Missions, Rewards, and Progression

This section covers the engine of AWorld Lab's gamification system: the rules, rewards, and progression mechanics that give meaning to user actions. Missions turn activities into goals, streaks reward consistency over time, virtual currencies quantify progress, reward rules automate incentives, and badges provide visible recognition for milestones reached — creating a complete engagement loop. For the foundational activities and content that feed into these mechanics, refer to the activities and content documentation.

Missions

Missions are the primary mechanism for turning user activities into structured goals. A mission defines a target — a specific number or combination of activities to complete — and tracks progress toward that target. When the target is reached, the mission is completed, and downstream rewards and recognitions are triggered.

Mission Types: Individual and Group

AWorld Lab supports two mission types:

Individual missions: assigned to a single user, tracking their personal progress toward the goal.

Group missions: assigned to a group of users identified by a shared tag, tracking collective progress across all group members. This enables team challenges where collaboration drives completion.

Mission Lifecycle: States and Timeframes

Every mission follows a state-based lifecycle:

Pending: the mission exists but its start date has not yet arrived.

Active: the mission is within its timeframe and accepting progress.

Ended: the mission's timeframe has expired.

Missions support three timeframe configurations:

Permanent: no end date — the mission remains active indefinitely.

Range: a fixed start and end date — ideal for time-limited campaigns.

Recurring: missions that reset and repeat at regular intervals — perfect for weekly or monthly engagement cycles.

Mission Matching and Progress Tracking

The mission system uses a flexible matching engine to determine which user actions count toward progress. Each mission specifies:

Match type: whether to match a specific activity instance, any activity of a certain type, or activities associated with a specific tag.

Match entity: the type of trackable action to monitor — activities, quizzes, or tags.

Match condition: a configurable expression that filters which events qualify (e.g., "only quizzes with outcome success" or "only activities with a specific tag").

When a matching event occurs, the system applies an increment expression to calculate how much progress to add, and compares the result against a target expression that determines the completion threshold.

This architecture enables missions ranging from simple ("Complete 10 activities") to sophisticated ("Accumulate 500 points from quizzes with difficulty above 3, within the current month").

Each progress update is recorded in the Mission Log, providing a complete audit trail of how the mission was completed.

Mission Rules and Assignment Modes

Rather than manually assigning missions to individual users, AWorld Lab provides a rules engine that automates mission distribution:

Mission Configurations act as templates, defining the matching logic, progress rules, and metadata for a type of mission.

Mission Rules determine how and when these templates are instantiated as actual missions for users.

Rules support different assignment modes:

Lazy: missions are created on-demand when a user browses available missions. If the user matches the rule's conditions, the mission is generated in real time. This is ideal for discovery-driven experiences.

Event: missions are assigned automatically when a specific event occurs — for example, assigning a follow-up mission when the user completes a Learning Path. Combined with recurring timeframes, this also enables campaign-style deployment at predetermined intervals.

Each rule includes user targeting conditions that determine which users are eligible, allowing precise segmentation by tags, attributes, or behavior.

Configurable Rules with JSONLogic

AWorld Lab's mission system is powered by a flexible expression language for defining conditions, increments, and targets. This means:

Match conditions can filter events by any combination of attributes — entity type, outcome, tags, difficulty, or custom metadata.

Increment expressions can assign different progress values based on context — for example, awarding double progress for activities completed during a promotional period.

Target expressions can dynamically calculate goals — for instance, setting the target based on the user's level or group size.

This configurability enables clients to design complex engagement mechanics without code changes, adapting missions to any business context through configuration alone.

Group Missions

Group missions enable collaborative challenges where multiple users contribute toward a shared goal. The mission is assigned to a group tag, and every qualifying action from any user in that group increments the shared counter.

This unlocks team-based engagement scenarios:

Department challenges: teams within an organization compete to complete the most activities.

Community goals: an entire user community works toward a collective milestone.

Event-based collaboration: participants at a conference or campaign pool their progress toward a common target.

Group mission progress is tracked per-user in the Mission Log, allowing visibility into both individual contributions and collective achievement.

Virtual Currencies

AWorld Lab's point system is built on a multi-currency model that goes beyond simple point accumulation. Each workspace can define multiple virtual currencies, each serving a different strategic purpose — from experience-based progression to spendable credits.

Multi-Currency Model

A virtual currency is defined by:

Name and icon: display identity for the currency.

Balance constraints: optional minimum and maximum balance limits to control the economy.

Origin: currencies can come from AWorld Lab's catalog (pre-configured) or be custom-defined by the client.

Multi-language support: currency names and descriptions localized for different markets.

A typical configuration uses two currencies: experience points that drive leaderboard rankings and credits that are earned from mission completion and redeemable for rewards. However, clients can define any number of currencies to fit their engagement model.

Virtual Balance and Transactions

Each user maintains a virtual balance per currency, tracking:

Total amount: the cumulative balance.

Available amount: the balance available for spending, excluding pending or frozen transactions.

All balance changes are processed through virtual transactions, which provide a complete financial-grade record of every credit and debit:

Direction: Credit (adding to balance) or Debit (subtracting from balance).

Initiator: who or what caused the transaction — a reward rule, a streak rule, a system process, an admin action, or the user themselves.

Counterpart: the other party in the transaction (user or system).

Transaction Lifecycle and Automation

Each transaction follows a state lifecycle:

Pending: the transaction has been created but not yet finalized.

Completed: the transaction is finalized and reflected in the balance.

Expired: the transaction was not redeemed within its validity period.

Rejected: the transaction was denied (e.g., insufficient balance for a debit).

Transactions support two redemption modes:

Auto: the transaction is immediately finalized upon creation — typical for reward payouts.

Manual: the transaction requires explicit user or admin action to finalize — useful for prize redemption flows.

Transactions can also carry an expiration date, enabling time-limited rewards that encourage prompt engagement.

Practical Configurations

The multi-currency model supports a wide range of engagement strategies:

Competition-focused: a single experience currency drives leaderboard rankings, with no spending mechanism.

Reward-focused: credits are earned and spent on prizes, without affecting competitive standings.

Hybrid: experience points track engagement while credits provide a parallel economy for rewards.

Multi-dimensional: specialized currencies for different program areas — training points, sustainability credits, loyalty tokens — each with independent balance management.

Each client retains full control over how currencies are generated, distributed, and used, building an economy aligned with their strategic goals.

Reward Rules

Reward Rules automate the distribution of virtual currency based on user actions. When a user completes an activity, finishes a quiz, reaches a mission goal, or completes a Learning Path, the reward engine evaluates all applicable rules and distributes the corresponding rewards.

Rule Structure and Match Entities

Each reward rule defines:

Rule type: whether the rule matches a specific instance, any entity of a type, or entities associated with a tag.

Match entity: the type of action that triggers the reward — Mission, Activity, Quiz, Learning Path, Learning Group, Slide, or Tag.

Match condition: a configurable expression that filters which events qualify for the reward.

Rewards: one or more currency payouts, each targeting a specific virtual currency with a calculated amount.

A single rule can distribute multiple rewards simultaneously — for example, granting both experience points and credits when a mission is completed.

Application Modes and Multi-Reward Configuration

Rules operate in different application modes:

Always: the reward is granted every time the conditions are met.

Fallback: the reward is only granted if no other rules matched the same event — useful for providing a baseline reward.

Disabled: the rule is inactive.

Reward amounts are calculated using configurable expressions, enabling dynamic payouts based on context. For instance, a rule could award more points for quizzes with higher difficulty, or bonus credits during a promotional period.

Like other platform elements, reward rules support both catalog (pre-built) and custom origins.

Achievements: Badges and Levels

The Achievements system provides visible progression and recognition, motivating users beyond points and rewards.

Badges

Badges are visual recognitions awarded when a user reaches a specific milestone — completing a learning path, finishing a series of missions, or achieving a recurring goal. Once earned, a badge remains in the user's profile as a permanent proof of achievement, and can be awarded multiple times if the triggering condition recurs.

Each badge is defined by a Badge Configuration that specifies:

Image: a visual asset that represents the achievement — required for every badge.

Translations: a localized label and description explaining what the badge represents and how to earn it.

Progress source: the specific Mission Configuration or Learning Path whose completion drives the badge — the frontend uses this to display a progress bar before the badge is earned.

Badges are awarded automatically through Reward Rules: when a user completes the linked mission or learning path, the reward engine evaluates the rule and assigns the badge. The assignment happens only upon full completion — not during partial progress.

The platform tracks the full history of each badge assignment, including how many times it has been earned (count), when it was first and most recently awarded, and a log of each individual assignment with the source entity and rule that triggered it.

Like other platform entities, Badge Configurations support a publish/archive lifecycle and can originate from the AWorld catalog (pre-built configurations) or be created as custom badges by the client.

Levels

Levels represent a configurable progression system tied to accumulated virtual currency within a specific currency line. As users earn points, they advance through levels, each representing a higher engagement tier. Levels can unlock new features, grant access to exclusive content, or provide additional benefits within the gamification system.

Clients can design structured progression paths by defining level thresholds, providing users with clear targets and a visible sense of advancement.

Streaks

AWorld Lab's Streak system is designed to reward users' consistency over time, promoting regular participation in platform activities. Unlike a basic counter for consecutive actions, the streak system tracks how often the user engages with the system within configurable cadences, offering a rich set of mechanics to encourage sustained interaction.

Streak Concept and Cadence

A streak represents a continuous chain of user engagement measured at a defined cadence:

Daily cadence: the user must perform a qualifying action each day to maintain the streak.

Weekly cadence: the user must perform a qualifying action each week.

The metric defines what the streak counter represents:

Days: counting the number of consecutive days with activity.

Weeks: counting the number of consecutive weeks with activity.

This flexibility allows programs to promote daily involvement or more relaxed weekly cycles, depending on the engagement strategy.

Streak Lifecycle and Statuses

Each streak follows a state-based lifecycle:

Active: the streak is ongoing — the user has been meeting the cadence requirements.

Completed: the streak has reached its defined goal target.

Broken: the user missed the required cadence — the streak chain is interrupted.

Ended: the streak rule's timeframe has expired.

Streak status transitions are evaluated automatically based on the user's activity and the configured cadence, ensuring real-time accuracy.

Streak Types: Regular, Freeze, and Combined

The system supports different streak kinds that determine how engagement periods are counted:

Regular: only days/weeks with actual user activity count toward the streak.

Freeze: days/weeks where the user activated a freeze (see below) count as maintained.

Any: both regular activity and freeze days count — providing a combined view of streak continuity.

Perfect Periods and Goals

Streaks can track perfect periods — unbroken activity across full calendar periods:

Perfect Week: the user maintained the streak every required day of the week.

Perfect Month: sustained activity throughout an entire month.

Perfect Year: a full year of consistent engagement.

Additionally, streaks support multiple goal targets, creating tiered achievements within a single streak. For example, a streak might have goals at 7 days, 30 days, and 100 days — each unlocking progressively greater rewards.

Streak Freeze Mechanism

A distinctive feature of AWorld Lab's streak system is the freeze mechanism, which allows users to temporarily pause their streak without breaking it. This is designed to prevent occasional lapses from destroying long-term progress.

The freeze works through the virtual currency system:

Users spend a defined amount of virtual currency to activate a freeze for a period.

The freeze cost is calculated using a configurable expression, allowing dynamic pricing — for instance, increasing the cost for longer streaks to maintain challenge.

While frozen, the streak counter does not increment but the chain is preserved.

This mechanic adds strategic depth to the engagement experience: users must weigh the cost of freezing against the risk of losing their streak, creating meaningful decisions within the gamification system.

Streak Rules and Configuration

Streaks are managed through a rules-based system similar to missions:

Streak Configurations define what counts as a valid contribution — which activities, quizzes, or tagged actions maintain the streak.

Streak Rules determine how streaks are assigned to users, with user targeting conditions for segmentation.

Configurations use the same matching engine as missions — matching by specific instance, entity type, or tag — ensuring consistency across the platform's rule systems.

Rules can enable or disable specific features per streak:

Perfect period tracking (week, month, year).

Freeze functionality with virtual currency integration.

Goal targets with progressive thresholds.

Tags and Entity Targeting

Tags are a foundational building block in AWorld Lab, used across the entire platform for categorization, targeting, and segmentation.

Tag Model: Namespace and Variant

Each tag is defined by a namespace and variant, enabling structured categorization:

Namespace: the category or domain (e.g., "department", "region", "tier").

Variant: the specific value within that namespace (e.g., "marketing", "europe", "gold").

This structure allows clients to create organized, hierarchical tag systems without naming conflicts.

Cross-Entity Tag Assignments

Tags can be assigned to virtually any entity in the platform — users, activities, quizzes, Learning Paths, Learning Groups, slides, mission configurations, mission rules, streak configurations, and streak rules. Each assignment includes a priority value for ordering.

This flexibility means a single tag can connect users to content, missions to activities, and reward rules to specific contexts — creating a powerful targeting fabric across the entire gamification system.

Tags in Missions, Rewards, and Streaks

Tags play a critical role in the platform's rule engines:

Mission matching: missions can be configured to track activities associated with specific tags, enabling thematic challenges.

Reward targeting: reward rules can match events by tag, applying different rewards to different categories of content.

Streak configuration: streak rules can target specific user segments based on tags.

User segmentation: tags on users enable group-targeted missions, community leaderboards, and differentiated engagement paths.

Event-Driven Gamification

AWorld Lab's gamification mechanics are connected through an event-driven architecture that ensures every user action automatically ripples through the entire system.

Event Flow

When a user performs an action — completing an activity, finishing a quiz, reaching a mission target — the platform generates an event that flows through a processing pipeline:

The action is recorded as a log entry (Activity Log, Quiz Log, etc.).

The log entry triggers an event that is routed to all relevant handlers.

Each handler evaluates the event against its rules and applies the appropriate mechanics.

How Events Connect the System

This event flow creates a seamless chain reaction:

A user completes a quiz → an Activity Log is created.

The mission engine evaluates whether the action counts toward any active missions → mission progress is updated.

If a mission is completed, a Mission Log is created → this triggers the reward engine.

The reward engine evaluates reward rules → virtual currency is credited to the user's balance.

The streak engine evaluates whether the action extends the user's streak → streak count is updated.

Leaderboard rankings are recalculated based on the updated currency balances.

This architecture means clients only need to configure the rules — the platform handles the real-time orchestration automatically, ensuring that every action is recognized and rewarded without manual intervention.

Missions, Rewards, and Progression

Missions#

Mission Types: Individual and Group#

Mission Lifecycle: States and Timeframes#

Mission Matching and Progress Tracking#

Mission Rules and Assignment Modes#

Configurable Rules with JSONLogic#

Group Missions#

Virtual Currencies#

Multi-Currency Model#

Virtual Balance and Transactions#

Transaction Lifecycle and Automation#

Practical Configurations#

Reward Rules#

Rule Structure and Match Entities#

Application Modes and Multi-Reward Configuration#

Achievements: Badges and Levels#

Badges#

Levels#

Streaks#

Streak Concept and Cadence#

Streak Lifecycle and Statuses#

Streak Types: Regular, Freeze, and Combined#

Perfect Periods and Goals#

Streak Freeze Mechanism#

Streak Rules and Configuration#

Tags and Entity Targeting#

Tag Model: Namespace and Variant#

Cross-Entity Tag Assignments#

Tags in Missions, Rewards, and Streaks#

Event-Driven Gamification#

Event Flow#

How Events Connect the System#