Collaborative problem-solving (CPS) engages students in solving ill-structured problems, creating group knowledge, and developing self-regulation and collaboration skills. Different scaffoldings, such as minimal-guided, task-oriented, and idea-oriented, can be used to facilitate students’ CPS activities, but their effects have not been comprehensively explored. In this research, we use minimally-guided, task-oriented, and idea-oriented scaffoldings to promote Chinese university students’ online CPS activities and use a multi-method approach to analyze the effects of three scaffolding on collaboration. The results indicate relatively complicated collaborative processes and outcomes supported by three scaffoldings. It is initially shown that the idea-centered scaffolding strengthens students’ connections between idea contribution, metacognitive regulation, and knowledge artifact behaviors, which are critical factors for improving the CPS quality. Based on the empirical research results, we conclude that future instructional design should carefully consider the educational culture, time constraint, and student regulation to better facilitate CPS practices.
Document skew detection is one of the key technologies in most of the document analysis systems. However, existing skew detection methods either have low accuracy or require a large amount of computation. To achieve a good tradeoff between efficiency and performance, we propose a novel skew detection approach based on bounding boxes, probability model, and Dixon’s Q test. Firstly, bounding boxes are used to pick out the eligible connected components (ECC). Then, we calculate the slopes of the skew document with the probability model. Finally, we find the optimal result with Dixon’s Q test and projection profile method. Moreover, the proposed method can detect the skew angle in a wider range. The experimental results show that our skew detection algorithm can achieve high speed and accuracy simultaneously compared with existing algorithms.
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