Step 1
The child completes the test tasks
Quantum G Beta is a digital multimodal testing system designed to construct an individualized Differential Domain Profile of a child’s rapid automatic perception and information-processing processes. The system analyzes not only the child’s final responses but also process-level data collected during task performance (including gaze dynamics, response selection trajectories, and other process indicators) to determine the types of content and tasks in which these processes operate most consistently, rapidly, and naturally.
Within the methodological framework of the Quantum G testing model, this profile is viewed as a configuration of already observable early predispositions, a foundational perceptual layer that the system directly records through the consistency, speed, and automaticity of cognitive processes. According to the working research hypothesis, given a supportive environment, sustained support, and purposeful development, this observable layer may, over time, become the foundation for the development of the ability to restructure problem-solving frameworks and generate fundamentally novel ideas.
In the public materials of the World of Geniuses project, the proprietary terms “genius potential” and “areas of genius potential” are used. These terms are intended to describe assessment results in language that is accessible to families and the general public.
Within the assessment methodology, genius potential corresponds to the working construct Principle-Level Novelty Potential (PLN-P). It describes a latent profile of early predispositions that, according to the working research hypothesis, is associated with the subsequent development of the ability to generate fundamentally novel ideas. This profile does not exist in a “pure” form; rather, it is expressed in a differential-domain manner, that is, through specific types of content and tasks.
Genius potential is an individual profile of a child’s early cognitive predispositions that are already observable in the way the child perceives and processes information, but have not yet been realized in the form of creative achievements. This profile may serve as a foundation for the future development of the ability to introduce something new: to recognize hidden principles, move beyond established frameworks, and find original ways of solving problems. It is not genius itself in its manifested form, nor is it a prediction of future achievements. Rather, it is a potential that may unfold in an appropriate environment, with support, and through sustained development.
Areas of genius potential are domain-differentiated expressions of the above-described profile of early predispositions. They indicate the types of content and tasks in which early automatic processes of perception, prediction, and information processing operate most strongly—whether with numbers and invariants, motion and causality, matter and transformation, technical structures, spatial systems, or social situations.
In the Quantum G results, each area is presented under an accessible label for ease of interpretation: “Mathematics,” “Physics,” “Chemistry,” “Macroengineering,” “Microengineering,” or “Communication.”
Areas of Genius Potential should not be understood as a direct measure of genius, a prediction of achievement in a specific academic subject, or a distinct anatomical region of the brain.
Rather, they reflect more fundamental, evolutionarily shaped ways in which the brain organizes reality.
digital multimodal testing system that uses process data and behavioral indicators to construct latent cognitive profiles, which may support the future development of original thinking and the ability to generate novel ideas
analysis of latent processing patterns that have not yet manifested in standard academic performance
investigation of developmental antecedents of learning, the capacity to infer novel principles, and future original thinking
an additional analytical layer designed to identify a child’s strongest cognitive predispositions, which, when combined with results from other assessments, may be used to support the design of a personalized educational trajectory
a system for constructing an individualized developmental profile of a child, aimed at identifying their unique strengths
IQ test and not a direct measure of already manifested creativity
a test of school achievement, knowledge, or accumulated skills
an instrument for the direct diagnosis of genius or a deterministic prediction of future outstanding achievements
a standalone basis for final educational decisions without additional expert evaluation or consideration of results from other methods
a tool for ranking, final assessment, or interpersonal comparison
Age
Format
Time
Design
The three-session design reduces the extent to which results depend on a child's temporary state at a single point in time, such as fatigue, excitement, a temporary decrease in attention, or their individual peak period of productivity. It also accounts for potential day-to-day variations in attention and performance. In addition, this design helps minimize the impact of possible technical inaccuracies and improves the stability of the final profile.
Step 1
The child completes the test tasks
Step 2
The system records the responses and process indicators
Step 3
The analytical module processes the data and generates an individual profile of the child’s strengths
Step 4
The data undergoes quality control; if necessary, a human review is conducted to verify the correctness of the analytical pipeline
Step 5
The parent receives a report with the test results
Several specialized AI subsystems operate in parallel throughout the testing process. These include condition validation, models for analyzing handwriting input, speech, gaze direction, as well as facial tracking and expression analysis. All AI components within the system are discriminative analytical models, and each is designed to perform a specific, narrowly defined procedural task.
While the child completes the tasks, the Quantum G system records not only the final answers but also process-level data, meaning data related to how the child completes the tasks and arrives at responses.
Depending on the specific test block, data availability, and input quality, the system may take into account:
gaze dynamics and scanning patterns,
response selection trajectories,
individual facial and postural markers,
speech characteristics,
and handwriting input, if it is included in the task design.
Thus, the system records not only the outcome but also features of the execution process, enabling the analysis of the hidden dynamics of decision-making.
The final processing of results is implemented on a hybrid architecture combining a rule-based system and machine learning (Rules + ML).
Taken together, the interactive task design, multi-channel collection of process-level data, specialized AI models, hybrid analytical architecture, and quality-control mechanisms enable the Quantum G testing system to generate an individualized profile of a child's areas of strong cognitive predisposition.
Such a profile typically lies beyond the scope of direct assessment methods that are primarily focused on already developed skills, demonstrated achievements, acquired knowledge, verbal explanation, conscious strategy, or the correctness of the final answer.
it does not generate content for the child;
it does not interact with the child as a conversational agent;
it does not make psychological, medical, or clinical diagnoses;
it does not interpret the child’s internal emotional states;
it does not make educational decisions on behalf of parents or specialists;
it does not produce arbitrary results or interpretations outside the approved methodology.
verifies the technical conditions of test administration;
processes data collected during task execution;
extracts structured features from video signals, audio signals, gaze tracking data, and interaction signals;
generates process-level indicators, including gaze patterns, speech characteristics, response selection trajectories, and individual facial expression markers;
checks input data quality and the suitability of specific segments for analysis;
identifies stable performance patterns;
computes metrics within a predefined methodological model;
supports the automatic generation of reports in accordance with an approved structure.
Learn more Technical Memo: AI Models and Data Processing in Quantum G Beta
Download Technical MemoThe Quantum G testing system incorporates the following data protection principles:
Only the data necessary for test administration, result calculation, report preparation, and the provision of technical and customer support to families regarding the testing process is collected.
The Quantum G system does not use biometric identification of the child and does not create or store biometric templates for identity recognition.
Data is protected during storage and transmission. Access to different processing stages is restricted by roles and access levels.
The processing and storage of the child’s data are carried out in accordance with the applicable legal requirements of the country or jurisdiction in which the testing is provided, including rules related to children’s data, parental consent, data retention, deletion, and access restrictions.
Data required for test administration and report preparation is processed under the primary consent provided by the parent or legal guardian. Any additional use of the data, including model improvement and training, research analysis of feedback, publication of case studies, or research validation activities, is permitted only with separate parental consent.
Parents have the right to receive information about what child data is being processed, how it is used, and how long it is stored. In accordance with applicable law and privacy policy, parents may request access to the data, its correction, restriction of processing, or deletion.
Detailed rules regarding data storage, use, and deletion are described in the privacy policy.
Privacy PolicyA Quantum G result is an individualized profile across six Areas of Genius Potential. It maps the types of content and problem domains in which a child’s early processing patterns appear most consistently, efficiently, and naturally.
The profile illustrates the unique configuration of the child’s strengths, showing which Areas of Potential are most strongly expressed, which are still emerging, and which combinations of Areas of Genius Potential, talents, and cognitive characteristics may be meaningful in shaping the child’s future educational path.
Upon completion of the assessment, the family receives a Quantum G Certificate of Completion and an analytical report that includes:
An individualized map of the child’s most strongly expressed Areas of Genius Potential, along with descriptions of each area.
A description of associated talents.
A description of the child's predominant cognitive characteristics.
An analysis of how the Areas of Genius Potential, talents, and cognitive characteristics combine to form the child’s unique profile.
General recommendations for parents on supporting the identified profile and creating a developmental learning environment that fosters the child’s growth.
During the beta version stage, the report is prepared within 3 days.
This is related to the fact that the result is not delivered instantly or automatically: the data undergoes technical quality control, algorithmic processing according to a predefined methodological model, and verification of the analytical pipeline’s correctness.
Human review does not alter the result or add subjective interpretation. Its function is to ensure that the input data is suitable for analysis, that the analytical pipeline has been executed correctly, and that the final profile complies with the methodological rules of Quantum G.
In a Quantum G report, the Areas of Genius Potential may vary in their level of expression. These levels help indicate how consistently and coherently the indicators associated with a particular area appeared under testing conditions.
Area of Genius Potential—the most strongly expressed category within the profile, where the child’s responses and task-completion patterns most consistently indicate a strong predisposition toward a particular type of content, problem-solving approach, or cognitive domain. Within the Quantum G framework, such an area is considered a potential leading direction for the future development of the child’s strengths.
Talent in a Quantum G report describes an area of high but secondary potential, an area in which the child's strengths are already evident but do not represent the central axis of the overall profile. Such a result indicates an important additional direction for development that may be further strengthened through an appropriate environment, practice, and support.
Early-Stage Area of Potential is a direction in which indicators of potential are currently less pronounced, less consistent, or appear only in certain types of tasks. This does not indicate an absence of ability. Rather, it suggests that progress in this area is likely to develop more gradually and may require greater effort and support.
These areas should be viewed as supplementary directions for overall development rather than as the primary path for cultivating the child's strongest potential.
A Quantum G profile describes the structure of a child's strengths as identified during the assessment process. It shows which Areas of Genius Potential emerged most consistently, which appear as supporting or developing areas, and which combinations of areas, talents, and cognitive characteristics may be meaningful in shaping the child's future educational path.
This profile is not a ranking, a comparison with peers, a diagnosis, a career prediction, or a forecast of future achievement. It does not limit the child’s choices and does not replace educational, psychological, or other professional interpretation.
Quantum G results should be viewed as an additional layer of analysis that helps families and professionals better understand the conditions that may support the child’s strengths. All recommendations are intended as developmental guidelines rather than limitations on the child’s opportunities or potential.
Most traditional tools used to assess children's abilities and creativity focus on already observable forms of performance, such as answer accuracy, the level of acquired skills, quality of reasoning, verbal explanations, creative output, or performance on open-ended tasks. These methods are valuable and well-suited to their intended purposes, but they primarily measure what a child can already consciously demonstrate.
Quantum G operates at a different level of observation.
The methodological contribution of Quantum G lies in shifting the focus away from already demonstrated achievements and consciously articulated strategies toward earlier, more automatic information-processing patterns that emerge before extended reasoning and verbal reporting.
Quantum G does not replace existing assessment tools but adds another layer of analysis: data on early precursors of a child’s strengths and on those information-processing characteristics that usually remain outside the field of observation but precede an explicit answer, explanation, skill, or achievement.
The Quantum G methodology is built at the intersection of several research streams in cognitive science, developmental neuroscience, perception psychology, and modern approaches to the design and validation of testing systems.
Core Knowledge
Automaticity
Psychophysics and Signal Detection Theory
Active Perception and Unconscious Inference
Perceptual Organization and Amodal Completion
Hidden Structure and Statistical Learning
Process-Based Assessment, eye-tracking
etc.
The Quantum G methodology is based on the principles of the Standards for Educational and Psychological Testing (AERA/APA/NCME).
American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (2014). Standards for educational and psychological testing. American Educational Research Association.
Embretson, S. E. (1998). A cognitive design system approach to generating valid tests. Psychological Methods, 3(3), 300–319.
Mislevy, R. J., Steinberg, L. S., & Almond, R. G. (2003). On the structure of educational assessments. Measurement: Interdisciplinary Research and Perspectives, 1(1), 3–62.
Spelke, E. S., & Kinzler, K. D. (2007). Core knowledge. Developmental Science, 10(1), 89–96.
Carey, S. (2009). The origin of concepts. Oxford University Press.
Green, D. M., & Swets, J. A. (1966). Signal detection theory and psychophysics. Wiley.
Macmillan, N. A., & Creelman, C. D. (2005). Detection theory: A user's guide (2nd ed.). Lawrence Erlbaum.
Helmholtz, H. von. (1925). Treatise on physiological optics (J. P. C. Southall, Trans.). Optical Society of America. (Original work published 1867)
Kersten, D., Mamassian, P., & Yuille, A. (2004). Object perception as Bayesian inference. Annual Review of Psychology, 55, 271–304.
Rao, R. P. N., & Ballard, D. H. (1999). Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience, 2(1), 79–87.
Moors, A., & De Houwer, J. (2006). Automaticity: A theoretical and conceptual analysis. Psychological Bulletin, 132(2), 297–326.
Kanizsa, G. (1979). Organization in vision: Essays on Gestalt perception. Praeger.
Kellman, P. J., & Shipley, T. F. (1991). A theory of visual interpolation in object perception. Cognitive Psychology, 23(2), 141–221.
Wagemans, J., Elder, J. H., Kubovy, M., Palmer, S. E., Peterson, M. A., Singh, M., & von der Heydt, R. (2012). A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure-ground organization. Psychological Bulletin, 138(6), 1172–1217.
Fiser, J., & Aslin, R. N. (2001). Unsupervised statistical learning of higher-order spatial structures from visual scenes. Psychological Science, 12(6), 499–504.
Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science, 274(5294), 1926–1928.
Yang, S.-C. H., Wolpert, D. M., & Lengyel, M. (2018). Theoretical perspectives on active sensing. Current Opinion in Behavioral Sciences, 11, 100–108.
Friston, K., Adams, R. A., Perrinet, L., & Breakspear, M. (2012). Perceptions as hypotheses: Saccades as experiments. Frontiers in Psychology, 3, 151.
A detailed reference on the scientific and methodological context, including individual external theories and research programs considered in the development of the Quantum G test, as well as an extended bibliography, is available here:
“Scientific and Methodological Context of the Quantum G Beta” (PDF)
DOWNLOADWhen developing the Quantum G Testing system, one of the key methodological principles was the identification of hidden patterns and the implicit extraction of rules, that is, information-processing mechanisms that operate automatically, before conscious analysis begins. For this reason, the first Testing is critically important. Only the initial Testing captures the child's authentic, unadapted response to each task before they become familiar with its structure.
When the identical version of the test is administered a second time, the stimulus material is no longer novel. Statistical, perceptual, procedural, and contextual memory traces are formed within the child's cognitive system. These traces may consolidate and persist over time, gradually shifting the mode of information processing. Processes that operate automatically and unconsciously during the first administration may, on subsequent administrations, partially transition to conscious strategies. As a result, repeated administration of the same Testing version no longer measures the child's original information-processing profile. Instead, it measures an artifact of repeated exposure, a combination of the child's original predispositions, memory traces from the first experience, and the effects of familiarity and practice.
Thus, repeated administration of an identical Testing version is not equivalent to the initial administration because it measures a different construct. For this reason, each Quantum G test version is used only once.
The reliability of the results is ensured through different methodological approaches. In conventional diagnostic instruments, such as those used to assess general intelligence, reproducibility is typically evaluated through repeated Testing conducted several months or even years later. In the Quantum G Testing system, however, this approach is methodologically invalid for the reasons described above. Instead, the stability of the profile is ensured through a three-session design. The test consists of three consecutive sessions, which are recommended to be completed on the same day. The consistency of the results across all three sessions serves as the indicator of the profile's stability and reproducibility.
For subsequent monitoring or future reassessment, only alternative Testing versions should be used. These versions must differ in their stimulus configuration, sequence, and surface features while strictly preserving the underlying principles and the structure of the measured process. Only under these conditions does repeated measurement remain valid.
All test tasks are designed with time limits for both stimulus presentation and response. This methodological approach is intended to minimize the contribution of deliberate analytical reasoning and to make the early mechanisms of information selection, attention, and sensorimotor responding more observable.
In some tasks, the direction of the first eye movement (the first saccade) is additionally recorded. In other tasks, both the first saccade and the response made by tapping on the device screen are recorded simultaneously. The first saccade reflects which element of the scene received attentional priority before a conscious choice was formed. Neurocognitive research shows that premotor preparation of a saccade and the selection of its target correlate with early patterns of brain activity that precede the movement itself and may occur before the conscious report of choice. In this sense, the first saccade is considered an indicator of early attentional orientation and the preliminary selection of relevant information.
Rapid selection by tapping the screen adds another layer of data. Under conditions of brief stimulus presentation, the motor response is initiated before a fully developed conscious decision can be formed. According to the premotor theory of attention, attentional control processes and motor response programming rely on shared neural structures. This means that the characteristics and direction of the tap provide cognitive information about how the child's brain processed the presented stimulus.
Comparing these two indicators makes it possible to assess the degree of consistency between automatic attentional orientation and rapid motor response, as well as to identify potential discrepancies between them. The dynamics of the transition from early information selection to the stabilization of choice represent one of the parameters that shape the child's overall cognitive profile.
Quantum G Beta has already undergone initial pilot testing on a first sample of children and is currently available in a controlled deployment mode. In this context, the beta status does not refer to an experimental technical build. Rather, it denotes a stage of phased scientific validation that includes expanding the empirical dataset, evaluating the stability of profile results, refining the interpretive framework, and preparing comprehensive technical documentation.
The basic test scenario, data collection, signal processing, and quality control are already established as a stable process.
At this stage, the team has already obtained initial empirical observations on children’s task performance, data quality, and the interpretability of profiles. Preliminary observations have also been collected on children’s development in contexts where educational support is structured in accordance with their Quantum G profile. These data are being prepared for inclusion in the Technical Manual and in the form of individual case studies, in compliance with confidentiality requirements and parental consent procedures.
The relationship between early Quantum G profiles and subsequent domain-specific originality and manifestations of principle-level novelty is considered a theoretically motivated developmental hypothesis. Its validation requires longitudinal follow-up, assessment of profile stability, and comparison with educational trajectory data.
Quantum G Beta is currently undergoing a phased scientific validation process. The program includes several key areas of investigation:
Verification of the internal structure of indicators, profile stability, and reproducibility of results.
Comparison of Quantum G results with established cognitive, creativity, and educational methods to assess convergent and discriminant validity.
Evaluation of whether the Quantum G profile adds new information beyond standard cognitive indicators and whether it is associated with later learning capacity, competence development, and educational trajectories.
Long-term observation of children’s development to assess profile stability and its relationship with further development of strengths.
Detailed information on the study design, psychometric indicators, external comparison instruments, longitudinal design, and boundaries of interpretation will be provided in the Technical Manual.
Quantum G Beta is not a clinical, medical, or psychiatric diagnostic tool. The test results should not be used as the sole basis for final educational decisions.
The Quantum G profile should be viewed as an additional analytical layer: it may help families, educators, and specialists better understand a child’s strengths and select more appropriate developmental conditions. However, it should be interpreted in conjunction with observations from parents and teachers, and, when necessary, with results from other assessment methods.
Technical Manual — “In Preparation for Publication”
Preprint in preparation
Page Last Updated: June 2026. Next scheduled update: after the publication of the preprint.
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