The teaching context is highly related to student’s learning process and the corresponding performance. The current study exploredthe influence of distance cue (the front seats or the back seats in a classroom) on in...The teaching context is highly related to student’s learning process and the corresponding performance. The current study exploredthe influence of distance cue (the front seats or the back seats in a classroom) on individual’s metacognition and performance. Theresults showed that participants seated in the front seats had higher JOLs and better perform than those in the back seats, and seatinghabits seem to have little impact on these scores. However, this superiority is only related to the participants who believed in that“position of the seat affects learning performance”. The results demonstrated that cognitive process and metacognitive process areaffected by the distance cues in the classroom. Importantly, individual’s belief plays a moderating role.展开更多
Accumulated studies have found that learners would have an illusion of ability during the learning process when predicting whether previously learned materials can be recalled in subsequent tests.Learners may overesti...Accumulated studies have found that learners would have an illusion of ability during the learning process when predicting whether previously learned materials can be recalled in subsequent tests.Learners may overestimate or underestimate their performance in the situation,and this phenomenon is called metacognitive illusion.Recently,the belief hypothesis proposed that relevant beliefs would be produced when individuals process perceptual information,and such belief would affect the judgment.This study explores the influence of beliefs on the metacognitive illusion of complete and incomplete nouns by manipulating font shape(nouns with complete or missing strokes)and using pre-study and immediate judgments of learning(JOLs).The results of the study found that the participants had a metacognitive illusion of complete nouns,that is,the nouns with complete strokes got higher JOLs but lower recall scores than nouns with incomplete strokes.展开更多
Transition prediction has always been a frontier issue in the field of aerodynamics.A supervised learning model with probability interpretation for transition judgment based on experimental data was developed in this ...Transition prediction has always been a frontier issue in the field of aerodynamics.A supervised learning model with probability interpretation for transition judgment based on experimental data was developed in this paper.It solved the shortcomings of the point detection method in the experiment,that which was often only one transition point could be obtained,and comparison of multi-point data was necessary.First,the Variable-Interval Time Average(VITA)method was used to transform the fluctuating pressure signal measured on the airfoil surface into a sequence of states which was described by Markov chain model.Second,a feature vector consisting of one-step transition matrix and its stationary distribution was extracted.Then,the Hidden Markov Model(HMM)was used to pre-classify the feature vectors marked using the traditional Root Mean Square(RMS)criteria.Finally,a classification model with probability interpretation was established,and the cross-validation method was used for model validation.The research results show that the developed model is effective and reliable,and it has strong Reynolds number generalization ability.The developed model was theoretically analyzed in depth,and the effect of parameters on the model was studied in detail.Compared with the traditional RMS criterion,a reasonable transition zone can be obtained using the developed classification model.In addition,the developed model does not require comparison of multi-point data.The developed supervised learning model provides new ideas for the transition detection in flight experiments and other experiments.展开更多
In the recent informatization of Chinese courts, the huge amount of law cases and judgment documents, which were digital stored,has provided a good foundation for the research of judicial big data and machine learning...In the recent informatization of Chinese courts, the huge amount of law cases and judgment documents, which were digital stored,has provided a good foundation for the research of judicial big data and machine learning. In this situation, some ideas about Chinese courts can reach automation or get better result through the research of machine learning, such as similar documents recommendation, workload evaluation based on similarity of judgement documents and prediction of possible relevant statutes. In trying to achieve all above mentioned, and also in face of the characteristics of Chinese judgement document, we propose a topic model based approach to measure the text similarity of Chinese judgement document, which is based on TF-IDF, Latent Dirichlet Allocation (LDA), Labeled Latent Dirichlet Allocation (LLDA) and other treatments. Combining with the characteristics of Chinese judgment document,we focus on the specific steps of approach, the preprocessing of corpus, the parameters choices of training and the evaluation of similarity measure result. Besides, implementing the approach for prediction of possible statutes and regarding the prediction accuracy as the evaluation metric, we designed experiments to demonstrate the reasonability of decisions in the process of design and the high performance of our approach on text similarity measure. The experiments also show the restriction of our approach which need to be focused in future work.展开更多
文摘The teaching context is highly related to student’s learning process and the corresponding performance. The current study exploredthe influence of distance cue (the front seats or the back seats in a classroom) on individual’s metacognition and performance. Theresults showed that participants seated in the front seats had higher JOLs and better perform than those in the back seats, and seatinghabits seem to have little impact on these scores. However, this superiority is only related to the participants who believed in that“position of the seat affects learning performance”. The results demonstrated that cognitive process and metacognitive process areaffected by the distance cues in the classroom. Importantly, individual’s belief plays a moderating role.
文摘Accumulated studies have found that learners would have an illusion of ability during the learning process when predicting whether previously learned materials can be recalled in subsequent tests.Learners may overestimate or underestimate their performance in the situation,and this phenomenon is called metacognitive illusion.Recently,the belief hypothesis proposed that relevant beliefs would be produced when individuals process perceptual information,and such belief would affect the judgment.This study explores the influence of beliefs on the metacognitive illusion of complete and incomplete nouns by manipulating font shape(nouns with complete or missing strokes)and using pre-study and immediate judgments of learning(JOLs).The results of the study found that the participants had a metacognitive illusion of complete nouns,that is,the nouns with complete strokes got higher JOLs but lower recall scores than nouns with incomplete strokes.
基金supported by the National Key Laboratory of Science and Technology on Aerodynamic Design and Research Foundation, China
文摘Transition prediction has always been a frontier issue in the field of aerodynamics.A supervised learning model with probability interpretation for transition judgment based on experimental data was developed in this paper.It solved the shortcomings of the point detection method in the experiment,that which was often only one transition point could be obtained,and comparison of multi-point data was necessary.First,the Variable-Interval Time Average(VITA)method was used to transform the fluctuating pressure signal measured on the airfoil surface into a sequence of states which was described by Markov chain model.Second,a feature vector consisting of one-step transition matrix and its stationary distribution was extracted.Then,the Hidden Markov Model(HMM)was used to pre-classify the feature vectors marked using the traditional Root Mean Square(RMS)criteria.Finally,a classification model with probability interpretation was established,and the cross-validation method was used for model validation.The research results show that the developed model is effective and reliable,and it has strong Reynolds number generalization ability.The developed model was theoretically analyzed in depth,and the effect of parameters on the model was studied in detail.Compared with the traditional RMS criterion,a reasonable transition zone can be obtained using the developed classification model.In addition,the developed model does not require comparison of multi-point data.The developed supervised learning model provides new ideas for the transition detection in flight experiments and other experiments.
文摘In the recent informatization of Chinese courts, the huge amount of law cases and judgment documents, which were digital stored,has provided a good foundation for the research of judicial big data and machine learning. In this situation, some ideas about Chinese courts can reach automation or get better result through the research of machine learning, such as similar documents recommendation, workload evaluation based on similarity of judgement documents and prediction of possible relevant statutes. In trying to achieve all above mentioned, and also in face of the characteristics of Chinese judgement document, we propose a topic model based approach to measure the text similarity of Chinese judgement document, which is based on TF-IDF, Latent Dirichlet Allocation (LDA), Labeled Latent Dirichlet Allocation (LLDA) and other treatments. Combining with the characteristics of Chinese judgment document,we focus on the specific steps of approach, the preprocessing of corpus, the parameters choices of training and the evaluation of similarity measure result. Besides, implementing the approach for prediction of possible statutes and regarding the prediction accuracy as the evaluation metric, we designed experiments to demonstrate the reasonability of decisions in the process of design and the high performance of our approach on text similarity measure. The experiments also show the restriction of our approach which need to be focused in future work.
