@article{oai:kagawa-u.repo.nii.ac.jp:00009759,
 author = {Sy, Khalifa and Sy, Khalifa and 八重樫, 理人 and Yaegashi, Rihito and 林, 敏浩 and Hayashi, Toshihiro},
 journal = {香川大学インターナショナルオフィスジャーナル, Journal of Kagawa University International Office},
 month = {Mar},
 note = {E‐learning is a tool that is used by both educational institutions and private companies. There is a tremendous amount of content on e‐Learning platforms such as Udemy 100000 courses. learned. Developing a way automate design of learning plan for e‐Learning is the purpose of this research. To achieve this, we use learning history collected using survey to identify skill mismatch. The learning path (Jih, H. J., 1996) of ICT professionals informs on skill mismatch (EU commission, 2020) when confronted to an academic learning path. People have a finite amount of time to achieve as much as possible. Learning path adaptation allows saving time on training. This gain of time allows people to seek the balance between skills diversification and specialization.E‐learning is a tool that is used by both educational institutions and private companies. There is a tremendous amount of content on e‐Learning platforms such as Udemy 100000 courses. learned. Developing a way automate design of learning plan for e‐Learning is the purpose of this research. To achieve this, we use learning history collected using survey to identify skill mismatch. The learning path (Jih, H. J., 1996) of ICT professionals informs on skill mismatch (EU commission, 2020) when confronted to an academic learning path. People have a finite amount of time to achieve as much as possible. Learning path adaptation allows saving time on training. This gain of time allows people to seek the balance between skills diversification and specialization.},
 pages = {211--212},
 title = {Extracting learning path data from learning history},
 volume = {14},
 year = {2022},
 yomi = {ヤエガシ, リヒト and ハヤシ, トシヒロ}
}