Evaluating Computerized Adaptive Testing Efficiency in Measuring Students’ Performance in Science TIMSS
Abstract
The current standards of assessment are demanding for high level of precision with less time-consuming and personalized opportunities, thus restrict the function of Paper and Pencil Test which has dominated the assessment field for a very long time. The Computerized Adaptive Testing (CAT) is viewed as an alternative testing tool to Paper and Pencil Test as it has adaptive feature which enables it to meet the current standards of assessment. This research is focusing on the evaluation of students’ ability in Grade 8 Science Trend in International Mathematics and Science Study (TIMSS) using Computerized Adaptive Testing (CAT) as an alternative instrument to Paper and Pencil Test to investigate whether the implementation of CAT can produce high level of precision with fewer items administered as well as differentiate different academic level among groups of students. CAT was configured in Concerto and was administered on Form 2 and Form 4 students selected through purposive sampling method from secondary schools in northern part of Malaysia. Students’ performance was analysed and compared in terms of score (theta value), SEM value and their response toward the items selected in CAT using SPSS. Finding shows that the administration of 20 objective items in fixed length CAT produced SEM ≤0.50 indicated that the implemented CAT increased the efficiency of assessment with fewer item administration. The t test showed that there was a significance difference between the two groups’ scores in CAT in which Form 4 students had higher ability level than Form 2 students proving that CAT’s configuration had been done correctly in Concerto and the test was more suitable in challenging Form 2 students’ Science knowledge thus the instrument fulfilled the known-group validity.
Keywords
Full Text:
PDFReferences
Aybek, E.C. &Demirtasli, R.N. (2017). Computerized Adaptive Test (CAT) Applications and Item Response Theory Models for Polytomous Items.International Journal of Research in Education and Science (IJRES),3(2), 475-487.
Bakker, S. (2014).The Introduction of Large-Scale Computer Adaptive Testing in Georgia.Russia Education Aid for Development. Retrieved from http://siteresources.worldbank.org/INTREAD/Resources/BakkerIntroductiontoCATGeorgiaforREAD.pdf
Barnard, J. J. (2018). From Simulation to Implementation: Two CAT Case Studies. Practical Assessment, Research & Evaluation, 23(14), 1-8. Retrieved from http://paronline.net/getvn.asp?v=23&n=14
Betz, N. E., & Turner, B. M. (2011). Using Item Response Theory and Adaptive Testing in Online Career Assessment. Journal of Career Assessment, 19(3), 274–286.
Beuchert, L. V. &Nandrup, A. B. (2015).The Danish National Test- A Practical Guide. Economic Working Papers. Retrieved from http://econ.au.dk/fileadmin/sitefiles/fileroekonomi/WorkingPapers/Economics/2014/wp1425.pdf
Chuesathuchon, C., & Waugh, R. F. (2010). Item Banking With Rasch Measurement : an Example for Primary Mathematics in Thailand. In EDU-COM 2008 International Conference. Sustainability in Higher Education: Directions for Change (pp. 19–21). Perth Western Australia. Retrieved from http://ro.ecu.edu.au/cgi/viewcontent.cgi?article=1007&context=ceducom
Davey, T. (2011). A Guide to Computer Adaptive Testing Systems. Washington, DC: Council of Chief School Officers. Retrieved from https://www.semanticscholar.org/paper/A-Guide-to-Computer-Adaptive-Testing-Systems-Davey/71d9d258a7b161db2a3848b85afaedc10 5ef11fa
Desa, Z. N. D. & Abdul Latif, A. (2007) Computerized Adaptive Testing: An Alternative Assessment Method. In: Simposium Pengajaran dan Pembelajaran UTM, Johor Bahru.
Fraenkel, J. R. &Wallen, N. E. (2009). How to Design and Evaluate Research in Education (7th Ed.). New York: McGraw-Hill.
IACAT. (2016, July 12). Operational CAT Programmes. Retrieved from http://www.iacat.org/content/operational- cat-programs.
Kalender, İ. (2012). Computerized adaptive testing for student selection to higher education. Yükseköğretim Dergisi, 2(1), 13-19.
Kiran, S., Kiani, A., Kayani, S.,Shahzadi, E., Sehar, A., Akhtar, K., Sohail, A. & Kayani, S. (2012). An Exploratory Study of Student’s Attitudes towards Online Assessment. International Journal of Humanities and Social Science,2(4), 304-309. Retrieved from http://www.pearsonassessments.com/research
Lazarus,S. (2010). Educational Psychology: In Social Context (4th edition). Cape Town: Oxford University Press.
Lilley, M. & Barker, T. (2003). Comparison between Computer Adaptive Testing and other Assessment Methods: An Empirical Study. Proceedings of 10th International Conference of the Association for Learning Technology (ALT-C), University of Sheffield, United Kingdom.
Linden, W. J. & Glas, C. A. W. (Eds.). (2010). Elements of Adaptive Testing. (Statistics for Social and Behavioral Sciences Series). New York: Springer.
Magis, D., & Barrada, J. R. (2017). Computerized Adaptive Testing with R: Recent Updates of the Package catR. Journal of Statistical Software, 76(1), 1-19.
Magis, D. & Raîche, G. (2012). Random Generation of Response Patterns under Computerized Adaptive Testing with the R Package catR. Journal of Statistical Software,48(8), 1–31.
Mansoor Al-A’ali. (2007). Implementation of an Improved Adaptive Testing Theory. Journal of Educational Technology and Society, 10(4), 80-94. Retrieved from https://www.reserachgate.net/publication/220374538_Implementation_of_an_Improved_Adaptive_Testing_Theory
Martin, A. J., & Lazendic, G. (2018). Computer-Adaptive Testing: Implications for Students’ Achievement, Motivation, Engagement, and Subjective Test Experience. Journal of educational psychology, 110(1), 27-45.
Ministry of Education (MOE) (2013). Pelan Pembangunan Pendidikan Malaysia 2013-2025. Retrieved from http://www.moe.gov.my/cms/upload_files/articlefile/2013/articlefile_file_003107.pdf
Mizumoto, A., Sasao, Y. & Webb, S. A. (2017). Developing and Evaluating A Computerized Adaptive Testing Version of the Word Part Levels Test. Language Testing, 36(1), 101-123.
Mullis, I. V. S. & Martin, M. O. (Eds.). (2017). TIMSS 2019 Assessment Framework. TIMSS & PIRLS International Study Center Lynch School of Education. Retrieved from http://timssandpirls.bc.edu/timss2019/frameworks/
National Survey of Student Engagement (NSSE).(2009). Validity – 2009 Known Groups Validation. Retrieved from http://nsse.indiana.edu/html/validity.cfm
Norah Md. Noor, & Noor AzeanAtan. (2008). Tahap Kesediaan dan Keyakinan Pelajar terhadap Penggunaan Ujian Adaptif dalam Mempelajari Konsep Pengaturcaraan Komputer. Proceedings of the 2nd International Malaysian Educational Technology Convention (pp. 271–278). Kuala Lumpur: META.
NorainiIdris. (2013). Penyelidikan dalam Pendidikan (2nd Ed.). Malaysia: McGraw-Hill Education (Malaysia) Sdn. Bhd.
Oppl, S., Reisinger, F., Eckmaier, A. & Helm, C. (2017). A Flexible Online Platform for Computerized Adaptive Testing. International Journal of Educational Technology in Higher Education, 14(2).
Özdemir, B. (2016). Comparison of Different Unidimensional-CAT Algorithms Measuring Students’ Language Abilities: Post-hoc Simulation Study. The European Proceedings of Social & Behavioural Sciences. Retrieved from http://dx.doi.org/10.15405/epsbs.2016.11.42
Pallant, J. (2011). SPSS Survival Manual: A Step by Step Guide to Data Analysis using SPSS (4thed.). Australia: Allen & Unwin.
Psychometric Unit, University of Cambridge. (2018). Open Source Online R-based Adaptive Testing Platform. Retrieved from http://www.psychometric.cam.ac.uk/newconcerto
Ryan, J. &Brockmann, F. (2018).A Practitioner’s Introduction to Equating. Washington, DC: Council of Chief State School Officers.
Scalise, K. & Allen, D. D. (2015). Use of Open-Source Software for Adaptive Measurement: Concerto as an R-based Computer Adaptive Development and Delivery Platform. British Journal of Mathematical and Statistical Psychology, 68(3), 478-496. Retrieved from https://doi.org/10.1111/bmsp.12057
Umar, N. I. & Hassan, S. A. (2015). Malaysia Teachers Levels of ICT Integration and its Perceived Impact on Teaching and Learning. Procedia-Social and Behavioral Sciences, 197, 2015-2021.
Utah State Board of Education. (2018). RISE: Readiness Improvement Success Empowerment. Retrieved from https://www.schools.utah.gov/
Venables, W. N., Smith, D. M. & The R Core Team. (2018, December 20). An Introduction to R. Retrieved from https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf
Refbacks
- There are currently no refbacks.