Adaptive Diagnostic Assessment Design through Google Forms Optimization and Jmetric to Detect Students' Mathematics Learning Difficulty Levels
Keywords:
adaptive diagnostic assesment design, Google Forms, jMetric, mathematics learning difficulty levelsAbstract
The level of difficulty students experience in learning mathematics can help teachers design learning activities that are appropriate for students' abilities and foster an independent learning environment. Google Forms and jMetric can be used as alternative software to construct adaptive assessments that accurately detect students' level of difficulty in learning mathematics and are easy to apply. The results of calibrating the content of the instrument with jMetric show that the overall instrument is in the “fairly good” category with a stratum of 2.81. Meanwhile, the development of adaptive assessments based on Google Forms is deemed valid in terms of website appeal and ease of use, with an average of 64.5%.
References
Abdullah, A. H., Abidin, N. L. Z., & Ali, M. (2015). Analysis of students’ errors in solving Higher Order Thinking Skills (HOTS) problems for the topic of fraction. Asian Social Science, 11(21), 133–142.
Aikenhead, G. S. (2021). A 21st century culture-based mathematics for the majority of students. Philosophy of Mathematics Education Journal, 37, 1–35.
Akhter, N., & Akhter, N. (2018). Learning in Mathematics: Difficulties and Perceptions of Students. Journal of Educational Research (1027-9776), 21(1).
Aksu, G., GÜZELLER, C. E. M., & Eser, M. (2019). JMETRIK: Classical test theory and item response theory data analysis software. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 10(2).
Anggara, B. (2020). Pengembangan soal higher order thinking skills sebagai tes diagnostik miskonsepsi matematis Siswa SMA. Algoritma: Journal of Mathematics Education, 2(2), 176–191.
Anggara, B., & Solahudin, I. (2022). Newman’s Error Analysis on Students’ Solving Numerical Problems Ability. Jurnal Pendidikan Matematika (Kudus), 5(2), 169–184.
Anggara, B., & Wandari, W. (2021). Misconceptions of senior high school students in solving high-order thinking skills questions. Journal of Physics: Conference Series, 1918(4), 042089.
Azmi, F., William, W., Salim, K. K., Hartanto, T. T., & Tham, F. (2019). Design of Smart Trash Can Using Fuzzy Logic Algorithm Based on Arduino. JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING, 3(1), 150–154.
Belkhatir, R., Oussalah, M., & Viguier, A. (2013). A method and a tool for evaluating the quality of an SOA. Proceedings of the International Conference on Software Engineering Research and Practice (SERP), 1.
Cetin-Berber, D. D., Sari, H. I., & Huggins-Manley, A. C. (2019). Imputation methods to deal with missing responses in computerized adaptive multistage testing. Educational and Psychological Measurement, 79(3), 495–511.
Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two decades of artificial intelligence in education. Educational Technology & Society, 25(1), 28–47.
Ebenbeck, N., & Gebhardt, M. (2022). Simulating computerized adaptive testing in special education based on inclusive progress monitoring data. Frontiers in Education, 7, 945733.
Elastika, R. W., & Dewanto, S. P. (2021). Analysis of Factors Affecting Students’ Mathematics Learning Difficulties Using SEM as Information for Teaching Improvement. International Journal of Instruction, 14(4), 281–300.
Fuchs, L. S., Fuchs, D., Malone, A. S., Seethaler, P. M., & Craddock, C. (2019). The role of cognitive processes in treating mathematics learning difficulties. In Cognitive foundations for improving mathematical learning (pp. 295–320). Elsevier.
Gusev, M., & Armenski, G. (2013). E-assessment systems and online learning with adaptive testing. In E-Learning Paradigms and Applications: Agent-based Approach (pp. 229–249). Springer.
Haddad, R. J., & Kalaani, Y. (2014). Google forms: A real-Time formative feedback process for adaptive learning. 2014 ASEE Annual Conference & Exposition, 24–649.
Hadianti, Y., Musthafa, B., & Fuadah, U. S. (2021). Learning from Home Activity Using Google Form Application toward Online Learning Assessment in Elementary School. International Conference on Elementary Education, 3(1), 606–610.
Harsela, K., Asih, E. C. M., & Dasari, D. (2021). Level of mastery of mathematical skills and mathematical resilience. Journal of Physics: Conference Series, 1806(1), 012078.
Hasan, A., & Fraser, B. J. (2015). Effectiveness of teaching strategies for engaging adults who experienced childhood difficulties in learning mathematics. Learning Environments Research, 18, 1–13.
Hasanah, N., Inganah, S., & Maryanto, B. P. A. (2023). Learning in the 21st century education era: Problems of mathematics teachers in the use of information and communication technology-based media. JEMS: Jurnal Edukasi Matematika Dan Sains, 11(1), 275–285.
Hula, W. D., Kellough, S., & Fergadiotis, G. (2015). Development and simulation testing of a computerized adaptive version of the Philadelphia Naming Test. Journal of Speech, Language, and Hearing Research, 58(3), 878–890.
Inayati, U. (2022). Konsep dan implementasi kurikulum merdeka pada pembelajaran abad-21 di SD/MI. ICIE: International Conference on Islamic Education, 2, 293–304.
Ishak, H., Sukestiyarno, Y. L., Waluya, S. B., & Mariani, S. (2021). Description of student’s difficulty in understanding online mathematics learning materials. Journal of Physics: Conference Series, 1918(4), 042095.
Istiyono, E., Dwandaru, W. S. B., Setiawan, R., & Megawati, I. (2020). Developing of Computerized Adaptive Testing to Measure Physics Higher Order Thinking Skills of Senior High School Students and Its Feasibility of Use. European Journal of Educational Research, 9(1), 91–101.
Kaplan, M., de la Torre, J., & Barrada, J. R. (2015). New item selection methods for cognitive diagnosis computerized adaptive testing. Applied Psychological Measurement, 39(3), 167–188.
Kleden, M. A., Lobo, M., Lapenangga, G., & Sugi, Y. (n.d.). Analysis of Difficulty Level on The Topic Line and Angle. Journal of Mathematics and Mathematics Education, 10(1), 1–9.
Langoban, M. A., & Langoban, M. A. (2020). What makes mathematics difficult as a subject for most students in higher education. International Journal of English and Education, 9(3), 214–220.
Liu, C., Zhang, D., Pandolpho, M., & Yi, J. (2023). Effects of Principled Digitalized Interactive Components on Geometry Computer-Based Assessment in High Schoolers With Learning Difficulties in Mathematics: A Preliminary Investigation. Assessment for Effective Intervention, 49(1), 29–40.
Loh, C. H., & Lee, S. P. (2008). Towards A Dynamic Object-Oriented Design Metric Plug-in Framework. Journal of Computer Science, 4(11), 903.
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.
Mutflu, Y., & Akgün, L. (2019a). Using Computer for Developing Arithmetical Skills of Students with Mathematics Learning Difficulties. International Journal of Research in Education and Science, 5(1), 237–251.
Mutflu, Y., & Akgün, L. (2019b). Using Computer for Developing Arithmetical Skills of Students with Mathematics Learning Difficulties. International Journal of Research in Education and Science, 5(1), 237–251.
Nelson, G., & Powell, S. R. (2018). A systematic review of longitudinal studies of mathematics difficulty. Journal of Learning Disabilities, 51(6), 523–539.
Özyurt, H., Özyurt, Ö., Baki, A., & Güven, B. (2012). Integrating computerized adaptive testing into UZWEBMAT: Implementation of individualized assessment module in an e-learning system. Expert Systems with Applications, 39(10), 9837–9847.
Plomp, T. (2013). Educational design research: An introduction. Educational Design Research, 1, 11–50.
Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), 22.
Powell, S. R., Lembke, E. S., Ketterlin-Geller, L. R., Petscher, Y., Hwang, J., Bos, S. E., Cox, T., Hirt, S., Mason, E. N., & Pruitt-Britton, T. (2021). Data-based individualization in mathematics to support middleschool teachers and their students with mathematics learning difficulty. Studies in Educational Evaluation, 69, 100897.
Pramesti, C., & Prasetya, A. (2021). Analisis tingkat kesulitan belajar matematika siswa dalam menggunakan prinsip matematis. Edumatica: Jurnal Pendidikan Matematika, 11(02), 9–17.
Rajnish, K. (2014). Another New Complexity Metric for Object-Oriented Design Measurement. International Journal of Hybrid Information Technology, 7(2), 203–216.
Reiser, R. A., & Dempsey, J. V. (2012). Trends and issues in instructional design and technology. Pearson Boston.
Rinaldi, R., Wiyaka, W., & Prastikawati, E. F. (2022). Google form as an online assessment tool to improve the students’ vocabulary mastery. SALEE: Study of Applied Linguistics and English Education, 3(1), 56–71.
Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26, 582–599.
Samawati, I. (2021). STUDENTS’MATHEMATICAL COMMUNICATION SKILLS IN SOLVING STORY PROBLEMS BASED ON MATHEMATICAL ABILITIES. IJIET (International Journal of Indonesian Education and Teaching), 5(1), 61–70.
Samsudin, M. A., Chut, T. S., & Ismail, M. E. (2019). Evaluating Computerized Adaptive Testing Efficiency in Measuring Studentsâ€TM Performance in Science TIMSS. Jurnal Pendidikan Ipa Indonesia, 8(4), 547–560.
Santoso, D. A., Farid, A., & Ulum, B. (2017). Error analysis of students working about word problem of linear program with NEA procedure. Journal of Physics: Conference Series, 855(1), 012043.
Sari, A., Iswahyuni, D., Rejeki, S., & Sutanto, S. (2020). Google Forms as an EFL assessment tool: Positive features and limitations.
Septiani, A. (2022). Implementasi kurikulum merdeka ditinjau dari pembelajaran matematika dan pelaksanaan P5 (studi di SMA Negeri 12 Kabupaten Tangerang). AKSIOMA: Jurnal Matematika Dan Pendidikan Matematika, 13(3), 421–435.
Sibaen, N. W., Buasen, J. A., & Alimondo, M. S. (2023). Principal Components of Students’ Difficulties in Mathematics in the Purview of Flexible Learning. Journal on Mathematics Education, 14(2), 353–374.
Stroulia, E., & Kapoor, R. (2001). Metrics of refactoring-based development: An experience report. OOIS 2001: 7th International Conference on Object-Oriented Information Systems, 27–29 August 2001, Calgary, Canada Proceedings, 113–122.
Tessmer, M. (2013). Planning and conducting formative evaluations. Routledge.
Uegatani, Y., Otani, H., Shirakawa, S., & Ito, R. (2024). Real and illusionary difficulties in conceptual learning in mathematics: Comparison between constructivist and inferentialist perspectives. Mathematics Education Research Journal, 36(4), 895–915.
Wandari, W., & Anggara, B. (2021). Analysis of students difficulties in completing mathematical communication problems. Journal of Physics: Conference Series, 1918(4), 042090.
Wandari, W., & Fardillah, F. (2021). Comparison of mathematic communication ability through problem based learning and guided discovery. Journal of Physics: Conference Series, 1764(1), 012116.
Whittaker, J. A., Arbon, J., & Carollo, J. (2012). How Google tests software. Addison-Wesley.
Wijaya, A., Retnawati, H., Setyaningrum, W., & Aoyama, K. (2019). Diagnosing Students’ Learning Difficulties in the Eyes of Indonesian Mathematics Teachers. Journal on Mathematics Education, 10(3), 357–364.
Wijaya, A., van den Heuvel-Panhuizen, M., Doorman, M., & Robitzsch, A. (2014). Difficulties in solving context-based PISA mathematics tasks: An analysis of students’ errors. The Mathematics Enthusiast, 11(3), 555–584.
Yang, A. C. M., Flanagan, B., & Ogata, H. (2022). Adaptive formative assessment system based on computerized adaptive testing and the learning memory cycle for personalized learning. Computers and Education: Artificial Intelligence, 3, 100104.
Yuberta, K. R., Mahdi, Y., Nari, N., & Yulivia, M. (2022). Analysis of factors affecting difficulties in learning mathematics during online learning. AIP Conference Proceedings, 2524(1).
Žakelj, A. (n.d.). Teachers’ views on the causes of pupils’ learning difficulties in mathematics. 2014 Letnik 29, 55.
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