Fast certificate issuance in a Moodle‐based MOOC platform: A large‐scale study

Abstract Background Instances of academic dishonesty are common in online learning environments because difficulties in their detection result in considerably low degrees of risks. However, if not identified, the noise introduced by dishonest learners in MOOCs' clickstream data could lead to biased results and conclusions in scientific research. Objectives This study aimed to identify and quantify the most frequent undesirable behaviour employed by students to earn completion certificates. Methods We employed descriptive and inferential statistics to analyse a Brazilian Moodle‐based MOOC platform's clickstream data. The database had information related to 113 MOOCs, and 297,687 students who obtained 109,050 certificates from 2016 to 2023. The MOOCs were organised in two groups, with and without a minimum time‐on‐course restriction. Results and Conclusions Amongst the issued certificates of MOOCs without the minimum time‐on‐course restriction, around 51% were obtained via Fast certificate issuance , while for MOOCs with the restriction, only 2% of certificates were obtained this way. We conclude that this difference in course configuration is key in explaining the identified behaviours. Implications The results indicate that the number of instances of undesirable behaviours in MOOCs might be much higher than reported, posing a potential threat to this educational model. Also, the nature of this behaviour is dependent on course configurations.

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Publication Details

Journal
Journal of Computer Assisted Learning
Published
2024-08-20
DOI
https://doi.org/10.1111/jcal.13054
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.41

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article

Fast certificate issuance in a Moodle‐based MOOC platform: A large‐scale study

Gabriela Trindade Perry, Marlise Bock Santos
1 citations
Journal of Computer Assisted Learning
Online Learning and Analytics
0.41
article

Fast certificate issuance in a Moodle‐based MOOC platform: A large‐scale study

Gabriela Trindade Perry, Marlise Bock Santos
article en
1 citations

Abstract

Abstract Background Instances of academic dishonesty are common in online learning environments because difficulties in their detection result in considerably low degrees of risks. However, if not identified, the noise introduced by dishonest learners in MOOCs' clickstream data could lead to biased results and conclusions in scientific research. Objectives This study aimed to identify and quantify the most frequent undesirable behaviour employed by students to earn completion certificates. Methods We employed descriptive and inferential statistics to analyse a Brazilian Moodle‐based MOOC platform's clickstream data. The database had information related to 113 MOOCs, and 297,687 students who obtained 109,050 certificates from 2016 to 2023. The MOOCs were organised in two groups, with and without a minimum time‐on‐course restriction. Results and Conclusions Amongst the issued certificates of MOOCs without the minimum time‐on‐course restriction, around 51% were obtained via Fast certificate issuance , while for MOOCs with the restriction, only 2% of certificates were obtained this way. We conclude that this difference in course configuration is key in explaining the identified behaviours. Implications The results indicate that the number of instances of undesirable behaviours in MOOCs might be much higher than reported, posing a potential threat to this educational model. Also, the nature of this behaviour is dependent on course configurations.

Journal of Computer Assisted LearningVol. 40(6)
Universidade Federal do Rio Grande do Sul (BR)
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Openalex Percentile: Top 28%
Online Learning and Analytics
0.41
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