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Formative assessment has been long emphasised as a powerful means for enhancing science learning. However, there is still a lack of research to investigate the impacts of formative assessment on both students' motivational beliefs and behaviours in science learning. This study examined such impacts using data from six Western and six East Asian countries/economies in PISA 2015. 96,491 15-year-old students were included. The SEM analysis of overall data showed that (i) formative assessment had both direct effects on students' science learning behaviours and indirect impacts mediated by students' motivational beliefs and (ii) the total effect of teacher feedback on science learning behaviours was greater than adaptive instruction. The comparison between Western and East Asian datasets indicated that (i) the impact of teacher feedback on East Asian students' motivational beliefs was greater than that on their Western counterparts; (ii) the impact of adaptive instruction on Western students' motivational beliefs was greater than that on East Asian counterparts; and (iii) the direct impacts of teacher feedback and adaptive instruction on science learning behaviours were similar for both groups of students. Suggestions were made on how to effectively implement formative assessment to enhance science learning in different cultural contexts.

Even though the importance of technical and vocational education is acknowledged in the Sustainable Development Goals (SDGs) adopted by the United Nations in 2015, the university sector has dominated the discourse on the role of postsecondary educational institutions in sustainability. This comparative study widens the scope by highlighting contributions that community colleges (CCs) and technical and vocational education and training institutions (TVETs) are making to sustainability in several developed and fast-developing countries. It examines five independent case studies -- conducted in Canada, Chile, China, Taiwan, and the United States -- and demonstrates that CCs and TVETs are uniquely positioned to make substantial contributions and should be an important part of the sustainability discussion. It also explores special features that allow these institutions to play a vital role in addressing the SDGs. The findings show that the SDGs related to economic development and social justice were a priority in all five case studies, while the environmental SDGs were foremost in the two North American studies. The main barriers to sustainable development include the high cost of education, low completion rates, graduates' inability to secure employment commensurate with their education, inadequate funding and the reputation of CCs and TVETs as second-tier institutions.

Sedimentary deposits from the northern South China Sea (SCS) can provide important constraints on past changes in ocean currents and the East Asian summer monsoon (EASM) in this region. However, the interpretation of such records spanning the last deglaciation is complicated because sea‐level change may also have influenced the depositional processes and patterns. Here, we present new records of grain size, clay mineralogy, and magnetic mineralogy spanning the past 24 kyr from both shallow and deep‐water sediment cores in the northern SCS. Our multi‐proxy comparison among multiple cores helps constrain the influence of sea‐level change, providing confidence in interpreting the regional climate‐forced signals. After accounting for the influence of sea‐level change, we find that these multi‐proxy records reflect a combination of changes in (a) the strength of the North Pacific Intermediate Water inflow, (b) the EASM strength, and (c) the Kuroshio Current extent. Overall, this study provides new insights into the roles of varying terrestrial weathering and oceanographic processes in controlling the depositional record on the northern SCS margin in response to climate and sea‐level fluctuations. Plain Language Summary: Sediments in the South China Sea (SCS) provide important records of past changes in the ocean circulation and atmospheric patterns in the Pacific Ocean. However, the interpretation of sedimentary archives from this region in terms of changes in the ocean currents or the climate‐driven sediment supply can be challenging because of the potential influence of global sea‐level fluctuations. In order to better constrain these multiple controls on the sedimentary regime of the northern SCS, we present new mineralogical records from sediment cores collected from both shallow‐ and deep‐water sites. After assessing the effects of sea‐level change, we find that the clay mineral assemblage in shallow sites from the northern SCS can generally be used to reconstruct the evolution of the East Asian summer monsoon. In deep‐water sites, the clay mineralogy instead reflects changes in the relative abundance of sediment supplied from Taiwan compared to Luzon, revealing an enhanced inflow of the Kuroshio Current during the mid‐late Holocene. Furthermore, millennial‐scale variability in the North Pacific Intermediate Water inflow can be traced using changes in magnetic mineralogy and the inflow appears to have been stronger at the end of the last ice age. Key Points: Sedimentary records from shallow and deep‐water sites have differing sensitivities to changes in ocean currents and the East Asian monsoonClay mineralogy in shallow sites reflects sea‐level change, while deep‐water records respond to incursion of the Kuroshio CurrentMagnetic grain‐size indicates stronger deep currents during Heinrich Stadial 1, associated with the North Pacific Intermediate Water [ABSTRACT FROM AUTHOR]

Data of 239+240Pu activities and 240Pu/239Pu atom ratios in surface and core sediments of the China Sea and adjacent waters were collected. We examine a dataset of 239+240Pu activities and 240Pu/239Pu ratios determined from surface sediments at 516 sites and 84 core sediment mainly across the China Sea and adjacent waters. For the first time the spatial distributions of the 239+240Pu activities, the 240Pu/239Pu ratios and the Pacific Proving Ground (PPG) fraction in the China Sea and adjacent waters are fully presented at the same time. Four types of typical 239+240Pu distribution with depth are commonly summarized: non-peak, pseudo single peak, single peak and multi peaks, which are based on the comprehensive analysis of the vertical distribution of 239+240Pu in 84 sediment cores that had been studied in the China Sea and adjacent waters. Their occurrence probability are ∼15%, ∼4%, ∼67% and ∼11%, respectively. This is the dominant Pu source in seawater which was transported by the North Equatorial Current and Kuroshio Current and its extension into the China Sea and adjacent waters first from east to west, then from south to north. A sea area to the northeast of Taiwan Island and the Okinawa Trough, shows high 239+240Pu activities and 240Pu/239Pu atom ratios spatial distribution trends, which are related to the intrusion of the Kuroshio Current carrying 239+240Pu from the PPG nuclear weapon tests. The used two end-member mixing model suggests that global fallout and PPG close-in fallout are the main sources of Pu in most of the investigate areas. As the 240Pu/239Pu of global fallout is relatively constant, the change of 240Pu/239Pu ratios in surface sediments of the China Sea and adjacent waters are mainly controlled by the PPG close-in fallout input. • 239+240Pu and 240Pu/239Pu database for surface and core sediments of the China Sea and adjacent waters. • Spatial and vertical distributions of 239+240Pu and 240Pu/239Pu in the China Sea and adjacent waters are fully presented. • The new correlation between 239+240Pu and 240Pu/239Pu in surface sediments was established in China Sea. • Four types of typical 239+240Pu vertical distribution with depth and three possible forming mechanisms are found in the China Sea and adjacent waters. • The change of 240Pu/239Pu in the China Sea was mainly controlled by the Pacific Proving Ground input. [ABSTRACT FROM AUTHOR]

Credit scoring is playing an increasingly critical role with the rising number of lending operations for micro and small enterprises as well as individuals. A large number of research is primarily based on the combination and construction methods of credit scoring models by the experts. However, different credit data have distinct requirements for the models, and how to automatically search and construct credit scoring models according to credit data has become essential, that is the main concern of this paper. In response to the current challenges for credit scoring research, we proposed an Automatic Credit Scoring Strategy (ACSS), designed a credit assessment platform which includes data import, classification model automatic search, feature selection, hyperparameter optimization, data mining, classification output and other modules. Aiming at the problem of substantial imbalance in credit data, we propose an improved SMOTE algorithm that is capable of generating supplementary data for the lack of minority in credit data, thereby making the credit data distribution well balanced. As for classification model selection, features engineering, parameter optimization and other parts, we further incorporate automatic search ways to reduce manual interaction. We utilize public and self-owned credit data sets to conduct experiments and compare them with the latest credit assessment methods. Extensive experiments have demonstrated that our ACSS method achieves relatively noticeable performance improvements using the German credit dataset, the Taiwan credit dataset and the personal credit dataset for credit scoring. The best results achieved by our proposed method are 0.98, 0.99, 0.895 and 0.901 for MAE, RMSE, accuracy and precision respectively. In addition, the experimental results also show that our proposed improved SMOTE algorithm contributes to the credit scoring performance enhancement. The experimental findings suggest that our proposed ACSS balances automation and accuracy, which can be implemented to the consumption industry to enhance the reliability of credit assessments. • We utilize an improved SMOTE that could decrease the impact of data imbalance that exists in the credit data. • We propose to leverage the credit feature pruning algorithm and memetic optimization algorithm. • We propose an automated credit scoring strategy (ACSS) method with a cost-effective neural architecture search (C-NAS) scheme. [ABSTRACT FROM AUTHOR]