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Feedback-seeking behavior is an important way for individuals to actively seek information feedback to achieve individuals' goals. In the environment driven by contactless digital technologies, the way of individual feedback-seeking behavior through monitoring indirectly becomes obvious, especially for people who complete the work online in digital collaboration. However, previous empirical research on feedback-seeking behavior mainly focused on direct inquiry. The purpose of this paper is to verify the impact of individual learning goal orientation and the digital feedback environment on individuals' feedback-seeking behaviors through inquiry and monitoring approaches. And the moderating effect of time pressure on these relationships was also investigated.

Based on socio-technical system theory, this study proposes a model to describe the formation of the two approaches of feedback-seeking behaviors (inquiry and monitoring). The hypotheses were examined with the structural equation model method and data were collected from 152 graduate students who completed online surveys.

The results show that both the digital feedback environment and learning goal orientation can promote individual inquiry and monitoring approaches of feedback-seeking. Furthermore, time pressure moderates the relationship between the digital feedback environment and feedback monitoring negatively.

This study establishes an antecedent model that influences the choice of feedback-seeking approaches in digital environments from the perspective of a socio-technical system. The empirical results supplement the explanation of the influence of both technical and social factors on individual feedback-seeking behavior in digital environments.

Due to the inability to directly apply an intra-oral image with esthetic restoration to restore tooth shape in the computer-aided design system, this paper aims to propose a method that can use two-dimensional contours obtained from the image for the three-dimensional dental mesh model restoration.

First, intra-oral image and smiling image are taken from the patient, then teeth shapes of the images are designed based on esthetic restoration concepts and the pixel coordinates of the teeth’s contours are converted into the vertex coordinates in the three-dimensional space. Second, the dental mesh model is divided into three parts – active part, passive part and fixed part – based on the teeth’s contours of the mesh model. Third, the vertices from the teeth’s contours of the dental model are matched with ones from the intra-oral image and with the help of matching operation, the target coordinates of each vertex in the active part can be calculated. Finally, the Laplacian-based deformation algorithm and mesh smoothing algorithm are performed.

Benefitting from the proposed method, the dental mesh model with esthetic restoration can be quickly obtained based on the intra-oral image that is the result of doctor-patient communication. Experimental results show that the quality of restoration meets clinical needs, and the typical time cost of the method is approximately one second. So the method is both time-saving and user-friendly.

The method provides the possibility to design personalized dental esthetic restoration solutions rapidly.