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* Comfort Level Computation
*
* Computes a 0-1 "comfort level" from existing BKT mastery data and session mode.
* This drives dynamic term count scaling - higher comfort → more terms per problem.
*
* Algorithm:
* 1. Base: Confidence-weighted average of pKnown across practicing skills
* 2. Mode multiplier: remediation × 0.6, progression × 0.85, maintenance × 1.0
* 3. Skill count bonus: min(0.15, log(skillCount + 1) / 20)
* 4. Clamp to [0, 1]; no BKT data → conservative default 0.3
*/
import type { BktModeResult, SkillBktResult } from './bkt'
import type { SessionMode } from './session-mode'
import type { TermCountExplanation } from './config/term-count-scaling'
// =============================================================================
// Types
// =============================================================================
export interface ComfortLevelResult {
comfortLevel: number
factors: TermCountExplanation['factors']
}
// =============================================================================
// Mode Multipliers
// =============================================================================
const MODE_MULTIPLIERS: Record<string, number> = {
remediation: 0.6,
progression: 0.85,
maintenance: 1.0,
}
/** Conservative default when no BKT data is available */
const NO_DATA_DEFAULT = 0.3
// =============================================================================
// Computation
// =============================================================================
/**
* Compute the comfort level for a student based on their mastery data and session mode.
*
* @param bktResults - BKT results keyed by skillId (undefined = no BKT data available)
* @param practicingSkillIds - Skills currently in the student's practice rotation
* @param sessionMode - Current session mode (remediation/progression/maintenance)
* @returns ComfortLevelResult with the comfort value and individual factors
*/
export function computeComfortLevel(
bktResults: Map<string, SkillBktResult> | undefined,
practicingSkillIds: string[],
sessionMode: SessionMode
): ComfortLevelResult {
const modeType = sessionMode.type
const modeMultiplier = MODE_MULTIPLIERS[modeType] ?? 1.0
// Skill count bonus: breadth of experience
const skillCountBonus = Math.min(0.15, Math.log(practicingSkillIds.length + 1) / 20)
// Base: confidence-weighted average of pKnown
let avgMastery: number | null = null
if (bktResults && bktResults.size > 0) {
let totalWeight = 0
let weightedSum = 0
for (const skillId of practicingSkillIds) {
const bkt = bktResults.get(skillId)
if (bkt) {
const weight = bkt.confidence
weightedSum += bkt.pKnown * weight
totalWeight += weight
}
}
if (totalWeight > 0) {
avgMastery = weightedSum / totalWeight
}
}
let comfortLevel: number
if (avgMastery !== null) {
comfortLevel = avgMastery * modeMultiplier + skillCountBonus
} else {
// No BKT data → conservative default
comfortLevel = NO_DATA_DEFAULT
}
// Clamp to [0, 1]
comfortLevel = Math.max(0, Math.min(1, comfortLevel))
return {
comfortLevel,
factors: {
avgMastery,
sessionMode: modeType,
modeMultiplier,
skillCountBonus,
},
}
}
// =============================================================================
// Per-Mode Comfort
// =============================================================================
/**
* Compute comfort levels separately for each mode (abacus, visualization, linear).
*
* For each mode present in byModeBkt, builds a SkillBktResult map and delegates
* to the existing computeComfortLevel(). Modes with no BKT data get the
* conservative 0.3 default (appropriate for unpracticed modes).
*
* @param byModeBkt - Per-mode BKT results from computeBktFromHistory
* @param practicingSkillIds - Skills in the student's practice rotation
* @param sessionMode - Current session mode
* @returns Record mapping mode names to their ComfortLevelResult
*/
export function computeComfortLevelByMode(
byModeBkt: Partial<Record<string, BktModeResult>> | undefined,
practicingSkillIds: string[],
sessionMode: SessionMode
): Record<string, ComfortLevelResult> {
const modes = ['abacus', 'visualization', 'linear'] as const
const result: Record<string, ComfortLevelResult> = {}
for (const mode of modes) {
const modeData = byModeBkt?.[mode]
if (modeData && modeData.skills.length > 0) {
const bktMap = new Map(modeData.skills.map((s) => [s.skillId, s]))
result[mode] = computeComfortLevel(bktMap, practicingSkillIds, sessionMode)
} else {
// No data for this mode → conservative default
result[mode] = computeComfortLevel(undefined, practicingSkillIds, sessionMode)
}
}
return result
}
// =============================================================================
// Override Helper
// =============================================================================
/**
* Apply a parent/teacher term count override as a ceiling.
*
* The override doesn't raise the computed range — it only caps it.
* If no override is provided, the computed range is returned as-is.
*
* @param computed - The dynamically computed term count range
* @param override - Parent/teacher cap (null/undefined = no cap)
* @returns The final range, capped by the override if applicable
*/
export function applyTermCountOverride(
computed: { min: number; max: number },
override: { min: number; max: number } | null | undefined
): { min: number; max: number } {
if (!override) {
return computed
}
// Override acts as ceiling — caps the computed range but doesn't raise it
const finalMax = Math.min(computed.max, override.max)
const finalMin = Math.min(computed.min, override.max) // min can't exceed override.max either
return {
min: Math.max(2, Math.min(finalMin, finalMax)),
max: Math.max(2, finalMax),
}
}
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