Implementing Computer Adaptive Testing for High-Stakes Assessment: A Shift for Examinations Council of Lesotho

作者

  • Musa Adekunle Ayanwale National University of Lesotho 莱索托 https://orcid.org/0000-0001-7640-9898
  • Julia Chere-Masopha National University of Lesotho 莱索托
  • Mapulane Mochekele National University of Lesotho 莱索托
  • Malebohang Catherine Morena National University of Lesotho 莱索托

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https://doi.org/10.24310/ijne.14.2024.20487

关键词:

评估技术, 计算机自适应测试, 教育测量, 莱索托考试委员会, 高水平评估

摘要

我们研究了将计算机辅助测试（CAT）应用于莱索托高风险评估的可行性，特别是通过莱索托考试委员会（ECoL）。计算机辅助测试是一种最先进的评估方法，可根据考生的能力实时调整测试项目，从而提高准确性和效率。尽管计算机辅助考试已在全球范围内得到广泛应用，但在发展中国家的实施却面临着巨大的挑战，尤其是在基础设施、专业知识和资源限制等方面。我们的研究弥补了莱索托等发展中国家在了解如何将计算机辅助考试有效融入教育系统方面的重大空白。我们在五个数据库（谷歌学术、ERIC、PsycINFO、JSTOR 和 PubMed）中进行了文献综述，共检索到 2013 年至 2023 年间发表的 48 篇研究。其中，18 项研究符合我们的纳入标准，重点关注 CAT 在教育评估中的优势、挑战和实际应用。我们采用主题分析法来确定主要优势和障碍，重点关注准确性、公平性和基础设施要求。我们概述了 CAT 开发的基本阶段，包括可行性研究、项目库创建、预测试和校准、规格确定以及实时发布 CAT。我们强调了一些关键任务，如使用蒙特卡洛模拟验证计算机辅助测试的可行性，以及开发使用项目反应理论（IRT）校准的强大项目库。我们还讨论了建立强大的技术基础设施、对利益相关者进行全面培训和确保充足资金等挑战。我们强调持续评估和利益相关者参与的重要性，以确保计算机辅助测验的成功实施和可持续性。全球趋势表明，在心理测量学和技术进步的推动下，CAT 的采用率正在不断提高。计算机辅助学习有可能提供更公平、更准确的评估，使其成为改善莱索托教育成果的一个前景广阔的解决方案。

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Department of Educational Foundations, National University of Lesotho

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Department of Educational Foundations

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Department of Educational Foundations, National University of Lesotho, Lesotho.

 

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Department of Educational Foundations

参考

Ayanwale, M. A., Chere-Masopha, J., & Morena, M. C. (2022). The Classical Test or Item Response Measurement Theory: The Status of the Framework at the Examination Council of Lesotho. International Journal of Learning, Teaching and Educational Research, 21(8), 384–406. https://doi.org/10.26803/IJLTER.21.8.22

Ayanwale, M. A., & Ndlovu, M. (2022). Transition from computer-based testing of national benchmark tests to adaptive testing: Robust application of fourth industrial revolution tools. Cypriot Journal of Educational Sciences, 17(9), 3327–3343. https://doi.org/10.18844/CJES.V17I9.7124

Han, K. C. T. (2018a). Components of the item selection algorithm in computerized adaptive testing. Journal of Educational Evaluation for Health Professions, 15, 7. https://doi.org/10.3352/JEEHP.2018.15.7

Han, K. C. T. (2018b). Conducting simulation studies for computerized adaptive testing using SimulCAT: an instructional piece. Journal of Educational Evaluation for Health Professions, 15, 20. https://doi.org/10.3352/jeehp.2018.15.20

Han, K. T. (2012). SimulCAT: Windows Software for Simulating Computerized Adaptive Test Administration. Applied Psychological Measurement, 36(1), 64–66. https://doi.org/10.1177/0146621611414407

Han, K. T. (2016). Maximum Likelihood Score Estimation Method With Fences for Short-Length Tests and Computerized Adaptive Tests. Applied Psychological Measurement, 40(4), 289–301. https://doi.org/10.1177/0146621616631317

Leroux, A. J., Lopez, M., Hembry, I., & Dodd, B. G. (2013). A Comparison of Exposure Control Procedures in CATs Using the 3PL Model. Educational and Psychological Measurement, 73(5), 857–874. https://doi.org/10.1177/0013164413486802

Meijer, R. R., & Nering, M. L. (n.d.). Computerized Adaptive Testing: Overview and Introduction.

Mujtaba, D. F., & Mahapatra, N. R. (2020). Artificial Intelligence in Computerized Adaptive Testing. Proceedings - 2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020, 649–654. https://doi.org/10.1109/CSCI51800.2020.00116

Ogunjimi, M. O., Ayanwale, M. A., Oladele, J. I., Daramola, D. S., Jimoh, I. M., & Owolabi, H. O. (2021). Simulated evidence of computer adaptive test length: Implications for high stakes assessment in Nigeria. Journal of Higher Education Theory and Practice, 21(2), 202–212. https://doi.org/10.33423/JHETP.V21I2.4129

Oladele, J. I., Ndlovu, M., & Spangenberg, E. D. (2022). Simulated computer adaptive testing method choices for ability estimation with empirical evidence. International Journal of Evaluation and Research in Education, 11(3), 1392–1399. https://doi.org/10.11591/IJERE.V11I3.21986

Oladele, J.I.; Ayanwale, M.A. ;Owolabi, H.O. (2020). Paradigm Shifts in Computer Adaptive Testing in Nigeria in Terms of Simulated Evidences. Journal of Social Science, 63(1–3), 9–20. https://doi.org/10.31901/24566756.2020/63.1-3.2264

Rice, N., Pêgo, J. M., Collares, C. F., Kisielewska, J., & Gale, T. (2022). The development and implementation of a computer adaptive progress test across European countries. Computers and Education: Artificial Intelligence, 3. https://doi.org/10.1016/j.caeai.2022.100083

Seo, D. G. (2017). Overview and current management of computerized adaptive testing in licensing/certification examinations. Journal of Educational Evaluation for Health Professions, 14, 17. https://doi.org/10.3352/JEEHP.2017.14.17

Stepanek, L., & Martinkova, P. (2020). Feasibility of computerized adaptive testing evaluated by Monte-Carlo and post-hoc simulations. Proceedings of the 2020 Federated Conference on Computer Science and Information Systems, FedCSIS 2020, 359–367. https://doi.org/10.15439/2020F197

Thompson, N. (2023). Computerized Adaptive Testing (CAT): An Introduction. https://assess.com/computerized-adaptive-testing/ Access date: 11-04-2024

Thompson, N. A. (2009). Item selection in computerized classification testing. Educational and Psychological Measurement, 69(5), 778–793. https://doi.org/10.1177/0013164408324460

Thompson, N. A., & Weiss, D. J. (2009). Computerized and Adaptive Testing in Educational Assessment. In F. Scheuermann & J. Björnsson (Eds.), The Transition to Computer-Based Assessment: New Approaches to Skills Assessment and Implications for Large-scale Testing (pp. 127–133). European Commission.

Thompson, N. A., & Weiss, D. J. (2011). A framework for the development of computerized adaptive tests. Practical Assessment, Research and Evaluation, 16(1), 1–9.

Tsaousis, I., Sideridis, G. D., & AlGhamdi, H. M. (2021). Evaluating a Computerized Adaptive Testing Version of a Cognitive Ability Test Using a Simulation Study. Journal of Psychoeducational Assessment, 39(8), 954–968. https://doi.org/10.1177/07342829211027753

Viswanandhne, S., & Nandakumar, G. S. (2017). Computer-Based Adaptive Testing. 2(2), 686–691.

Wainer, H., Dorans, N. J., Flaugher, R., Green, B. F., & Mislevy, R. J. (2000). Computerized Adaptive Testing. Computerized Adaptive Testing. https://doi.org/10.4324/9781410605931/Computerized-Adaptive-Testing-Howard-Wainer-Neil-Dorans-Ronald-Flaugher-Bert-Green-Robert-Mislevy

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已出版

2024-12-09

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Ayanwale, M. A., Chere-Masopha, J., Mochekele, M., & Morena, M. C. (2024). Implementing Computer Adaptive Testing for High-Stakes Assessment: A Shift for Examinations Council of Lesotho. 國際新教育雜誌, (14). https://doi.org/10.24310/ijne.14.2024.20487

期

编号 14 (2024)

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