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dc.contributor.authorMwakondo, Fullgence M
dc.contributor.authorMuchemi, Lawrence
dc.contributor.authorOmwenga, Elijah
dc.date.accessioned2024-02-23T09:25:03Z
dc.date.available2024-02-23T09:25:03Z
dc.date.issued2016-01
dc.identifier.citationMwakondo, F., Muchemi, L., & Omwenga, E. (2016). Trends towards Predictive Mapping of Graduates’ Skills to Industry Roles: A Case Study of Software Engineering. British Journal of Education, Society & Behavioural Science, 18(1), 1-17.en_US
dc.identifier.issn2278-0998
dc.identifier.urihttp://ir.tum.ac.ke/handle/123456789/17460
dc.descriptionDOI: 10.9734/BJESBS/2016/28711en_US
dc.description.abstractAim: To investigate whether industry roles in the same occupation have similar academic requirements and establish learning trends in the academia towards occupational industry roles. Design of Study: Descriptive survey research design was adopted where truism about the phenomenon under study was arrived at by gathering respondent’s perception about the phenomenon. Place and Duration of Study: This study was conducted in the Kenyan software engineering industry and universities in the academia in the month of May 2016. Methodology: 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 graduate’s skills to industry roles was used as the research model for the study while for academic requirements analyses purposes the model’s variables were double classified into two dimensions i.e. knowledge or skill type and domain specific or domain general. Results: Findings indicate while domain specific knowledge (χ 2 =2.44, P=.87) and skills (χ 2 =1.86, P=.93) for industry roles in the same occupation are similar, domain general knowledge (χ 2 =13.10, P=.04) and skills (χ 2 =16.151, P=.01) are significantly different for these industry roles. Further revelation indicates, 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 employability chances.en_US
dc.description.sponsorshipTECHNICAL UNIVERSITY OF MOMBASAen_US
dc.language.isoenen_US
dc.publisherBritish Journal of Education, Society & Behavioural Scienceen_US
dc.subjectEvaluationen_US
dc.subjectmapping skillsen_US
dc.subjectlong term unemploymenten_US
dc.subjectproblem-solvingen_US
dc.subjectsoftware engineeringen_US
dc.subjecttrendsen_US
dc.titleTrends towards Predictive Mapping of Graduates’ Skills to Industry Rolesen_US
dc.title.alternativeA Case Study of Software Engineeringen_US
dc.typeArticleen_US


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