Anonymized Dataset for Comparing Game-Based and Gamified Quiz-Based Formative Practice in a Large-Scale MOOC

README Dataset title:Anonymized dataset for "Comparing Game-Based and Gamified Quiz-Based Formative Practice for Sustained Participation in a Large-Scale MOOC" Study context:This dataset is linked with a study conducted in the SWAYAM MOOC "Introduction to Cyber Security" during the January 2026 cohort. The course had a total enrollment of 9,076 learners. The study compared two formats of supplementary formative practice in a large-scale MOOC. Learners who volunteered for the study were assigned to either the Game-Based Learning (GBL) group or the Control group through an automated randomizer. The GBL group received custom game-based formative practice activities linked with weekly course topics. The Control group received the same or equivalent formative questions through a gamified quiz-based portal. After the supplementary formative activity, learners in both groups attempted the same weekly MCQ quiz available on the SWAYAM platform. The scores from the custom game-based activities and the gamified quiz portal activities were not used as outcome scores. The common SWAYAM quiz records were used for assessment comparison. Final analytical sample:The public anonymized dataset contains 525 learners. GBL group: 274 learnersControl group: 251 learners The dataset was prepared after duplicate checking, overlap screening, and final eligibility screening. Overlapping cases across the GBL and Control groups were removed before the final analysis. Files included in this repository: 1. anonymized_clean_dataset.csv This is the main anonymized analytical dataset. It contains the variables required to reproduce the main results reported in the paper. 2. data_dictionary.csv This file explains the variables included in the anonymized dataset. 3. dataset_summary.csv This file gives a short summary of the final analytical sample and group counts. 4. gbl_activity_mapping.csv This file provides the weekly mapping of custom game-based formative practice activities used in the GBL group. 5. gbl_mooc_zenodo_dataset.xlsx This Excel workbook contains the anonymized dataset and related supporting sheets in spreadsheet format. 6. gbl_mooc_results_analysis.py This Python script reproduces the main descriptive statistics, group comparisons, tables, figures, and result summaries used in the paper. 7. analysis_results_for_paper.zip This ZIP file contains the output tables, result summaries, and figures generated from the analysis script. 8. Supplementary Table S1 Full Frequency Distribution of Learner Response Items.docx This file provides the full frequency distribution of learner response items. In the main manuscript table, Agree and Strongly Agree were combined as positive responses. 9. LICENSE.txt This file states the reuse conditions for the dataset, if included. 10. CITATION.txt This file provides the suggested citation format for this dataset, if included. Anonymization:The dataset has been anonymized before public release. The following direct or sensitive identifiers were removed: * names* email addresses* mobile numbers* enrollment keys* ABC IDs* date of birth* city* college name* roll number* Google Form timestamps* user IDs* open-ended learner comments Open-ended comments were excluded because they may contain identifying information. The learner IDs in the public dataset are newly assigned anonymous IDs after shuffling the row order. Important scoring and analysis rules: 1. Common SWAYAM quiz outcome: After the supplementary formative activity, learners in both groups attempted the same weekly MCQ quiz available on SWAYAM. These SWAYAM quiz records were used as the common assessment outcome. 2. Supplementary activity scores: Scores from the custom game-based activities and the gamified quiz portal activities were not used as outcome scores in the main paper. 3. "All learners" analysis: Non-attempted SWAYAM assessments were coded as zero. This approach was used to measure realised course performance because non-attempt is also an important outcome in a MOOC. 4. "Attempters only" analysis: Only learners with a recorded score for the relevant SWAYAM assessment were included. 5. active_weeks: This variable represents the number of weeks from Week 1 to Week 10 in which the learner had a recorded SWAYAM weekly quiz attempt. 6. final_quiz_attempted: This variable is coded as 1 if a final quiz score was available and 0 if no final quiz score was available. 7. final_quiz_score_zero_coded: This variable treats non-attempted final quiz records as zero. Main tables reproduced by the analysis script:The Python script reproduces the following tables used in the paper: * Table 1: Sample screening and final analytical sample* Table 2: Sample characteristics and group balance* Table 3: Sustained participation and SWAYAM assessment outcomes by group* Table 4: Weekly participation and weekly SWAYAM quiz performance* Table 5: Learner response summary* Table 6: Exploratory subgroup analysis of participation outcomes* Table 7: Summary of hypothesis testing Figures reproduced by the analysis script:The analysis script generates the weekly SWAYAM quiz participation figure used in the main manuscript. The script may also generate additional checking figures. These are for review and verification only, unless included by the authors. How to reproduce the analysis:To reproduce the analysis, run the Python script: gbl_mooc_results_analysis.py The script requires the following input file: anonymized_clean_dataset.csv The script will generate the analysis output folder and result files, including manuscript-ready tables, CSV tables, result summaries, and figures. Software requirements:The analysis was conducted using Python. The main libraries used were: * pandas* NumPy* SciPy* Matplotlib* openpyxl These libraries are commonly available in Google Colab. If needed, they can be installed using pip. Data use note:This dataset is shared for academic transparency and reproducibility. It should be used only for research, teaching, review, and verification purposes. The dataset should not be used to identify or attempt to identify any learner.