Crossref DOIMemberCiteFactoropen accessissn
SJIF Impact Factor 8.659 | ISSN: 2582-3930
IJSREM Logo

International Journal of Scientific Research in Engineering and Management

(Gateway to Global Scholars - An International, Scholarly, Multi-Disciplinary, Open Access Journal)

Peer-Reviewed Journal Designed to Meet UGC's Quality Parameters

HomeCurrent IssuePast IssuesPay OnlineConferencesEditorial BoardAbout UsContact Us
IJSREM

Loading article...

Follow Us

  • Google Scholar
  • ResearchGate
  • Academia.edu
  • Mendeley
  • LinkedIn
  • Facebook
  • Instagram

Journal Policies

  • Peer Review Policy
  • Publication Ethics
  • Copyright Infringement
  • Refund & Cancellation Policy
  • Terms and Conditions
  • Privacy Policy

Journal Identifiers & Licenses

  • ISSN Verified: 2582-3930ISSN Verified: 2582-3930
  • Crossref DOI: 10.55041Crossref DOI: 10.55041
  • SJIF Ranking: 08.659SJIF Ranking: 08.659
  • Licensed under CC BY 4.0Licensed under CC BY 4.0
  • ISO Certification: 9001:2015ISO Certification: 9001:2015
  • Indexed & Cited In: Google ScholarIndexed & Cited In: Google Scholar

Contact Us

International Journal of Scientific Research in Engineering and Management (IJSREM)

#62/1, New No 7, 1st Cross, 2nd Main, Ganganagar, R T Nagar, Bangalore North, Bangalore, Karnataka, India – 560032
[email protected]+91 93911 67991
logos
logos
Working Hours

Mon – Sat: 9:00 AM – 6:00 PM

Sunday: 10:00 AM – 4:00 PM

+91 93911 67991

© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

DisclaimerPrivacy PolicyTerms and Conditions
ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM36266

CO Attainment: Assessment of Course Outcomes for Engineering Colleges Affiliated to Anna University

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM36266

Volume:

8 |

7 |

Jul 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Share this article:

Authors

AS

Arunkumar S

BJJ

Beni Joe J

RG

Raihaan G

RA

Ramsundar A

NP

Nareshprabu P

MAP

Ms. Anu Prabhakar

Author Services & Downloads

Full Articles

Abstract

The CO Attainment project addresses the challenges associated with the manual assessment of student answer scripts in colleges, which is often labor-intensive, prone to errors, and inefficient. The project leverages a deep learning approach to automate the recognition of marks from scanned answer scripts and facilitates the systematic tracking of curriculum outcomes (COs). The core of the project is a Convolutional Neural Network (CNN) trained on the MNIST dataset, which is adept at recognizing handwritten digits with high accuracy. This model is integrated into a user-friendly Tkinter-based GUI, allowing college staff to input subject details and curriculum outcome question numbers, and upload scanned answer scripts for automatic mark extraction. The project follows a multi-step methodology: it begins with the collection and preprocessing of scanned answer scripts to enhance image quality and standardize formatting. The CNN model, trained on the MNIST dataset, is fine-tuned to accurately recognize marks on these scripts. A Tkinter GUI facilitates interaction with the system, enabling staff to seamlessly upload scripts and input necessary metadata. The extracted marks are processed using Pandas to compute aggregated scores for each curriculum outcome and are then stored in a structured CSV format. The CSV data is subsequently integrated into a database management system (DBMS) with robust access control mechanisms to ensure data security and integrity. The database allows for efficient storage, retrieval, and analysis of the assessment data, which is accessible to authorized personnel across the college campus. Comprehensive testing and validation are conducted to ensure the accuracy and reliability of the system. Furthermore, college staff are provided with thorough training to effectively use the GUI and interpret the results. Through the automation of mark recognition and the systematic tracking of curriculum outcomes, the CO Attainment project aims to enhance the efficiency, accuracy, and transparency of the academic evaluation process. This project not only reduces the workload of college staff but also facilitates timely feedback and data-driven decision-making in educational institutions.

KEYWORDS

Deep Learning Database Management System Graphical User Interface Comma Separated Values Toolkit Interface Course Outcome Artificial Intelligence Convolutional Neural Network Machine Learning Database Sum of Points College Staff Subject Assessment Data Management System

Cite This Article

Arunkumar S, Beni Joe J, Raihaan G, Ramsundar A, Nareshprabu P, Ms. Anu Prabhakar, "CO Attainment: Assessment of Course Outcomes for Engineering Colleges Affiliated to Anna University," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 7, Jul 2024.

Full Article/Conclusion

References

Editorial & Review Transparency

Publication Date

4/6/2024

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

Documents

Review Report (Confidential)
Copyright Form (Office)

Article Metrics & Impact

Article Views

0

Total views since publication

PDF Downloads

0

Total downloads since publication

Geographic Reach

5

Indexing, Archiving & Preservation

Google Scholar
Academia
ResearchGate
Crossref
SSRN
Semantic Scholar
Thomson Reuters
WorldCat
Mendeley
OpenAlex
EBSCO
Zenodo

Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.

Ethics, Compliance & Transparency

Plagiarism Screening

This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.

Conflict of Interest

The authors declare no conflict of interest related to this research work.

Funding Information

No funding information available for this research.

Similar & Recommended Articles

Similar Articles by Topic

Related research in the same subject area

Loading similar articles...