An analysis of the professional preferences and choices of computer engineering students

Kabakuş, Abdullah Talha; Şentürk, Arafat

doi:10.1002/cae.22279

Cited by 2 publications

(1 citation statement)

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“…The job preferences of university students are the subject of a significant number of investigations covering different perspectives. Some papers focus on factors that impact on work preferences in different disciplines [17][18][19][20][21][22], others are concentrated on changing preferences during the time for completing their degree and after finishing it [23][24][25], yet another large body of literature focuses on gender differences [26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Are Cooperatives an Employment Option? A Job Preference Study of Millennial University Students

2020

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Millennials represent the most important group among the working age population. Destined to be the leaders of the future, their professional and personal profiles differ considerably from previous generations. Despite being considered as the most successful generation, millennials face a societal transformation and a labor reality marked by high levels of unemployment and underemployment that shape their career choice. Although millennials’ and university students’ job preferences have long been debated in the literature, some research gaps remain. Studies rarely consider the interplay between individuals’ profiles and the institutional form of business, particularly cooperative versus non cooperative options. To predict the compatibility between Millennials’ profiles and the cooperative job preference, a multinomial logit model is developed based on a survey of millennial business college students. Our key findings showed that some extrinsic issues are related to cooperative job preference, however the factor that has the most significant impact is the cooperative knowledge. This has important implications for the cooperative movement and for policy makers in charge of cooperative development.

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Section: Introductionmentioning

confidence: 99%

Are Cooperatives an Employment Option? A Job Preference Study of Millennial University Students

2020

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Contributions of Machine Learning Models towards Student Academic Performance Prediction: A Systematic Review

et al. 2021

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Machine learning is emerging nowadays as an important tool for decision support in many areas of research. In the field of education, both educational organizations and students are the target beneficiaries. It facilitates the educational sector in predicting the student’s outcome at the end of their course and for the students in deciding to choose a suitable course for them based on their performances in previous exams and other behavioral features. In this study, a systematic literature review is performed to extract the algorithms and the features that have been used in the prediction studies. Based on the search criteria, 2700 articles were initially considered. Using specified inclusion and exclusion criteria, quality scores were provided, and up to 56 articles were filtered for further analysis. The utmost care was taken in studying the features utilized, database used, algorithms implemented, and the future directions as recommended by researchers. The features were classified as demographic, academic, and behavioral features, and finally, only 34 articles with these features were finalized, whose details of study are provided. Based on the results obtained from the systematic review, we conclude that the machine learning techniques have the ability to predict the students’ performance based on specified features as categorized and can be used by students as well as academic institutions. A specific machine learning model identification for the purpose of student academic performance prediction would not be feasible, since each paper taken for review involves different datasets and does not include benchmark datasets. However, the application of the machine learning techniques in educational mining is still limited, and a greater number of studies should be carried out in order to obtain well-formed and generalizable results. We provide future guidelines to practitioners and researchers based on the results obtained in this work.

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An analysis of the professional preferences and choices of computer engineering students

Cited by 2 publications

References 26 publications

Are Cooperatives an Employment Option? A Job Preference Study of Millennial University Students

Are Cooperatives an Employment Option? A Job Preference Study of Millennial University Students

Contributions of Machine Learning Models towards Student Academic Performance Prediction: A Systematic Review

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