A Systematic Model of an Adaptive Teaching, Learning and Assessment Environment Designed Using Genetic Algorithms
Source abstract
Abstract
The educational assessment is an essential task within the educational process. The generation of right and correct assessment content is a determinant process within the assessment. The creation of an automated method of generation similar to a human experienced operator (teacher) deals with a complex series of issues. This paper presents a compiled set of methods and tools used to generate educational assessment content in the form of assessment tests. The methods include the usage of various structures (e.g., trees, chromosomes and genes, and genetic operators) and algorithms (graph-based, evolutionary, and genetic) in the automated generation of educational assessment tests. This main purpose of the research is developed in the context of the existence of several requirements (e.g., degree of difficulty, item topic), which gives a higher degree of complexity to the issue. The paper presents a short literature review related to the issue. Next, the description of the models generated in the authors’ previous research is presented. In the final part of the paper, the results related to the implementations of the models are presented, as well as results and performance. Several conclusions were drawn based on this compilation, the most important of them being that tree and genetic-based approaches to the issue have promising results related to performance and assessment content generation.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Online Learning and Analytics · Intelligent Tutoring Systems and Adaptive Learning
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mathematics and Computer Science, Pitesti University Center, National University of Science and Technology POLITEHNICA Bucharest, 1 Targul din Vale, 110040 Pitesti, Romania
Department of Informatics, Ionian University, 1, Kapodistriou, 49100 Corfu, Greece
References (64)
Show source-provided references
1. Test data generation using genetic algorithms and information content
2. Creating a personality model using genetic algorithms, behavioral psychology, and a happiness dataset
3. Non-dominated sorting genetic optimisation for charging scheduling of electrical vehicles with time and cost awareness
4. World wide web and its journey from web 1.0 to web 4.0
5. MacKenzie, I.S. (2024). Human-Computer Interaction: An Empirical Research Perspective, Morgan Kaufmann.
6. Klašnja-Milićević, A., and Ivanović, M. (2021). E-learning personalization systems and sustainable education. Sustainability, 13.10.3390/su13126713 ↗
7. Kolb, D.A. (2014). Experiential Learning: Experience as the Source of Learning and Development, FT Press.
8. Educational data mining and learning analytics: An updated survey10.1002/widm.1355 ↗
9. Digital collaboration inside and outside educational systems10.1177/2042753014567245 ↗
10. Digital professional development: Towards a collaborative learning approach for taking higher education into the digitalized age10.18261/issn.1891-943x-2018-01-03 ↗
11. Digital Accessibility Education in Context: Expert Perspectives on Building Capacity in Academia and the Workplace10.1145/3649508 ↗
12. On the students’ perceptions of the knowledge formation when submitted to a Project-Based Learning environment using web applications10.1016/j.compedu.2017.10.001 ↗
13. Trends In Educational Training for Agriculture In Olt County
14. Wang, F., Wang, W., Yang, H., and Pan, Q. (2009, January 19–20). A novel discrete differential evolution algorithm for computer-aided test-sheet composition problems. Proceedings of the Information Engineering and Computer Science ICIECS 2009, Wuhan, China.10.1109/ICIECS.2009.5363231 ↗
15. Science, D. (2024, March 27). Dimensions [Software]. Free Version. Digital Science, London, UK. Under Licence Agreement. Available online: https://www.dimensions.ai.
16. Vosviewer10.1080/07317131.2018.1425352 ↗
17. Learning Management System (LMS) use with online instruction10.46328/ijte.36 ↗
18. Ortakand, B.R. (2024). Monitor and Predict Student Engagement and Retention Using Learning Management System (LMS). Teaching and Learning in the Digital Era: Issues and Studies, World Scientific Publishing Co Pte Ltd.10.1142/9789811285622_0010 ↗
19. Exploring pedagogical foundations of existing virtual reality educational applications: A content analysis study10.1177/0047239517745560 ↗
20. How educational are “educational” apps for young children? App store content analysis using the Four Pillars of Learning framework10.1080/17482798.2021.1882516 ↗
21. Comprehensive Insights into E-Learning in Contemporary Education: Analyzing Trends, Challenges, and Best Practices10.51178/jetl.v6i1.1720 ↗
22. What is a significant educational experience?10.1111/j.1467-9752.2011.00820.x ↗
23. Video-based learning assistant scheme for sustainable education10.1080/13614568.2019.1678682 ↗
24. Towards pervasive mobile learning–the vision of 21st century10.1016/j.sbspro.2011.04.247 ↗
25. AI-enabled adaptive learning systems: A systematic mapping of the literature10.1016/j.caeai.2021.100017 ↗
26. O’Donnell, A.M., and Hmelo-Silver, C.E. (2013). Introduction: What is collaborative learning?: An overview. The International Handbook of Collaborative Learning, Taylor and Francis.10.4324/9780203837290 ↗
27. Hamari, J., Xi, N., Legaki, Z., and Morschheuser, B. (2023, January 3–6). Gamification. Proceedings of the Hawaii International Conference on System Sciences, Maui, HI, USA.
28. Professional development with universal design for learning: Supporting teachers as learners to increase the implementation of UDL
29. Knowing what all students know: Procedures for developing universal design for assessment
30. An overview of learning analytics10.1080/13562517.2013.827653 ↗
31. Bokander, L. (2022). Psychometric Assessments. The Routledge Handbook of Second Language Acquisition and Individual Differences, Routledge.10.4324/9781003270546-36 ↗
32. Moses, T. (2017). A Review of Developments and Applications in Item Analysis. Methodology of Educational Measurement and Assessment, Springer.10.1007/978-3-319-58689-2_2 ↗
33. Challenges for information technology supporting educational assessment10.1111/jcal.12033 ↗
34. Towards more substantively meaningful automated essay scoring
35. On the relation between automated essay scoring and modern views of the writing construct10.1016/j.asw.2012.10.002 ↗
36. Artificial intelligence in educational assessment: ‘Breakthrough? Or buncombe and ballyhoo?’10.1111/jcal.12577 ↗
37. Multiple-choice question generation with auto-generated distractors for computer-assisted educational assessment10.1007/s11042-021-11222-2 ↗
38. Automatic Multiple Choice Question Generation From Text: A Survey10.1109/TLT.2018.2889100 ↗
39. Zou, B., Pengfei, L., Liangming, P., and Ai, T.A. Automatic True/False Question Generation for Educational Purpose. Proceedings of the 17th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2022).10.18653/v1/2022.bea-1.10 ↗
40. Factual open cloze question generation for assessment of learner’s knowledge
41. Malafeev, A. (2014). Automatic Generation of Text-Based Open Cloze Exercises. Communications in Computer and Information Science, Springer.10.1007/978-3-319-12580-0_14 ↗
42. Husam, A., Yllias, C., and Sadid, A.H. (2010, January 19–22). Automatic Question Generation from Sentences. Proceedings of the Actes de la 17e Conférence sur le Traitement Automatique des Langues Naturelles, Montréal, QC, Canada.
43. Zheng, X. (2022). Automatic Question Generation from Freeform Text. [Master’s Thesis, Nanyang Technological University].
44. The eras and trends of automatic short answer grading10.1007/s40593-014-0026-8 ↗
45. Mohd, J.A.A., Fatimah, D.A., Abdul, A.A.G., and Ramlan, M. (2009, January 25–27). Automated marking system for Short Answer Examination (AMS-SAE). Proceedings of the 2009 IEEE Symposium on Industrial Electronics & Applications, Xi’an, China.
46. Zhong, V., Shi, W., Yih, W.T., and Zettlemoyer, L. (2022). RoMQA: A Benchmark for Robust, Multi-evidence Multi-answer Question Answering. arXiv.10.18653/v1/2023.findings-emnlp.470 ↗
47. Development of a practical system for computerized evaluation of descriptive answers of Middle School Level Students
48. Ganz, R. (1966). An individualistic approach to item analysis. Readings in Mathematical Social Science, The MIT Press.
49. Testing & the impact of item analysis in improving students’ performance in end-of-year final exams10.5430/elr.v11n2p30 ↗
50. The axioms and principal results of classical test theory10.1016/0022-2496(66)90002-2 ↗
51. Weiss, D.J., and Yoes, M.E. (1991). Item response theory. Advances in Educational and Psychological Testing: Theory and Applications, Springer.10.1007/978-94-009-2195-5_3 ↗
52. An NCME instructional module on Comparison of classical test theory and item response theory and their applications to test development10.1111/j.1745-3992.1993.tb00543.x ↗
53. Knowledge Tracing: A Survey10.1145/3569576 ↗
54. Popescu, D.A., Nijloveanu, D., and Bold, N. Approaches on Generating Optimized Sequences of Items Used in Assessment. Proceedings of the GeNeDis 2016: Computational Biology and Bioinformatics.10.1007/978-3-319-56246-9_6 ↗
55. The generation of tests of knowledge check using genetic algorithms10.1007/978-3-319-62524-9_3 ↗
56. Reusing Assessments Tests by Generating Arborescent Test Groups Using a Genetic Algorithm
57. Popescu, D.A., Bold, N., and Domşa, O. (2016, January 1–3). Generating assessment tests with restrictions using genetic algorithms. Proceedings of the 2016 12th IEEE International Conference on Control and Automation (ICCA), Kathmandu, Nepal.10.1109/ICCA.2016.7505360 ↗
58. Popescu, D.A., Constantin, D., and Bold, N. (2023, January 1–4). Generating assessment tests using image-based items. Proceedings of the 2023 IEEE International Conference on Data Mining Workshops (ICDMW), Shanghai, China.10.1109/ICDMW60847.2023.00054 ↗
59. Learning Using Connections Between Concepts10.12753/2066-026X-17-033 ↗
60. Popescu, D.A., Nijloveanu, D., and Bold, N. (2019, January 20–22). Generator of Tests for Learning Check in Case of Courses that Use Learning Blocks. Proceedings of the Methodologies and Intelligent Systems for Technology Enhanced Learning, 8th International Conference, Toledo, Spain.10.1007/978-3-319-98872-6_28 ↗
61. Puzzle Learning Trail Generation Using Learning Blocks10.1007/978-3-030-51992-6_30 ↗
62. Determining the Similarity of Two Web Applications Using the Edit Distance. In Proceedings of the Soft Computing Applications-Proceedings of the 6th International Workshop Soft Computing Applications, SOFA 2014, Volume 1, Timisoara, Romania, 24–26 July 2014
63. Popescu, D.A., Domsa, O., and Bold, N. (March, January 27). The Determination of the Learning Performance based on Assessment Item Analysis. Proceedings of the CSW@WSDM, Singapore.
64. Popescu, D.A., Cristea, D.M., and Bold, N. (2023, January 2–5). On an Integrated Assessment for the Students Within an Academic Consortium. Proceedings of the International Conference on Intelligent Tutoring Systems, Corfu, Greece.