Student academic performance stochastic simulator based on the Monte Carlo method

Caro, Eduardo; González, Celina; Mira, José

doi:10.1016/j.compedu.2014.03.007

Cited by 11 publications

(7 citation statements)

References 8 publications

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“…Learning outcomes is the related to the quantification for academic deliverables as a set of measurement. Caro et al (2014) in their argument related to academic research, mentioned that the tools, like, scores in examinations, grade point average (GPA) are the tools to measure the academic performance, and there are no such qualitative tools. There is no direct relationship between IQ and scores earned in examinations.…”

Section: Sq and Academic Performancementioning

confidence: 99%

Human Resource Development and Spiritual Intelligence: An investigation amongst Management students in Delhi NCR

Gera¹,

Vesperi

Fatta

et al. 2021

IJIL

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The study seeks to investigate the relationship between spiritual intelligence and its relative impact on students' academic performance. Several studies link SI with intellectual development. This study aims to analyse the phenomenon of spiritual intelligence (SI) within the framework of human resource development (HRD) research. Qualitative and quantitative data were analysed. The study was conducted among management students residing in Delhi NCR. The findings confirm that spiritual quotient factors are applicable in the Indian context. In addition, the study reveals that the spiritual quotient is significantly correlated with academic performance. The study uses the scale developed by King (2008) to measure spiritual intelligence through spiritual intelligence self report inventory (SISRI) which includes 24 statements. From the available constructs of the spiritual quotient, the critical existential thinking (CET) and the personal meeting production (PMP) have a positive relationship with academic performance. The academic performance is explained by 19% using CET and PMP. Therefore, management institutions must also instil the culture of spiritualism within the institute to improve the performance of management students. The study tries to cover part of the gap in the HRM literature on the SI topic.

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Section: Sq and Academic Performancementioning

confidence: 99%

Human Resource Development and Spiritual Intelligence: An investigation amongst Management students in Delhi NCR

Gera¹,

Vesperi

Fatta

et al. 2021

IJIL

View full text Add to dashboard Cite

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“…Moreover, awareness of one's capacities and capabilities is also linked with higher performance (Mushtaq & Khan, 2012). Caro, González, and Mira (2014) contended that there are many papers focused on the student performance indicators of individual students for particular subjects or actually for a complete year. A few elements are analyzed and compared to enhance the students' academic performance.…”

Section: Service Quality and Student Performance In Heismentioning

confidence: 99%

The relationship between e‐learning and academic performance of students

Rasheed

Khalid

et al. 2020

Journal of Public Affairs

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The purpose of this paper is to investigate the relationship of service quality dimensions (tangibility, responsiveness, assurance, reliability, empathy, and e‐learning) on student's academic performance through student motivation, and student satisfaction. Primary data were collected from 384 participants studying in higher education institutes (HEI's) in the Punjab province of Pakistan and the research model was empirically tested. The findings reveal that all service quality dimensions (tangibility, responsiveness, assurance, reliability, empathy, and e‐learning) are positively associated with student's academic performance through student's motivation and student satisfaction. This study makes a substantial contribution to the literature of service quality, by adding a novel dimension “e‐learning” into the most renowned and frequently used SERVQUAL (tangibility, reliability, empathy, assurance, and responsiveness) model. By doing so we not only establish the link between e‐learning and student's academic performance through student satisfaction and student motivation but also extended the SERVQUAL model by incorporating an important neglected area.

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“…To generate multiple sets of the student's learning data, inspired from [10], the random nested sampling for evolving data streams is used. Hence, many of the original data are repeated in the resulting simulated date set.…”

Section: B Understanding Data Mining Actionable Trendsmentioning

confidence: 99%

Measuring Students' Academic Performance through Educational Data Mining

Wong¹,

Yip²

2020

IJIET

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Based on a mix of real world data and a simulated dataset for predicting the students’ academic performance, we study/compare various decision tree (DT) based algorithms (which include ID3, C4.5 and CART) with different choices of information entropy metrics (which include Shannon, Quadratic, Havrda and Charvát, Rényi, Taneja, Trigonometric and R-norm entropies) to build a decision tree in order to provide appropriate counseling/advise at an earlier stage. DT is one such important technique in educational data mining (EDM) which creates hierarchical structures of classification rules “If ⋯, Then ⋯” building a tree structure by incrementally breaking down the datasets in smaller subsets. The results suggest that basic training of the students has no significant predictive power on performance, while information about their abilities, diligence, motivation and activity in the learning process can predict their grades. As such, the resulting forecasts can be used by the instructor in optimizing the learning process and designing the course content and schedule.

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Student academic performance stochastic simulator based on the Monte Carlo method

Cited by 11 publications

References 8 publications

Human Resource Development and Spiritual Intelligence: An investigation amongst Management students in Delhi NCR

Human Resource Development and Spiritual Intelligence: An investigation amongst Management students in Delhi NCR

The relationship between e‐learning and academic performance of students

Measuring Students' Academic Performance through Educational Data Mining

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