Evaluation of the Effectiveness of the Genomics & Science DOJO 3.0 Learning Method in Improving Research Skills and Scientific Writing Among Researchers in Indonesia

Evaluation of the Effectiveness of the Genomics & Science DOJO 3.0 Learning Method in Improving Research Skills and Scientific Writing Among Researchers in Indonesia: A Randomized Controlled Trial

The goal of this study is to rigorously evaluate the effectiveness of the DOJO 3.0 learning methodology in enhancing research skills and scientific writing among researchers in Indonesia compared to non-DOJO learning method. The main questions it aims to answer are:

How effective is the Dojo 3.0 methodology in improving participants' research skills and scientific writing, including critical thinking, data analysis ability, knowledge acquisition, and scientific manuscript quality and publication progress? How do participants' experiences, perceptions of the learning process and teaching quality, as well as their engagement, performance, and learning behaviors, differ between the intervention (DOJO) and control groups throughout the program?

Researchers will compare two groups, control group and intervention group to see if there is a significant difference between these two groups.

Standard learning method Non-DOJO (Control) DOJO learning method (Intervention)

For the intervention group, participants will participate in Shinjitsu class, an interactive dynamic lecture with real time engagement, an offline minicamp session with lecture that is more intense, intentionally more provocative and dynamic, wounded healer, shinjitsu ninja obstacles, shinjitsu ninja run, sparring and Tournament.

Detailed Description

This study is using a randomised controlled trial method conducted in Jakarta, Indonesia, designed to rigorously evaluate the effectiveness of the DOJO 3.0 learning methodology in enhancing research skills and scientific writing among researchers in Indonesia compared to non-DOJO learning methods.

This study consists of a cluster randomized trial with two intervention arms, to evaluate the effectiveness of the genomics and science DOJO 3.0 learning method, specifically comparing between standard learning method and DOJO learning method. The DOJO learning method will be delivered through structured components, including modularized minicamps, structured mentoring, expanded Shinjitsu tournaments, and the introduction of the Shinjitsu Ninja component, providing a platform for scientific capacity building, collaboration, and innovation.

To support implementation across both study components, several structured operational procedures will be applied. To minimize contamination between groups,activities for the control and intervention arms will be conducted in separate locations. However, to ensure consistency in content delivery, both groups will receive the same core instructional materials and be taught by the same instructors (Sensei). The primary distinction between groups will lie in the learning approach and environment, with the intervention group receiving the DOJO learning method and the control group receiving a standard (non-DOJO) learning method.

• Sample Size and Statistical Considerations The sample size calculation is based on the expected effect size of the intervention on primary outcomes (critical thinking, knowledge improvement, data analysis, personal empowerment, manuscript quality and quality of teaching), anticipated attrition among participants, and statistical power considerations to ensure meaningful results. Taking these factors into account, it is estimated that approximately 48 teams or 96 individuals will be recruited and participating in this study.
• Quality Assurance and Data Management A comprehensive quality assurance framework will be implemented to ensure data integrity, accuracy, and consistency across all study sites. Electronic data capture systems will incorporate built-in validation rules, including range checks, consistency checks, and logical constraints across related variables.

Routine centralized data monitoring will be conducted to assess data completeness, timeliness, and internal consistency. Key indicators will include baseline/endline test results, activity logs, pre- and post-test results, and other study-related outputs, which will be systematically reviewed and used as primary inputs for analysis.

A standardized data management system will be implemented, including a comprehensive data dictionary that defines all study variables, formats, permissible values, coding structures, and data sources. Where applicable, standardized coding approaches will be applied to ensure consistency.

All study procedures will be guided by Standard Operating Procedures (SOPs) and a detailed manual to ensure standardized implementation across sites.

• Handling of Missing Data Data quality checks during data collection will aim to minimize missingness. During analysis, appropriate statistical techniques, such as multiple imputation will be applied as specified in the statistical analysis plan. In cases where key supporting variables, such as participants' educational background and research stage, are missing, efforts will be made to retrieve this information from participants or relevant records.
• Statistical Analysis Plan All analyses will follow the intention-to-treat principle. Primary analyses will assess effectiveness of the DOJO learning method across intervention arms using quantitative methods to account for cluster randomization and potential confounders.

Primary analysis will examine differences in participants' critical thinking, improvement of knowledge, data analysis skills, personal empowerment, manuscript quality, publication, and quality of teaching. These outcomes will be assessed using structured assessment scoring and appropriate statistical models, by comparing endline results with baseline measurement.

Secondary analysis will assess differences in activity effectiveness, such as lecture and activity (i.e Ninja obstacles), or lectures only. These outcomes will be assessed using a structured assessment scoring and appropriate statistical models, by comparing post-test results with pre-test results that are administered each day of the minicamp offline session.

Depending on the nature of the outcome variables, appropriate statistical models will be applied. Continuous outcome variables like daily pre and post test scores, knowledge improvements, critical thinking scores, journal scores, tournament or mini tournament scores, and days distance to submission, will be primarily analyzed with repeated ANCOVA which is implemented to assess the changes over the time for each observation within the teams. Binary outcomes, such as paper finished or workshop completion, will be analyzed with chi-square test or logistic regression. Beside being analyzed as a variable, days distance to publication that act as a time-related outcomes, may be explored using survival analysis.

All analysis will include baseline characteristics of the participants, including the stratification of the research stage when joining the program and educational background, to improve comparability and reduce confounding.

Inclusion Criteria:

• Registered participants of Genomics & Science DOJO 3.0
• Teams consisting of two members
• Submission of research concept note
• Completion of screening and assessment stages (administratively and substantially through blind concept note screening and team's curriculum vitae)
• Willingness and commitment to participate in the full program will be ensured through a structured confirmation process.
• In addition, participants will be required to review, sign, and submit a commitment letter outlining the full schedule, expectations for attendance, and participation requirements.
• Information regarding program schedule and participation expectations will be communicated at multiple stages, including during registration, program launch, and post-selection, to ensure participants are fully informed prior to confirming their participation.
• Involvement/ attendance of the first author

Exclusion Criteria:

• Incomplete registration or documentation
• Failure to meet team composition requirements
• Withdrawal before intervention
• Incomplete baseline data