Background: Long-term unemployment (LTU) has been a major
concern in many countries, including Kenya. LTU would not be a trouble if job
characteristics for each kind of worker, levels of education and skills,
experience, and occupation were precisely known by new graduates. Employability
of skilled graduates in the industry is a challenge not only because of the
effect of unemployment duration, but also due to increased skills variation
among both graduates and industry roles, emanating from the industry-academia
gap.
Aim: The aim of this study is to investigate whether
industry roles in the same occupation have similar academic requirements and
establish learning trends in academia towards occupational industry roles.
Methodology: This study was conducted in the Kenyan software
engineering industry and universities in academia in the month of May 2016. A
descriptive survey research design was adopted in this study. Perception from
113 employees used as respondents and 24 examinations past papers from 5 Kenyan
universities, both in the domain of software engineering, were involved. Two
experts, a software engineering lecturer and a pedagogy lecturer, were used to
extract data from the exam past papers after their reliability test was
confirmed. Both descriptive procedures and non-parametric tests of hypotheses
were conducted using SPSS version 16 software and .05 as the test limit for
significance. A proposed model for mapping graduates’ skills to industry roles
was used as the research model for the study, while for academic requirements
analysis purposes, the model’s variables were double classified into two
dimensions, i.e. knowledge or skill type and domain-specific or domain-general.
Results: This study showed that the most common job entry
roles for software engineers after graduation are 'web programmer' and 'analyst
programmer'. A frequency analysis of 17 role performance activities (RPAs)
performed by software engineers at entry-level industry positions reveals that
‘design database’ is the most frequently performed activity (11%), while ‘manage
project workflows’ is the least performed (2%). Regarding the proposed model,
findings indicated that while domain-specific knowledge (χ2=2.44, P=.87) and
skills (χ2=1.86, P=.93) for industry roles in the same occupation are similar,
domain general knowledge (χ2=13.10, P=.04) and skills (χ2=16.151, P=.01) are
significantly different for these industry roles. Further revelation indicated
that, while academia trends towards various industry roles within the same
occupation are fairly good for knowledge (80%) and poor for skills (45.7%),
trends towards various industry roles within the same occupation are not
uniform among universities.
Conclusion: Academic knowledge and skills requirements for
occupational industry roles are not similar, and trends towards occupational
industry roles are not uniform among universities. Therefore, students should
select universities that have a higher trending profile for industry roles in
order to increase their chances. It is also recommended that domain-specific
knowledge and skills must be covered well during learning in academia.
Author(s) Details
Fullgence Mwachoo
Mwakondo
Institute of Computing and Informatics, Technical University of Mombasa,
P.O. Box 90420-80100, Kenya.
Please see the book here:- https://doi.org/10.9734/bpi/erpra/v9/5733
