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Machine translation (MT) is the process of using a computer to convert one language into another language with the same semantics. With the introduction of neural network, neural machine translation (NMT), as a powerful machine translation technology, has achieved remarkable success in the field of automatic translation and artificial intelligence. Due to the problem of redundant parameters and structure in traditional neural translation models, knowledge distillation (KD) technology is proposed to compress the model and accelerate the inference of neural machine translation, which has attracted wide attention in the field of machine learning and natural language processing. This paper systematically investigates and compares various translation models with introduction of know-ledge distillation from the perspectives of evaluation indicators and technical innovations. Firstly, this paper briefly reviews the development process, mainstream frameworks and evaluation indicators of machine translation. Secondly, the knowledge distillation technology is introduced in detail. Thirdly, the development direction of neural machine translation based on knowledge distillation is detailed from four perspectives: multi-language model, multi-modal translation, low-resource language, autoregressive and non-autoregressive, and the research status of other fields is briefly introduced. Finally, the problems of existing large language models, zero-resource languages and multi-modal machine translation are analyzed, and the development trend of neural machine translation is prospected.

This study explored young Chinese learners' beliefs about English as an international language through project-based language learning in a Chinese rural school. Three English teachers and 102 Grade 6 Chinese EFL learners participated in two separate phases. Phase 1 explored how teachers implemented the project-based language learning via classroom observation and semi-structured interviews. The findings from this phase were used to construct the six aspects of the EIL project-based language learning questionnaire in Phase 2. The questionnaire was developed to explore learners' beliefs about EIL and project-based language learning in a Chinese rural school. The questionnaire revealed that the learners strongly believed in learning English as an international language through project-based language learning. Five aspects received similar positive responses, namely, collaboration, authenticity, intellectual challenge and accomplishment, and project management and reflection. However, only the aspect of public product received a more negative response.

Studying online has currently evolved into a global 'new normal' trend in education. However, students' intention to adopt online interactive behaviors is still relatively low, and few studies have attempted to obtain an in-depth understanding of students' online interactive behaviors. This study aims to explain and predict students' intention to adopt online interactions by synthesizing the theory of planned behavior (TPB) with cognitive and motivational factors. The proposed model was validated by surveying 368 junior high school students in China who had experienced formal online education for one semester. The results showed that perceived behavioral control was the strongest predictor of students' adoption of online interactions, followed by subjective norms and attitudes, while cognitive and motivational factors were significant antecedents of the three core constructs of TPB. These findings of the study provide valuable insights to understand secondary school students' learning behaviors in an online context and improve their adoption of online interactive behaviors.

The adoption of hydraulic fracturing (fracking) and horizontal drilling technology substantively altered the structure of oil supply. Using disaggregate state-level data from the U.S, this paper provides empirical evidence that oil supplies are now asymmetric with respect to price changes as a result of the adoption of new production methods. The changed structure of U.S. oil supply--particularly the low supply elasticities for price declines and large supply elasticities for price increases--is consistent with the ineffectiveness of OPEC policies intended to drown fracking American producers in oil. Keywords: Fracking, Oil Supply, OPEC, 1. INTRODUCTION Oil producers in North Dakota, Texas, and a few other regions have helped to catapult America to its position of prominence as the world's leading producer of crude [...]

AbstractOnline education transforms many aspects of teaching and learning in higher education. International students studying abroad already face considerable stress and negative emotions, and the transition to online learning can further intensify their learning anxiety. This study systematically investigated the factors associated with international students’ online learning anxiety by integrating demographic, adjustment, and online learning readiness-related factors. A sample of 380 Chinese students studying in South Korea was investigated. A three-step hierarchical multivariate regression revealed that doctoral students demonstrated significantly lower learning anxiety levels compared to freshmen. Adjustment-related factors explained significant additional variance in online learning anxiety, with length of stay, social support and language proficiency emerging as significant predictors. Online learning readiness-related factors were found to be the most powerful predictors in explaining learning anxiety, with self-directed learning, learner control, computer/internet self-efficacy and online communication self-efficacy being significant predictors. The findings were discussed, and future research implications were suggested. [ABSTRACT FROM AUTHOR]