Publication2019
Analyzing student performance in engineering placement using data mining
The record
- Type
- Publication
- Date
- 1 January 2019
- Level
- National
- Journal
- Lecture Notes on Data Engineering and Communications Technologies
- Volume
- 28
- Pages
- 171-181
- Published
- 1 January 2019
- DOI
- 10.1007/978-981-13-6459-4_18
- Scopus ID
- 85083034964
- ISSN
- 23674512
- Authors
- 5
- Open access
- No
- Citations
- 12
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
4 Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all
Data mining approach predicts engineering student placement outcomes using classification algorithms, addressing educational performance analysis and student success evaluation.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1.1 Education and lifelong learning
Education data mining methodology supports quality improvements in engineering education and student skill development through predictive performance analysis.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- 1
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Citing this record
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KIIT Deemed to be University. “Analyzing student performance in engineering placement using data mining”. Kortex.