数据结构与算法自动组题系统的研究与实现
Research and Implementation of Automatic Question Combination System for Data Structures and Algorithms
摘要: 随着网络应用的普及,网络教学已经成为教育的新形势。为了保证网络教学的效果,公平地对学生进行考核,就需要有庞大的题库来支撑。题库的构建繁杂且费时,如何自动地建立题库是非常值得研究的。本文的研究目的是通过自动组题来生成各种题目,丰富题库。自动组题系统中,用户可以设计组题规则,自动生成题目及答案。本文对自动组题的方法和形式进行了研究,可以实现二叉树、哈夫曼树、无向图、有向图、无向网、有向网的图形自动生成,并将生成的图形和相同或不同的题干组合形成不同问题,供练习和考试使用。组题系统不仅可以帮助教师提高效率,提升教学和考试的质量,还可以提供完备和有针对性的题目,提高学生的学习体验感和教学效果。
Abstract: With the popularization of online applications, online teaching has become a new form of education. A large question bank is needed to support the effectiveness of online teaching and the fair assessment of students. The construction of question banks is complex and time-consuming, and it is worth studying how to automatically establish a question bank. This article aims to study the generation of various questions and enrich the question bank through automatic question combinations. In the automatic question combination system, users can design question rules and automatically generate questions and answers. This article studies the methods and forms of online question combinations, which can automatically generate graphs from binary trees, Huffman trees, undirected graphs, directed graphs, undirected networks, and directed networks. The generated graphs can be combined with the same or different question stems to form different questions for practice and examination. The question system can not only help teachers improve efficiency and enhance the quality of teaching and exams, but also provide comprehensive and targeted questions to enhance students’ learning experience and teaching effectiveness.
参考文献
|
[1]
|
陶冶. 基于深度学习的问题生成技术研究[D]: [硕士学位论文]. 南京: 南京理工大学, 2019.
|
|
[2]
|
张天霖. 基于领域术语的中文问题自动生成技术[D]: [硕士学位论文]. 北京: 中国科学院大学(中国科学院计算机科学与技术学院), 2020.
|
|
[3]
|
赵豫. 基于深度学习的问题生成方法研究与实现[D]: [硕士学位论文]. 成都: 电子科技大学, 2020.
|
|
[4]
|
蒋玉茹, 陶宇阳, 王霞, 等. 基于关键句和题型的阅读理解问题生成技术研究[J/OL]. 计算机工程与应用, 1-17. http://kns.cnki.net/kcms/detail/11.2127.TP.20240822.1624.013.html, 2024-09-18.
|
|
[5]
|
Jouault, C. and Seta, K. (2013) Adaptive Self-Directed Learning Support by Question Generation in a Semantic Open Learning Space. International Journal of Knowledge and Web Intelligence, 4, 349-363. [Google Scholar] [CrossRef]
|
|
[6]
|
丁向民, 顾宏斌. 基于本体的中文多项选择题自动生成技术研究[J]. 计算机工程与设计, 2010, 31(6): 1397-1400.
|
|
[7]
|
Willert, N. and Thiemann, J. (2023) Template-Based Generator for Single-Choice Questions. Technology, Knowledge and Learning, 29, 355-370. [Google Scholar] [CrossRef]
|
|
[8]
|
徐建. 基于知识图谱的工科专业概念选择题生成工具[D]: [硕士学位论文]. 武汉: 华中科技大学, 2021.
|
|
[9]
|
Quan, P., Shi, Y., Niu, L., Liu, Y. and Zhang, T. (2018) Automatic Chinese Multiple-Choice Question Generation for Human Resource Performance Appraisal. Procedia Computer Science, 139, 165-172. [Google Scholar] [CrossRef]
|
|
[10]
|
张虎, 张颖, 杨陟卓, 等. 基于数据增强的高考阅读理解自动答题研究[J]. 中文信息学报, 2021, 35(9): 132-140.
|
|
[11]
|
徐伟. 基于遗传算法与评价诊断模型混合成卷系统的研究与开发[D]: [硕士学位论文]. 南昌: 江西师范大学, 2023.
|
|
[12]
|
周小平. 基于改进粒子群算法的计算机考试自动组卷方法[J]. 自动化技术与应用, 2023, 42(7): 70-73.
|
|
[13]
|
黄河. 基于资源推荐和自动组卷的在线学习平台[D]: [硕士学位论文]. 中南大学, 2023.
|