Exploratory Longitudinal Profile Analysis via Multidimensional Scaling

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Examining the context of better science literacy outcomes among U.S. schools using visual analytics: A machine learning approach

The primary purpose of this study was to use visual analytics to examine the context in which U.S. schools can excel concerning science literacy. The school context was assessed using 49 various student-, teacher-, and principal-reported variables related to school resources, characteristics of the teaching force, and student dispositions regarding science learning at a school level. Using multidimensional scaling preference analysis as a visual analytical method of data mining, we examined the data of 238 U.S. schools collected from the Program for International Student Assessment in 2015. The visual analytic results suggested that the context in which schools can achieve better science literacy includes high- quality science teachers and favorable student dispositions toward science learning. The analysis of variance further supported the results. The results were discussed concerning the implications for school leaders for setting program priorities

Examining item content validity using property fitting analysis via multidimensional scaling

Objectives: Multiple-item measuring instruments are frequently used in a wide range of disciplines for the purpose of research in substantive areas. The quality of items in these instruments determine to a large extent whether the results are trustworthy. In this paper, we suggested to use property fitting analysis to evaluate the appropriateness of items content validity based on explicit item property criteria. Methods: Using Center for Epidemiologic Studies Depression scale as an example, item property fitting analyses via multidimensional scaling model was used to quantitatively evaluate the properties of items based on rating data from 12 counselors. Results: The results of the analyses indicated that using explicit item property criteria to select items for subsequent psychometric analyses improved the item quality in terms of reliability and factor structure. Conclusions: Item property fitting analysis seemed to provide the researcher a viable quantitative method when evaluating item content validity

Using Regression Mixture Analysis in Educational Research

Conventional regression analysis is typically used in educational research. Usually such an analysis implicitly assumes that a common set of regression parameter estimates captures the population characteristics represented in the sample. In some situations, however, this implicit assumption may not be realistic, and the sample may contain several subpopulations such as high math achievers and low math achievers. In these cases, conventional regression models may provide biased estimates since the parameter estimates are constrained to be the same across subpopulations. This paper advocates the applications of regression mixture models, also known as latent class regression analysis, in educational research. Regression mixture analysis is more flexible than conventional regression analysis in that latent classes in the data can be identified and regression parameter estimates can vary within each latent class. An illustration of regression mixture analysis is provided based on a dataset of authentic data. The strengths and limitations of the regression mixture models are discussed in the context of educational research. Accessed 40,971 times on https://pareonline.net from November 28, 2006 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Profile analysis: multidimensional scaling approach

Accessed 55,882 times on https://pareonline.net from April 27, 2001 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Using MDS preference plot as visual analytics of data: A machine learning approach

The primary purpose of this paper is to advocate the use of multidimensional scaling (MDS) preference plot to study relationships among variables and individual differences in these variables. MDS preference plot is not a new visual technique; nevertheless, its application to visualize individual differences in variables for high-dimensional data is rare, particularly in education and social sciences. We illustrated its application using a real example in an educational setting. The results indicate that the MDS preference plot is a viable visualization technique for data mining and analytics. Traditional statistical methods, such as the analysis of variance, can be used to further support the visual analysis results

How Emotional Intelligence Influences Students’ Life Satisfaction During University Lockdown: The Chain Mediating Effect of Interpersonal Competence and Anxiety

Students’ life satisfaction is an essential reflection of their well-being, particularly during challenging times. The COVID-19 pandemic, a global catastrophe, has had an immeasurably negative impact on individuals’ daily lives. It has also provided an opportunity to investigate the factors contributing to students’ life satisfaction during such difficult times. Considering the unique characteristics of these university students, the current study examines the impact of emotional intelligence (EI) on students’ life satisfaction, as well as the direct and sequential mediating effects of interpersonal competence and anxiety on this relationship. A total of 297 university students in Shanghai, China, participated in the study. All participants were recruited online during the early phase of the COVID-19 pandemic in 2022. Four well-established questionnaires were utilized to assess students’ trait emotional intelligence, interpersonal competence, anxiety, and life satisfaction. The findings indicate that interpersonal competence significantly mediates the relationship between EI and life satisfaction. Although anxiety does not significantly mediate this relationship, it plays a notable role in the sequential mediating effect involving interpersonal competence and anxiety. The study reveals that nurturing students’ EI can significantly enhance their interpersonal competence, which can reduce anxiety and ultimately increase their self-reported life satisfaction

A simple method for deriving functional MSCs and applied for osteogenesis in 3D scaffolds

We describe a simple method for bone engineering using biodegradable scaffolds with mesenchymal stem cells derived from human induced-pluripotent stem cells (hiPS-MSCs). The hiPS-MSCs expressed mesenchymal markers (CD90, CD73, and CD105), possessed multipotency characterized by tri-lineages differentiation: osteogenic, adipogenic, and chondrogenic, and lost pluripotency – as seen with the loss of markers OCT3/4 and TRA-1-81 – and tumorigenicity. However, these iPS-MSCs are still positive for marker NANOG. We further explored the osteogenic potential of the hiPS-MSCs in synthetic polymer polycaprolactone (PCL) scaffolds or PCL scaffolds functionalized with natural polymer hyaluronan and ceramic TCP (PHT) both in vitro and in vivo. Our results showed that these iPS-MSCs are functionally compatible with the two 3D scaffolds tested and formed typically calcified structure in the scaffolds. Overall, our results suggest the iPS-MSCs derived by this simple method retain fully osteogenic function and provide a new solution towards personalized orthopedic therapy in the future

Age Difference in Roles of Perceived Social Support and Psychological Capital on Mental Health During COVID-19

Due to the outbreak of the Coronavirus Disease-2019 (COVID-19) pandemic and consequent confinement measures, young people are vulnerable to mental health problems. The current study compared a group of 440 young adolescents (10–12 years) and a group of 330 emerging adults (18–25 years) to investigate the extent to which perceived social support and psychological capital (PsyCap) were differentially associated with mental health problems. Participants were asked to report their current psychosocial adaptation status during the COVID-19 pandemic, and data were collected via online questionnaires during a relatively severe period of COVID-19 in China. Results of the multi-group path analysis indicated that the effect of perceived social support on mental health problems was mediated by PsyCap for young adolescents, but not for emerging adults. These results were discussed with respect to the mechanism of how social support and PsyCap serve as protective mental health factors for youth in the context of the COVID-19 pandemic

The role of mindfulness and dysexecutive functioning in the association between depression and COVID-19-related stress: cross-sectional and longitudinal analyses

Background: Since the COVID-19 outbreak, the severity of college student\u27s mental health has increased, with depression being the most prominent. This study\u27s primary purpose was to explore (1) whether the perceived stress of COVID-19 was associated with depression through sequential mediation of mindfulness and dysexecutive function and also (2) the temporal association among mindfulness, dysexecutive function and depression. Methods: We performed two studies to evaluate dysexecutive function as a mechanism through which mindfulness impacts depression under the stress of the COVID-19 pandemic. Study 1 used a sequential mediation model to test the mediating role of mindfulness and dysexecutive function between the perceived stress of COVID-19 and depression based on 1,665 emerging adults. Study 2 used a random-effect, cross-lagged panel model (RE-CLPM) to test the directionality among mindfulness, dysexecutive function, and depression based on 370 emerging adults. Results: The cross-sectional study showed that perceived stress of COVID-19 was positively associated with depression through the sequential mediation of mindfulness and dysexecutive function (effect: 0.08, 95%CI = [0.07, 0.10]), also through the mediation of mindfulness (effect: 0.05, 95%CI = [0.03, 0.06]) and dysexecutive function (effect: 0.08, 95%CI = [0.06, 0.10]) separately. The RE-CLPM study indicated that dysexecutive function mediates the reciprocal relation between mindfulness and depression at the within-person level. Conclusion: These results suggest that dysexecutive function is an intermediate psychological mechanism that exacerbates depression under pandemic-related stress. Mindfulness can predict dysexecutive function and subsequently improve depression. As depression under pandemic-related stress can weaken the mindful state, long-term mindfulness practices are needed to maintain mental health during COVID-19