Personalized Learning Task Assignment Based on Bipartite Graph
“Learning” is a complex event.Individual's learning effect is affected by many factors.Moreover, different individuals have different learning habits.Therefore, it is challenging for students to plan their learning schedule reasonably according to their own characteristi...
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| Format: | Article |
| Language: | zho |
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Editorial office of Computer Science
2022-04-01
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| Series: | Jisuanji kexue |
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| Online Access: | https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2022-49-4-269.pdf |
| _version_ | 1811244477800513536 |
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| author | TAN Zhen-qiong, JIANG Wen-Jun, YUM Yen-na-cherry, ZHANG Ji, YUM Peter-tak-shing, LI Xiao-hong |
| author_facet | TAN Zhen-qiong, JIANG Wen-Jun, YUM Yen-na-cherry, ZHANG Ji, YUM Peter-tak-shing, LI Xiao-hong |
| author_sort | TAN Zhen-qiong, JIANG Wen-Jun, YUM Yen-na-cherry, ZHANG Ji, YUM Peter-tak-shing, LI Xiao-hong |
| collection | DOAJ |
| description | “Learning” is a complex event.Individual's learning effect is affected by many factors.Moreover, different individuals have different learning habits.Therefore, it is challenging for students to plan their learning schedule reasonably according to their own characteristics.Although some general theoretical strategies for task management have been proposed, the differences among individuals are usually neglected.Furthermore, existing research cannot provide a calculation method to form a specific task mana-gement schedule.To this end, this paper tries to explore students'learning characteristics by deeply studying the relation between learning efficiency and time factor through data analysis.Based on this, it quantifies personalized learning efficiency.Furthermore, it exploits the bipartite graph method to construct the learning task assignment scenario, and designs adaptive utility function according to different learning goals.Then, a dynamic allocation algorithm TLTA based on transfer learning is proposed to formulate a reasonable schedule for students.Finally, a large number of experiments are carried out on real learning datasets, and the results validate the effectiveness and applicability of the proposed work. |
| first_indexed | 2024-04-12T14:24:37Z |
| format | Article |
| id | doaj.art-df4617534a2c4f84b5d67afff7251fa0 |
| institution | Directory Open Access Journal |
| issn | 1002-137X |
| language | zho |
| last_indexed | 2024-04-12T14:24:37Z |
| publishDate | 2022-04-01 |
| publisher | Editorial office of Computer Science |
| record_format | Article |
| series | Jisuanji kexue |
| spelling | doaj.art-df4617534a2c4f84b5d67afff7251fa02022-12-22T03:29:28ZzhoEditorial office of Computer ScienceJisuanji kexue1002-137X2022-04-0149426928110.11896/jsjkx.210500125Personalized Learning Task Assignment Based on Bipartite GraphTAN Zhen-qiong, JIANG Wen-Jun, YUM Yen-na-cherry, ZHANG Ji, YUM Peter-tak-shing, LI Xiao-hong01 School of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China;<br/>2 Department of Special Education and Counselling, The Education University of Hong Kong, Hong Kong 810014, China;<br/>3 Zhejiang Lab, Hangzhou 310012, China;<br/>4 Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong 999077, China“Learning” is a complex event.Individual's learning effect is affected by many factors.Moreover, different individuals have different learning habits.Therefore, it is challenging for students to plan their learning schedule reasonably according to their own characteristics.Although some general theoretical strategies for task management have been proposed, the differences among individuals are usually neglected.Furthermore, existing research cannot provide a calculation method to form a specific task mana-gement schedule.To this end, this paper tries to explore students'learning characteristics by deeply studying the relation between learning efficiency and time factor through data analysis.Based on this, it quantifies personalized learning efficiency.Furthermore, it exploits the bipartite graph method to construct the learning task assignment scenario, and designs adaptive utility function according to different learning goals.Then, a dynamic allocation algorithm TLTA based on transfer learning is proposed to formulate a reasonable schedule for students.Finally, a large number of experiments are carried out on real learning datasets, and the results validate the effectiveness and applicability of the proposed work.https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2022-49-4-269.pdfbipartite graph|task allocation|time factor|learning effect|transfer learning |
| spellingShingle | TAN Zhen-qiong, JIANG Wen-Jun, YUM Yen-na-cherry, ZHANG Ji, YUM Peter-tak-shing, LI Xiao-hong Personalized Learning Task Assignment Based on Bipartite Graph Jisuanji kexue bipartite graph|task allocation|time factor|learning effect|transfer learning |
| title | Personalized Learning Task Assignment Based on Bipartite Graph |
| title_full | Personalized Learning Task Assignment Based on Bipartite Graph |
| title_fullStr | Personalized Learning Task Assignment Based on Bipartite Graph |
| title_full_unstemmed | Personalized Learning Task Assignment Based on Bipartite Graph |
| title_short | Personalized Learning Task Assignment Based on Bipartite Graph |
| title_sort | personalized learning task assignment based on bipartite graph |
| topic | bipartite graph|task allocation|time factor|learning effect|transfer learning |
| url | https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2022-49-4-269.pdf |
| work_keys_str_mv | AT tanzhenqiongjiangwenjunyumyennacherryzhangjiyumpetertakshinglixiaohong personalizedlearningtaskassignmentbasedonbipartitegraph |