Abstract
Psychological changes will often play a huge influence on the teaching effects in the English vocabulary learning and teaching process. To further explore the relationship of psychological regulation with English vocabulary teaching, the hybrid collaborative recommender technology may be underlying to propose a hybrid algorithm for studying how the English vocabulary teaching effect is subjected to the psychological emotion factors as parameters added in the original similarity calculation method in the psychological regulation environment where the emotion is the core of study. In the end, the paper conducts the questionnaire survey among 300 students. Test data show that positive emotion acts as the catalyst of the English vocabulary teaching effect, having basically reached the expected goal of study.
Highlights
It is common knowledge that people who have accepted English education generally learn from ABC of vocabulary to the phrases and syntax, and further to entry to allwave training for listening, speaking, reading and writing skills
To solve problems mentioned above and respond to the challenge of cold boot and sparsity in the recommender system, this paper proposes the hybrid collaborative recommender algorithm based on the similarity of emotional factors
In the hybrid collaborative recommender algorithm, the similarity calculation should be performed on the psychological factors and English vocabulary teaching effects based on the emotional factors
Summary
It is common knowledge that people who have accepted English education generally learn from ABC of vocabulary to the phrases and syntax, and further to entry to allwave training for listening, speaking, reading and writing skills. Instead, when the students are highly emotional and optimistic, the English vocabulary learning will get relaxed and cheerful and yield immediate results In this sense, the psychological regulation has a far-reaching significance in future study of English vocabulary. There are major algorithms including the Collaborative Filtering (CF), Contents-Based Filtering (CBF), the Principal Elemental Analysis, and Knowledge Discovery [3,4,5], which only involve the "hardware" indicators such as knowledge and content for calculating the similarity of factors, but lack of deliberation of "software" indicators such as psychology and emotion For this purpose, the paper attempts to facilitate the English vocabulary teaching by merging the emotional factors into simulation calculation of traditional collaborative recommender algorithm. Test data show that the catalyst for English vocabulary learning is possible as long as positive and optimistic emotion exist, basically reaching the intended purpose of study
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