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Technology integration refers to the process of innovation diffusion, from understanding technology knowledge to achieving a high level quality of technology usage. To address the gap in research regarding the critical factors that influence K-12 teachers' practice of technology integration at the initial stage of a massive government-led training programme in rural areas, this study sought to explore the comprehensive effects of teachers' technological pedagogical content knowledge (TPACK) and beliefs on their technology integration. Participants included 267 in-service K-12 teachers from four pilot schools in a remote rural area in north-western China. We found that: (a) T-related knowledge positively predicted the teachers' technology integration quality and quantity, while T-unrelated knowledge negatively influenced technology integration quality and quantity; (b) the positive valence of teachers' beliefs (PVTBs) was positively related to technology integration quality, the negative valence of teachers' beliefs was negatively related to technology integration quantity; (c) the PVTBs impacted the quality and quantity of technology integration through T-related knowledge; and (d) gender significantly moderated the impact of positive beliefs and T-related knowledge on technology integration. This study suggests that improving K-12 teachers' technology integration in rural areas requires prioritizing professional development programmes that improve teachers' beliefs in the initial stage of technology diffusion.

Lesson study (LS) is an effective means of improving teachers' facility with teaching design. This research designs a case study of online to offline (O2O) LS and explores the social interaction and behaviour patterns in the process of the LS. The participants included 29 chemistry teachers from 10 secondary schools and two educational technology experts from a university in western China, who participated in the O2O LS, with Chemistry Teaching Design based on Augmented Reality (AR): Molecules and Atoms as its topic. Through social network analysis (SNA) and lag sequence analysis (LSA), the findings of this case study indicate that: (1) in the LS process, the two co-hosts played their due roles well, while different teachers played strong guiding and controlling roles in different discussion phases, and (2) in different discussion phases, the behaviour sequence of teachers' knowledge construction presented different characteristics in that high-level knowledge construction took place among teachers in the later phases under the leadership of the host. This study will aid in the design and implementation of O2O LS and the description of interactive characteristics in teachers' collaborative learning so as to provide reference for using teacher training process data and improving teachers' professional abilities.

Steer-by-wire is a key technology to realize full self-driving for intelligent vehicles, where this is a challenge for steering angle following accurately. Therefore, a hybrid control thinking is proposed to design a model-tuned predictive sliding control approach, which is utilized to realize angle following of the electric motor steer-by-wire system. Here, sliding mode control is used as a core algorithm to be fit for the dynamics characteristics of the steer-by-wire system. Model tuning control is proposed to update model parameters by a receding horizon method, which means that some posteriori knowledge of the control system is utilized to make the model more accurate. Model predictive control is used to optimize the sliding manifold parameters of sliding mode control, which means that some priori knowledge of the control system is used to make the control law much fitter. Then we discuss a series of studies on the steer-by-wire system model and the control algorithm that, collectively, develop an approach of how the hybrid control algorithm precisely makes the front wheel angles follow desired steering commands. The designed approach has been deployed into a steering control unit, and tested in a steering test vehicle to realize the angle following of the electric motor steer-by-wire system. Based on the experimental results and statistical analysis, it can be concluded that the hybrid control thinking is a good idea of how to fuse several algorithms into a control approach, and the model-tuned predictive sliding control approach is a good candidate for the steering angle following of full self-driving vehicles. [ABSTRACT FROM AUTHOR]