Testes Adaptativos Computadorizados baseados na Teoria de Resposta ao Item em Sistemas e-learning: uma revisão sistemática da literatura
Resumo
Testes Adaptativos Computadorizados (CAT) baseados na Teoria de Resposta ao Item (IRT) permitem realizar avaliações mais precisas e mostram vantagens quando incorporados a ambientes de aprendizado virtual (e-learning). Entretanto, devido à multiplicidade de soluções, este conhecimento encontra-se fragmentado na literatura, o que dificulta o entendimento dos dissensos e desafios enfrentados na área. Neste sentido, este trabalho buscou entender e caracterizar os estudos que usam CAT e IRT que estão inseridos em sistemas e-learning. Para tal, uma revisão sistemática da literatura foi realizada, na qual quatro questões de pesquisa foram analisadas em 9 artigos previamente selecionados pelos critérios estabelecidos no protocolo de revisão.
Palavras-chave:
Testes Adaptativos Computadorizados, Teoria de Resposta ao Item, sistemas e-learning
Referências
Baker, F. B. and Kim, S.-H. (2004). Item response theory: Parameter estimation techniques. CRC Press.
Birnbaum, A. (1968). Some latent trait models and their use in inferring an examinee’s ability. Statistical theories of mental test scores
Chen, C.-M., Lee, H.-M., and Chen, Y.-H. (2005). Personalized e-learning system using item response theory. Computers & Education, 44(3):237–255.
Chen, C.-M., Liu, C.-Y., and Chang, M.-H. (2006). Personalized curriculum sequencing utilizing modified item response theory for web-based instruction. Expert Systems with Applications, 30(2):378 – 396.
de Andrade, D. F., Tavares, H. R., and da Cunha Valle, R. (2000). Teoria da resposta ao item: conceitos e aplicações. ABE, Sao Paulo.
Guzmán, E. and Conejo, R. (2004). A model for student knowledge diagnosis through adaptive testing. In International Conference on Intelligent Tutoring Systems, pages 12–21. Springer.
Heitink, M. and Veldkamp, D. B. P. (2015). Computer adaptive assessment for learning in a virtual learning environment. In Proceedings of the 18th International Computer Assisted Assessment Conference, number 571, pages 22 – 26. Springer.
Jeong, H.-Y. and Hong, B.-H. (2013). A service component based CAT system with SCORM for advanced learning effects. Multimedia Tools Appl., 63(1):217–226.
Kitchenham, B. A. (2012). Systematic review in software engineering: Where we are and where we should be going. In Proceedings of the 2Nd International Workshop on Evidential Assessment of Software Technologies, EAST ’12, pages 1–2. ACM.
Kovatcheva, E. and Nikolov, R. (2009). An adaptive feedback approach for e-learning systems. IEEE Technology and Engineering Education (ITEE), 4(1):55–57.
Lee, Y., Cho, J., Han, S., and Choi, B.-U. (2010). A personalized assessment system based on item response theory. In Proceedings of the International Conference on Advances in Web-Based Learning (ICWL 2010), pages 381–386. Springer Berlin Heidelberg.
Lendyuk, T., Rippa, S., and Sachenko, S. (2013). Simulation of computer adaptive learning and improved algorithm of pyramidal testing. In 2013 IEEE 7th International Conference on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), volume 02, pages 764–769.
Lilley, M., Barker, T., and Britton, C. (2005). Learners’ and tutors’ perspectives on the usefulness of an automated tool for feedback on test performance. In Proceedings of the European Conference on Games-based Learning, volume 2005-January, pages 181–190.
Lord, F. M. (1980). Applications of item response theory to practical testing problems. Routledge.
Ostini, R. and Nering, M. L. (2006). Polytomous item response theory models. Number 144. Sage.
Rajamani, K. and Kathiravan, V. (2013). An adaptive assessment system to compose serial test sheets using item response theory. In International Conference on Pattern Recognition, Informatics and Mobile Engineering, pages 120–124.
Rasch, G. (1960). Probabilistic models for some intelligence and achievement tests. Copenhagen: Danish Institute for Educational Research.
Spenassato, D., Trierweiller, A. C., de Andrade, D. F., and Bornia, A. C. (2016). Testes adaptativos computadorizados aplicados em avaliações educacionais. Revista Brasileira de Informatica na Educação, 24(2).
Wainer, H., Dorans, N. J., Flaugher, R., Green, B. F., and Mislevy, R. J. (2000). Computerized adaptive testing: A primer. Routledge.
Wauters, K., Desmet, P., and Van Den Noortgate, W. (2010). Adaptive item-based learning environments based on the item response theory: possibilities and challenges. Journal of Computer Assisted Learning, 26(6):549–562.
Wong, K., Leung, K., Kwan, R., and Tsang, P. (2010). E-learning: Developing a simple web-based intelligent tutoring system using cognitive diagnostic assessment and adaptive testing technology. In Third International Conference on Hybrid Learning (ICHL), pages 23–34. Springer Berlin Heidelberg.
Özyurt, H., Ozcan Ozyurt, Baki, A., and 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.
Birnbaum, A. (1968). Some latent trait models and their use in inferring an examinee’s ability. Statistical theories of mental test scores
Chen, C.-M., Lee, H.-M., and Chen, Y.-H. (2005). Personalized e-learning system using item response theory. Computers & Education, 44(3):237–255.
Chen, C.-M., Liu, C.-Y., and Chang, M.-H. (2006). Personalized curriculum sequencing utilizing modified item response theory for web-based instruction. Expert Systems with Applications, 30(2):378 – 396.
de Andrade, D. F., Tavares, H. R., and da Cunha Valle, R. (2000). Teoria da resposta ao item: conceitos e aplicações. ABE, Sao Paulo.
Guzmán, E. and Conejo, R. (2004). A model for student knowledge diagnosis through adaptive testing. In International Conference on Intelligent Tutoring Systems, pages 12–21. Springer.
Heitink, M. and Veldkamp, D. B. P. (2015). Computer adaptive assessment for learning in a virtual learning environment. In Proceedings of the 18th International Computer Assisted Assessment Conference, number 571, pages 22 – 26. Springer.
Jeong, H.-Y. and Hong, B.-H. (2013). A service component based CAT system with SCORM for advanced learning effects. Multimedia Tools Appl., 63(1):217–226.
Kitchenham, B. A. (2012). Systematic review in software engineering: Where we are and where we should be going. In Proceedings of the 2Nd International Workshop on Evidential Assessment of Software Technologies, EAST ’12, pages 1–2. ACM.
Kovatcheva, E. and Nikolov, R. (2009). An adaptive feedback approach for e-learning systems. IEEE Technology and Engineering Education (ITEE), 4(1):55–57.
Lee, Y., Cho, J., Han, S., and Choi, B.-U. (2010). A personalized assessment system based on item response theory. In Proceedings of the International Conference on Advances in Web-Based Learning (ICWL 2010), pages 381–386. Springer Berlin Heidelberg.
Lendyuk, T., Rippa, S., and Sachenko, S. (2013). Simulation of computer adaptive learning and improved algorithm of pyramidal testing. In 2013 IEEE 7th International Conference on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), volume 02, pages 764–769.
Lilley, M., Barker, T., and Britton, C. (2005). Learners’ and tutors’ perspectives on the usefulness of an automated tool for feedback on test performance. In Proceedings of the European Conference on Games-based Learning, volume 2005-January, pages 181–190.
Lord, F. M. (1980). Applications of item response theory to practical testing problems. Routledge.
Ostini, R. and Nering, M. L. (2006). Polytomous item response theory models. Number 144. Sage.
Rajamani, K. and Kathiravan, V. (2013). An adaptive assessment system to compose serial test sheets using item response theory. In International Conference on Pattern Recognition, Informatics and Mobile Engineering, pages 120–124.
Rasch, G. (1960). Probabilistic models for some intelligence and achievement tests. Copenhagen: Danish Institute for Educational Research.
Spenassato, D., Trierweiller, A. C., de Andrade, D. F., and Bornia, A. C. (2016). Testes adaptativos computadorizados aplicados em avaliações educacionais. Revista Brasileira de Informatica na Educação, 24(2).
Wainer, H., Dorans, N. J., Flaugher, R., Green, B. F., and Mislevy, R. J. (2000). Computerized adaptive testing: A primer. Routledge.
Wauters, K., Desmet, P., and Van Den Noortgate, W. (2010). Adaptive item-based learning environments based on the item response theory: possibilities and challenges. Journal of Computer Assisted Learning, 26(6):549–562.
Wong, K., Leung, K., Kwan, R., and Tsang, P. (2010). E-learning: Developing a simple web-based intelligent tutoring system using cognitive diagnostic assessment and adaptive testing technology. In Third International Conference on Hybrid Learning (ICHL), pages 23–34. Springer Berlin Heidelberg.
Özyurt, H., Ozcan Ozyurt, Baki, A., and 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.
Publicado
30/10/2017
Como Citar
JATOBÁ, Victor M. G.; DELGADO, Karina V.; FARIAS, Jorge S.; FREIRE, Valdinei.
Testes Adaptativos Computadorizados baseados na Teoria de Resposta ao Item em Sistemas e-learning: uma revisão sistemática da literatura. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 28. , 2017, Recife/PE.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2017
.
p. 273-283.
DOI: https://doi.org/10.5753/cbie.sbie.2017.273.
