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<record>
  <title>Foreign Language Skills For Professional Improvement With Learning Trajectories</title>
  <journal>International Journal of Computational Linguistics Research</journal>
  <author>Wang Lina, Liu Juanyin, Li rui, Ma Jifei</author>
  <volume>14</volume>
  <issue>3</issue>
  <year>2023</year>
  <doi>https://doi.org/10.6025/jcl/2023/14/3/82-89</doi>
  <url>https://www.dline.info/jcl/fulltext/v14n3/jclv14n3_2.pdf</url>
  <abstract>With the improvement of Chinaâ€™s international status, the demand for foreign language application talents is becoming increasingly significant for hosting the Winter Olympics. To meet this demand, we propose a solution based on the Viterbi algorithm aimed at cultivating applied talents with foreign language skills and professional knowledge required for the Winter Olympics. This plan first determines the foreign language skills and professional knowledge required for the Winter Olympics, including English, French, German and other languages, and professional knowledge related to ice and snow sports. Then, we used the Viterbi algorithm to identify studentsâ€™ learning patterns and difficulties based on their learning trajectories and performance data, providing them with more personalized and targeted teaching solutions. In addition, we have combined the cultivation of professional knowledge and foreign language skills in ice and snow sports to enhance studentsâ€™ practical abilities and comprehensive qualities. Through experimental verification, we found that the Viterbi algorithm-based solution can significantly improve studentsâ€™ foreign language application ability and professional knowledge level. This program has higher teaching efficiency and lower teaching costs than traditional training models. In addition, students also showed higher satisfaction and stronger learning motivation towards the program.</abstract>
</record>
