On September 21, the Supreme People＇s Court released the Opinions on Perfecting the Judicial Accountability System of People＇s Courts, which makes it clear that the objective principle of the Judicial Accountability...On September 21, the Supreme People＇s Court released the Opinions on Perfecting the Judicial Accountability System of People＇s Courts, which makes it clear that the objective principle of the Judicial Accountability System ＂should take strict adjudicative liabilities as the core＂, indicates that the core content of the litigation system reform focusing on court proceedings is the strict adjudicative liabilities, and manifests that the adjudicative liabilities system includes both ＂let the adjudicator judge＂ and ＂let the judge be accountable＂. 1 ＂Let the adjudicator judge＂ is the logical premise and accountable basis of ＂let the judge be accountable＂, and ＂let the judge be accountable＂ is the supervisory means and power-control mode of ＂let the adjudicator judge＂.展开更多
The use of programming online judges(POJs)has risen dramatically in recent years,owing to the fact that the auto-evaluation of codes during practice motivates students to learn programming.Since POJs have greater numb...The use of programming online judges(POJs)has risen dramatically in recent years,owing to the fact that the auto-evaluation of codes during practice motivates students to learn programming.Since POJs have greater number of pro-gramming problems in their repository,learners experience information overload.Recommender systems are a common solution to information overload.Current recommender systems used in e-learning platforms are inadequate for POJ since recommendations should consider learners’current context,like learning goals and current skill level(topic knowledge and difficulty level).To overcome the issue,we propose a context-aware practice problem recommender system based on learners’skill level navigation patterns.Our system initially performs skill level navigation pattern mining to discover frequent skill level navigations in the POJ and tofind learners’learning goals.Collaborativefiltering(CF)and con-tent-basedfiltering approaches are employed to recommend problems in the cur-rent and next skill levels based on frequent skill level navigation patterns.The sequence similarity measure is used tofind the top k neighbors based on the sequence of problems solved by the learners.The experiment results based on the real-world POJ dataset show that our approach considering the learners’cur-rent skill level and learning goals outperforms the other approaches in practice problem recommender systems.展开更多
文摘On September 21, the Supreme People＇s Court released the Opinions on Perfecting the Judicial Accountability System of People＇s Courts, which makes it clear that the objective principle of the Judicial Accountability System ＂should take strict adjudicative liabilities as the core＂, indicates that the core content of the litigation system reform focusing on court proceedings is the strict adjudicative liabilities, and manifests that the adjudicative liabilities system includes both ＂let the adjudicator judge＂ and ＂let the judge be accountable＂. 1 ＂Let the adjudicator judge＂ is the logical premise and accountable basis of ＂let the judge be accountable＂, and ＂let the judge be accountable＂ is the supervisory means and power-control mode of ＂let the adjudicator judge＂.
文摘The use of programming online judges(POJs)has risen dramatically in recent years,owing to the fact that the auto-evaluation of codes during practice motivates students to learn programming.Since POJs have greater number of pro-gramming problems in their repository,learners experience information overload.Recommender systems are a common solution to information overload.Current recommender systems used in e-learning platforms are inadequate for POJ since recommendations should consider learners’current context,like learning goals and current skill level(topic knowledge and difficulty level).To overcome the issue,we propose a context-aware practice problem recommender system based on learners’skill level navigation patterns.Our system initially performs skill level navigation pattern mining to discover frequent skill level navigations in the POJ and tofind learners’learning goals.Collaborativefiltering(CF)and con-tent-basedfiltering approaches are employed to recommend problems in the cur-rent and next skill levels based on frequent skill level navigation patterns.The sequence similarity measure is used tofind the top k neighbors based on the sequence of problems solved by the learners.The experiment results based on the real-world POJ dataset show that our approach considering the learners’cur-rent skill level and learning goals outperforms the other approaches in practice problem recommender systems.
