variability of higher education supply and employers needs for academic, technical, interpersonal, and generic skills. The smaller the value of the standard deviation, the closer the score around the mean and the less the variability of higher education skill supply and employers\u0026rsquo; needs, while the highest standard deviation value indicates the existence of a wider gap between higher education skill supply and employers\u0026rsquo; needs.\u003c/p\u003e\n\u003cp\u003eA paired sample t-test was used to check whether or not there was a statistically significant mean difference between employees\u0026rsquo;, employers, and instructors\u0026rsquo; responses related to higher education skill supply and labor market skill needs and if the difference was a real difference or a difference by chance using respondent categories (employee, employer, and instructor) as independent variables and acquired and required skills as dependent variables. In all inferential statistical tests employed to analyze quantitative data, a preselected probability level (test of significance) \u0026alpha;= 05 was employed because such a confidence interval is often used by educational researchers\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(Gay et al., 2012).\u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u003c/strong\u003eIn conducting a test of significance, a test value with greater than \u0026alpha;= 05 indicates existence of significant difference between comparison groups (real difference) while a test value less than \u0026alpha;= 05 (preselected probability level) reflecting no statistically significant difference between comparison groups (any difference found is attributed to sampling error or chance). The researcher transcribed, translated and thematically coded data collected via key informant interviews and document reviews, and integrated,\u0026nbsp;supported, substantiated,\u0026nbsp;and checked the\u0026nbsp;data gathered using questionnaires.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical considerations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data collection process commenced after clearance was guaranteed by the Addis Ababa University Department of Educational Planning and Management. Informed consent was obtained from all eligible respondents before distributing the questionnaire. While obtaining informed consent, the respondents were informed about the anonymity and confidentiality of their responses. Thus, confidentiality issues were properly addressed in all data collection processes\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e5.1 The match between\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ehigher education skill supply and employers or labor market needs\u003c/p\u003e\n\u003cp\u003eThe match between higher education skill supply and labor market skill needs was investigated in terms of graduates acquisition and employers and labor market requirements for such skills as discipline-specific academic skills, technical skills, interpersonal skills, and generic skills.\u003c/p\u003e\n\u003cp\u003eTable 1: Mean difference between acquired and required skills\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.934102141680395%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSkill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMean of acquired skills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.696869851729819%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMean of required skills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.014827018121911%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMean difference\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.8500823723229%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eStandard deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.630971993410213%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003ePaired sample t-tests\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.375%\" valign=\"top\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.375%\" valign=\"top\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.25%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.934102141680395%\" valign=\"top\"\u003e\n \u003cp\u003eDiscipline specific academic skill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" valign=\"top\"\u003e\n \u003cp\u003e3.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.696869851729819%\" valign=\"top\"\u003e\n \u003cp\u003e3.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.014827018121911%\" valign=\"top\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.8500823723229%\" valign=\"top\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" valign=\"top\"\u003e\n \u003cp\u003e17.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" valign=\"top\"\u003e\n \u003cp\u003e259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.884678747940692%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.934102141680395%\" valign=\"top\"\u003e\n \u003cp\u003eTechnical skill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" valign=\"top\"\u003e\n \u003cp\u003e3.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.696869851729819%\" valign=\"top\"\u003e\n \u003cp\u003e4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.014827018121911%\" valign=\"top\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.8500823723229%\" valign=\"top\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" valign=\"top\"\u003e\n \u003cp\u003e18.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" valign=\"top\"\u003e\n \u003cp\u003e259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.884678747940692%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.934102141680395%\" valign=\"top\"\u003e\n \u003cp\u003eInterpersonal skill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" valign=\"top\"\u003e\n \u003cp\u003e3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.696869851729819%\" valign=\"top\"\u003e\n \u003cp\u003e4.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.014827018121911%\" valign=\"top\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.8500823723229%\" valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" valign=\"top\"\u003e\n \u003cp\u003e16.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" valign=\"top\"\u003e\n \u003cp\u003e259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.884678747940692%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.934102141680395%\" valign=\"top\"\u003e\n \u003cp\u003eGeneric skill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" valign=\"top\"\u003e\n \u003cp\u003e3.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.696869851729819%\" valign=\"top\"\u003e\n \u003cp\u003e4.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.014827018121911%\" valign=\"top\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.8500823723229%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" valign=\"top\"\u003e\n \u003cp\u003e19.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.873146622734762%\" valign=\"top\"\u003e\n \u003cp\u003e259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.884678747940692%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 2: Comparisons of higher education skill supply and employers and labor market needs as reported by employees, employers, and instructors\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"631\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.924050632911392%\" valign=\"top\"\u003e\n \u003cp\u003eType of skill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.72151898734177%\" valign=\"top\"\u003e\n \u003cp\u003eRespondent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired and required skill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.291139240506329%\" valign=\"top\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.49367088607595%\" valign=\"top\"\u003e\n \u003cp\u003eMean\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.443037974683545%\" valign=\"top\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.088607594936708%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired and required skills mean difference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.924050632911392%\" rowspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eDiscipline specific skill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.72151898734177%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEmployee\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.291139240506329%\" valign=\"top\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.49367088607595%\" valign=\"top\"\u003e\n \u003cp\u003e3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.443037974683545%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.088607594936708%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.18518518518518%\" valign=\"top\"\u003e\n \u003cp\u003eRequired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37037037037037%\" valign=\"top\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.58823529411765%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEmployers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.955882352941178%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.441176470588236%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.029411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e3.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.132352941176471%\" valign=\"top\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.852941176470587%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.18518518518518%\" valign=\"top\"\u003e\n \u003cp\u003eRequired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e3.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37037037037037%\" valign=\"top\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.58823529411765%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eInstructors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.955882352941178%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.441176470588236%\" valign=\"top\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.029411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.132352941176471%\" valign=\"top\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.852941176470587%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.18518518518518%\" valign=\"top\"\u003e\n \u003cp\u003eRequired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e4.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37037037037037%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.924050632911392%\" rowspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eTechnical skill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.72151898734177%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEmployee\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.291139240506329%\" valign=\"top\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.49367088607595%\" valign=\"top\"\u003e\n \u003cp\u003e3.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.443037974683545%\" valign=\"top\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.088607594936708%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.18518518518518%\" valign=\"top\"\u003e\n \u003cp\u003eRequired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e3.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37037037037037%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.58823529411765%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEmployers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.955882352941178%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.441176470588236%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.029411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e3.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.132352941176471%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.852941176470587%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.18518518518518%\" valign=\"top\"\u003e\n \u003cp\u003eRequired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e4.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37037037037037%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.58823529411765%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eInstructors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.955882352941178%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.441176470588236%\" valign=\"top\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.029411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.132352941176471%\" valign=\"top\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.852941176470587%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.18518518518518%\" valign=\"top\"\u003e\n \u003cp\u003eRequired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e4.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37037037037037%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.924050632911392%\" rowspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eInterpersonal skill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.72151898734177%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEmployee\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.291139240506329%\" valign=\"top\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.49367088607595%\" valign=\"top\"\u003e\n \u003cp\u003e3.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.443037974683545%\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.088607594936708%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.18518518518518%\" valign=\"top\"\u003e\n \u003cp\u003eRequired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e3.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37037037037037%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.58823529411765%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEmployers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.955882352941178%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.441176470588236%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.029411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.132352941176471%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.852941176470587%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.18518518518518%\" valign=\"top\"\u003e\n \u003cp\u003eRequired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37037037037037%\" valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.58823529411765%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eInstructors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.955882352941178%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.441176470588236%\" valign=\"top\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.029411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.132352941176471%\" valign=\"top\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.852941176470587%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.18518518518518%\" valign=\"top\"\u003e\n \u003cp\u003eRequired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e4.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37037037037037%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.924050632911392%\" rowspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eGeneric skill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.72151898734177%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEmployee\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.037974683544302%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.291139240506329%\" valign=\"top\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.49367088607595%\" valign=\"top\"\u003e\n \u003cp\u003e3.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.443037974683545%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.088607594936708%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.18518518518518%\" valign=\"top\"\u003e\n \u003cp\u003eRequired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37037037037037%\" valign=\"top\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.58823529411765%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEmployers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.955882352941178%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.441176470588236%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.029411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.132352941176471%\" valign=\"top\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.852941176470587%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.18518518518518%\" valign=\"top\"\u003e\n \u003cp\u003eRequired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e4.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37037037037037%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.58823529411765%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eInstructors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.955882352941178%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.441176470588236%\" valign=\"top\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.029411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e3.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.132352941176471%\" valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.852941176470587%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.18518518518518%\" valign=\"top\"\u003e\n \u003cp\u003eRequired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"top\"\u003e\n \u003cp\u003e4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37037037037037%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3: \u0026nbsp;Paired sample t-test for overall acquired and required skills as reported by employee, employer and instructor\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"630\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003eRespondent type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.380952380952381%\" valign=\"top\"\u003e\n \u003cp\u003ePair\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.523809523809524%\" valign=\"top\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003eMean\u0026nbsp;difference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.380952380952381%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;S.D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.333333333333334%\" valign=\"top\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.619047619047619%\" valign=\"top\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\" valign=\"top\"\u003e\n \u003cp\u003ep\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.238095238095237%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEmployee\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.380952380952381%\" valign=\"top\"\u003e\n \u003cp\u003eRequired-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.523809523809524%\" valign=\"top\"\u003e\n \u003cp\u003e3.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.380952380952381%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.333333333333334%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e9.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.619047619047619%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.52173913043478%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.47826086956522%\" valign=\"top\"\u003e\n \u003cp\u003e3.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.238095238095237%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEmployer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.380952380952381%\" valign=\"top\"\u003e\n \u003cp\u003eRequired-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.523809523809524%\" valign=\"top\"\u003e\n \u003cp\u003e4.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.380952380952381%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.333333333333334%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e10.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.619047619047619%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.52173913043478%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.47826086956522%\" valign=\"top\"\u003e\n \u003cp\u003e3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.238095238095237%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eInstructor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.380952380952381%\" valign=\"top\"\u003e\n \u003cp\u003eRequired-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.523809523809524%\" valign=\"top\"\u003e\n \u003cp\u003e4.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.380952380952381%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.333333333333334%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e19.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.619047619047619%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.52173913043478%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.47826086956522%\" valign=\"top\"\u003e\n \u003cp\u003e3.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDiscipline specific academic skills\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDiscipline-specific skills help graduates perform tasks in the 21st century and are more relevant to one\u0026rsquo;s career (Shivoro al., 2019). In this study, discipline-specific academic skill was measured in terms of 10 variables, including the foundation of engineering , manufacturing and construction, operation, measurement, and control technology, applying technical fields, planning, design, calculation, and construction, quality control and assurance, environmental safety, health, and \u0026nbsp;security, applying knowledge of science and \u0026nbsp;engineering principles, skill in a specific engineering discipline, and skill in application and \u0026nbsp;practice.\u003c/p\u003e\n\u003cp\u003eAs seen in Table 1, higher learning institutes moderately equip graduates with discipline-specific skills, with a mean value of 3.23 lying between 2.61 and 3.4, while it is highly required in engineering graduate labor markets, with a mean value of 3.98 lying between 3.4 and 4.20.\u0026nbsp;Compared to generic, interpersonal, and technical skills, the gap between higher education supply of discipline-specific skills and engineering labor market need for the same skill was narrowest (mean difference =0.74; SD = 0.68).\u0026nbsp;The mean of required discipline specific academic skills was also higher than the mean of acquired academic skills. A paired sample t-test in Table 1 also confirms the existence of a statistically significant mean difference between acquired and required discipline specific skills (mean =0.74, SD =0.68, t = 17.51, p = 0.01) at the 0.05 level of confidence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs indicated in Table 2 attempts were made to identify the match of higher education skill supply and employers/ labor market needs based on the reports of employees, employers and instructors. Employees (mean = 3.14; SD = 0.44), employers (mean = 3.14; SD = 0.34), and instructors (mean = 3.32; SD = 0.34) reported that higher learning institutes moderately equip graduates with discipline specific skills. However, the requirement the same skills by employers and the labor market was high as reported by employees (mean = 3.67; SD = 0.65), employers (mean = 3.91; SD = 0.49), and instructors of higher learning institutes (mean = 4.21; SD = 0.56).\u0026nbsp;When compared to employees (mean difference = 0.53) and employers (mean difference = 0.74), instructors reported that graduates acquire more discipline specific academic skills during studies at higher learning institutes, and employers and labor market needs for the same skill were very high. Yet, the report of the instructors (mean difference 0.89) revealed the existence of a significant mismatch between discipline specific academic skills acquired at higher learning institutes (mean = 3.32; SD = 0.34); and the requirements of the same skills by employers and the labor market (mean = 4.21; SD = 0.56).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTechnical skills\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTechnical skills are among the employability skills required by most employers. Graduates acquisition of these skills indicates their proficiency to perform highly in a particular job (Fitriani \u0026amp; Ajayi, 2022). For the purpose of this study, computer skills, the skill of planning and organizing tasks, problem-solving skills, decision-making skills, professional skills, and the skill of seeking and developing opportunities were indicators used to measure technical skills. As shown in Table 1, graduates moderately acquire technical skills, with a mean value of 3.31 lying between 2.61 and 3.4. However, its requirement in the engineering labor market is high, with a mean value of 4.16 lying between 3.4 and 4.20. The gap between higher education supply of technical skills and engineering labor market need for the same skills was widest (mean difference =0.85; SD = 0.75) next to generic skills. A paired sample t-test result depicts a statistically significant mean difference between technical skills acquired at higher learning institutes and employers\u0026rsquo; needs for the same skills (mean difference =0.85; SD = 0.75; t = 18.19; p =0.01) at a 0.05 level of confidence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe report of employers (mean = 3.35; SD = 0.47) and instructors (mean = 3.19; SD = 0.39) in Table 2 revealed that higher learning institutes moderately equip engineering graduates with technical skills, while employees (mean = 3.45; SD = 0.49) reported that higher learning institutes highly equip graduates with the same skill.\u0026nbsp;While the report of employees revealed that technical skills (mean = 3.96; SD = 0.70) is highly required in the engineering labor market, employers (mean = 4.27; SD = 0.54) and instructors (mean = 4.26; SD = 0.59) confirmed that the employers and labor market\u0026apos;s need for technical skill is very high. Therefore, the reports of employees (mean difference = 0.51), employers (mean difference = 0.92), and instructors (mean difference = 1.07) confirmed the existence of a mismatch between technical skills acquired at higher learning institutes and those required by the labor market among engineering graduates. The mean difference between technical skills acquired at higher learning institutes and those required by the graduate labor market was highest for instructors, followed by employers and employees.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInterpersonal skills\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eInterpersonal skills are\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ethe \u003cem\u003eability\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eto work in a team and communicate and cooperate effectively with diverse colleagues and clients \u003cstrong\u003e(\u003c/strong\u003eVelasco-Mart\u0026iacute;nez \u0026amp; T\u0026oacute;jar-Hurtado, 2018\u003cstrong\u003e)\u003c/strong\u003e. In this study, interpersonal skills were measured in terms of teamwork, client/stakeholder focus, working with people from different cultures, communication skills (both written and verbal), interpersonal skills, empathy, adaptability, and flexibility. The finding of this study reveals graduates moderately acquire interpersonal skills, with a mean value of 3.37 lying between 2.61 and 3.4, though the requirement the current Ethiopian engineering labor market is high, with a mean value of 4.11 lying between 3.4 and 4.20. The gap between higher education supply of interpersonal skills and engineering labor market need for the same skill was the third widest (mean difference =0.74; SD = 0.71), next to technical skills.\u0026nbsp;The paired sample test in Table 1 confirms the prevalence of statistically significant mean differences between required interpersonal skills (mean =4.11) and acquired interpersonal skills (mean = 3.37), with a mean difference of 0.74, S.D. = 0.71, t = 16.68, p =0.01 at the 0.05 level of confidence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs depicted in Table 2, employees (mean = 3.4; SD = 0.51) and instructors (mean = 3.34; SD = 0.49) reported that interpersonal skill was moderately acquired at higher learning institutes, while employers (mean = 3.44; SD = 0.76) confirmed that higher learning institutes highly equip graduates of engineering disciplines with the same skill. For both employees (mean = 3.82; SD = 0.59) and employers (mean = 4.20; SD = 0.59), interpersonal skills were highly required by employers. Instructors (mean = 4.29; SD = 0.52), on their part, reported that the requirement for interpersonal skills in the engineering labor market was very high. Employees (mean difference = 0.42), employers (mean difference = 0.76), and instructors (mean difference = 0.95) hold different views about graduate acquisition of interpersonal skills and the requirement of the same skill in the engineering labor market. These indicate existence of mismatch between interpersonal skills acquired at higher learning institutes and employers or labor market needs for the same skill.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGeneric skills\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eScholars (e.g., Asai, Breda, Rain, Romanello, Sangnier, 2020; Green, 2016) argue that generic skills are general skills that could apply to a whole range of industries and are increasingly important in modern economies. In this study, creative thinking, willingness to learn, leadership skill, integrity, sense of responsibility, innovativeness, determination, loyalty to the institution and its objectives, ability to assert oneself, self-confidence, and sense of independence are observable indicators used to measure generic skills. The aggregate mean response in the above Table 1 confirms that generic skills (mean = 3.27) were moderately acquired during university studies, with mean values lying in between 2.6 and 3.4. Nevertheless, the need for generic skills in the Ethiopian engineering labor market was high, with a mean value of 4.14 lying between 3.4 and 4.20. The gap between higher education supply and engineering labor market need for generic skills was the widest (mean difference =0.88; SD = 0.72) of all skill types under scrutiny. A paired sample t-test result affirms evidence of a statistically significant mean difference between generic skills acquired at higher learning institutes and those required by employers or the labor market (mean difference = 0.87; SD = 0.72; t = 19.38; p=0.01) at a 0.05 level of confidence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs shown in Table 2, Employees (mean = 3.35; SD = 0.50) and employers (mean = 3.36; SD = 0.45) who took part in the study reported that higher learning institutes moderately equip graduates with generic skills, while the instructors affirmed that universities equip graduates with the same skills to a very high extent. With regard to employers and labor market needs, employees (mean = 4.00; SD = 0.53) and instructors (mean = 4.20; SD = 0.59) believed that generic skills were highly required in the engineering labor market. Interestingly, employers (mean = 4.24; SD = 0.47) reported that the needs for generic skills among employers and the labor market were very high. The reports of employees (mean difference = 0.65), employers (mean difference = 0.88), and instructors (mean difference = 1.02) confirmed the existence of wider gaps between generic skills acquired during studies at university and the requirements of generic skills in the engineering labor market.\u003c/p\u003e\n\u003cp\u003ePaired sample t-tests\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ewere computed to test mean differences among employees, employers, and instructors in responding to levels of skills acquired at higher learning institutes and levels of labor market needs for the same skills. As seen in Table 3, there is a statistically significant mean difference between skills acquired at higher learning institutes and the mean requirement of the same skills in the labor market (p 0.01; \u0026alpha; \u0026le; 0.05). The mean difference was highest for instructors (mean difference = 0.99 SD = 58; t = 19.32; df = 129; p = 0.01), followed by employers (mean difference = 0.85 SD = 0.50; t = 10.69; df = 39; p = 0.01), and the lowest difference among employees (mean difference = 0.59 SD = 0.561; t = 9.21; df = 89; p = 0.01). Thus, the mean responses of employees, employers, and instructors revealed the existence of a significant mismatch between the skills supplied by higher learning institutes and the skills required by employers in the Ethiopian context.\u003c/p\u003e\n\u003cp\u003eCorroborating the above ideas, reports of key informant interviews and reviews of policy documents revealed that the recent higher learning institutes in Ethiopia give minimal attention to equipping learners with most aspects of discipline-specific, technical, interpersonal, and generic skills. Due to weak university-industry linkage, students\u0026rsquo; exposure to the real world of work and the teaching of practitioners from industry remained inadequate, which results in a lack of technical and practical skills among engineering graduates. Higher learning institutes also marginalized strategies and tactics to prepare programs requiring intensive use of IT in teaching and learning tasks. The quality of education has shown a sharp decline; competences are not well identified in higher education curricula; the organization of modules is found to be weak; the teaching methods employed are highly dominated by the traditional lecture method; the world of work is not yet aware of the movement of HEIs towards competence-based curricula; and higher education institutions neglected the development of employability and other lifelong learning skills in graduates.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, there is increasing policy and strategic emphasis on producing qualified engineers and natural scientists capable of understanding and utilizing appropriate technologies in growing manufacturing and service providing enterprises; developing science and technology institutions to produce highly qualified technicians, engineers, and scientists in line with the demand of the national economy; modifying the balance of the enrollment of higher education in favor of the science and technology needs of the country and conducting practical training in cooperation and collaboration with industries; and enabling the establishment of a workforce in manufacturing and service-provider enterprises with the knowledge and skills necessary to learn, adapt, and utilize technology. Ethiopia has witnessed the implementation of a modular approach that requires changing the old knowledge-based curriculum to a contemporary competency-based type of curriculum. The competency-based curriculum emphasizes the identification of professional and vocational skills, job-specific skills, and transferable skills that higher education graduates may have after completing the curriculum.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study of\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eEthiopian higher education engineering graduates\u0026rsquo; skill match in labor markets found that higher learning institutes moderately equip graduates with discipline-specific skills, while the need of the engineering graduate labor market for the same skills was high. Though the study by Wongnaa and Boachie (2018\u003cstrong\u003e)\u0026nbsp;\u003c/strong\u003eunderscores\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ethe importance of discipline-specific skills in the fields of science, technology, engineering, and math,\u0026nbsp;the commitment of Ethiopian higher learning institutes to equip learners with discipline-specific skills was seemingly low. This might be due to the fact that countries differently value discipline specific skills and generic skills. For instance, most British and German employers want new graduates with good transferable skills rather than excellent academic grades, while French and Spanish employers prefer graduates with excellent academic qualifications over transferable skills (Branine \u0026amp; Avramenko, 2015).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHigher learning institutes tend to equip students with indicators of discipline specific skills like skill in applying knowledge of science and engineering principles and skills in planning, designing, calculation, and construction over other aspects. Skill in applying knowledge of science and engineering, specific engineering discipline skill, work place safety, health, and security, the foundation of engineering, and operation, measurement, and control technology were highly required among employers than others. Supporting the idea, scholars (e.g., Shivoro et al., 2019) argued that discipline-specific skills are more relevant to one\u0026rsquo;s career and help graduates perform tasks in the 21\u003csup\u003est\u003c/sup\u003e century. Nevertheless, scholars (e.g., Fitriani \u0026amp; Ajayi, 2022) reported that academic institutions often fail to provide the right skillsets for graduates due to weak collaboration between universities, employers, and professional accreditation bodies.\u003c/p\u003e\n\u003cp\u003eAs discussed above, scholars argued that discipline-specific skills are crucial in hard science fields like engineering and technology, enable graduates to secure employment in their field of studies and receive higher wages, and help graduates perform tasks in the 21\u003csup\u003est\u003c/sup\u003e century. The findings of this study revealed that the need for discipline-specific skills in the engineering labor market was high while the supply of graduates with the same skills was low. The differences between scholars arguments and the findings of this study might be attributed to higher learning institutes\u0026rsquo; negligence in considering the importance of such skills in engineering graduates labor markets, the declining quality of higher education with the current increasing enrollment and graduation rates, and the absence of assessment of employers\u0026rsquo; skill needs by higher learning institutes in curriculum design, delivery, and evaluation. Such a mismatch between higher education discipline specific skill supply and employers needs results in a scarcity of well-qualified engineers capable of applying, testing, and improving existing engineering-related scientific theories and knowledge that fit the changing technological environment. It also increases the rate of graduate unemployment, and employers opt to recruit new employees from non-graduates and are exposed to the additional cost of training.\u003c/p\u003e\n\u003cp\u003eThe current emerging technologies require continuously updating and improving technical skills, which are very important for engineering (Azmi, Kamin, \u0026amp; Noordin, 2018). The findings of this study showed that graduates of higher learning institutes moderately acquire technical skills during university study, while the same skills are highly required in the engineering labor market. Next to generic skills, there was the widest gap between higher education supply and employers needs for technical skills. Employees, employers, and instructors have different views related to graduates\u0026rsquo; acquisition and employers\u0026rsquo; need for technical skills. According to the reports of employers and instructors, engineering graduates moderately acquire technical skills, while employees believe that higher learning institutes well equip graduates with the same skills. Employers and instructors believed that technical skills were highly required in the engineering graduate labor market. Concomitantly, local study by Siraye, Abebe, Melese, and Wale (2018) identified technical skills such as problem-solving skills, information technology skills, adapting to change, and risk-taking skills as the skills most demanded by employers and graduates acquisition of technical skills is an indication of their proficiency to perform highly in a particular job.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNevertheless, except for computer skills, in Ethiopia, little attention has been given to equipping graduates with aspects of technical skills like skill in planning and organizing tasks, problem-solving skills, appropriate decision-making skills, research skills, creative skills, the skill to learn, adapt, and utilize technology, professional skills, and skill in seeking and developing opportunities. Higher education graduates in Ethiopia lack technical and practical skills related to the work they are assigned to do and need close supervision to perform certain assigned tasks because of insufficient practical attachment during studies at higher learning institutes.\u0026nbsp;Supporting the findings by Fitriani and Ajayi (2022), the finding of this study revealed that employers prefer and value graduates with high technical skills, including skill in manipulating computers, problem-solving skills, decision-making skills, and skill in organizing and planning tasks. However, the mismatch of higher education supply and employers need for technical skills indicate that higher learning institutes and employers are not closely working together in identification of technical skills demanded by the world of work and integrating in both curricular and extra-curricular activities.\u003c/p\u003e\n\u003cp\u003eDespite its high requirement in the current Ethiopian engineering labor market, moderate attention was given to graduates\u0026rsquo; interpersonal skills development.\u0026nbsp;Employees, employers, and instructors holding different views about graduate acquisition of interpersonal skills and its requirement in the engineering graduate labor market indicate the existence of a mismatch between graduates\u0026rsquo; acquisition of interpersonal skills and employers\u0026rsquo; needs. Little attention has been given to the development of aspects of interpersonal skills such as the ability to focus on stakeholders\u0026rsquo; or clients\u0026rsquo; needs, empathy, working with people from different cultures, adaptability, and flexibility in the higher education curriculum. In contrast to the finding by Getahun et al. (2020), this study found that engineering graduates of Ethiopian higher learning institutes better develop the ability to work in teams and communication skills than other skills. The study by Ahmed, Philbin, and Cheema (2020) argued that communication skill, together with other skills, determines the success or failure of a given project and is a very important competency to be valued. Yet, graduates of Ethiopian higher learning institutes lack oral and written communication skills in English, a medium of instruction in higher learning institutions. Supporting the study by Collet and Hine (2015), teamwork, communication skills, the ability to work with people from different cultures, and empathy were components of interpersonal skills highly required by employers. Interpersonal skills such as communication skills, empathy, negotiation skills, and focusing on client needs are main requirements for any job and assist organizational success. Thus, higher learning institutes and employers properly identify interpersonal skills and integrate them into higher education curricular and extracurricular activities that positively contribute to engineering graduates\u0026rsquo; and organizational success.\u003c/p\u003e\n\u003cp\u003eScholars (e.g., Asai, Breda, Rain, Romanello, \u0026amp; Sangnier, 2020; Green, 2016) argue that generic skills are general skills that could apply to a whole range of industries and are increasingly important in modern economies. The findings of this study showed that Ethiopian higher learning institutes moderately equip graduates with generic skills, while the need in the Ethiopian engineering labor market is very high. The gap between higher education supply and engineering labor market need for generic skills was the widest of all skill types under scrutiny indicating significant mismatch between generic skills acquired at higher learning institutes and employers\u0026rsquo; needs. Though scholars argue that the employment and job qualities of graduates are primarily determined by generic skills acquired during university studies, higher learning institutes in Ethiopia highly neglected equipping students with generic skills such as creative thinking skills, leadership skills, integrity, innovativeness, determination, loyalty to institutions and objectives, the ability to assert oneself, self-confidence, and independence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study showed that most graduates lack aspects of generic skills such as entrepreneurship skill, leadership skills, psychological, emotional, and social maturity, intellectual skills, accountability, readiness or motivation to learn new things; a feeling of belongingness; and life skills. In contrast, aspects of generic skills like willingness to learn, willingness to perform, commitment, and sense of responsibility are better acquired during the curricular and extracurricular activities of higher learning institutes. Yet scholars (e.g., Asai et al., 2020) revealed that individuals with stronger generic competences are more widely employed outside their own field of study and easily adapt to tasks and requirements with which they are not familiar. It has also been argued that the acquisition of general skills will translate into higher earnings in a competitive labor market (Asai, Breda, Rain, Romanello, \u0026amp; Sangnier, 2020). Thus, generic skills are core employability skills that are more or less equally required in all organizations and critical for graduate success in the labor market and organizational competitiveness. However, higher learning institutes in Ethiopia seemingly failed to identify these key employability skills to incorporate into curricular and extracurricular tasks in the current booming higher education enrollment, graduation, and unemployment rates. Such a mismatch between higher education skill supply and employers\u0026rsquo; skill need is an indication of inefficiency in the labor market that can hinder productive capacities, which generate unemployment and underemployment, harm organizational productivity due to lower output per worker, inflate average labor costs, affect firm-level profitability, and affect the capacity of enterprises to innovate and adapt to changing market conditions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eT\u003cem\u003ehis study\u0026nbsp;\u003c/em\u003eassessed the match between higher education skill supply and labor market skill needs, with a special focus on engineering graduates of public higher education institutions in Ethiopia. The findings of this study showed\u003cem\u003e\u0026nbsp;\u003c/em\u003ethat higher learning institutes moderately equip graduates with discipline-specific academic skills, technical skills, interpersonal skills, and generic skills, while the need for these skills in the engineering graduate labor market is high. Compared to other skill types under scrutiny, the gap between higher education supply of discipline-specific academic skills and engineering labor market need for the same skill was narrowest. Next to generic skills, there is the widest gap between higher education supply and employers needs for technical skills. The gap between higher education supply of interpersonal skills and engineering labor market need for the same skill was the third widest, next to generic skills and technical skills. Employees, employers, and instructors have different views related to graduates\u0026rsquo; acquisition and employers\u0026rsquo; need for all types of skills under scrutiny. For instance, while employers and instructors believe that engineering graduates moderately acquire technical skills; employees believe that higher learning institutes well equip graduates with the same skill. Similarly, employers and instructors believe that technical skills are highly required in the engineering graduate labor market. These indicate existence of a significant mismatch between higher education\u0026apos;s supply of the four types of skills and employers and the labor market\u0026apos;s needs. The mismatch between higher education skill supply and employers skill needs has several impacts and implications for companies and organizations. Among other things, skill mismatch impacts workers or firms that are currently employing or looking to employ workers, compromises firms\u0026rsquo; productivity, quality, and competitiveness, results in higher wages, increases recruitment costs, requires more investment in current personnel, results in market losses, implies a greater workload and pressure on current personnel, may result in lower company competitiveness, and prevents investments in and the development of knowledge-intensive and innovative industries, which hamper economic growth, competitiveness, and innovative capacity at the macroeconomic level. Despite having not impacted the primary outcomes of the paper, this study excluded skills employees acquire at work through experience and prospective graduates in sample selection, factors attributed to mismatch of higher education skill supply and employers\u0026rsquo; skill needs. It didn\u0026rsquo;t employ sophisticated statistical techniques like factor and regression analysis in its data analysis. Thus, future research could consider all these limitations. Higher education institutes could also conduct real employers\u0026rsquo; needs assessments before preparing training curricula for different fields of study and updating training styles and contents based on the needs of employers.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmed, R., Philbin, S. P., \u0026amp; Cheema, F. E. A. (2021). Systematic literature review of project manager\u0026apos;s leadership competencies. \u003cem\u003eEngineering, Construction and Architectural Management\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(1), 1-30.https://doi:10.1108/ECAM-05-2019-0276.\u003c/li\u003e\n\u003cli\u003eAsai, K., Breda, T., Rain,A., Romanello, L., \u0026amp; Sangnier, M. (2020). Education, skills and skill mismatch. A review and some new evidence based on the PIAAC survey. URL: https://shs.hal.science/halshs-02514746.\u003c/li\u003e\n\u003cli\u003eAzmi, A. N., Kamin, Y., \u0026amp; Noordin, M. K. (2018). Competencies of engineering graduates: what are the employer\u0026rsquo;s expectations. \u003cem\u003eInternational Journal of Engineering \u0026amp; Technology\u003c/em\u003e, \u003cem\u003e7 \u003c/em\u003e(2.29), 519-523. https://doi: 10.14419/ijet.v7i2.29.13811.\u003c/li\u003e\n\u003cli\u003eBabalola, S. (2015).Strategies for improving the employability skills and life chances of youths in Nigeria. \u003cem\u003eCurrent studies in comparative Education\u003c/em\u003e, 2 (1), 137-147. URL=https://api.semanticscholar.org/CorpusID:56331785.\u003c/li\u003e\n\u003cli\u003eBeyene, B.M., \u0026amp; Teklesilassie, T.G. (2018). The State, Determinants, and Consequences of Skills Mismatch in the Ethiopian Labour Market. EDRI Working Paper 21. Addis Ababa: Ethiopian Development Research Institute.\u003c/li\u003e\n\u003cli\u003eBranine, M., \u0026amp; Avramenko, A. (2015). A comparative analysis of graduate employment prospects in European labour markets: A study of graduate recruitment in four countries. \u003cem\u003eHigher Education Quarterly\u003c/em\u003e, \u003cem\u003e69\u003c/em\u003e(4), 342-365. https://doi: 10.1111/hequ.12076.\u003c/li\u003e\n\u003cli\u003eCreswell, J. W. (2014). \u003cem\u003eResearch design: Qualitative, quantitative and mixed approaches.\u003c/em\u003e SAGE publication, Inc. \u003c/li\u003e\n\u003cli\u003eFenta, H. M., Asnakew, Z. S., Debele, P. K., Nigatu, S. T., \u0026amp; Muhaba, A. M. (2019). Analysis of supply side factors influencing employability of new graduates: A tracer study of Bahir Dar University graduates. Journal of Teaching and Learning for Graduate Employability, 10(2), 67-85.\u003c/li\u003e\n\u003cli\u003eFitriani, H., \u0026amp; Ajayi, S. (2022). Preparing Indonesian civil engineering graduates for the world of work. \u003cem\u003eIndustry and Higher Education\u003c/em\u003e, \u003cem\u003e36\u003c/em\u003e(4), 471-487. https:// doi. 10.1177/09504222211046187.\u003c/li\u003e\n\u003cli\u003eGay, L.R., Mills, G.E. \u0026amp; Airasian, P.W. (2012) Educational Research: Competencies for Analysis and Application. 10th Edition, Pearson, Upper Saddle River.\u003c/li\u003e\n\u003cli\u003eGetahun, M., \u0026amp; Mersha, D. (2020). Skill gap perceived between employers and accounting graduates in Ethiopia. \u003cem\u003eFinancial Studies\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(2 (88)), 65-90. http://hdl.handle.net/10419/231700. \u003c/li\u003e\n\u003cli\u003eGreen, F. (2016). Skills demand, training and skills mismatch: A review of key concepts, theory and evidence. \u003cem\u003eForesight, Government Office for Science\u003c/em\u003e. http://hdl.voced.edu.au/10707/422302.\u003c/li\u003e\n\u003cli\u003eJote, T. (2017). Exploring employment status and education\u0026ndash;job match among engineering graduates in Ethiopia: policy implications. \u003cem\u003eInternational Journal of African Higher Education\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(1), 42-65. https://doi.org/10.6017/ijahe.v4i1.10249.\u003c/li\u003e\n\u003cli\u003eKarorsa, D. L., \u0026amp; Polka, W. S. (2015). The Equity-Quality Dilemma of Higher Education Expansion: A Goal-Oriented Planning Approach for Maintaining High Quality Standards in Ethiopia. \u003cem\u003eEducational Planning\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(3), 19-35. \u003c/li\u003e\n\u003cli\u003eMaarouf, H. (2019). Pragmatism as a supportive paradigm for the mixed research approach: Conceptualizing the ontological, epistemological, and axiological stances of pragmatism. \u003cem\u003eInternational Business Research\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(9), 1-12. https://doi:10.5539/ibr.v12n9p1\u003c/li\u003e\n\u003cli\u003eMinistry of Education, MoE. (2015). Education statistics annual abstract. Addis Ababa. \u003c/li\u003e\n\u003cli\u003eOlkaba, T., \u0026amp; Tamene, E. (2017). Bologna process and reality on the ground in Ethiopian higher education. \u003cem\u003eAsian Journal of Educational Research\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(4), 43-51. ISSN 2311-6080.\u003c/li\u003e\n\u003cli\u003ePăcurariu, G. (2019). The Integration of Higher Education Graduates on the Labor Market. \u003cem\u003eEuropean Review of Applied Sociology\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(19), 23-32. https://doi.org/10.1515/eras-2019-0008.\u003c/li\u003e\n\u003cli\u003ePalmer, R. (2017). Jobs and skills mismatch in the informal economy. \u003cem\u003eILO.ISBN:978-92-2-131613. \u003c/em\u003e\u003c/li\u003e\n\u003cli\u003ePang, E., Wong, M., Leung, C. H., \u0026amp; Coombes, J. (2019). Competencies for fresh graduates\u0026rsquo; success at work: Perspectives of employers. \u003cem\u003eIndustry and Higher Education\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(1), 55-65. https://doi.org/10.1177/0950422218792333.\u003c/li\u003e\n\u003cli\u003eReda, N. W., \u0026amp; Gebre-Eyesus, M. T. (2018). Graduate unemployment in Ethiopia: the \u0026lsquo;red flag\u0026rsquo;and its implications. \u003cem\u003eInternational Journal of African Higher Education\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(1), 32-43. https://doi.org/10.6017/ijahe.v5i1.10967.\u003c/li\u003e\n\u003cli\u003eRowe, A. D., \u0026amp; Zegwaard, K. E. (2017). Developing graduate employability skills and attributes: Curriculum enhancement through work-integrated learning. Asia-Pacific Journal of Cooperative Education, Special Issue, 18 (2), 87-99.\u003c/li\u003e\n\u003cli\u003eShivoro, R. S., Shalyefu, R. K., \u0026amp; Kadhilaho, N. (2019). A critical analysis of universal literature on graduate employability. \u003cem\u003eJournal for Studies in Humanities and Social Sciences\u003c/em\u003e, 6 (2), 248-268.\u003c/li\u003e\n\u003cli\u003eSiraye, Z., Abebe, T., Melese, M., \u0026amp; Wale, T. (2018). A tracer study on employability of business and economics graduates at Bahir Dar University. \u003cem\u003eInternational Journal of Higher Education and Sustainability\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(1), 45-63. https://doi: 10.1504/IJHES.2018.092406.\u003c/li\u003e\n\u003cli\u003eVelasco-Mart\u0026iacute;nez, L. \u0026amp; T\u0026oacute;jar-Hurtado, J. (2018). Competency-Based Evaluation in Higher Education\u0026mdash; Design and Use of Competence Rubrics by University Educators. \u003cem\u003eInternational Education Studies; 11 (2), 118-132. \u003c/em\u003ehttps://doi:10.5539/ies.v11n2p118.\u003c/li\u003e\n\u003cli\u003eWongnaa, C. A., \u0026amp; Boachie, W. K. (2018). Perception and adoption of competency-based training by academics in Ghana. \u003cem\u003eInternational journal of STEM education\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(1), 1-13. https://doi.org/10.1186/s40594-018-0148-x.\u003c/li\u003e\n\u003cli\u003eYibeltal, J. (2016). Higher education and labor market in Ethiopia: A tracer study of graduate employment in engineering from Addis Ababa and Bahir Dar Universities. \u003cem\u003eAddis Ababa University, Addis Ababa, Ethiopia\u003c/em\u003e. URI: http://etd.aau.edu.et/handle/123456789/3799.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"engineering graduates, higher education institutes, employers’ need, skill match, competences","lastPublishedDoi":"10.21203/rs.3.rs-3845044/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3845044/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe purpose of this study investigated the match between higher education skill supply and employers’ skill needs, with a special focus on engineering graduates in Ethiopia. Using an embedded mixed method design, the study analyzed both primary and secondary data on the match between higher education supply and employers needs for discipline-specific, technical, interpersonal, and generic skills. 275 research participants recruited from employees, employers, higher education instructors, and decision-makers took part in the study. The findings of the study revealed that higher learning institutes moderately equip graduates with discipline-specific skills, technical skills, interpersonal skills, and generic skills, while employers’ need for these skills is high. These indicate existence of a significant mismatch between higher education skill supply and employers’ needs, which was higher for technical and generic skills than interpersonal and discipline-specific academic skills. Such mismatch between higher education skill supply and employers’ skill needs negatively affect economic performance and social security \u0026nbsp;through increasing rate of graduates’ unemployment. To mitigate such problems, higher learning institutes could conduct real employers’ needs assessments before preparing training curricula and need to update training styles and contents accordingly. The skills employees acquire at work, factors contributing to the mismatch between skill supply and employers’ needs, and impacts of skill mismatch could be future research areas.\u003c/p\u003e","manuscriptTitle":"The match between higher education skill supply and employers’ skill needs in Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-09 04:40:38","doi":"10.21203/rs.3.rs-3845044/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"89228237-2d8a-462e-b282-1d479e27ef57","owner":[],"postedDate":"January 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-09T04:40:38+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-09 04:40:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3845044","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3845044","identity":"rs-3845044","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}