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Predicting performance of electrical engineering students using cognitive and non-cognitive features for identification of potential dropouts
Research article (International Journal of Electrical Engineering Education, 2017) · cited 66× · AI/ML
Predicting performance of electrical engineering students using cognitive and non-cognitive features for identification of potential dropouts
Summary
Predicting performance of electrical engineering students using cognitive and non-cognitive features for identification of potential dropouts is a scholarly article[1].
Key Facts
Predicting performance of electrical engineering students using cognitive and non-cognitive features for identification of potential dropouts's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Predicting performance of electrical engineering students using cognitive and non-cognitive features for identification of potential dropouts. Retrieved May 24, 2026, from https://4ort.xyz/entity/predicting-performance-of-electrical-engineering-students-using-cognitive-and-non-cognitive-features-for-identification-
MLA“Predicting performance of electrical engineering students using cognitive and non-cognitive features for identification of potential dropouts.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/predicting-performance-of-electrical-engineering-students-using-cognitive-and-non-cognitive-features-for-identification-.
BibTeX@misc{4ortxyz_predicting-performance-of-electrical-engineering-students-using-cognitive-and-non-cognitive-features-for-identification-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Predicting performance of electrical engineering students using cognitive and non-cognitive features for identification of potential dropouts}}, year = {2026}, url = {https://4ort.xyz/entity/predicting-performance-of-electrical-engineering-students-using-cognitive-and-non-cognitive-features-for-identification-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Predicting performance of electrical engineering students using cognitive and non-cognitive features for identification of potential dropouts — https://4ort.xyz/entity/predicting-performance-of-electrical-engineering-students-using-cognitive-and-non-cognitive-features-for-identification- (retrieved 2026-05-24)
