Robust calibration for estimating the population mean using stratified random sampling

Zaman, Tolga; Bulut, Hasan

doi:10.24200/sci.2023.59408.6224

Cited by 7 publications

(4 citation statements)

References 30 publications

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“…The study was conducted at a public university in Spain, with 215 students participating from three distinct computer engineering degree programs, but having the same previous subjects about programming. Stratified random sampling [21,22] was employed to ensure a representative sample for the case study, with students divided into strata corresponding to their specific degree programs. This approach provided a comprehensive perspective on the effects of the gamified learning environment across diverse educational paths.…”

Section: Methodsmentioning

confidence: 99%

Influence of Gamification on the Commitment of the Students of a Programming Course: A Case Study

Calles-Esteban,

Hellín,

Tayebi

et al. 2024

Applied Sciences

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In the realm of programming education, enhancing student commitment is pivotal for both academic success and practical application. Traditional methodologies often fall short in catering to the evolving needs of today’s learners. Addressing this gap, this paper introduces a web-based gamified tool designed to transform the pedagogical approach in programming courses. The study’s theoretical contribution lies in its exploration of gamification as a strategy to augment student commitment, bridging the divide between conventional teaching and contemporary learning needs. From a practical standpoint, empirical data encompassing performance metrics, dropout rates, and student feedback demonstrate the tool’s significant positive impact. Notably, students exhibited improved pass rates and reduced dropout tendencies, underscoring the tool’s practical efficacy. Furthermore, feedback highlighted the tool’s usability and the enhanced satisfaction derived from its engagement. Aligned with the existing literature, the findings advocate for the broader adoption of gamification in programming education. This research substantiates the potential of gamification as both a theoretical model and a practical strategy, enriching the discourse on modern programming education.

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Section: Methodsmentioning

confidence: 99%

Influence of Gamification on the Commitment of the Students of a Programming Course: A Case Study

Calles-Esteban,

Hellín,

Tayebi

et al. 2024

Applied Sciences

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“…Given the robust correlation between the variables, it is anticipated that effective weights applied to the auxiliary variable would also be effective for the research variable. Drawing from the groundbreaking contributions of Deville and Sarndal [27] , numerous researchers have delved into calibration estimation, employing various calibration constraints in the field of survey sampling, as documented in references [28] , [29] , [30] .…”

Section: Adapted Memory Type Calibrated Estimatormentioning

confidence: 99%

Calibrated EWMA estimators for time-scaled surveys with diverse applications

Alomair,

Iftikhar

2024

Heliyon

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“…Refs. [26][27][28] proposed a novel robust calibrated technique for computing the population parameter under StRS. Ref.…”

Section: Introductionmentioning

confidence: 99%

Calibrated Empirical Neutrosophic Cumulative Distribution Function Estimation for Both Symmetric and Asymmetric Data

Abbasi,

Shahzad,

Emam

et al. 2024

Symmetry

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The traditional stratification weight is widely used in survey sampling for estimation under stratified random sampling (StRS). A neutrosophic calibration approach is proposed under neutrosophic statistics for the first time with the aim of improving conventional stratification weight. This addresses the challenge of estimating the empirical cumulative distribution function (CDF) of a finite population using the neutrosophic technique. The neutrosophic technique extends traditional statistics, dealing with indeterminate, vague, and uncertain values. Thus, using additional information, we are able to obtain an effective estimate of the neutrosophic CDF. The suggested estimator yields an interval range in which the population empirical CDF is likely to exist rather than a single numerical value. The proposed family of neutrosophic estimators will be defined under suitable calibration constraints. A simulation study is also computed in order to assess the effectiveness of the suggested and adapted neutrosophic estimators using real-life symmetric and asymmetric datasets.

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Robust calibration for estimating the population mean using stratified random sampling

Cited by 7 publications

References 30 publications

Influence of Gamification on the Commitment of the Students of a Programming Course: A Case Study

Influence of Gamification on the Commitment of the Students of a Programming Course: A Case Study

Calibrated EWMA estimators for time-scaled surveys with diverse applications

Calibrated Empirical Neutrosophic Cumulative Distribution Function Estimation for Both Symmetric and Asymmetric Data

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