Examination Database and Online Paper Forming Algorithm for Mobile Personalized Learning Test

Authors

  • Wanwu Li Shandong University of Science and Technology, Qingdao, China
  • Lin Liu Shandong University of Science and Technology, Qingdao, China
  • Hui Zhang KQ GEO TECHNOLOGIES CO., LTD, Beijing, China
  • Jinhong Li Yantai Institute of Technology, Yantai, China
  • Zhi Wang Shandong University of Science and Technology, Qingdao, China

DOI:

https://doi.org/10.23887/ijerr.v6i1.54381

Keywords:

GIS examination database, Examination database structure design, Fuzzy query method, SQL Server

Abstract

It is crucial to advance network education exam informatization and mobile learning. One of them is the creation of a database system for exams, which contains crucial information. This study aims to analyze and solves key technologies including constraint check paper forming algorithms. This study using fuzzy query methods and spatial queries design a single exam table structure and exam papers for the exam database. The process of this study including collect and sort the complete set of GIS exams at major universities across the country, design a variety of GIS single questions, and build an exam database system. The result of this research is a personalized random paper formation system and query and spatial analysis by college and area for exam papers for the first time. It describes rich functions and stable performance by testing. The built system becomes an indispensable technical support instead of paper-based exams for information exams and scientific exams of many colleges and universities.

References

Abass, O. A., Olajide, S. A., & Samuel, B. O. (2017). Development of web-based examination system using open source programming model. Turkish Online Journal of Distance Education, 18(2), 30–42. https://doi.org/10.17718/tojde.306555.

Alghamdi, A., Alanezi, M., & Khan, F. (2020). Design and implementation of a computer aided intelligent examination system. International Journal of Emerging Technologies in Learning (IJET), 15(1), 30–44. https://www.learntechlib.org/p/217064/.

Bhardwaj, M., & Singh, A. J. (2011). Automated integrated university examination system. Himachal Pradesh University Journal, 1, 156–162. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=6c81336cc2fec7ace9dce5789143f6362ebf9733.

Chatzi, A. V., & Kourousis, K. I. (2023). Are concept map exam papers reliable as assessment tools in nursing education? A quantitative research pilot study. Teaching and Learning in Nursing, 18(2), 293–298. https://doi.org/10.1016/j.teln.2023.01.001.

Code, J., Ralph, R., & Forde, K. (2020). Pandemic designs for the future: perspectives of technology education teachers during COVID-19. Information and Learning Science, 121(5–6), 409–421. https://doi.org/10.1108/ILS-04-2020-0112.

Demetres, C. (2009). Randomized algorithms for the majority problem. Electronic Notes in Discrete Mathematics, 34, 453–457. https://doi.org/10.1016/j.endm.2009.07.075.

Engin, O., & Güçlü, A. (2018). A new hybrid ant colony optimization algorithm for solving the no-wait flow shop scheduling problems. Applied Soft Computing, 72, 166–176. https://doi.org/10.1016/j.asoc.2018.08.002.

Guan, L. (2017). The design of the automatic generative system of examination papers. (pp. ). . In 2017 Sixth International Conference on Future Generation Communication Technologies (FGCT), 1–4. https://doi.org/10.1109/FGCT.2017.8103731.

Hameed, M. R., & Abdullatif, F. A. (2017). Online examination system. International Advanced Research Journal in Science, Engineering and Technology, 4(3), 106–110. https://www.academia.edu/download/82493304/IARJSET_2021.pdf.

Hang, B. (2011). The design and implementation of on-line examination system. In 2011 International Symposium on Computer Science and Society, 227–230. https://doi.org/10.1109/ISCCS.2011.68.

Kaya a, B., Kaya, G., & Dağdeviren, M. (2014). A Sample Application of Web Based Examination System for Distance and Formal Education. Procedia-Social and Behavioral Sciences, 141, 1357–1362. https://doi.org/10.1016/j.sbspro.2014.05.234.

Liu, J., Liu, H., Chen, X., Guo, X., Zhao, Q., Liu, J., & Kang, L. (2022). Rapid Retrieval of Geospatial Data Considering Semantic Knowledge. Geomatics and Information Science of Wuhan University, 47(3), 463–472. https://doi.org/10.13203/j.whugis20200058.

Ma, Z. (2012). Ma. Chaotic populations in genetic algorithms. Applied Soft Computing, 12, 2409–2424. https://doi.org/10.1016/j.asoc.2012.03.001.

Makeham, S., & Lee, C. (2012). Making the aural presentation of examination papers student friendly: an alternative to a reader in examinations. Assessment & Evaluation in Higher Education, 37(2), 237–243. https://doi.org/10.1080/02602938.2010.527915.

Mama, R., & Machkour, M. (2021). Fuzzy querying with SQL: Fuzzy view-based approach. Journal of Intelligent & Fuzzy Systems, 40(5), 9937–9948. https://doi.org/10.3233/JIFS-202551.

Mishra, S. (2021). Determining patent filing targets based on patent cost retrieval from Patent Examination Data System. World Patent Information, 65, 102024. https://doi.org/10.1016/j.wpi.2021.102024.

Moon, H. J., Kim, E. K., Yoon, J. H., & Kwak, J. Y. (2015). Malignancy risk stratification in thyroid nodules with nondiagnostic results at cytologic examination: combination of thyroid imaging reporting and data system and the Bethesda System. Radiology, 273(1), 287–295. https://doi.org/10.1148/radiol.14140359.

Muzaffar, A., Ragab Hassen, H., Lones, M. A., & Zantout, H. (2022). An in-depth review of machine learning based Android malware detection. Computers and Security, 121, 102833. https://doi.org/10.1016/j.cose.2022.102833.

Narayanan, S., & Adithan, M. (2015). Analysis Of Question Papers In Engineering Courses With Respect To Hots (Higher Order Thinking Skills). American Journal of Engineering Education (AJEE), 6(1), 1–10. https://doi.org/10.19030/ajee.v6i1.9247.

Nelson, R. R., Todd, P. A., & Wixom, B. H. (2005). Antecedents of information and system quality: an empirical examination within the context of data warehousing. Journal of Management Information Systems, 21(4), 199–235. https://doi.org/10.1080/07421222.2005.11045823.

Nie, J. (2019). Research on optimizing intelligent test paper forming strategy based on improved genetic algorithms. Proceedings of the 2019 International Conference on Artificial Intelligence and Computer Science, 117–120. https://doi.org/10.1145/3349341.3349387.

Peng, K. H., Huang, Y. F., & Yao, J. M. (2018). Comparison of automatic test paper generation for database technology course based on various artificial intelligence algorithms. Computer System Application, 27(3), 210–216. https://ieeexplore.ieee.org/abstract/document/6295121/.

Pinar, C. (2013). Backtracking Search Optimization Algorithm for numerical optimization problems. Applied Mathematics and Computation, 219, 8121–8144. https://doi.org/10.1016/j.amc.2013.02.017.

Protopopova, J., & Kulik, S. (2020). Educational intelligent system using genetic algorithm. Procedia Computer Science, 168, 168–172. https://doi.org/10.1016/j.procs.2020.02.130.

Smith, S., & Wink, D. (2011). Teaching with Technology Free Web Resources for Teaching and Learning [J]. Nurse Educator, 36(4), 137–139. https://doi.org/10.1097/NNE.0b013e31821fd990.

Sun, J. (2019). Analysis and Research on Test Paper Generation Algorithms of Test Item Bank System. Office Informatization, 13(48). https://doi.org/10.21125/edulearn.2019.0498.

Sunday, C. E., & Vera, C. C. E. (2018). Examining information and communication technology (ICT) adoption in SMEs: A dynamic capabilities approach. Journal of Enterprise Information Management, 31(2), 338–356. https://doi.org/10.1108/JEIM-12-2014-0125.

Swart, A. (2010). Evaluation of Final Examination Papers in Engineering: A Case Study Using Bloom’s Taxonomy. IEEE Transactions On Education, 53(2). https://doi.org/10.1109/TE.2009.2014221.

Wang, Q., Deng, X., Cai, W., & Pan, L. (2021). Design and lmplementation of Online Examination System Based on Genetic Algorithm. In 2011 International Conference on Computer Science and Service System (CSSS), 33(21), 33(21. https://doi.org/10.1109/CSSS.2011.5974429.

Watts, B. V., Groft, A., Bagian, J. P., & Mills, P. D. (2011). An examination of mortality and other adverse events related to electroconvulsive therapy using a national adverse event report system. The Journal of ECT, 27(2), 105–108. https://doi.org/10.1097/YCT.0b013e3181f6d17f.

Xi, J., & Hang, X. (2018). Design of online intelligent examination system based on UML and particle swarm optimization. Automation & Instrumentation, 9. https://doi.org/10.14016/j.cnki.1001-9227.2018.09.121.

Xiao, J., Wang, M., Jiang, B., & Li, J. (2018). A personalized recommendation system with combinational algorithm for online learning. Journal of Ambient Intelligence and Humanized Computing, 9, 667–677. https://doi.org/10.1007/s12652-017-0466-8.

Yong-Sheng, Z., Xiu-Mei, F., & Ai-Qin, B. (2015). The research and design of online examination system. In 2015 7th International Conference on Information Technology in Medicine and Education (ITME), 687–691. https://doi.org/10.1109/ITME.2015.96.

Zhang, L. (2021). An Intelligent Teaching Test Paper Generation System Based on Ant Colony Hybrid Genetic Algorithms. 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), 467–470. https://doi.org/10.1109/ICMTMA52658.2021.00107.

Zhang, Y., Han, Y., & Zhou, Y. (2014). The Study on Network Examinational Database based on ASP Technology. Physics Procedia, 24, 2194–2199. https://doi.org/10.1016/j.phpro.2012.02.322.

Downloads

Published

2023-04-12

Issue

Section

Articles