Personality as a Predictor of Computer Science Students’ Learning Motivation
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-5443-6_50
Reference23 articles.
1. Rountree, N., Rountree, J., & Robins, A. (2002). Predictors of success and failure in a CS1 course. ACM SIGCSE Bulletin, 34(4), 121–124.
2. Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138(2), 353–387.
3. Farsides, T., & Woodfield, R. (2003). Individual differences and undergraduate academic success: The roles of personality, intelligence, and application. Personality and Individual Differences, 34(7), 1225–1234.
4. Gray, G., Mcguinness, C., & Owende, P. (2014). An application of classification models to predict learner progression in tertiary education. In 2014 IEEE International Advance Computing Conference (IACC). IEEE (pp. 549–54)
5. Román-González, M., Moreno-león, J., Robles, G., & Pérez-González, J.-C. (2018). Extending the nomological network of computational thinking with non-cognitive factors. Computers in Human Behavior [Internet], 80, 441–459.
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
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