基於二分圖的個性化學習任務分配

學習是一種複雜的事件。個體的學習效果受多方面因素的影響，且不同個體有不同的學習習慣，學生通常難以根據自身學習特點合理規劃學習時間表。雖然目前有關任務管理方面的研究提出了一些具有通用性的理論管理策略，但其忽略了個體間的差異性；另外，現有研究不能提供一種計算方法來形成具體的任務管理方案。針對上述問題，文中通過資料分析找出學習效率與時間因素的關聯性，從而理解學生的學習特徵，量化出個性化的學習效率；使用二分圖的方法構建學習任務分配場景，根據不同的學習目標設計自我調整效用函數，並基於此提出了一種基於遷移學習的動態分配演算法TLTA，用於為學生制定合理的任務分配方案。在真實的學生資料集上進行了大量實驗，驗證了所提方案的有效性及適用性。
“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. Copyright © 2022 重慶西南信息有限公司.