Search results

This study explored how teachers change, what teachers learn and how they learn during the implementation of project-based learning through lesson study.

In this study, three university researchers, one doctoral student and six mathematics school teachers formed a lesson study team. Using a qualitative research method, this study employed a locally integrating networking strategy to combine the modified Interconnected Model of Teacher Professional Growth (IMTPG) and Bannister's framework to describe the teachers' knowledge change when participating in a lesson study on project-based learning.

The research revealed that the school teachers' knowledge about authenticity and assessment in the context of project-based learning was changed after the lesson study and how the changes were triggered.

The study demonstrates how the networking of two different theories—modified IMTPG and Bannister's framework—contributes to a better understanding of the process of teachers' collective practice, as well as the knowledge change in PjBL. This networking was done by combining the two theories, which were superimposed at the domain of practice.

The purpose of this study is to establish a method for accurately extracting torch and seam features. This will improve the quality of narrow gap welding. An adaptive deflection correction system based on passive light vision sensors was designed using the Halcon software from MVtec Germany as a platform.

This paper proposes an adaptive correction system for welding guns and seams divided into image calibration and feature extraction. In the image calibration method, the field of view distortion because of the position of the camera is resolved using image calibration techniques. In the feature extraction method, clear features of the weld gun and weld seam are accurately extracted after processing using algorithms such as impact filtering, subpixel (XLD), Gaussian Laplacian and sense region for the weld gun and weld seam. The gun and weld seam centers are accurately fitted using least squares. After calculating the deviation values, the error values are monitored, and error correction is achieved by programmable logic controller (PLC) control. Finally, experimental verification and analysis of the tracking errors are carried out.

The results show that the system achieves great results in dealing with camera aberrations. Weld gun features can be effectively and accurately identified. The difference between a scratch and a weld is effectively distinguished. The system accurately detects the center features of the torch and weld and controls the correction error to within 0.3mm.

An adaptive correction system based on a passive light vision sensor is designed which corrects the field-of-view distortion caused by the camera’s position deviation. Differences in features between scratches and welds are distinguished, and image features are effectively extracted. The final system weld error is controlled to 0.3 mm.

The authors study the effectiveness of the anti-corruption campaign in all of mainland China's provinces in terms of risk and volatility spillovers.

A nonlinear model describes interdependencies and determines how shocks and uncertainty spillovers from the first suspects to the rest of the country are dynamically transmitted.

The authors find that both idiosyncratic and systematic risk increase after the first investigation, suggesting that investors do react to the political shocks induced by the new policy. However, even if the scope of the inquiry expands, as the current policy is almost certain to be maintained, investors do not need to update their beliefs, stock news about their political costs does not matter and shocks cease to spread.

In this paper, the authors contribute to the literature by examining the financial effects of China's anti-corruption campaign and determining whether such a large-scale campaign affects risk. Qian and Wen (2015) and Ke et al. (2016) show that the anticorruption campaign has a negative impact on the consumption of luxury goods. Agarwal et al. (2020) provide evidence that government officials' access to credit decreases following the anti-corruption campaign. According to Zhang (2018), firms are less prone to commit fraud after the anti-corruption campaign. However, Griffin et al. (2018) find little evidence that the anti-corruption campaign reduces corporate corruption. Kim et al. (2018) assess market reaction during the investigation and discover that the anti-corruption examination has a significant positive influence on Chinese financial markets. The authors intend to fill the gap in the literature concerning the campaign's impact on risk and volatility spillovers across the country during the first stage of the campaign.

This article proposes a strategy to make the testing step easier, generating user acceptance tests (UATs) in an automatic way from requirements artifacts.

This strategy is based on two modeling frameworks: scenarios and task/method paradigm. Scenarios are a requirement artifact used to describe business processes and requirements, and task/method paradigm is a modeling paradigm coming from the artificial intelligence field. The proposed strategy is composed of four steps. In the first step, scenarios are described through a semantic wiki website. Then scenarios are automatically translated into a task/method model (step two). In the third step, the task/method model obtained in step two is executed in order to produce and store all possible achievements of tasks and thus scenarios. The stored achievements are saved in a data structure called execution tree (ET). Finally, from this ET (step four), the UATs are generated.

The feasibility of this strategy is shown through a case study coming from the agriculture production systems field.

Generally, test design approaches deal with a small number of variables describing one specific situation where a decision table or workflow is used to design tests. The proposed approach can deal with many variables because the authors rely on scenarios that can be composed in order to obtain a tree with all the testing paths that can arise from their description.

The purpose of this study was to identify the effects of emerging technologies in e-learning on university librarians and libraries. The study also intended to identify emerging technologies in e-learning and challenges being faced to implement e-learning technologies.

The preferred reporting items for the systematic review and meta-analysis method was applied as the research methodology for conducting the study. A total of 25 core studies published in peer-reviewed journals were selected to conduct a systematic literature review. The data were analysed through a thematic approach.

The results of the study revealed that e-learning technologies assist library professionals to strengthen their expertise and support them in initiating smart library services to deliver customer-focused services. A shortage of skilled manpower, the unavailability of adequate IT infrastructure, a lack of technical support, copyright issues, poor planning and ineffective library leadership are major challenges to implementing emerging technologies in e-learning.

The study offers theoretical implications by adding valuable literature to the existing body of knowledge. It has a societal impact as it has offered recommendations and practical solutions for the successful adoption of emerging technologies in e-learning. The study also offers managerial implications to develop fruitful policies for implementing e-learning technologies for the innovative sustainable competence development of library manpower and implementation of smart library services.