Measuring User Engagement in Mobile Classroom Response System: A Case Study

Mobile classroom response system, formerly known as clicker, is a promising technology to engage students in a lecture hall. Previous studies reported the positive effects of clickers on student engagement. However, most studies focused on patterns of cohort transitions using clickers during peer-instruction activities. This paper describes a mixed method approach to explore the dynamic of user engagement among undergraduate students in a local Malaysian university. Both interaction log and diary study were selected to track the pattern of ninety five registered students using mobile classroom response system across seven lecture weeks. Interaction logs were used to profile user type, participation type and submission type. The analysis of interaction logs revealed that seven visitors participated during lecture, only around 18% of registered students participated actively, registered students were more likely to answer all questions at the end of lecture compared to the beginning of lecture and middle of lecture. On the other hand, the analysis of diary entries provided qualitative information about user engagement attributes such focused attention, felt involvement, endurability, perceived usability and novelty. Both interaction log and students diary indicated that two registered students had positive engagement using mobile classroom response system during lecture

Replication and Meta-analysis of the Association between BDNF Val66Met Polymorphism and Cognitive Impairment in Patients Receiving Chemotherapy.

Cancer-related cognitive impairment (CRCI) adversely affects cancer patients. We had previously demonstrated that the BDNF Val66Met genetic polymorphism is associated with lower odds of subjective CRCI in the multitasking and verbal ability domains among breast cancer patients receiving chemotherapy. To further assess our previous findings, we evaluated the association of BDNF Val66Met polymorphism with subjective and objective CRCI in a temporally separate cohort of patients and pooled findings from both the original (n = 145) and current (n = 193) cohorts in a meta-analysis. Subjective CRCI was assessed using FACT-Cog. Objective CRCI was evaluated using computerized neuropsychological tests. Genotyping was carried out using Sanger sequencing. The association of BDNF Val66Met genotypes and CRCI was examined with logistic regression. A fixed-effect meta-analysis was conducted using the inverse variance method. In the meta-analysis (n = 338), significantly lower odds of CRCI were associated with Met allele carriers based on the global FACT-Cog score (OR = 0.52, 95% CI 0.29-0.94). Furthermore, Met allele carriers were at lower odds of developing impairment in the domains of memory (OR = 0.34, 95% CI: 0.17-0.70), multitasking (OR = 0.33, 95% CI: 0.18-0.59), and verbal ability (OR = 0.46, 95% CI: 0.24-0.88). Consistent with the previous study, lower odds of subjective CRCI among patients with the BDNF Met allele was observed after adjusting for potential confounders in the multitasking (OR = 0.30, 95% CI: 0.14-0.67) domain. In conclusion, carriers of the BDNF Met allele were protected against global subjective CRCI, particularly in the domains of memory, multitasking, and verbal ability. Our findings further contribute to the understanding of CRCI pathophysiology

Replication and Meta-Analysis of GWAS Identified Susceptibility Loci in Kawasaki Disease Confirm the Importance of B Lymphoid Tyrosine Kinase (BLK) in Disease Susceptibility

10.1371/journal.pone.0072037PLoS ONE88-POLN

A study assessing the association of glycated hemoglobin a1C (HbA1C) associated variants with HbA1C, chronic kidney disease and diabetic retinopathy in populations of asian ancestry

10.1371/journal.pone.0079767PLoS ONE811-POLN

A statistical method for region-based meta-analysis of genome-wide association studies in genetically diverse populations

Genome-wide association studies (GWAS) have become the preferred experimental design in exploring the genetic etiology of complex human traits and diseases. Standard SNP-based meta-analytic approaches have been utilized to integrate the results from multiple experiments. This fundamentally assumes that the patterns of linkage disequilibrium (LD) between the underlying causal variants and the directly genotyped SNPs are similar across the populations for the same SNPs to emerge with surrogate evidence of disease association. We introduce a novel strategy for assessing regional evidence of phenotypic association that explicitly incorporates the extent of LD in the region. This provides a natural framework for combining evidence from multi-ethnic studies of both dichotomous and quantitative traits that (i) accommodates different patterns of LD, (ii) integrates different genotyping platforms and (iii) allows for the presence of allelic heterogeneity between the populations. Our method can also be generalized to perform gene-based or pathway-based analyses. Applying this method on real GWAS data in type 2 diabetes (T2D) boosted the association evidence in regions well-established for T2D etiology in three diverse South-East Asian populations, as well as identified two novel gene regions and a biologically convincing pathway that are subsequently validated with data from the Wellcome Trust Case Control Consortium

Genome-Wide Meta-Analysis of Five Asian Cohorts Identifies PDGFRA as a Susceptibility Locus for Corneal Astigmatism

Corneal astigmatism refers to refractive abnormalities and irregularities in the curvature of the cornea, and this interferes with light being accurately focused at a single point in the eye. This ametropic condition is highly prevalent, influences visual acuity, and is a highly heritable trait. There is currently a paucity of research in the genetic etiology of corneal astigmatism. Here we report the results from five genome-wide association studies of corneal astigmatism across three Asian populations, with an initial discovery set of 4,254 Chinese and Malay individuals consisting of 2,249 cases and 2,005 controls. Replication was obtained from three surveys comprising of 2,139 Indians, an additional 929 Chinese children, and an independent 397 Chinese family trios. Variants in PDGFRA on chromosome 4q12 (lead SNP: rs7677751, allelic odds ratio = 1.26 (95% CI: 1.16–1.36), Pmeta = 7.87×10−9) were identified to be significantly associated with corneal astigmatism, exhibiting consistent effect sizes across all five cohorts. This highlights the potential role of variants in PDGFRA in the genetic etiology of corneal astigmatism across diverse Asian populations

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes

Prediction of interest rate using CKLS model with stochastic parameters

The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ(j) of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ(j), we assume that φ(j) depends on φ(j−m), φ(j−m+1),…, φ(j−1) and the interest rate r j+n at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1] -dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r j+n+1 of the interest rate at the next time point when the value r j+n of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r j+n+d at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters

Learning Effectiveness and Efficiency in Tertiary Mathematics Education under Core-and-Spoke Model

In Malaysia, traditional teaching approach is still the most common approach used in the tertiary mathematics education. Under the traditional teaching approach, students learn mathematics through rote-learning and being “spoon-fed”. Traditional teaching approach may lead to students have loss of interest in learning mathematics and consequently, students seriously do not reach in-depth understanding of mathematics. This shows that students do not learn mathematics effectively and efficiently. The motivation of this research is to find out student’s learning effectiveness and efficiency in learning the tertiary mathematics course under a designed blended learning approach that incorporates the core-and-spoke model. A preliminary statistical analysis is conducted at early stage to give a better understanding on the collected data. The analysis of student’s learning effectiveness is carried out based on the student’s learning outcome achievement and learning satisfaction. Technical efficiency in data envelopment analysis (DEA) is employed to evaluate the student’s learning efficiency. The results show that the students not only have more interest in learning the tertiary mathematics, but also they are able to learn in a more effective and efficient way under the designed blended learning approach

The value-at-risk evaluation of Brent’s crude oil market

This study investigates the market risk of the Brent’s crude oil market. First the long memory time-varying volatility is modelled under the Chung’s specification. Second, for model adequacy evaluations on the heavy-tailed, long memory and endogenously estimated power transformation models indicated superior performance in out-of-sample forecasts. Lastly, these findings are further applied in the long and short trading positions of market risk evaluations of the Brent’s market