Search

This study attempts to: (a) investigate whether positive and negative emotions mediate the pathways linking self-efficacy for learning programming with effort and persistence in undergraduates' learning Scratch programming combining with a programmable hardware platform (i.e., Arduino), and (b) assess the effect of academic major (i.e., information technology-related majors vs non-information technology-related majors) on self-efficacy for learning programming and emotions. With the use of responses collected from a sample of 156 undergraduate students, the research model is empirically validated using partial least squares structural equation modeling (PLS-SEM). The findings reveal that undergraduates' effort and persistence while learning programming were significantly predicted by positive emotions, but not by negative emotions. Self-efficacy for learning programming significantly and positively influenced positive emotions and negatively influenced negative emotions. Finally, variations in predicting positive emotions were found between different academic majors: students in information technology-related majors experienced less negative emotional experiences than those in non-information technology-related majors.

The study investigated the relationships among quality dimensions, three types of interactions (i.e. learner-content, learner-instructor, and learner-learner interaction), perceived learning and learning satisfaction with flipped courses in the context of the flipped classroom based on the information system (IS) success model. In this study, the quality dimensions in the original IS success model were replaced by flipped learning platform quality, instructional video content quality, and teaching quality (i.e. instructor monitoring and instructor facilitation). The data from 70 participants were analyzed using partial least squares structural equation modeling. The results indicate that all the quality dimensions have the influences on both learning satisfaction with flipped courses and perceived learning through the mediation of learner-content interaction or learner-instructor interaction. Moreover, learner-learner interaction significantly influences perceived learning, but not learning satisfaction with flipped courses. Finally, a positive and direct link between perceived learning and learning satisfaction with flipped courses was found.

The necessity of socially assistive AI robots that can assist the elderly in their daily lives to mitigate the burden of family caregivers in aged-care settings continues to increase. However, there is a lack of empirical research on the drivers of family caregivers' behavioral intention to use these types of robots within their own home environment. This study investigates how family caregivers' intention to adopt socially assistive AI robots for their elderly family members can be predicted based on utilitarian and hedonic attitudes, product smartness dimensions, and conscientiousness with demographic characteristics as control variables. The partial least squares structural equation modeling (PLS-SEM) method was used to process data collected from 399 respondents. The results show that utilitarian and hedonic attitudes positively affect family caregivers' intention to adopt socially assistive AI robots. Moreover, utilitarian attitudes are influenced by ability to cooperate, personality, and conscientiousness, while hedonic attitudes are influenced by autonomy, ability to cooperate, humanlike interaction, and personality. Important implications for developing family caregivers' adopting intention toward socially assistive AI robots are presented based on the findings. [ABSTRACT FROM AUTHOR]

Background: Anti-calcitonin gene-related peptide (CGRP) monoclonal antibodies have emerged as promising therapeutic options for the treatment of chronic migraine. However, treatment response varies considerably among individuals, suggesting a potential role for genetic factors. This study aimed to identify genetic variants affecting the efficacy of anti-CGRP monoclonal antibody therapy in chronic migraine among the Han Chinese population in Taiwan to enhance treatment precision and to understand the genetic architecture of migraine. Methods: We conducted a quantitative trait locus (QTL) association study in patients with chronic migraines from a tertiary medical center in Taiwan using the Taiwan Precision Medicine Array Chip. The patients received fremanezumab or galcanezumab for at least 12 weeks. Treatment efficacy was assessed based on the improvement rate in monthly migraine days. Genetic variants were identified, and their associations with treatment efficacy were examined through quantitative trait loci analysis, linkage disequilibrium studies, and functional annotations using the Gene Ontology database. Results: Six single nucleotide polymorphisms (SNPs) relative variants were significantly associated with anti-CGRP therapy response (p < 1 × 10− 7): rs116870564, rs75244870, rs56216870, rs12938101, rs74655790, and rs149540851. These variants are located in or near genes, including LRRC4C, ATAD2B, and OXR1, which are involved in neuronal development, DNA-dependent ATPase activity, and oxidation-reduction processes, respectively. The rs116870564 variant in LRRC4C showed the strongest association (β = -0.551, p = 6.65 × 10− 9). The functional impact of these variants is attributed to their regulatory effects on gene expression, which are influenced by intron splicing regulation, transcription factors, and changes in chromatin structure. Conclusion: The identification of key genetic markers associated with response to anti-CGRP therapy emphasizes the importance of genetic variability in treatment efficacy. This could lead to more personalized chronic migraine management strategies and tailored therapeutic approaches based on individual genetic profiles. Further research in larger, diverse populations is warranted to validate these findings and refine our understanding of the role of CGRP in chronic migraine pathophysiology. Trial registration: Not applicable. [ABSTRACT FROM AUTHOR]

The present study investigates the effects that Facebook-based online peer assessment with micro-teaching videos can have on attitudes toward peer assessment and perceived learning from peer assessment. The study recruited a sample of 31 university students who were enrolled in a teacher-training course. Using assessees' microteaching videos, the experimental group performed two rounds of online peer assessments targeting teacher performance; by comparison, the control group performed two identical rounds of peer assessment, but without the assessees' microteaching videos. The results show that the two groups experienced significantly positive changes in attitudes toward peer assessment over time. Moreover, the experimental group's perceived learning about teaching competency was lower than the control group's after completing the first-round peer assessment, but significantly increased over time. Finally, the open-ended responses show that participants regarded Facebook as a convenient tool for performing peer assessments, but voiced their concerns about Facebook's open and non-anonymous features.