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dc.contributor.authorMwangi, Anne Wanjiru
dc.date.accessioned2016-07-18T09:50:11Z
dc.date.available2016-07-18T09:50:11Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/11071/4630
dc.descriptionA dissertation submitted in partial fulfillment of the requirements for the Degree of Masters of Science in Mobile Telecommunications and Innovation (MSc.MTI)en_US
dc.description.abstractCurrently, students mainly get career advice from their parents, teachers, peers or career counsellors. These career information sources consider factors like expected remuneration, job location, the current market trends and social preferences in their recommendation. Personality is very influential in the career decision-making process of high school and university students. Moreover, when students select careers that do not agree with their personalities, they lack interest in the course and eventually drop out or request for career change. In this dissertation we present the design and development of a proposed personality-based career recommender expert system that aims to assist high school students to select the best suitable career choice program in Institutions of Higher Learning in Kenya. In order to generate recommendations it applies the results achieved in the personality analysis from the personality assessment test to the knowledge base system. This system contains degree programs classified using the Dictionary Holland of Occupational Classification. The main aim of the proposed model is to eventually minimize frustrations that come with selecting the wrong careers in pursuit of one's career goals. The system stores its data on a cloud server, which provides real time updates for new requests on mobile devices. The mobile application source code is written in Apache Cordova platform and integrated with android. This makes it a hybrid application that can be run on any platform. To test the application, a questionnaire form is prepared and issued to all the students who participated in the main study and they are allowed to use the system and give their feedback. This enabled evaluation of the system usability, efficiency and effectiveness. The test results indicated that the system was able to accurately recommend careers to students with an accuracy prediction level of 80%.en_US
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectPersonalityen_US
dc.subjectCareer choiceen_US
dc.subjectRecommender Systemen_US
dc.subjectHolland Theoryen_US
dc.titleM-Career : a personality-based career recommender expert systemen_US
dc.typeThesisen_US


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