Learning Situation Risk Cognition and Measurement Based on Data-Driven

Author:

Mi Chunqiao,Deng Qingyou,Zhao Changhua,Yin Dong,Liu Yiwen

Publisher

Springer Nature Singapore

Reference23 articles.

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2. Mat, U.B., Buniyamin, N., Arsad, P.M., et al.: An overview of using academic analytics to predict and improve students’ achievement: a proposed proactive intelligent intervention. In: ICEE. Proceedings of the IEEE 5th International Conference on Engineering Education, pp. 126–130. IEEE, Selangor (2013)

3. Christian, T.M., Ayub, M.: Exploration of classification using NB tree for predicting students’ performance. In: ICODSE. Proceedings of the International Conference on Data and Software Engineering, pp. 1–6. IEEE, Bandung (2014)

4. Romero, C., López, M.I., Luna, J.M., et al.: Predicting students’ final performance from participation in on-line discussion forums. Comput. Educ. 68, 458–472 (2013)

5. Zhang, W.Y.: Design and development of online learning environment evaluation model, index system and evaluation scale. China Educ. Technol. 7, 29–33 (2004)

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