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  1. Lin XF, Wong SY, Zhou W, Shen W, Li W, Tsai CC
    Int J Sci Math Educ, 2023 May 04.
    PMID: 37363784 DOI: 10.1007/s10763-023-10376-9
    Research evidence indicated that a specific type of augmented reality-assisted (AR-assisted) science learning design or support might not suit or be effective for all students because students' cognitive load might differ according to their experiences and individual characteristics. Thus, this study aimed to identify undergraduate students' profiles of cognitive load in AR-assisted science learning and to examine the role of their distinct profiles in self-efficacy together with associated behavior patterns in science learning. After ensuring the validity and reliability of each measure, a latent profile analysis confirmed that 365 Chinese undergraduates carried diverse dimensions of cognitive load simultaneously. The latent profile analysis findings revealed four fundamental profiles: Low Engagement, Immersive, Dabbling, and Organized, characterized as carrying various respective cognitive loads. The multivariate analysis of variance findings revealed different levels of the six AR science learning self-efficacy dimensions across profiles. Low Engagement students displayed the lowest self-efficacy among all dimensions. Organized students recorded better conceptual understanding and higher-order cognitive skills than Dabbling ones. Students with the Immersive profile had the highest science learning self-efficacy. The lag sequential analysis results showed significant differences in behavior patterns among profiles. Among them, profiles with social interaction, test, and reviewing feedback behavior had a significantly higher score for self-efficacy than those patterns mainly based on test learning and resource visits. This finding provides a unified consideration of students' diverse profiles and can inform interventions for effective design of AR-assisted science learning to match appropriate strategies to facilitate the science learning effect.
  2. Chen CJ, Michaelis M, Hsu HK, Tsai CC, Yang KD, Wu YC, et al.
    J Ethnopharmacol, 2008 Oct 30;120(1):108-11.
    PMID: 18762235 DOI: 10.1016/j.jep.2008.07.048
    Severe acute respiratory syndrome (SARS) is a life-threatening disease caused by the SARS coronavirus (SARS-CoV). The development of new antiviral agents for SARS-CoV is an important issue. We tried to find potential resource from Traditional Chinese medicine (TCM) for development of new drugs against SARS-CoV.
  3. Chen FS, Chen CC, Tsai CC, Lu JH, You HL, Chen CM, et al.
    Front Endocrinol (Lausanne), 2023;14:1173449.
    PMID: 37334296 DOI: 10.3389/fendo.2023.1173449
    BACKGROUND: Organophosphate flame retardants (OPFRs) are widely distributed in the environment and their metabolites are observed in urine, but little is known regarding OPFRs in a broad-spectrum young population from newborns to those aged 18 years.

    OBJECTIVES: Investigate urinary levels of OPFRs and OPFR metabolites in Taiwanese infants, young children, schoolchildren, and adolescents within the general population.

    METHODS: Different age groups of subjects (n=136) were recruited from southern Taiwan to detect 10 OPFR metabolites in urine samples. Associations between urinary OPFRs and their corresponding metabolites and potential health status were also examined.

    RESULTS: The mean level of urinary Σ10 OPFR in this broad-spectrum young population is 2.25 μg/L (standard deviation (SD) of 1.91 μg/L). Σ10 OPFR metabolites in urine are 3.25 ± 2.84, 3.06 ± 2.21, 1.75 ± 1.10, and 2.32 ± 2.29 μg/L in the age groups comprising of newborns, 1-5 year-olds, 6-10 year-olds, and 11-18 year-olds, respectively, and borderline significant differences were found in the different age groups (p=0.125). The OPFR metabolites of TCEP, BCEP, DPHP, TBEP, DBEP, and BDCPP predominate in urine and comprise more than 90% of the total. TBEP was highly correlated with DBEP in this population (r=0.845, p<0.001). The estimated daily intake (EDI) of Σ5OPFRs (TDCPP, TCEP, TBEP, TNBP, and TPHP) was 2,230, 461, 130, and 184 ng/kg bw/day for newborns, 1-5 yr children, 6-10 yr children, and 11-17 yr adolescents, respectively. The EDI of Σ5OPFRs for newborns was 4.83-17.2 times higher than the other age groups. Urinary OPFR metabolites are significantly correlated with birth length and chest circumference in newborns.

    CONCLUSION: To our knowledge, this is the first investigation of urinary OPFR metabolite levels in a broad-spectrum young population. There tended to be higher exposure rates in both newborns and pre-schoolers, though little is known about their exposure levels or factors leading to exposure in the young population. Further studies should clarify the exposure levels and factor relationships.

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