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2020 | OriginalPaper | Chapter

Research on DINA Model in Online Education

Authors : Jia Liu, Wensheng Tang, Xuping He, Bo Yang, Shengchun Wang

Published in: e-Learning, e-Education, and Online Training

Publisher: Springer International Publishing

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Abstract

Learning tests play an important role in both traditional learning and online learning. The traditional education test can only report students’ scores or abilities, but not their knowledge level, which is no longer satisfied with people’s requirements. In recent years, DINA model of cognitive diagnosis model has been widely used to diagnose students’ knowledge mastery. DINA model can dig out the students’ knowledge points and give feedback to the teachers, so that the teachers can make remedial plans for the students’ deficiencies in time. This paper first introduces the basic principle of DINA model and the improvement of DINA model in the field of education in recent years. Secondly, we introduce the development of Dina model under the trend of online education, and prove the availability of DINA model in online platform with experimental data. Finally, we predict and analyze the research direction of DINA algorithm in the future.

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Literature
1.
go back to reference Chen, Q.M., Zhang, M.Q.: Development of cognitive diagnosis models and their application methods. Adv. Psychol. Sci. 18(03), 522–529 (2010) Chen, Q.M., Zhang, M.Q.: Development of cognitive diagnosis models and their application methods. Adv. Psychol. Sci. 18(03), 522–529 (2010)
2.
go back to reference Dongbo, T., Cai, Y., Qi, S., Dai, H.: A review on cognitive diagnostic models under modern test theory. Psychol. Explor. 28(2), 64–68 (2008) Dongbo, T., Cai, Y., Qi, S., Dai, H.: A review on cognitive diagnostic models under modern test theory. Psychol. Explor. 28(2), 64–68 (2008)
3.
go back to reference Tu, D.B., Cai, Y., Dai, H.-Q.D.: A polytomous cognitive diagnosis model: P-DINA model. Acta Psychologica Sinica 42(10), 1011–1020 (2010)CrossRef Tu, D.B., Cai, Y., Dai, H.-Q.D.: A polytomous cognitive diagnosis model: P-DINA model. Acta Psychologica Sinica 42(10), 1011–1020 (2010)CrossRef
4.
go back to reference Fischer, G.H.: The linear logistic test model as an instrument in educational research. Acta Physiol. (Oxf) 7(6), 359–374 (1973) Fischer, G.H.: The linear logistic test model as an instrument in educational research. Acta Physiol. (Oxf) 7(6), 359–374 (1973)
5.
go back to reference Tatsuoka, K.K.: Rule space: an approach for dealing with misconceptions based on item response theory. J. Educ. Meas. 20(4), 345–354 (1983)CrossRef Tatsuoka, K.K.: Rule space: an approach for dealing with misconceptions based on item response theory. J. Educ. Meas. 20(4), 345–354 (1983)CrossRef
6.
go back to reference Hartz, M.C.: A Bayesian framework for the unified model for assessing cognitive abilities: blending theory with practicality. Am. J. Gastroenterol. 95(4), 906–909 (2002) Hartz, M.C.: A Bayesian framework for the unified model for assessing cognitive abilities: blending theory with practicality. Am. J. Gastroenterol. 95(4), 906–909 (2002)
7.
go back to reference Leighton, J.P., Gierl, M.J., Hunka, S.M.: The attribute hierarchy method for cognitive assessment: a variation on Tatsuoka’s rule-space approach. J. Educ. Meas. 41(3), 205–237 (2004)CrossRef Leighton, J.P., Gierl, M.J., Hunka, S.M.: The attribute hierarchy method for cognitive assessment: a variation on Tatsuoka’s rule-space approach. J. Educ. Meas. 41(3), 205–237 (2004)CrossRef
8.
go back to reference De La Torre, J.: DINA model and parameter estimation: a didactic. J. Educ. Behav. Stat. 34(1), 115–130 (2009)CrossRef De La Torre, J.: DINA model and parameter estimation: a didactic. J. Educ. Behav. Stat. 34(1), 115–130 (2009)CrossRef
9.
go back to reference Qian, J.X., Yu, J.Y.: The neural network-based PSP method in cognitive diagnosis. Psychol. Sci. 33(4), 915–917 (2010) Qian, J.X., Yu, J.Y.: The neural network-based PSP method in cognitive diagnosis. Psychol. Sci. 33(4), 915–917 (2010)
10.
go back to reference Ozaki, K.: DINA models for multiple-choice items with few parameters: considering incorrect answers. Appl. Psychol. Meas. 39(6), 431–447 (2015)CrossRef Ozaki, K.: DINA models for multiple-choice items with few parameters: considering incorrect answers. Appl. Psychol. Meas. 39(6), 431–447 (2015)CrossRef
11.
go back to reference De La Torre, J., Douglas, J.A.: Higher-order latent trait models for cognitive diagnosis. Psychometrika 69(3), 333–353 (2004)MathSciNetCrossRef De La Torre, J., Douglas, J.A.: Higher-order latent trait models for cognitive diagnosis. Psychometrika 69(3), 333–353 (2004)MathSciNetCrossRef
12.
go back to reference de la Torre, J., Chiu, C.Y.: A general method of empirical Q-matrix validation. Psychometrika 81(2), 253–273 (2016)MathSciNetCrossRef de la Torre, J., Chiu, C.Y.: A general method of empirical Q-matrix validation. Psychometrika 81(2), 253–273 (2016)MathSciNetCrossRef
13.
go back to reference Chen, Y., Culpepper, S.A., Chen, Y., Douglas, J.: Bayesian estimation of the DINA Q matrix. Psychometrika 83(1), 89–108 (2018)MathSciNetCrossRef Chen, Y., Culpepper, S.A., Chen, Y., Douglas, J.: Bayesian estimation of the DINA Q matrix. Psychometrika 83(1), 89–108 (2018)MathSciNetCrossRef
14.
go back to reference Liu, T.H., Zhao, Y., Dai, H.: Mix-DINA model based on mixture distribution for multiple strategy cognitive diagnosis. Psychol. Explor. 36(5), 464–471 (2016) Liu, T.H., Zhao, Y., Dai, H.: Mix-DINA model based on mixture distribution for multiple strategy cognitive diagnosis. Psychol. Explor. 36(5), 464–471 (2016)
15.
go back to reference Huo, Y., de la Torre, J.: Estimating a cognitive diagnostic model for multiple strategies via the EM algorithm. Appl. Psychol. Meas. 38(6), 464–485 (2014)CrossRef Huo, Y., de la Torre, J.: Estimating a cognitive diagnostic model for multiple strategies via the EM algorithm. Appl. Psychol. Meas. 38(6), 464–485 (2014)CrossRef
17.
go back to reference Xiong, X.H., Yao, J.C.: Research and application of data mining based on fuzzy sets. Comput. Eng. Appl. 01, 203–205 (2002) Xiong, X.H., Yao, J.C.: Research and application of data mining based on fuzzy sets. Comput. Eng. Appl. 01, 203–205 (2002)
19.
go back to reference Li, G., Yang, B., Liu, Y., et al.: Survey of data mining based on fuzzy set theory. Comput. Eng. Des. 32(12), 4064–4067 (2011) Li, G., Yang, B., Liu, Y., et al.: Survey of data mining based on fuzzy set theory. Comput. Eng. Des. 32(12), 4064–4067 (2011)
20.
go back to reference Wu, R., Liu, Q., Liu, Y., et al.: Cognitive modelling for predicting examinee performance. In: International Conference on Artificial Intelligence, pp. 1017–1024. AAAI Press (2015) Wu, R., Liu, Q., Liu, Y., et al.: Cognitive modelling for predicting examinee performance. In: International Conference on Artificial Intelligence, pp. 1017–1024. AAAI Press (2015)
22.
go back to reference Li, Y.X., Wen, Y.M., Yi, X.H., et al.: Revised model of fuzzy cognitive diagnosis framework. J. Data Acquisition Process. 05, 110–121 (2017) Li, Y.X., Wen, Y.M., Yi, X.H., et al.: Revised model of fuzzy cognitive diagnosis framework. J. Data Acquisition Process. 05, 110–121 (2017)
23.
go back to reference Tianyu, Z., Zhenya, H., Enhong, C., et al.: Personalized test item recommendation method based on cognitive diagnosis. Chin. J. Comput. 01, 178–193 (2017) Tianyu, Z., Zhenya, H., Enhong, C., et al.: Personalized test item recommendation method based on cognitive diagnosis. Chin. J. Comput. 01, 178–193 (2017)
24.
go back to reference Qi, B., Zou, H.X., Wang, Y., et al.: Question recommendation based on collaborative filtering and cognitive diagnosis. Comput. Sci. 235–240 (2019) Qi, B., Zou, H.X., Wang, Y., et al.: Question recommendation based on collaborative filtering and cognitive diagnosis. Comput. Sci. 235–240 (2019)
25.
go back to reference Xiong, H.J., Song, Y.F., Zhang, P., et al.: Personalized question recommendation based on autoencoder and two-step collaborative filtering. Comput. Sci. 172–177 (2019) Xiong, H.J., Song, Y.F., Zhang, P., et al.: Personalized question recommendation based on autoencoder and two-step collaborative filtering. Comput. Sci. 172–177 (2019)
26.
go back to reference Shan, R.T., Luo, Y.C., Sun, Y.: Collaborative filtering algorithm based on cognitive diagnosis. Comput. Syst. Appl. 27(3), 136–142 (2018) Shan, R.T., Luo, Y.C., Sun, Y.: Collaborative filtering algorithm based on cognitive diagnosis. Comput. Syst. Appl. 27(3), 136–142 (2018)
27.
go back to reference Li, Q., Liu, X.H., Xu, X.H., et al.: Personalized test question recommendation method based on unified probalilistic matrix factorization. J. Comput. Appl. 38(3), 639–643 (2018) Li, Q., Liu, X.H., Xu, X.H., et al.: Personalized test question recommendation method based on unified probalilistic matrix factorization. J. Comput. Appl. 38(3), 639–643 (2018)
28.
go back to reference Aparicio, M., Bacao, F.: E-learning concept trends. In: Proceedings of the 2013 International Conference on Information Systems and Design of Communication, pp. 81–86. ACM, New York (2013) Aparicio, M., Bacao, F.: E-learning concept trends. In: Proceedings of the 2013 International Conference on Information Systems and Design of Communication, pp. 81–86. ACM, New York (2013)
29.
go back to reference Chen, C., Wang, Y.P., Li, C., et al.: The research and application of big data in the field of online education. J. Comput. Res. Dev. S1, 67–74 (2014) Chen, C., Wang, Y.P., Li, C., et al.: The research and application of big data in the field of online education. J. Comput. Res. Dev. S1, 67–74 (2014)
30.
go back to reference Torre, J., Minchen, N.: Cognitively diagnostic assessments and the cognitive diagnosis model framework. Educ. Psychol. 20(2), 89–97 (2014) Torre, J., Minchen, N.: Cognitively diagnostic assessments and the cognitive diagnosis model framework. Educ. Psychol. 20(2), 89–97 (2014)
31.
go back to reference Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm. J. Roy. Stat. Soc.: Ser. B (Methodol.) 39(1), 1–22 (1977)MathSciNetMATH Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm. J. Roy. Stat. Soc.: Ser. B (Methodol.) 39(1), 1–22 (1977)MathSciNetMATH
32.
go back to reference Wang, C., Liu, Q., Chen, E.H., et al.: The rapid calculation method of DINA model for large scale cognitive diagnosis. Acta Electronica Sinica 46(5), 1047–1055 (2018) Wang, C., Liu, Q., Chen, E.H., et al.: The rapid calculation method of DINA model for large scale cognitive diagnosis. Acta Electronica Sinica 46(5), 1047–1055 (2018)
33.
go back to reference Goldberg, D., Nichols, D., Oki, B.M., et al.: Using collaborative filtering to weave an information tapestry. Commun. ACM 35(12), 61–70 (1992)CrossRef Goldberg, D., Nichols, D., Oki, B.M., et al.: Using collaborative filtering to weave an information tapestry. Commun. ACM 35(12), 61–70 (1992)CrossRef
34.
go back to reference Xiao, Z., Ruxue, S.: Research advance in DINA model of cognitive diagnosis. China Examinations 1, 32–37 (2013) Xiao, Z., Ruxue, S.: Research advance in DINA model of cognitive diagnosis. China Examinations 1, 32–37 (2013)
35.
go back to reference Zhang, M.Q., Fan, X.Z., Guo, K.Y., et al.: The evolution and development of education quality assessment under the concept of big data. Mod. Educ. J. 3, 2–6 (2016) Zhang, M.Q., Fan, X.Z., Guo, K.Y., et al.: The evolution and development of education quality assessment under the concept of big data. Mod. Educ. J. 3, 2–6 (2016)
Metadata
Title
Research on DINA Model in Online Education
Authors
Jia Liu
Wensheng Tang
Xuping He
Bo Yang
Shengchun Wang
Copyright Year
2020
DOI
https://doi.org/10.1007/978-3-030-63955-6_24

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