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Monitoring of student learning in learning management systems: an application of educational data mining techniques.
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1. introduction, 1.1. learning analytics procedures, 1.2. educational data mining (edm) procedures.
- Apply an external logs analysis tool in Moodle to detect students at risk over the course of a semester in different phases (initial, intermediate, and final);
- Detect in the sample, with an external log analysis tool in Moodle, the clusters in different phases (initial, intermediate, and final) differentiating by type of algorithm ( k -means ++, fuzzy k -means, DBSCAN);
- Check if there were differences in the clusters found depending on the type of algorithm ( k -means ++, fuzzy k -means, DBSCAN);
- To check students’ satisfaction with the teaching process and the monitoring of learning.
2. Materials and Methods
2.1. participants, 2.2. instruments, 2.2.1. ubumonitor tool, 2.2.2. teaching methodology, 2.2.3. questionnaire of student opinion on quality of teaching—qsoqt—by bol, sáiz and pérez-mateos (2012), 2.3. procedure, 2.4. statistical analysis, 4. discussion, 5. conclusions, author contributions, institutional review board statement, informed consent statement, acknowledgments, conflicts of interest.
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Click here to enlarge figure
| n (Students) | Students Gender | |||||||
|---|---|---|---|---|---|---|---|---|
| Women | Men | |||||||
| n | % | Mage | SDage | n | % | Mage | SDage | |
| 49 | 41 | 83.67 | 22.37 | 2.19 | 8 | 16.32 | 21.63 | 1.77 |
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 1 | 0.14 | 0.30 | 0.45 | 0.14 | 0.22 | 0.008 | −0.13 | −0.02 |
| 2 | 0.14 | 1 | 0.17 | 0.09 | 0.34 | 0.12 | −0.05 | −0.18 | 0.02 |
| 3 | 0.30 | 0.17 | 1 | 0.09 | 0.03 | 0.62 | −0.04 | −0.12 | −0.03 |
| 4 | 0.45 | 0.09 | 0.09 | 1 | 0.14 | 0.13 | 0.28 | −0.09 | −0.03 |
| 5 | 0.14 | 0.34 | 0.03 | 0.14 | 1 | 0.09 | 0.02 | −0.06 | 0.02 |
| 6 | 0.22 | 0.12 | 0.62 | 0.13 | 0.09 | 1 | −0.04 | −0.11 | 0.05 |
| 7 | 0.008 | −0.05 | −0.04 | 0.28 | 0.02 | −0.04 | 1 | −0.03 | 0.11 |
| 8 | −0.13 | −0.18 | −0.12 | −0.09 | −0.06 | −0.11 | −0.03 | 1 | 0.04 |
| 9 | −0.02 | 0.02 | −0.03 | −0.03 | 0.02 | 0.05 | 0.11 | 0.04 | 1 |
| Goodness-of-Fit Index | k-Means ++ | Fuzzy k-Means | DBSCAN | Accepted Value |
|---|---|---|---|---|
| df | 24 | 24 | 24 | |
| χ | 102.47 * | 96.750 * | 91.588 * | * p > 0.05 α = 0.05 |
| RMSEA | 0.261 | 0.251 | 0.242 | >0.05–0.08 |
| RMSEA Interval (90%) | 0.210–0.341 | 0.200–0.305 | 0.191–0.296 | |
| SRMR | 0.196 | 0.205 | 0.00 | >0.05–0.08 |
| TLI | 0.704 | 0.628 | 0.704 | 0.85–0.90< |
| IFC | 0.803 | 0.752 | 0.803 | 0.95–0.97< |
| AIC | 162.47 | 156.750 | 151.588 | The lowest value |
| ECVI | 3.385 | 3.266 | 3.158 | The lowest value |
| ECVI interval (90%) | 2.810–4.117 | 2.712–3.977 | 2.624–3.850 | The lowest value |
| Cluster | Measurement | Mean | SD | Max | Min | MRange | χ | gl | p |
|---|---|---|---|---|---|---|---|---|---|
| Initial | |||||||||
| k-means ++ | 13.00 | 13.46 | 2 | 28 | 1.83 | 0.55 | 2 | 0.76 | |
| Fuzzy k-means | 9.45 | 9 | 27 | 2.33 | |||||
| DBSCAN | 12.67 | 17.62 | 2 | 33 | 1.83 | ||||
| Intermediate | |||||||||
| k-means ++ | 16.33 | 17.21 | 4 | 36 | 2.17 | 0.55 | 2 | 0.76 | |
| Fuzzy k-means | 16.33 | 15.70 | 4 | 34 | 2.17 | ||||
| DBSCAN | 14.67 | 21.08 | 2 | 39 | 1.67 | ||||
| Final | |||||||||
| k-means ++ | 16.33 | 23.18 | 1 | 43 | 2.33 | 2.00 | 2 | 0.37 | |
| Fuzzy k-means | 16.33 | 11.06 | 6 | 28 | 2.33 | ||||
| DBSCAN | 13.33 | 21.39 | 0 | 38 | 1.33 |
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Sáiz-Manzanares, M.C.; Rodríguez-Díez, J.J.; Díez-Pastor, J.F.; Rodríguez-Arribas, S.; Marticorena-Sánchez, R.; Ji, Y.P. Monitoring of Student Learning in Learning Management Systems: An Application of Educational Data Mining Techniques. Appl. Sci. 2021 , 11 , 2677. https://doi.org/10.3390/app11062677
Sáiz-Manzanares MC, Rodríguez-Díez JJ, Díez-Pastor JF, Rodríguez-Arribas S, Marticorena-Sánchez R, Ji YP. Monitoring of Student Learning in Learning Management Systems: An Application of Educational Data Mining Techniques. Applied Sciences . 2021; 11(6):2677. https://doi.org/10.3390/app11062677
Sáiz-Manzanares, María Consuelo, Juan José Rodríguez-Díez, José Francisco Díez-Pastor, Sandra Rodríguez-Arribas, Raúl Marticorena-Sánchez, and Yi Peng Ji. 2021. "Monitoring of Student Learning in Learning Management Systems: An Application of Educational Data Mining Techniques" Applied Sciences 11, no. 6: 2677. https://doi.org/10.3390/app11062677
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such as teachers, system administrators, and students. A survey was conducted with the objective of discovering the need for eLearning in the education sector and how to avoid issues related to online learning. Other important subjects within the thesis include eLearning technologies, eLearning system, eLearning pros and cons and lastly eLearning
Bucharest in Romania, with the main focus of analysing Learning Management Systems (LMS) in terms of quality assessment. Their research scope explores effectively the importance of quality analyses which is relevant to this research when comes to identify appropriate Learning Management System (LMS). 1.2 Structure of thesis
AA learning management system (LMS) provides the platform for the web-based learning environment by enabling the management, delivery, and tracking of learning. LMS are often viewed as being the starting point of any web-based learning program. A good LMS should be 100 percent web-deployable, requiring no additional client applications.
Abstract. Education Sector in the Philippines has been successful by means of integrating of E-Learning (Online Learning) LMS with Schools, Colleges and Universities, because of the conventional ...
E-learning System. shakir abdirahman. 2022. In this thesis, we present a practical guide to developing and implementing successful e-learning management systems. We cover a range of topics, including: Planning and designing effective online courses and programs Utilizing technology and software to facilitate learning and engagement Managing and ...
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles. Consult the top 50 dissertations / theses for your research on the topic 'Learning Management System.'. Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference ...
E-learning management system for thesis process support from a supervisor perspective: The case of SciPro System at University of Rwanda. Jönköping University; 2015. 5. Aghaee N, Hansson H, Tedre M, Drougge U. Learners' perceptions on the structure and usefulness of e-resources for the thesis courses. EURODL. 2014;17(1):154-71. doi: 10. ...
Learning at IAIN Metro was an LMS-based e-learning system during the pandemic. The web-based learning media used were Google Meet and Zoom, but LMS was most widely used by teaching lecturers in 2021-2022. Although other web-based learning media, such as Google Meet and Zoom, can be employed, the LMS will continue to dominate in 2021-2022.
The system is developed to address the performance gap existed in the analysis and design phases. Implementation: In the implementation phase, it is the time to decide how to intend to deliver course-content to the learners. The delivered process of the course is based on the analysis phase performance.