MP01 — Atom Browser
L01 (57)
L02 (42)
L03 (103)
L04 (36)
L05 (103)
L06 (56)
L07 (44)
L08 (40)
MP01 (61)
MP02 (32)
MP03 (65)
MP04 (48)
MP05 (68)
MP06 (45)
61 Atoms
| ID | Name | Family | Definition | File |
|---|---|---|---|---|
MP01-A-CMP-001 |
Student Profile Completeness Gauge | CMP | Measures whether the LOPA student profile provides sufficient evidence families to support pedagogical evaluation. | MP01-A-CMP-001_Learner_Profile_Completeness_Gauge.json |
MP01-A-CMP-002 |
Student Profile Confidence Gauge | CMP | Measures the aggregate confidence scores from the LOPA student state vector. | MP01-A-CMP-002_Learner_Profile_Confidence_Gauge.json |
MP01-A-CMP-003 |
Student Profile Recency Gauge | CMP | Measures how recently the LOPA student state vector was updated relative to the current session. | MP01-A-CMP-003_Learner_Profile_Recency_Gauge.json |
MP01-A-CMP-004 |
Objective Specification Clarity Gauge | CMP | Measures whether LODA learning objectives are specified with sufficient precision for pedagogical evaluation. | MP01-A-CMP-004_Objective_Specification_Clarity_Gauge.json |
MP01-A-CMP-005 |
Theory Mapping Coverage Gauge | CMP | Measures whether CogniStruct has mapped the instructional design to sufficient learning theories. | MP01-A-CMP-005_Theory_Mapping_Coverage_Gauge.json |
MP01-A-CMP-006 |
Instructional Path Completeness Gauge | CMP | Measures whether the instructional path covers all stated learning objectives without gaps. | MP01-A-CMP-006_Instructional_Path_Completeness_Gauge.json |
MP01-A-CMP-007 |
Content Sequencing Validity Gauge | CMP | Measures whether the CSA content sequencing output has valid structure and internal logic. | MP01-A-CMP-007_Content_Sequencing_Validity_Gauge.json |
MP01-A-CMP-008 |
Modality Selection Presence Gauge | CMP | Measures whether MSA (Modality Selection Agent) has provided modality specifications for the instructional design. | MP01-A-CMP-008_Modality_Selection_Presence_Gauge.json |
MP01-A-CMP-009 |
Assessment Alignment Presence Gauge | CMP | Measures whether L06 (Outcomes Assessment) layer has provided assessment framework specifications. | MP01-A-CMP-009_Assessment_Alignment_Presence_Gauge.json |
MP01-A-DIR-001 |
Issue Specificity Gauge | DIR | Measures whether each flagged issue is described with enough specificity for a layer agent to act on it. | MP01-A-DIR-001_Issue_Specificity_Gauge.json |
MP01-A-DIR-002 |
Directive Actionability Gauge | DIR | Measures whether each directive is concrete and actionable by the target layer agent. | MP01-A-DIR-002_Directive_Actionability_Gauge.json |
MP01-A-DIR-003 |
Directive Proportionality Gauge | DIR | Measures whether each directive's remediation demand is proportional to the severity of the issue. | MP01-A-DIR-003_Directive_Proportionality_Gauge.json |
MP01-A-DIR-004 |
Bundle Completeness Gauge | DIR | Measures whether the directive bundle addresses all flagged issues without omissions. | MP01-A-DIR-004_Bundle_Completeness_Gauge.json |
MP01-A-DIR-005 |
Bundle Internal Consistency Gauge | DIR | Measures whether directives within the bundle are mutually consistent and don't conflict. | MP01-A-DIR-005_Bundle_Internal_Consistency_Gauge.json |
MP01-A-DIR-006 |
Remediation Path Clarity Gauge | DIR | Measures whether the directive bundle provides a clear remediation path — what to fix, in what order, by when. | MP01-A-DIR-006_Remediation_Path_Clarity_Gauge.json |
MP01-A-GOV-001 |
Evidence Sufficiency Gauge | GOV | Measures whether there is sufficient evidence from upstream atoms to make a reliable governance decision. | MP01-A-GOV-001_Evidence_Sufficiency_Gauge.json |
MP01-A-GOV-002 |
Confidence Threshold Gauge | GOV | Measures whether the aggregate confidence across all evidence families meets the minimum threshold for the assigned clearance tier. | MP01-A-GOV-002_Confidence_Threshold_Gauge.json |
MP01-A-GOV-003 |
Charter Compliance Gauge | GOV | Measures whether the governance decision aligns with the APLM charter's stated principles and constraints. | MP01-A-GOV-003_Charter_Compliance_Gauge.json |
MP01-A-GOV-004 |
Precedent Consistency Gauge | GOV | Measures whether this governance decision is consistent with prior decisions for similar cases. | MP01-A-GOV-004_Precedent_Consistency_Gauge.json |
MP01-A-GOV-005 |
Rationale Completeness Gauge | GOV | Measures whether the governance decision rationale addresses all flagged issues from upstream assessment. | MP01-A-GOV-005_Rationale_Completeness_Gauge.json |
MP01-A-GOV-006 |
Rationale Traceability Gauge | GOV | Measures whether each rationale claim can be traced back to specific atom evidence. | MP01-A-GOV-006_Rationale_Traceability_Gauge.json |
MP01-A-GRD-001 |
CLT Element Count Gauge | GRD | Measures whether the number of interacting information elements respects Cognitive Load Theory's working memory limits. | MP01-A-GRD-001_CLT_Element_Count_Gauge.json |
MP01-A-GRD-002 |
Intrinsic Load Calibration Gauge | GRD | Measures whether intrinsic cognitive load is appropriately calibrated to the student's current expertise level. | MP01-A-GRD-002_Intrinsic_Load_Calibration_Gauge.json |
MP01-A-GRD-003 |
Extraneous Load Minimisation Gauge | GRD | Measures whether non-essential cognitive demands have been minimised in the instructional design. | MP01-A-GRD-003_Extraneous_Load_Minimisation_Gauge.json |
MP01-A-GRD-004 |
Scaffolding Completeness Gauge | GRD | Measures whether the design includes proper scaffolding for transitions between competence levels within the Zone of Proximal Development. | MP01-A-GRD-004_Scaffolding_Completeness_Gauge.json |
MP01-A-GRD-005 |
ZPD Boundary Respect Gauge | GRD | Measures whether the instructional difficulty stays within the student's Zone of Proximal Development. | MP01-A-GRD-005_ZPD_Boundary_Respect_Gauge.json |
MP01-A-GRD-006 |
Bloom Level Appropriateness Gauge | GRD | Measures whether the target Bloom's Revised Taxonomy level is appropriate for the student's current competence. | MP01-A-GRD-006_Bloom_Level_Appropriateness_Gauge.json |
MP01-A-GRD-007 |
Objective-Activity Alignment Gauge | GRD | Measures the degree of alignment between stated learning objectives and designed learning activities. | MP01-A-GRD-007_Objective-Activity_Alignment_Gauge.json |
MP01-A-GRD-008 |
Activity-Assessment Alignment Gauge | GRD | Measures the degree of alignment between learning activities and assessment methods. | MP01-A-GRD-008_Activity-Assessment_Alignment_Gauge.json |
MP01-A-GRD-009 |
Objective-Assessment Alignment Gauge | GRD | Measures the degree of alignment between stated learning objectives and assessment methods. | MP01-A-GRD-009_Objective-Assessment_Alignment_Gauge.json |
MP01-A-GRD-010 |
Theory Consistency Gauge | GRD | Measures whether the applied learning theories are used consistently and without internal contradiction. | MP01-A-GRD-010_Theory_Consistency_Gauge.json |
MP01-A-GRD-011 |
Dual Coding Compliance Gauge | GRD | Measures whether the design properly leverages dual coding — presenting information in both verbal and visual channels. | MP01-A-GRD-011_Dual_Coding_Compliance_Gauge.json |
MP01-A-GRD-012 |
Multimedia Principle Adherence Gauge | GRD | Measures overall adherence to Mayer's 12 principles of multimedia learning across the instructional design. | MP01-A-GRD-012_Multimedia_Principle_Adherence_Gauge.json |
MP01-A-INQ-001 |
Hidden Curriculum Detection Gauge | INQ | Detects unstated assumptions or values embedded in the instructional design — the 'hidden curriculum'. | MP01-A-INQ-001_Hidden_Curriculum_Detection_Gauge.json |
MP01-A-INQ-002 |
Deficit Framing Detection Gauge | INQ | Detects whether the design frames student characteristics as deficits rather than differences. | MP01-A-INQ-002_Deficit_Framing_Detection_Gauge.json |
MP01-A-INQ-003 |
Cultural Assumption Exposure Gauge | INQ | Measures the degree to which cultural assumptions about learning are made explicit in the design. | MP01-A-INQ-003_Cultural_Assumption_Exposure_Gauge.json |
MP01-A-INQ-004 |
Prior Knowledge Assumption Validity Gauge | INQ | Measures whether the design's assumptions about student prior knowledge are warranted by evidence. | MP01-A-INQ-004_Prior_Knowledge_Assumption_Validity_Gauge.json |
MP01-A-INQ-005 |
Epistemological Diversity Gauge | INQ | Measures whether the design accommodates multiple ways of knowing and learning. | MP01-A-INQ-005_Epistemological_Diversity_Gauge.json |
MP01-A-INQ-006 |
Accessibility Representation Gauge | INQ | Measures whether the design represents diverse student needs in its activity and assessment options. | MP01-A-INQ-006_Accessibility_Representation_Gauge.json |
MP01-A-INQ-007 |
Voice Distribution Balance Gauge | INQ | Measures whose perspectives, voices, and knowledge systems are centred or marginalised in the design. | MP01-A-INQ-007_Voice_Distribution_Balance_Gauge.json |
MP01-A-INQ-008 |
Stereotype Reinforcement Risk Gauge | INQ | Measures the risk that the design inadvertently reinforces harmful stereotypes through content, examples, or adaptive behaviour. | MP01-A-INQ-008_Stereotype_Reinforcement_Risk_Gauge.json |
MP01-A-INQ-009 |
Single-Point-of-Failure Detection Gauge | INQ | Detects components in the instructional design where a single failure cascades across the learning experience. | MP01-A-INQ-009_Single-Point-of-Failure_Detection_Gauge.json |
MP01-A-INQ-010 |
Engagement Decay Probability Gauge | INQ | Estimates the probability that the design will fail to sustain student engagement over its duration. | MP01-A-INQ-010_Engagement_Decay_Probability_Gauge.json |
MP01-A-INQ-011 |
Motivational Collapse Scenario Gauge | INQ | Identifies design patterns that could systematically undermine intrinsic motivation. | MP01-A-INQ-011_Motivational_Collapse_Scenario_Gauge.json |
MP01-A-INQ-012 |
Assessment Washback Risk Gauge | INQ | Measures the risk that assessments distort learning behaviours (negative washback). | MP01-A-INQ-012_Assessment_Washback_Risk_Gauge.json |
MP01-A-PCH-001 |
Design-Theory Contradiction Gauge | PCH | Detects contradictions between the claimed theoretical approach and the actual design decisions. | MP01-A-PCH-001_Design-Theory_Contradiction_Gauge.json |
MP01-A-PCH-002 |
Cross-Layer Pedagogical Consistency Gauge | PCH | Measures whether L01 through L06 outputs tell a coherent pedagogical story. | MP01-A-PCH-002_Cross-Layer_Pedagogical_Consistency_Gauge.json |
MP01-A-PCH-003 |
Learning Pathway Continuity Gauge | PCH | Measures whether the learning pathway has logical continuity without gaps or unexplained jumps. | MP01-A-PCH-003_Learning_Pathway_Continuity_Gauge.json |
MP01-A-PCH-004 |
Prerequisite Readiness Level Gauge | PCH | Measures whether the student has demonstrated prerequisites for the designed instruction. | MP01-A-PCH-004_Prerequisite_Readiness_Level_Gauge.json |
MP01-A-PCH-005 |
Cognitive Demand Appropriateness Gauge | PCH | Measures whether the total cognitive demand across the design is manageable for the student. | MP01-A-PCH-005_Cognitive_Demand_Appropriateness_Gauge.json |
MP01-A-PCH-006 |
Time-to-Mastery Realism Gauge | PCH | Measures whether the allotted time is realistic for achieving the stated learning objectives. | MP01-A-PCH-006_Time-to-Mastery_Realism_Gauge.json |
MP01-A-PCH-007 |
Adaptation Pedagogical Safety Gauge | PCH | Measures whether proposed adaptations maintain fundamental pedagogical integrity. | MP01-A-PCH-007_Adaptation_Pedagogical_Safety_Gauge.json |
MP01-A-PCH-008 |
Adaptation Regression Risk Gauge | PCH | Measures the risk that adaptations in one area cause regression in another. | MP01-A-PCH-008_Adaptation_Regression_Risk_Gauge.json |
MP01-A-PCH-009 |
Adaptation Student Autonomy Impact Gauge | PCH | Measures whether adaptations respect and build the student's self-regulation capacity rather than creating dependency. | MP01-A-PCH-009_Adaptation_Learner_Autonomy_Impact_Gauge.json |
MP01-A-PCH-010 |
Design Internal Consistency Gauge | PCH | Measures whether all pedagogical design components are mutually consistent and non-contradictory. | MP01-A-PCH-010_Design_Internal_Consistency_Gauge.json |
MP01-A-TCL-001 |
Tiered Clearance Framework | TCL | A graduated governance clearance model replacing binary APPROVE/REJECT with six tiers (T0-T5) that enable flexible remediation windows while maintaining pedagogical integrity. | MP01-A-TCL-001_Tiered_Clearance_Framework.json |
MP01-A-TCL-002 |
Issue Severity Classification | TCL | Classification schema for governance issues by severity level and domain, enabling consistent scoring and tier determination. | MP01-A-TCL-002_Issue_Severity_Classification.json |
MP01-A-TCL-003 |
Cumulative Scoring Engine | TCL | The scoring engine that calculates cumulative issue scores with layer-specific amplification to determine appropriate clearance tier. | MP01-A-TCL-003_Cumulative_Scoring_Engine.json |
MP01-A-TCL-004 |
Remediation Deadline Tracker | TCL | Mechanism for tracking remediation deadlines assigned in tiered clearance decisions, with escalation pathways when deadlines approach or are missed. | MP01-A-TCL-004_Remediation_Deadline_Tracker.json |
MP01-A-TCL-005 |
Clearance Signature Generator | TCL | Generates compact clearance signatures that encode the complete tiered clearance decision for chain attachment and downstream processing. | MP01-A-TCL-005_Clearance_Signature_Generator.json |
MP01-A-TCL-006 |
Rejection Signature Protocol | TCL | Protocol for generating and routing rejection signatures when tiered clearance results in T0 or T1 (blocked) outcomes. | MP01-A-TCL-006_Rejection_Signature_Protocol.json |