International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 4 July-August 2024 Submit your research before last 3 days of August to publish your research paper in the issue of July-August.

A Deep Learning Model Using CNN & LSTM to Forecast Student Learning Outcomes in Learning Management System

Author(s) Chaitrali Balu Kadam., Darshan Pratap Deshmukh., Tejas Rajendra Saraf
Country India
Abstract The administration, monitoring, and reporting of educational activities are being done more and more with Learning Management Systems (LMSs). Blackboard is one such extensively utilized LMS at universities all over the world. This is because it may be used to match learning material pieces, student-teacher and student-student interactions, and assessment activities to predetermined objectives and student learning outcomes. This study aimed to determine the predictive power of various KPIs obtained from students' Blackboard interactions in order to forecast students' learning outcomes. Deep learning algorithms to forecast academic achievement were looked at as part of a mixed-methods study design.
The degree of linear relationship between these factors and measures of student performance was ascertained by correlational tests. Out of the four models that were assessed, the CNN-LSTM predictive model proved to be the most effective because it combined long short-term memory with convolutional neural networks. The primary inference made from this data is that the CNN-LSTM technique might result in solutions that maximize and enhance how universities use the Blackboard LMS.
Keywords Learning management systems, student prediction, deep learning, CNN, LSTM.
Field Engineering
Published In Volume 5, Issue 6, November-December 2023
Published On 2023-12-20
Cite This A Deep Learning Model Using CNN & LSTM to Forecast Student Learning Outcomes in Learning Management System - Chaitrali Balu Kadam., Darshan Pratap Deshmukh., Tejas Rajendra Saraf - IJFMR Volume 5, Issue 6, November-December 2023. DOI 10.36948/ijfmr.2023.v05i06.10850
DOI https://doi.org/10.36948/ijfmr.2023.v05i06.10850
Short DOI https://doi.org/gs98sg

Share this