Intensive Co-Learning Incentive Program V2.0

General
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TL;DR

To ensure the long-term operation of the Intensive Co-Learning Incentive Plan and to guarantee the effectiveness of the incentives, while optimizing the overall budget allocation, it is proposed to transition the Intensive Co-Learning Incentive Program from an initial 150 LXPU base incentive + 350 LXPU influence retrospective incentive to a total incentive pool set on a quarterly basis, with LXDAO Builder and participants jointly scoring to assess their contributions and influence.

The specific plan is as follows:

Intensive Co-Learning Application:

  1. Active Application: LXDAO community members proactively contact the PM @soleil0289 of the current quarter’s operations team to apply for initiating a Intensive Co-Learning.
    (1) Define Clear Goals: Clearly define the specific goals and expected outcomes of the cruel co-study, such as improving skills, solving problems, and promoting innovation.
    (2) Confirm Specific Co-Learning Content
  2. Public Discussion: Publish a detailed Co-Learning plan on the forum to attract community members to participate and discuss, clarifying the goals and content of the Co-Learning.
  3. Weekly Meeting Review: After the plan is clear, the operations team conducts a voting review during the weekly meeting.
  4. Github Plan: Create the Intensive Co-Learning project on Github, recording plans, progress, and outcomes, facilitating registration and participation by students and review.

Intensive Co-Learning Incentive Mechanism

Whether initiated by community members or co-organizers, the initiators can receive a certain value of retrospective incentives (LXPU) issued by LXDAO through quarterly reviews.

  1. S11 Intensive Co-Learning incentive pool: 400 LXPU
  2. Incentive Mechanism: Jointly scored by LXDAO Builder and participants to assess their contributions and influence.
    (1) Assessment Criteria Content Output: Assess the valuable content generated during the Intensive Co-Learning process, such as articles, demos, etc.
    (2) Data: Examine the number of participants, the final number of Co-Learning completers, personnel transformation, and growth.
    (3) Other: Community activity, atmosphere, participant feelings, etc.

Continuous Optimization and Feedback

  1. User Feedback
    (1) Follow-up Survey: Conduct a survey of participants after the Intensive Co-Learning to collect feedback and suggestions.
    (2) Improvement Measures: Continuously optimize and improve the Intensive Co-Learning mechanism and content services based on feedback and retrospectives of each Intensive Co-Learning.
  2. Community Discussion
    Public Discussion: Openly discuss plans and optimization suggestions on community platforms, fully listening to members’ opinions.
  3. Transparent Management
    Public Transparency: All decision-making processes and incentive distributions are open and transparent, enhancing community trust.

中文版：

为确保残酷共学激励计划的长期运行，并保证激励的有效性，优化整体预算分配，现拟将残酷共学激励方案从前期 150 LXPU 基础激励+ 350 LXPU 影响力回溯激励转为以每季度为单位设定总激励池，由 LXDAO Builder 与参与者共同评分，评估其贡献与影响力。

具体方案如下：

一、残酷共学申请：

1. 主动申请：LXDAO 社区成员主动联系本季度运营小组 PM @Soleil Yi ，申请发起残酷共学。
（1）明确目标：清晰定义残酷共学的具体目标和期望成果，例如提高技能、解决问题、推动创新等。
（2）确认具体共学内容
2. 公开讨论：在论坛上发布详细的共学方案，吸引社区成员参与和讨论，明确共学的目标和内容。
3. 周会评审：方案明确后，运营小组在周会上进行投票评审。
4. Github 方案：在 Github上创建该残酷共学项目，记录计划、进展和成果，便于学员报名参与和回顾。

二、残酷共学激励机制

无论是由社区成员 or 联合主办方发起的残酷共学，均可通过每季度的评审获得由 LXDAO 发放一定值的回溯性激励（LXPU）。

1. S11 季度残酷共学激励总值：400 LXPU
2. 激励机制：由 LXDAO Buidler 和参与者共同评分，评估其贡献和影响力。
3. 评估标准
（1）内容产出：评估残酷共学过程中产生的有价值内容，如文章、Demo 等。
（2）数据：参与人员的数量、最终完成共学的人员、人员转化及增长情况。
（3）其他：社区活跃，氛围，参与者感受等

三、持续优化和反馈

1. 用户反馈
（1）后续调查：共学结束后对参与的人员进行调查，收集反馈和建议。
（2）改进措施：根据反馈与每期残酷共学复盘不断优化和改进残酷共学机制和内容服务。
2. 社区讨论
（1）公开讨论：在社区平台上公开讨论方案和优化建议，充分听取成员的意见。
3. 透明化管理
（1）公开透明：所有决策过程和激励发放公开透明，提升社区信任度。

附：原激励方案：残酷共学 Bounty 激励方式分享和讨论

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