UGC Regulations on Credit Framework for Online Courses through SWAYAM, 2021

Naveen, H. M.

doi:10.32628/ijsrst229438

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…Working people, students, and educators predominantly use these online certification courses. Higher education recently oriented a credit-based course completion method [3]. Accordingly, a regular student can fulfill 20% to 40% of credits through MOOCs available in the SWAYAM platform [4].…”

Section: Introductionmentioning

confidence: 99%

Ed-Net: Multivariate Time Series Approach for Uncovering Student Learning Outcome in Higher Education Using Blended Deep Learning Technique

2024

IJIES

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The higher education system (HES) in every country depicts the progress and prominence of that nation. So, the government endures the most care at all levels to enrich the quality of education on both the educator and learner side. The new academic policies also urge for worthwhile education. The HES abides by multiple steps for students' welfare in the academic curriculum, including a revamped syllabus, teaching methodology, and evaluation system. Nevertheless, students' performance is falling yearly, particularly in undergraduate programs. After COVID-19, students' study behaviour transformed abruptly due to online classes where students use mobile phones for education. They spend valuable time on the internet and gaming applications, which makes the students addicted. The evolution of Artificial Intelligence and massive student data permits us to get back the next generation by doing periodic assessments during their study period. This paper proposed a blended deep learning binary classification model (Ed-Net) using convolutional neural network and bidirectional long short term memory to predict the students' performance. Multivariate time series (MTS) student academic data is employed to train the model. To accomplish this systematic research, we followed two stages in the experiment. Stage one identifies the superlative student input data, approach (tabular/time-series), and algorithm (machine/deep learning) for better classification. Stage two executes the proposed system (Ed-Net) to attain the highest accuracy with less classification error. The synthetic minority oversampling technique (SMOTE) is applied to balance the students' pass-fail ratio. Finally, the experimental result exhibits the proposed method surpassed the baseline models with 98% accuracy, 97% precision, 94% recall, and 95% fl-score. The proposed model also uses a benchmark dataset to simulate the data and evaluate its efficacy. Moreover, any educational institution can quickly fit the academic data into this model to identify the students lacking in studies early for giving proper intervention to the parents, teachers, and students.

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Section: Introductionmentioning

confidence: 99%

Ed-Net: Multivariate Time Series Approach for Uncovering Student Learning Outcome in Higher Education Using Blended Deep Learning Technique

2024

IJIES

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Correlation between swayam learning and its achievement among prospective teachers - a study in kanniyakumari district

Robert¹,

Sheeja²

2022

JSCH

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In the current scenario, Swayam learning is becoming a part of the curriculum of higher education. At this point, the prospective teachers are not staying away from the word "swayam." In the curriculum of the College of Education, there is a compulsory certificate course from Swayam Learning App. All the candidates who are getting a degree in education must complete any one of the online courses from Swayam. Therefore, the prospective teachers are very excited for the completion of the online Swayam course. After the results were revealed, certificates were given to the candidates who had completed the course. The ultimate aim of the investigator is to find the correlation between Swayam learning and its achievement among prospective teachers. For that, the investigators designed a tool called "Checklist for Swayam Learning" and administered it in the College of Education in Kanniyakumari District. The investigator used the survey method for the present investigation. The population of the present study was the Prospective Teachers who are studying in College of Education at Kanniyakumari District. In the present investigation, there is no significant difference between the residential locality and branch of the subjects, there is a significant difference between the results of the Swayam examination and finally, there is no significant difference between the father's and mother's occupations. The prospective teachers are requested to study the concepts clearly and watch the video classes frequently with concentration. The use of the online platform Swayam is not only for getting certificates but also to collect information about their learning.

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UGC Regulations on Credit Framework for Online Courses through SWAYAM, 2021

Cited by 2 publications

References 4 publications

Ed-Net: Multivariate Time Series Approach for Uncovering Student Learning Outcome in Higher Education Using Blended Deep Learning Technique

Ed-Net: Multivariate Time Series Approach for Uncovering Student Learning Outcome in Higher Education Using Blended Deep Learning Technique

Correlation between swayam learning and its achievement among prospective teachers - a study in kanniyakumari district

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