Evidence map›Paper›PMID 40683915›Full record

ArticleScientific reports2025

The effectiveness of MOOCs in Technical Education: an Indian perspective.

Priyanka Jarial, Himanshu Aggarwal, Bhim Sain Singla

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Priyanka JarialDepartment of Computer Science & Engg., Punjabi University, Patiala, India. jarial.priyanka@gmail.com.
Himanshu AggarwalDepartment of Computer Science & Engg., Punjabi University, Patiala, India.
Bhim Sain SinglaPunjabi University, Patiala, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The analysis of user engagement in online educational courses has drawn considerable attention from researchers due to the rise of Massive Open Online Courses (MOOCs). The effectiveness of MOOCs (EMOOCs) has been identified as one of the crucial factors by numerous researchers. This led to the development of various MOOC frameworks, models, theories, designs, and principles for evaluating online learning for both students and instructors. This study uses the IBM SPSS statistical package to identify the factors contributing to the effectiveness of MOOCs (EMOOCs). It examined eight direct and indirect determinants contributing to the effectiveness of MOOCs. Data were collected from Technical courses offered at Tertiary institutions in the Punjab region, Northern India, assuming that the students already possessed knowledge of Massive Open Online Courses (MOOCs). The study revealed that the effectiveness of MOOCs (EMOOCs) is enhanced by concentrating on factors such as Course Content and Design, Performance Evaluation, Learner Feedback, Teacher-Student Interaction, and Technological Support in Massive Open Online Courses. The Discriminant Validity (HTMT ratio and Fornell-Larcker Criteria) validates the results. This study provides valuable insights into the development and implementation of Massive Open Online Courses (MOOCs) tailored to meet the specific needs of learners in Northern India, with a focus on Punjab. The research identifies key characteristics that impact the effectiveness of MOOCs, providing practical suggestions for educators and organizations seeking to enhance the learning experience in this domain.

Indexed as

Education, DistanceCurriculumHumansIndiaLearningStudentsConfirmatory factor analysisDiscriminant ValidityEMOOCs (effectiveness of MOOCs)Reliability analysisStructural equation modelling (SEM)

Identifiers

PMID40683915
PMCPMC12276326

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.