Revitalizing Pastoral Care: Leveraging Stupa Learning Management System in Diocese of Maumere
Bibliographic record
Abstract
The Catholic Church of the Diocese of Maumere is developing a learning management system (LMS) for its pastoral training program called the Weekend Pastoral Study, which is also abbreviated in Indonesian as Stupa.The aim of this LMS development is to enhance access and flexibility in pastoral education.Utilizing Design science research methodology (DSRM), the LMS was designed and developed using the Moodle platform along with various technologies such as PHP, MariaDB with MySQLi extension, HTML, CSS, and JavaScript.The performance of the Stupa LMS was evaluated through Black Box Testing based on ISO 25010 standards, focusing on pastoral ministers as the end users.The research findings indicate that this LMS has the potential to enrich spiritual experiences and enhance the effectiveness of learning for pastoral ministers at Diocese of Maumere, helping the Catholic Church address challenges in the digital era.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".