Relational agency is pivotal for understanding how language teachers seek and utilize relational resources in different contexts and grow to be agents of change amid various educational challenges. This study explored how three university teachers of Chinese as a second language enacted their relational agency to enhance their research capacity and sustain their professional development. Data on their personal network development was collected through concentric circle interviews, life-history interviews and written reflections over three months. Thematic analysis was adopted for iterative (...) coding and interpretation of the data. The findings revealed that teachers’ personal networks provided them with value guidance, emotional support and academic support, which exerted differential levels of impact on them to make agentic choices and actions. The study suggests that personal network analysis may serve as a suitable theoretical lens to achieve a multi-layered understanding of relational agency. The study also calls for more efforts to create learning opportunities and spaces in the relational context for teachers to build their career as agentic academics in language teacher education and development programs. (shrink)

Cognitive diagnostic models show great promise in language assessment for providing rich diagnostic information. The lack of a full understanding of second language listening subskills made model selection difficult. In search of optimal CDM that could provide a better understanding of L2 listening subskills and facilitate accurate classification, this study carried a two-layer model selection. At the test level, A-CDM, LLM, and R-RUM had an acceptable and comparable model fit, suggesting mixed inter-attribute relationships of L2 listening subskills. At the item (...) level, Mixed-CDMs were selected and confirmed the existence of mixed relationships. Mixed-CDMs had better model and person fit than G-DNIA. In addition to statistical approaches, the content analysis provided theoretical evidence to confirm and amend the item-level CDMs. It was found that semantic completeness pertaining to the attributes and item features may influence the attribute relationships. Inexplicable attribute conflicts could be a signal of suboptimal model choice. Sample size and the number of multi-attribute items should be taken into account in L2 listening cognitive diagnostic modeling studies. This study provides useful insights into the model selection and the underlying cognitive process for L2 listening tests. (shrink)

Although the management and planning of water resources are extremely significant to human development, the complexity of implementation is unimaginable. To achieve this, the high-precision water consumption prediction is actually the key component of urban water optimization management system. Water consumption is usually affected by many factors, such as weather, economy, and water prices. If these impact factors are directly combined to predict water consumption, the weight of each perspective on the water consumption will be ignored, which will be greatly (...) detrimental to the prediction accuracy. Therefore, this paper proposes a deep neural network-based complex system for urban water management. The essence of it is to formulate a water consumption prediction model with the aid of principal component analysis and the integrated deep neural network, which is abbreviated as UWM-Id. The PCA classifies the factors affecting water consumption in the original data into three categories according to their correlation and inputs them into the neural network model. The results in the previous step are assigned weights and integrated into the form of fully connected layer. Finally, analyzing the sensitivity of the proposed UWM-Id and comparing its performance with a series of commonly used baseline methods for data mining, a large number of experiments have proved that UWM-Id has good performance and can be used for urban water management system. (shrink)

The purpose of this study is to examine preservice Chinese language teachers’ cognition in teaching intercultural communicative competence. In the study we collected data through in-depth interviews with seven preservice teachers in a Master of Education program at a university in Hong Kong SAR, China. The findings indicated that the participants had a relatively positive attitude and inclination toward the development of students’ intercultural communicative competence, while their conceptualizations of culture tended to be static and ambiguous. In addition, the participants’ (...) objectives in teaching intercultural communicative competence were found to be more attitude-than knowledge- or skill-oriented. The study offers valuable insights that preservice language teachers’ cognition plays a crucial role in their future professional development and calls for curricular innovations with intercultural aims in teacher education programs. (shrink)

Computer multistage adaptive test combines the advantages of paper and pencil-based test and computer-adaptive test. As CAT, MST is adaptive based on modules; as P&P, MST can meet the need of test developers to manage test forms and keep test forms parallel. Cognitive diagnosis can accurately measure students’ knowledge states and provide diagnostic information, which is conducive to student’s self-learning and teacher’s targeted teaching. Although MST and CD have a lot of advantages, many factors prevent MST from applying to CD. (...) In this study, we first attempt to employ automated test assembly to achieve the objectives of MST in the application of CD via heuristic algorithms. The mean correct response probability of all KSs for each item is used to describe the item difficulty of CD. The attribute reliability in CD is defined as the test quantitative target. A simulation study with the G-DINA model was carried out to investigate the proposed CD-MST, and the results showed that the assembled panels of CD-MST satisfied the statistical and the non-statistical constraints. (shrink)

In recent years, attention to researchers’ scientific misconduct has increased dramatically. Although existing research reflects a shared value that occupational calling is an ethical good (i.e., being more likely to make ethical choices), no empirical study has yet examined the ethical outcomes of occupational calling. Drawing on the integrated ethical decision-making model (I-EDM), this study first investigated _whethe_r occupational calling inhibits researchers’ unethical decision-making. Secondly, it examined _why_ and _when_ occupational calling relates to researchers’ unethical decision-making. The findings from a (...) four-wave survey, with 257 researchers working in research roles in universities in China, reveal that occupational calling (time 1) inhibits researchers’ unethical decision-making (time 4). Moral disengagement (time 3) provides an explanation for the negative link between occupational calling (time 1) and unethical decision-making (time 4). The moderated mediation analysis further shows that the inhibitory effect of occupational calling (time 1) on researchers’ unethical decision-making (time 4) disappears when the work-unit structure (time 2) is perceived to be organic. These findings provide meaningful theoretical and practical implications for research and practice. (shrink)

This study develops a short Creative Expression Interest Scale among Chinese freshmen based on the perspective of item response theory. Nine hundred fifty-nine valid Chinese freshmen participated in the Creative Expression Interest survey. Researchers applied the initial data for unidimensionality, item fit, discrimination parameter, and differential item functioning to obtain a short CEIS. The results show that the Short CEIS meets the psychometric requirements of the IRT. Pearson correlation coefficient of theta between the short and long CEIS is 0.922. The (...) marginal reliability of the short CEIS is 0.799. These indicate that the short CEIS developed in this study among Chinese freshmen, meets the psychometric requirements. Although the Short CEIS can eliminate redundant, uninformative items, save time, and improve the quality of data collection. However, the validity of this short scale needs further validation. (shrink)