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Using education survey data from 153, 317 Grade 4 students and 150, 040 Grade 8 students in China, this study examined the relationship between time on homework and academic achievement and learning anxiety with hierarchical linear modeling (HLM) and classification and regression tree (CART) approaches. With a classification of time spent on homework into four related variables, this study found that, firstly, time spent on in-school homework during weekdays had positive effects on students’ achievement for both grades, and the positive effect was stronger for Grade 8 students than Grade 4 students. Moreover, a maximum of 1 h was recommended for Grade 4 students. Secondly, time spent on out-of-school homework on weekdays was negatively correlated with students’ academic achievement and positively with learning anxieties. It had greater detrimental effect on Grade 8 than Grade 4. Thirdly, Grade 8 students were encouraged to have more out-of-school homework on weekend with more than 2.8 h on average recommended. It was expected to complement extant studies and provide the practical findings for teachers, practitioners and school policy makers in making any homework assignment planning or conducting interventions.

To better understand the latest developments in global science, technology, engineering, and mathematics (STEM) education research, this study collected STEM education research materials to sort out the development of STEM education as a whole, so as to get a clearer path and trend of STEM education development. This study conducted a visualization and quantitative analysis of the literature on STEM education research in Science Citation Index Extended (SCI-E) and Social Science Citation Index (SSCI) using the CiteSpace (5.8.R3) tool. First, the basic information of STEM education was analyzed in terms of annual publication volume, authors, countries, and research institutions. Secondly, the main fields, basic contents and research hotspots of this research were analyzed by keyword co-occurrence and keyword time zone mapping. Finally, the research frontiers and development trends are presented through co-citation clustering and high-frequency keyword bursts. The research hotspots are focused on engineering education, teachers’ professional development, and gender differences. The research frontiers are mainly related to teacher professional development, 21st century skills, early childhood creativity, and gender differences. This study systematically analyzes the latest developments in global STEM education research, which is beneficial for readers to understand the full picture of STEM education research so that researchers can conduct more in-depth studies and promote better development of STEM education. The number of analyzed literature is limited. We only analyzed articles from SSCI and SCI-E databases, and the articles were written in English. In addition, we only analyzed the literature and lacked empirical studies on the findings of the literature.

Ability of data analysis, as one of the essential core qualities of modern citizens, has received widespread attention from the international education community. How to evaluate students’ data analysis ability and obtain the detailed diagnosis information is one of the key issues for schools to improve education quality. With an employment of cognitive diagnostic assessment (CDA) as the basic theoretical framework, this study constructed the cognitive model of data analysis ability for 503 Grade 9 students in China. The follow-up analyses including the learning path, learning progression and corresponding personalized assessment were also provided. The result indicated that first, almost all the students had the data awareness. Furthermore, the probability of mastering the attribute Interpretation and inference of data was relatively low with only 60% or so. Also, the probabilities of mastering the rest of attributes were about 70% on average. It was expected that this study would provide a new cognitive diagnostic perspective on the assessment of students’ essential data analysis abilities.

Scientific explanation is one of the most core concepts in science education, and its mastery level is crucial for a deep understanding of the nature of science. As a new generation of assessment theory, cognitive diagnostic assessment (CDA) can get the knowledge of students' mastery of fine-grained knowledge. Based on the extant research, this research has formed eight attributes of scientific explanation concepts. By coding the Trends in International Mathematics and Science Study (TIMSS) test items, a CAD tool was formed. Data collected from 574 Grade 4 students in Hangzhou, China, combined with the data of the United States, Singapore, Australia, the United Kingdom, and Russia, were used in our study. The Deterministic Inputs, Noisy “And” gate (DINA) model was used to analyze the results from three aspects: the probability of mastery of attributes, the international comparison of knowledge states, and the analysis of learning paths. This study provided a new perspective from a CDA approach on the assessment of scientific explanation.

As one of the most influential international large-scale educational assessments, the Program for International Student Assessment (PISA) provides a valuable platform for the horizontal comparisons and references of international education. The cognitive diagnostic model, a newly generated evaluation theory, can integrate measurement goals into the cognitive process model through cognitive analysis, which provides a better understanding of the mastery of students of fine-grained knowledge points. On the basis of the mathematical measurement framework of PISA 2012, 11 attributes have been formed from three dimensions in this study. Twelve test items with item responses from 24,512 students from 10 countries participated in answering were selected, and the analyses were divided into several steps. First, the relationships between the 11 attributes and the 12 test items were classified to form a Q matrix. Second, the cognitive model of the PISA mathematics test was established. The liner logistic model (LLM) with better model fit was selected as the parameter evaluation model through model comparisons. By analyzing the knowledge states of these countries and the prerequisite relations among the attributes, this study explored the different learning trajectories of students in the content field. The result showed that students from Australia, Canada, the United Kingdom, and Russia shared similar main learning trajectories, while Finland and Japan were consistent with their main learning trajectories. The primary learning trajectories of the United States and China were the same. Furthermore, the learning trajectory for Singapore was the most complicated, as it showed a diverse learning process, whereas the trajectory in the United States and Saudi Arabia was relatively simple. This study concluded the differences of the mastery of students of the 11 cognitive attributes from the three dimensions of content, process, and context across the 10 countries, which provided a reference for further understanding of the PISA test results in other countries and shed some evidence for a deeper understanding of the strengths and weaknesses of mathematics education in various countries.