Estimating a Prediction Model for the Early Identification of Low Employability Graduates in Malaysia

Hashim, Rosna Awang; Lim, Hock Eam; Yatim, Bidin; Ariffin, Tengku Faekah Tengku; Zubairi, Ainol Madziah; Yon, Haniza; Osman, Omar

doi:10.1142/s0217590815500277

Cited by 9 publications

(5 citation statements)

References 11 publications

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“…Pedagogies often develop courses that embed skills for employability (Awang-Hashim et al, 2015) or that align directly to career specialization. Most of the pedagogies often help to analyze the progress only at the assessment stage, with a continual quality improvement at the course level and programme level.…”

Section: Educational Priorities For the Futurementioning

confidence: 99%

“…Newer curriculum design and execution in engineering education targeting to support the IR 4.0 (Zainal-Abidin, Y., Haseeb, 2018Dalto, 2018Herrington, Reeves, & Oliver, 2007 is need of the hour for educational sustainability primarily due to the disruption caused by the technology in the current generation lives. The effectiveness of such systems in place is evaluated in most of the cases only upon student graduations (Awang-Hashim, R. 2015, Yusof, N., 2016, Yusof, N., 2016. The striking balance on the improvement of the quality of the graduates throughout their study as a check and balance act will help both the learner and the institutions to make the learning more personalized making meaning educational journey.…”

Section: End Of Semester Assessment Tool Analyticsmentioning

confidence: 99%

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Empowered Pedagogy: Catching Up with the Future

Vaithilingam

Gamboa

Lim

2019

Malaysian Journal of Learning and Instruction

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Purpose - Recently, a layered and lateral framework that provides opportunities for students to design the pedagogy that creates a broad based, flexible and personalized learning is introduced by the Taylor’s University School of Engineering. This approach creates avenue for the students to design their own curriculum within the framework that is developed with inputs from the industry. The framework, the key components, and the tracking of the performance to align the set outcomes through assessment tool is presented. Methodology - My Study Plan (MySP) a macro-enabled software is used to develop a four-year tier model for the students to design the curriculum with the help of a mentor at the start of the programme. Student’s learning is monitored on a semester-based learning analytics process implementing the Programme Outcomes (PO) Scorecard. The August 2018 cohort of the Electrical and Electronic Engineering programme is used to pilot this pedagogy. Findings - Currently the PO measurement is done for the graduating student and focus only on the effectiveness of the programme. The Programme Outcome Assessment Review (POAS) used in this study to monitor the MySP the continual monitoring each semester rather towards the end of graduation. Initial simulation of existing PO attainment record of students suggest that this can generate interest towards the learning progress on a semester basis. Significance - The successful adoption sees an effectiveness in the long run in developing graduates through the continual monitoring of the programme outcomes. The graduating students carry the PO scorecard that complements a second transcript for value addition for their studies. Prospective employers can use the PO scorecard as a metric for initial recruitment purposes, a measure for the soft skills achievements of the applicant.

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Section: Educational Priorities For the Futurementioning

confidence: 99%

Section: End Of Semester Assessment Tool Analyticsmentioning

confidence: 99%

Empowered Pedagogy: Catching Up with the Future

Vaithilingam

Gamboa

Lim

2019

Malaysian Journal of Learning and Instruction

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“…In this regard, it is believed that a high percentage of unemployed graduates can have negative consequences for society, resulting in economic costs. This includes a decrease in productivity and an unsatisfactory return on the investments made in higher education institutions by individuals and the government [3].…”

Section: Introductionmentioning

confidence: 99%

Classification Techniques Using Machine Learning for Graduate Student Employability Predictions

Haque,

Quek,

Ting

et al. 2024

Int. J. Adv. Sci. Eng. Inf. Technol.

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The issue of employability has gained significant importance, not only for graduate students but also for higher educational institutions. In this regard, employability prediction models using machine learning have emerged as crucial techniques for assessing students' potential to secure employment after graduation. Enhancing university graduate employability is critical because student unemployment is a global concern that has widespread negative effects on both individuals and institutions. Therefore, focusing on graduate employability predictions using machine learning techniques is considered essential in addressing this issue. Traditionally, demographic and academic attributes, such as CGPA, have been considered key factors in determining student employment status. However, research suggests that various other factors, such as student satisfaction, might influence employability. This study employs machine learning techniques to identify the factors that affect graduate student employability. The objective is to investigate the features significantly influencing students' ability to secure employment. Data was collected from Malaysia's Ministry of Education's graduate tracer study (SKPG). Several classification algorithms were applied, including Logistic Regression, Random Forest, Naïve Bayes, Support Vector Machine, Extreme Gradient Boosting, and Artificial Neural Networks (ANN). The results show that ANN achieved the highest accuracy, with around 80%. The findings also revealed that student demographic and academic features and student satisfaction level with the university facilities (e.g., library and counseling service) are considered significant for graduate student employability predictions. Consequently, the empirical results can help higher educational institutions enhance facilities and prepare students with the necessary skills for future employability.

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“…The role of entrepreneurship has also been highlighted in resolving various economic and social issues that today's societies are grappling with; one notable example of which is increasing graduate unemployment (Liñán and Chen 2009;Muscio and Ramaciotti 2019). Studies report a high percentage of graduates are either unemployed or were unable to pursue a career in industries relevant to their field (Awang-Hashim et al 2015;Silva et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Designing and developing a sport entrepreneurship course: an educational design-based study

Ansari¹,

Khoo

Ismail

2020

Entrep Educ

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There is an evident gap in the studies that provide a systematic process of designing sport entrepreneurship courses.This study employed an educational design-based approach to design a sport entrepreneurship course. The 'Theory of Planned Behaviour' and Gagné's 'nine events of instructions' were used as the theoretical foundation and teaching strategy guidelines of the course. The study included three main phases, namely needs analysis, course design, and reflection. Needs assessment phase resulted to the design of outline for an introductory sport entrepreneurship course.The completed design was instructed to sport students in a public university in Malaysia. The post-test results showed significant increase in students' entrepreneurial intention. The classroom observations showed more attention must be paid to opportunity recognition topic and cultural contexts for an introductory entrepreneurship course. In addition, using the nine events of instruction as the basis for teaching strategy provided a clear structure and solid framework for the teaching and learning process and classroom experience.

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Estimating a Prediction Model for the Early Identification of Low Employability Graduates in Malaysia

Cited by 9 publications

References 11 publications

Empowered Pedagogy: Catching Up with the Future

Empowered Pedagogy: Catching Up with the Future

Classification Techniques Using Machine Learning for Graduate Student Employability Predictions

Designing and developing a sport entrepreneurship course: an educational design-based study

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