Displaying all 2 publications

Abstract:
Sort:
  1. Roslan MHB, Chen CJ
    Educ Inf Technol (Dordr), 2023;28(2):1427-1453.
    PMID: 35919875 DOI: 10.1007/s10639-022-11259-2
    This study attempts to predict secondary school students' performance in English and Mathematics subjects using data mining (DM) techniques. It aims to provide insights into predictors of students' performance in English and Mathematics, characteristics of students with different levels of performance, the most effective DM technique for students' performance prediction, and the relationship between these two subjects. The study employed the archival data of students who were 16 years old in 2019 and sat for the Malaysian Certificate of Examination (MCE) in 2021. The learning of English and Mathematics is a concern in many countries. Three main factors, namely students' past academic performance, demographics, and psychological attributes were scrutinized to identify their impact on the prediction. This study utilized the Orange software for the DM process. It employed Decision Tree (DT) rules to determine the characteristics of students with low, moderate, and high performance in English and Mathematics subjects. DT and Naïve Bayes (NB) techniques show the best predictive performance for English and Mathematics subjects, respectively. Such characteristics and predictions may cue appropriate interventions to improve students' performance in these subjects. This study revealed students' past academic performance as the most critical predictor, as well as a few demographics and psychological attributes. By examining top predictors derived using four different classifier types, this study found that students' past Mathematics performance predicts their MCE English performance and students' past English performance predicts their MCE Mathematics performance. This finding shows students' performances in both subjects are interrelated.
  2. Ananda R, Roslan MHB, Wong LL, Botross NP, Ngim CF, Mariapun J
    Cerebrovasc Dis, 2023;52(3):239-250.
    PMID: 36167034 DOI: 10.1159/000526470
    INTRODUCTION: Recent randomized controlled trials (RCTs) have assessed the role of vagus nerve stimulation (VNS) when paired with standard rehabilitation in stroke patients. This review aimed to evaluate the efficacy and safety of VNS as a novel treatment option for post-stroke recovery.

    METHODS: We searched PubMed, EMBASE, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials (CENTRAL), and CINAHL Plus for articles published from their date of inception to June 2021. RCTs investigating the efficacy or safety of VNS on post-stroke recovery were included. The outcomes were upper limb sensorimotor function, health-related quality of life, level of independence, cardiovascular effects, and adverse events. The risk of bias was assessed using the Cochrane risk-of-bias tool, while the certainty of the evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria. Review Manager 5.4 was used to conduct the meta-analysis.

    RESULTS: Seven RCTs (n = 236 subjects) met the eligibility criteria. Upper limb sensorimotor function, assessed by the Fugl-Meyer Assessment for Upper Extremity (FMA-UE), improved at day 1 (n = 4 RCTs; standardized mean difference [SMD] 1.01; 95% confidence interval [CI]: 0.35-1.66) and day 90 post-intervention (n = 3 RCTs; SMD 0.64; 95% CI: 0.31-0.98; moderate certainty of evidence) but not at day 30 follow-up (n = 2 RCTs; SMD 1.54; 95% CI: -0.39 to 3.46). Clinically significant upper limb sensorimotor function recovery, as defined by ≥6 points increase in FMA-UE, was significantly higher at day 1 (n = 2 RCTs; risk ratio [RR] 2.01; 95% CI: 1.02-3.94) and day 90 post-intervention (n = 2 RCTs; RR 2.14; 95% CI: 1.32-3.45; moderate certainty of the evidence). The between-group effect sizes for upper limb sensorimotor function recovery was medium to large (Hedges' g 0.535-2.659). While the level of independence improved with VNS, its impact on health-related quality of life remains unclear as this was only studied in two trials with mixed results. Generally, adverse events reported were mild and self-limiting.

    CONCLUSION: VNS may be an effective and safe adjunct to standard rehabilitation for post-stroke recovery; however, its clinical significance and long-term efficacy and safety remain unclear.

Related Terms
Filters
Contact Us

Please provide feedback to Administrator ([email protected])

External Links