The current study employed latent profile analysis to examine the application patterns of students\' reading metacognitive strategies using PISA 2018 data in China. Subsequently, it explored the differences in students\' mathematics learning efficiency and performance. The results revealed that: (1) Six types of reading metacognitive strategies application patterns were identified: \"Novice - indifferent,\" \"Veteran - average,\" \"Novice - low evaluating,\" \"Veteran - skilled,\" \"Novice - mixed,\" and \"Novice - arbitrary.\" (2) The primary factors that affect the classification of reading metacognitive strategies application patterns were gender, and family economic, social, and cultural statuses (ESCS). (3) Mathematics learning time could positively predict performance overall, but the mathematics learning time of \"Veteran - skilled\" and \"Novice - mixed\" students had no significant correlation with their mathematics performance. The findings suggests that educators should not blindly increase students\' mathematics learning time but instead provide appropriate guidance based on their mastery patterns of reading metacognitive strategies to enhance mathematics learning efficiency and performance.

Diagnostic classification models (DCMs) have seen wide applications in educational and psychological measurement, especially in formative assessment. DCMs in the presence of testlets have been studied in recent literature. A key ingredient in the statistical modeling and analysis of testlet-based DCMs is the superposition of two latent structures, the attribute profile and the testlet effect. This paper extends the standard testlet DINA (T-DINA) model to accommodate the potential correlation between the two latent structures. Model identifiability is studied and a set of sufficient conditions are proposed. As a byproduct, the identifiability of the standard T-DINA is also established. The proposed model is applied to a dataset from the 2015 Programme for International Student Assessment. Comparisons are made with DINA and T-DINA, showing that there is substantial improvement in terms of the goodness of fit. Simulations are conducted to assess the performance of the new method under various settings.

Metal-free organic photocatalysts for photo-mediated reversible deactivation radical polymerization (photo-RDRP) are witnessed to make increasing advancement in the precise synthesis of polymers. However, challenges still exist in the development of high-efficiency and environmentally sustainable carbon dots (CDs)-based organocatalysts. Herein, N-doped CDs derived from phenanthroline derivative (Aphen) are prepared as metal-free photocatalysts for photoinduced electron transfer reversible addition-fragmentation chain transfer (PET-RAFT) polymerization. The introduction of phenanthroline structure enhances the excited state lifetime of CDs and expands the conjugated length of their internal structure to enable the light-absorption to reach green light region, thereby enhancing photocatalytic activity. The as-designed CDs exhibit unprecedented photocatalytic capacity in photopolymerization even in large-volume reaction (100 mL) with high monomer conversion and narrow polymer dispersity (Mw/Mn < 1.20) under green light. The photocatalytic system is compatible with PET-RAFT polymerization of numerous monomers and the production of high molecular weight polyacrylate (Mn >250 000) with exquisite spatiotemporal control. Above results confirm the potential of CDs as photocatalyst, which has not been achieved with other CDs catalysts used in photo-RDRP. In addition, the construction of fluorescent polymer nanoparticles using CDs as both photocatalyst and phosphor through photoinitiated polymerization-induced self-assembly (Photo-PISA) technology is successfully demonstrated for the first time.

Computer-based assessments provide the opportunity to collect a new source of behavioral data related to the problem-solving process, known as log file data. To understand the behavioral patterns that can be uncovered from these process data, many studies have employed clustering methods. In contrast to one-mode clustering algorithms, this study utilized biclustering methods, enabling simultaneous classification of test takers and features extracted from log files. By applying the biclustering algorithms to the \"Ticket\" task in the PISA 2012 CPS assessment, we evaluated the potential of biclustering algorithms in identifying and interpreting homogeneous biclusters from the process data. Compared with one-mode clustering algorithms, the biclustering methods could uncover clusters of individuals who are homogeneous on a subset of feature variables, holding promise for gaining fine-grained insights into students\' problem-solving behavior patterns. Empirical results revealed that specific subsets of features played a crucial role in identifying biclusters. Additionally, the study explored the utilization of biclustering on both the action sequence data and timing data, and the inclusion of time-based features enhanced the understanding of students\' action sequences and scores in the context of the analysis.

BACKGROUND: Socio-economic status is one of the most important factors shaping students\' motivation and achievement but has seldom been explored in relation to achievement goals.
OBJECTIVE: This study aimed to investigate whether mastery-approach goals explain the link between SES and key learning-related outcomes (mediation) and whether SES modifies the relationship between mastery-approach goals and these outcomes (moderation).
METHODS: Data came from 595,444 students nested in 21,322 schools across 77 countries.
METHODS: Data were analysed using multilevel-moderated mediation analyses.
RESULTS: We found significant mediation and moderation. In terms of mediation, mastery-approach goals mediated the association between family SES and learning-related outcomes. However, a different pattern emerged for school SES, as students in higher SES schools had lower mastery-approach goals. In terms of moderation, we found that family SES strengthened the association between mastery-approach goals and learning-related outcomes. However, the association between mastery-approach goals and learning-related outcomes was weaker in higher SES schools.
CONCLUSIONS: Theoretical and practical implications for the achievement goal approach to achievement motivation are discussed.

Poly(glycerol monomethacrylate)-block-poly(2-hydroxypropyl methacrylate) (PGMA-PHPMA) with worm-like morphology is a typical example of reversible addition-fragmentation chain transfer (RAFT) dispersion polymerized thermo-responsive copolymer via polymerization-induced self-assembly (PISA) in aqueous solution. Chain transfer agents (CTAs) are the key component in controlling RAFT, the structures of which determine the end functional groups of the polymer chain. It is therefore of interest to monofunctionalize the polymers via CTA moiety, for bioactive functionality conjugation and in the meantime maintain the precisely controlled morphology of the copolymers and the related property. In this work, a newly designed CTA 5-(2-(tert-butoxycarbonylamino) ethylamino)-2-cyano-5-oxopentan-2-yl benzodithioate (t-Boc CPDB) was synthesized and used for the RAFT polymerization of PGMA45-PHPMA120. Subsequently, PGMA45-PHPMA120 copolymers with primary amine, maleimide, and reduced L-glutathione (a tripeptide) monofunctionalized terminals were synthesized via deprotection and conjugation reactions. These monofunctionalized copolymers maintain worm-like morphology and thermo-responsive property in aqueous solution (10% w/v), as confirmed by the transmission electron microscopy (TEM) images, and the observation of the phase transition behavior in between 4 °C and room temperature (~20 °C), respectively. Summarily, a range of thermo-responsive monofunctionalized PGMA45-PHPMA120 diblock copolymer worms were successfully synthesized, which are expected to offer potential biomedical applications, such as in polymer therapeutics, drug delivery, and diagnostics.

Polymerization-induced self-assembly (PISA) combines polymerization and in situ self-assembly of block copolymers in one system and has become a widely used method to prepare block copolymer nanoparticles at high concentrations. The persistence of polymers in the environment poses a huge threat to the ecosystem and represents a significant waste of resources. There is an urgent need to develop novel chemical approaches to synthesize degradable polymers. To meet with this demand, it is crucial to install degradability into PISA nanoparticles. Most recently, degradable PISA nanoparticles have been synthesized by introducing degradation mechanisms into either shell-forming or core-forming blocks. This Minireview summarizes the development in degradable block copolymer nanoparticles synthesized by PISA, including shell-degradable, core-degradable, and all-degradable nanoparticles. Future development will benefit from expansion of polymerization techniques with new degradation mechanisms and adaptation of high-throughput approaches for both PISA syntheses and degradation studies.

Responsive photonic crystals (RPCs) assembled by monodisperse colloidal particles have attracted enormous interest recently due to their tremendous applications in smart devices. Their structural colors can be determined by particle sizes. However, the lack of a reliable way to tune the sizes in situ limits their development. Herein, we present an efficient route to solve this problem through the fabrication of spherical polymeric particles with light-triggered reversible swelling behavior via surfactant-free reversible addition-fragmentation chain transfer (RAFT) emulsion polymerization-induced self-assembly (PISA). Amphiphilic macro-RAFT agents containing azobenzene groups were synthesized and subsequently employed to mediate the polymerization of methyl methacrylate. Uniform submicron spheres were obtained by modulating solid contents and other parameters. Benefiting from the photoisomerization of azobenzene moieties, the particle sizes expanded and contracted upon alternative ultraviolet/visible-light irradiation accordingly. This strategy will be a supplement to the emulsion PISA and especially give aid to the progress of the RPC materials.

Due to the challenging nature of teaching and learning in the 21st century, educators must assume additional roles in schools to meet the expectations of students, parents, and communities. Studies in general have focused on all teachers as a group. The PISA 2015 assessment and analysis framework indicates that the focus of the current round of assessment is on science literacy. Therefore, science teacher professional collaboration, teaching self-efficacy, and teacher job satisfaction were also the focus of its measurement. In this study, 1039 science teachers from Hong Kong participated. Through literature review analysis, this study concluded that (a) teacher professional collaboration and teaching self-efficacy have a positive effect on job satisfaction; (b) teacher professional collaboration has a positive effect on teaching self-efficacy, and (c) teaching self-efficacy has a mediating role in teacher professional collaboration and teacher job satisfaction. A mediation model was developed to test this hypothesis. Data were analyzed using structural equation modeling (SEM). The results of the study confirmed our hypothesis. In addition, we examined the applicability of the model using multi-group SEM mode, and the results demonstrated that the effect of professional collaboration on job satisfaction among science teachers in Hong Kong, China did not differ by gender.

Five undescribed dihydroflavonoid glycoside derivatives, namely albvisosides A‒E, together with two known compounds were isolated from the roots and stem leaves of Viscum album L. var. album. (European mistletoe). Their structures were determined by HRESIMS, 1D and 2D NMR, and ECD analysis. Albvisoside B exhibits significant inhibitory effect on hepatic lipid accumulation in HepG2 cells at very low concentrations (EC50: 0.7 nM). Using proteome integral solubility alteration assay, the direct targets or downstream effectors of albvisoside B were elucidated. As a result, 97 proteins were identified based on ligand-induced alterations in the protein thermal stability. Bioinformatics analysis indicated that albvisoside B primarily ameliorated oleic acid-induced lipid accumulation by regulating the selenoamino acids metabolism signaling pathway. RPL3, ADAM17, and RPL14 were likely to be involved in mediating the lipid-lowering effect of albvisoside B.