System for determining the match of the graduate profile based on data on grades in the study program

Abstract

A computer-based system for determining the degree of conformity with a graduate profile of an academic program based on academic performance data, wherein the system comprises the following: a communication interface unit configured to receive academic data from remote computer terminals connected to an academic unit via a communication network; a storage unit that is operationally connected to the communication interface unit and is configured to store graduate profile data, training area identifiers, subject identifiers, semester identifiers and subject grade values; a profile processing unit connected to the storage unit and configured to generate an education area data matrix by storing a variety of education areas for graduate profiles in the storage unit, each education area corresponding to a competency area associated with the completion of the academic program; a curriculum mapping processing unit coupled to the storage unit, configured to generate a mapping table between subjects and training areas by mapping each subject of a curriculum to at least one training area for graduate profiles stored in the storage unit; a grade processing unit connected to the communication interface unit and the storage unit, configured to receive semester grade values ​​corresponding to subjects in the curriculum and to generate a semester grade record by storing the received grade values ​​in the storage unit along with subject and semester identifiers; a contribution calculation unit connected to and configured with the storage unit, which generates a student contribution matrix representing the proportional contribution values ​​of the students in relation to the respective training areas of the university profile; a semester assessment unit configured to determine a semester performance value for each area of ​​study within the graduate profile, based on the subject contribution matrix and the semester grade data set; and A control unit connected to the semester assessment unit and configured to determine a cumulative conformance score representing the overall degree of attainment of the graduate profile over several semesters, wherein the contribution calculation unit is configured to generate the subject contribution matrix using a matrix generation circuit that stores subject identifiers along a first dimension and identifiers of the graduate profile's areas of study along a second dimension of the matrix, each matrix element representing a proportional contribution value corresponding to a subject's participation in a respective area of ​​study, and wherein the control unit is configured to classify the cumulative conformance score into a variety of predefined conformance levels based on stored threshold ranges representing the graduate profile's performance categories.

Description

AREA OF INVENTION

[0001] The present invention relates generally to systems for academic evaluation and educational analysis. In particular, it relates to a structured computer system for determining the degree of conformity of students with a predefined competency profile for university graduates based on academic performance over several semesters. The invention specifically relates to a machine-based system with networked hardware units, including communication interfaces, data storage, matrix generation circuits, evaluation modules, and control units, which perform structured data transformations to determine the degree of fulfillment of the competency profile. BACKGROUND OF THE INVENTION

[0002] Universities typically define a "graduate profile" that encompasses the competencies, professional skills, subject-specific competencies, and behavioral characteristics expected of students upon completion of a degree program. The graduate profile generally includes several competency areas such as subject-specific knowledge, job-related competencies, ethical awareness, communication skills, and teamwork skills.

[0003] In traditional educational institutions, the assessment of graduates' acquired competencies often involves manual review of learning outcomes or subjective evaluations by academic bodies. Such approaches frequently suffer from several drawbacks, including inconsistent assessment methods, a lack of systematic quantification of competency development, a lack of integrated assessment across multiple semesters, and difficulties in correlating subject-specific performance with the curriculum's learning objectives.

[0004] Furthermore, existing digital academic management platforms typically only record grades at the subject level, without providing a structured mechanism to determine how individual course performance contributes to the graduate's broader competency areas. Therefore, it is difficult for universities to objectively determine whether students have achieved the defined graduate profile.

[0005] Therefore, there is a need for a structured technical apparatus capable of recording academic grade data, linking curriculum content with competence areas for university graduates, calculating the contribution values ​​of subjects in relation to the competence areas, and determining cumulative levels of fulfillment that represent the achievement of the graduate profile over several semesters.

[0006] Universities are increasingly relying on structured competency frameworks to define the expected skills of graduates from a degree program. These competency frameworks, often referred to as graduate profiles, describe the knowledge, professional skills, subject-specific competencies, and behavioral competencies that students are expected to acquire during their studies. Graduate profiles typically encompass several competency areas, such as subject-matter expertise, analytical thinking, ethical awareness, professional communication, teamwork, and social responsibility. Degree programs are designed so that individual subjects or courses contribute to the development of one or more of these competency areas. Therefore, effective university management requires mechanisms that can determine whether the overall performance of students across the curriculum actually leads to the achievement of the defined graduate profile.Despite the increasing importance of competency-based education models, many universities still lack reliable technical systems that can objectively determine the degree of alignment between academic performance and the expectations for graduate competencies.

[0007] In traditional academic settings, the assessment of graduates' competency development is often indirect or fragmented. Colleges typically rely on individual course grades, faculty evaluations, program reviews, or accreditation documents to determine whether students have met the intended learning objectives. Faculty members often assess subject-level learning outcomes through exams, assignments, lab work, and project work. These assessments result in numerical grades or qualitative performance indicators assigned to individual students. While such subject-level assessments provide information about students' performance in specific courses, they do not offer a structured mechanism for determining how each subject contributes to the overarching competencies defined at the program level.Therefore, the relationship between course grades and the achievement of the graduate profile remains largely implicit and is not systematically quantified.

[0008] A common approach at universities is to manually map course learning objectives to graduate profiles during curriculum development. Academic bodies create matrices that link each course to one or more graduate competencies. While these matrices are helpful for curriculum planning, they are typically static documents that are not dynamically linked to student performance data. Consequently, once courses have been delivered and grades assigned, the initial mapping between subjects and competencies is rarely used for automated competency assessment. Instead, program coordinators or accreditation teams manually analyze grade distributions and learning outcomes to estimate whether learning objectives have been met.This manual analysis process is time-consuming, error-prone, and difficult to standardize across different departments.

[0009] Another common approach is the use of learning management systems (LMS) and academic information systems that record course grades, attendance, and exam results. These digital platforms provide central repositories for academic data and facilitate communication between instructors and students. However, most existing LMS platforms are primarily designed for course management and less for competency-based assessment of degree programs. While they store grades and exam results, they typically lack mechanisms to determine how individual grades contribute to course competencies or the achievement of the graduate profile. Consequently, the available data remains scattered across different courses and does not allow for an integrated analysis of competency development across the entire curriculum.

[0010] Some institutions attempt to overcome this limitation using spreadsheet-based assessment tools or manually created performance matrices. In these cases, university administrations extract course grades from institutional databases and perform further calculations using spreadsheet programs. The course grades can be weighted according to predefined contribution factors assigned to different competencies. While spreadsheet programs offer flexibility in such calculations, they have significant drawbacks. Spreadsheet-based systems require time-consuming manual data preparation, do not offer automatic data synchronization with institutional databases, and are highly susceptible to data entry errors. Furthermore, spreadsheet solutions often reach their limits in large degree programs with hundreds of courses and thousands of students.As the size and complexity of the data set increases, the reliability and maintainability of spreadsheet-based solutions deteriorate significantly.

[0011] In addition to manual evaluation methods, some educational institutions have explored statistical analysis techniques to estimate learning outcomes at the program level. These techniques involve aggregating course assessment results and applying statistical models to determine the overall performance of the program. For example, some institutions calculate average grades across course groups that are associated with specific competencies. While such statistical aggregation provides a general indication of performance trends, it does not accurately reflect each course's contribution to the development of specific competencies. Different courses may contribute differently to various competency areas, depending on curriculum structure, course content, and the weighting of credit points. Simple averaging methods, therefore, fail to capture the complex relationships between subjects and competency areas within the curriculum.

[0012] Another emerging approach involves using data analytics tools or educational data mining platforms to analyze academic performance data. These systems can employ predictive analytics or machine learning to identify patterns in academic performance or predict academic success. While such systems provide valuable insights into student behavior and academic risk factors, they are typically designed for predictive analytics rather than structured competency assessment. Often, these platforms require extensive data preprocessing and rely on statistical models that are difficult to interpret within the context of specific curriculum structures. Furthermore, such solutions frequently lack mechanisms for explicitly illustrating the relationship between curriculum and competencies, preventing them from directly determining the degree of alignment with the graduate profile.

[0013] Accreditation bodies and quality assurance systems require universities to demonstrate the competency development of their graduates. To meet these requirements, universities often produce outcome assessment reports that summarize course evaluations, surveys, and faculty assessments. These reports are typically generated regularly and require significant manual effort from faculty and administrative staff. Because the evaluation process is largely manual, the results can vary depending on the evaluators' interpretations. Furthermore, the lack of automated calculation mechanisms limits the frequency of such assessments. Consequently, universities struggle to continuously monitor the competency development of their graduates throughout their academic lifecycle.

[0014] A further limitation of existing solutions arises from the difficulty of integrating performance data across multiple semesters of a degree program. Most degree programs extend over several years and comprise numerous subjects spread across successive semesters. Each subject can contribute differently to one or more of the graduate's competencies. Determining cumulative competency acquisition therefore requires a systematic aggregation of performance data across multiple semesters, taking into account the relative contribution of each subject. Existing academic information systems typically lack structured mechanisms for conducting such cross-semester analyses. Consequently, universities cannot generate objective indicators that reflect the fulfillment of the overall profile of graduates based on actual academic achievements.

[0015] Furthermore, many existing educational management systems focus primarily on administrative data collection rather than analytical evaluation. While these systems are designed for storing enrollment data, timetables, and grade lists, they lack specialized software modules that enable a structured, matrix-based evaluation of student performance in relation to competency frameworks. Therefore, educational institutions are forced to rely on external analysis tools or manual evaluation methods to interpret student performance data.

[0016] In addition to the technical limitations described above, the lack of automated evaluation mechanisms also hinders institutional decision-making processes. Without reliable indicators of graduates' competency development, university administrations struggle to identify gaps in the curriculum, assess the effectiveness of teaching methods, or implement evidence-based curriculum improvements. Program revisions are therefore often based on subjective assessments rather than quantitative analyses of curriculum performance data.

[0017] Consequently, there is a need for a structured technical system capable of capturing grade data from the course of study, assigning subjects to the competency areas of the degree program, determining the respective contribution of each subject to these areas, and calculating the performance levels for each competency across multiple semesters. Such a system should be able to perform matrix-based calculations to determine compliance with competency targets for each semester and overall performance. Furthermore, the system should offer a structured computational architecture that enables consistent assessment across different degree programs while minimizing manual intervention and reducing the risk of calculation errors. A technical system capable of performing these functions would significantly improve the ability of educational institutions to objectively determine whether students have achieved the competencies defined in a degree program's competency profile. SUMMARY OF THE INVENTION

[0018] The present invention provides a machine-based system configured to determine compliance with the graduate profile based on curriculum grade information stored in the institutional academic database environment.

[0019] The system includes a communication interface configured to receive academic grade information from distributed academic devices or institutional data repositories via a communication network. A storage structure stores graduate profile data, including competency area codes, subject codes, semester codes, and associated grades.

[0020] A profile configuration unit generates a training area matrix that represents the competency areas assigned to the graduate profile. A curriculum mapping unit establishes connections between the curriculum subjects and the defined competency areas.

[0021] A module for calculating contributions creates a contribution matrix in which participant IDs and competency areas form two orthogonal matrix dimensions. Each matrix element represents a proportional contribution value corresponding to a participant's involvement in a specific competency area.

[0022] A module for semester assessment determines the performance levels for each competency area by combining the subject grades with the corresponding contribution coefficients. A control unit then calculates the cumulative fulfillment values ​​over several semesters and assigns the resulting values ​​to predefined performance categories of the graduate profile.

[0023] The system thus provides a technical infrastructure that enables educational institutions to determine the competence acquisition of graduates through a structured, machine-assisted analysis of curriculum grade data.

[0024] The present invention aims to provide a system for determining the competence attainment of graduates based on their academic performance. The system is configured as an integrated, machine-based device that receives information on academic performance from distributed data sources and determines the degree of competence attainment over the course of studies. The invention aims to establish a structured computing architecture in which the subject grades derived from academic performance are processed using a defined mapping between subjects and competence areas. This enables an objective determination of competence attainment based on measurable academic performance.

[0025] A further objective of the invention is to provide a technical system with multiple interconnected processing units and storage structures. This system is configured to organize the educational areas of graduate profiles, subject codes, semester codes, and the corresponding grades in a structured storage environment. By using such an architecture, the system enables the systematic representation of the relationships between curriculum elements and graduates' competency areas. This allows higher education institutions to conduct consistent and repeatable assessments of competency development based on stored academic data.

[0026] A further objective of the invention is to provide a system for generating a structured subject-matter contribution matrix that represents the proportional contribution values ​​of the subjects in relation to the respective training areas of the graduate profile. By creating such a matrix structure in the system memory, the invention enables the representation of curriculum relationships in a form suitable for computer-aided processing. This allows academic performance at the subject level to be quantitatively linked to the competency areas defined within the graduate profile.

[0027] A further objective of the invention is to provide a calculation device for determining semester-by-semester performance values ​​for each area of ​​study within the respective degree program. This is achieved by combining subject grades with the corresponding subject contribution values ​​stored in the contribution matrix. Through this mechanism, the system enables the automated assessment of competence development in various phases of the study program and thus offers a technical mechanism for monitoring competence acquisition throughout the entire course of study.

[0028] Another important objective of the invention is to provide a system that can aggregate semester performance across multiple study phases to determine cumulative conformance scores for the graduate profile. These scores represent the overall level of competence achieved by students upon completion of their studies. This cumulative assessment capability allows the system to determine whether the overall performance across the entire curriculum meets the competence expectations defined in the graduate profile.

[0029] A further objective of the invention is to provide a technical device for normalizing subject grades within a predefined calculation range. This allows academic performance data from different courses, from different lecturers, or using different grading scales to be processed in a unified analysis model. This normalization enables a consistent assessment of academic performance across multiple subjects and semesters while simultaneously minimizing the influence of differing grading practices.

[0030] A further objective of the invention is to provide a system capable of performing matrix-based calculations to determine competency scores using structured relationships between curriculum content and training areas. The use of matrix-based data structures within the system improves computational efficiency and enables the scalable processing of large academic datasets encompassing numerous subjects, competency areas, and semester records.

[0031] A further objective of the invention is to provide a system that can classify the determined cumulative fulfillment value based on predefined performance categories of the graduate profile. This is based on a comparison with predetermined threshold ranges stored in the system memory. This classification enables universities to determine whether the graduate profile has been achieved at different performance levels and thus supports academic evaluation, program accreditation, and curriculum development.

[0032] A further objective of the invention is to provide a technical system for generating structured output data, including indicators of competence achievement, contribution values ​​of study subjects, and cumulative values ​​for fulfilling the graduate profile. The system can generate graphical or analytical representations of the calculated results, thus supporting university administrations and curriculum developers in interpreting the relationship between academic performance and competence development.

[0033] A further objective of the invention is to provide a reliable and automated device for assessing the competence development of university graduates, thereby reducing dependence on manual assessment methods, spreadsheet-based analyses, or subjective academic evaluation processes. By providing an integrated computing architecture for processing academic performance data, the invention improves the accuracy, reproducibility, and efficiency of competence assessment for university graduates.

[0034] A further objective of the invention is to provide a system capable of managing extensive academic programs spanning multiple subjects and semesters, while ensuring structured data processing and consistent assessment of competency acquisition. Through the integration of communication interfaces, storage structures, processing modules, and matrix generation mechanisms, the system enables educational institutions to systematically and data-drivenly evaluate graduates' adherence to the curriculum profile.

[0035] The aforementioned objectives of the invention together form a technical framework for determining the extent to which academic programs achieve the competence outcomes defined in their graduate profiles, thus enabling improved academic quality assurance, optimized curriculum design and evidence-based educational management. BRIEF DESCRIPTION OF THE IMAGE

[0036] These and other features, aspects and advantages of the present invention will be better understood if the following detailed description is read with reference to the accompanying drawing, in which the same symbols represent the same parts: Fig. Figure 1 shows a block diagram of a computer-based system for determining the degree of conformity with a graduate profile of an academic program based on academic performance data.

[0037] Furthermore, those skilled in the art will recognize that the elements in the drawing are simplified and not necessarily drawn to scale. For example, the flowcharts illustrate the process by highlighting the main steps to facilitate understanding of the present disclosure. With regard to the construction of the device, one or more components may be represented in the drawing by conventional symbols. The drawing may show only the specific details relevant to understanding the embodiments of the present disclosure, so as not to clutter the drawing with details that are already apparent to those skilled in the art from the description contained herein. Detailed description of the invention

[0038] To facilitate understanding of the principles of the invention, reference is made below to the embodiment shown in the drawing, which is described using specific terms. It is understood, however, that this does not limit the scope of protection of the invention. Rather, modifications and further developments of the depicted system, as well as further applications of the inventive principles shown therein, are conceivable, insofar as they would normally occur to a person skilled in the art in the field of the invention.

[0039] It will be clear to those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the invention and are not to be understood as a limitation thereof.

[0040] References to “an aspect”, “another aspect”, or similar phrases in this description mean that a particular feature, structure, or property described in connection with the embodiment is included in at least one embodiment of the present disclosure. Therefore, phrases such as “in one embodiment”, “in another embodiment”, and similar expressions in this description may, but do not necessarily, all refer to the same embodiment.

[0041] The terms "includes," "comprehensive," or similar expressions denote non-exclusive inclusion. Thus, a procedure or method containing a list of steps does not only include those steps but may also include further steps not explicitly listed or inherent in the procedure or method. Likewise, the statement "includes..." for one or more devices, subsystems, elements, structures, or components, without further limitations, does not preclude the existence of other devices, subsystems, elements, structures, or components.

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meanings generally known to those skilled in the art in the field to which this invention belongs. The systems, methods, and examples described herein serve only for illustration and are not to be understood as limiting.

[0043] Embodiments of the present disclosure are described in detail below with reference to the attached drawing.

[0044] Fig.Figure 1 shows a block diagram of a computer-based system for determining the degree of correspondence with the graduate profile of a study program based on academic performance data. The system 100 comprises: a communication interface unit (102) configured to receive academic data from remote computer terminals assigned to an academic unit via a communication network; a storage unit (104) operationally connected to the communication interface unit and configured to store graduate profile data, study area identifiers, subject identifiers, semester identifiers, and subject grade values;a profile processing unit (106) connected to the storage unit and configured to generate a training area data matrix by storing a plurality of training areas for graduate profiles in the storage unit, each training area corresponding to a competency area associated with the completion of the academic program; a curriculum mapping processing unit (108) coupled to the storage unit and configured to generate a subject-to-training area mapping table by mapping each subject of a curriculum to at least one training area for graduate profiles stored in the storage unit;a grade processing unit (110) connected to the communication interface unit and the storage unit, configured to receive semester grade values ​​corresponding to subjects in the curriculum and to generate a semester grade record by storing the received grade values ​​in the storage unit along with subject identifiers and semester identifiers; a contribution calculation unit (112) connected to the storage unit, configured to generate a subject contribution matrix representing the proportional contribution values ​​of the subjects in relation to the respective training areas of the graduate profile; a semester assessment processing unit (114) configured to determine a semester performance value for each training area of ​​the graduate profile based on the subject contribution matrix and the semester grade record;and a control unit (116) connected to the semester assessment unit and configured to determine a cumulative conformity score representing the overall degree of attainment of the graduate profile over several semesters, wherein the contribution calculation unit is configured to generate the subject contribution matrix using a matrix generation circuit that stores subject identifiers along a first dimension and identifiers of the training areas of the graduate profile along a second dimension of the matrix, wherein each matrix element represents a proportional contribution value corresponding to a subject's participation in a respective training area, and wherein the control unit is configured to classify the cumulative conformity score into several predefined conformity levels based on stored threshold ranges representing the performance categories of the graduate profile.

[0045] In an embodiment further comprising a grade normalization unit coupled to the grade processing unit, configured to generate a normalized grade record by converting the grade values ​​of each student into normalized numerical values ​​within a predefined computational range stored in the memory unit.

[0046] In one embodiment, the storage unit (104) stores the subject-matter contribution matrix in a two-dimensional indexed data structure. The processing unit is configured to access matrix elements by using training area and subject-matter identifiers as indexing parameters for retrieving proportional contribution values.The system according to claim 1 further comprises: a parallel computing unit coupled to the semester assessment unit and configured to simultaneously determine semester performance values ​​for multiple areas of the graduate profile using parallel matrix operations on the subject contribution matrix and the semester grade data set; a data aggregation unit configured to generate a multi-semester performance data set by sequentially combining the semester performance values ​​stored in the storage unit to generate cumulative graduate profile conformance values ​​over multiple semesters.

[0047] In one embodiment, the profile processing unit (106) generates the training area data matrix, which contains identifiers representing disciplinary competencies, professional competencies, and behavioral competencies associated with the completion of the academic program, and wherein the curriculum mapping processing unit generates the subject-to-training area mapping table, which contains subject identifiers, semester identifiers, and training area identifiers that form a relational mapping structure.

[0048] In one embodiment, the grade processing unit (110) records the subject grade values ​​on a numerical scale between 1.0 and 7.0, wherein the contribution calculation unit determines a proportional contribution value for each subject based on the ratio between the number of subjects assigned to a training area and the total number of subjects in the curriculum.

[0049] In one embodiment, the contribution calculation unit (112) generates the subject contribution matrix, which represents the weighted participation of the subjects across the training areas of the graduate profile, wherein the semester assessment unit determines the semester performance value for each training area using weighted combinations of subject grades and corresponding contribution values.

[0050] In an embodiment further comprising a comparison processing unit configured to compare the cumulative fulfillment value with a predefined target achievement value stored in the storage unit, wherein the comparison processing unit categorizes the degree of fulfillment of the graduate profile into predefined categories, including achieved, achieved with merit, and achieved with distinction.

[0051] In an embodiment further comprising a visualization interface configured to generate graphical outputs representing the percentage contributions of each subject, the semester achievements, and the cumulative values ​​for adherence to the graduate profile, wherein the semester assessment processing unit generates a performance vector for the training areas, representing the semester-by-semester performance values ​​for the respective training areas of the graduate profile.

[0052] In one embodiment, the control unit (116) generates a multi-semester conformity vector that represents the cumulative graduate profile success values ​​over successive semesters of the curriculum.

[0053] In one embodiment, the contribution calculation unit (112) determines a deviation value that represents the difference between the cumulative fulfillment value and an ideal graduate profile fulfillment value stored in the memory module. The memory module stores data on the curriculum structure, which represents the semester-by-semester allocation of subjects within the academic program.

[0054] The present invention provides a system that determines adherence to graduate profiles based on academic performance using a structured computing apparatus. This apparatus consists of interconnected functional units that acquire data on academic performance, organize study structures, generate contribution matrices, and determine the competency values ​​associated with a graduate profile. The system operates with a sequence of machine-controlled operations in which study information, competency definitions, and academic performance are processed using structured data relationships and matrix-based computational methods stored in a memory architecture.

[0055] In one embodiment of the invention, the system comprises a communication interface configured for data communication with remote computer terminals of academic departments, institutional information systems, or instructor evaluation terminals. The communication interface receives academic data representing the grades derived from the subject assessments conducted during the semesters. The received academic data includes subject identifiers corresponding to the courses within the curriculum, semester identifiers indicating the academic period in which the course took place, and the grades assigned to students upon completion of the course assessments. The communication interface transmits the received academic data to a memory location via an internal data bus structure.

[0056] The storage unit features a structured digital storage architecture capable of storing various data categories necessary for determining graduate profile conformance. Stored data includes graduate profile definitions, which represent competency areas related to completing the degree program. Each competency area corresponds to a field of study, describing a specific category of skills, knowledge, or professional attributes expected of graduates. The storage unit also stores curriculum data, including subject codes assigned to individual courses within the degree program and semester codes indicating the sequence of academic periods in which the courses are offered. Furthermore, the storage unit stores subject grades, representing the academic achievements attained through course assessment.

[0057] A profile processing unit is connected to the storage unit and configured to generate a training area data matrix representing the competency areas defined in the graduate profile. The training area data matrix is ​​created by assigning a unique identifier to each competency area and storing these identifiers in the storage structure. In one implementation, the training area matrix is ​​represented as a structured array where each index corresponds to a competency area defined in the graduate profile. The training area matrix thus serves as a reference structure, enabling subsequent processing modules to access and process competency-related data during evaluation.

[0058] A processing unit for curriculum mapping is operationally linked to the storage unit and configured to create a mapping table between subjects and training areas. This table represents the relationship between curriculum subjects and the graduates' competency areas. Each subject in the curriculum is assigned to one or more training areas according to the competency contributions defined in the curriculum design. The mapping unit stores these assignments in the storage unit as a relational mapping structure containing subject and associated training area identifiers. Using this relational structure, the system can determine which competency areas are influenced by the academic achievements in a particular subject.

[0059] A grade processing unit receives semester grades for the individual subjects of the curriculum and creates a semester grade record, which is stored in memory. Each grade value received by the grade processing unit is linked to a subject and a semester identifier to ensure the correct organization of academic achievements in memory. In certain embodiments, the grade processing unit also includes a normalization mechanism that converts grade values ​​from different grading scales into standardized numerical values ​​within a predefined range. This normalization process may involve converting the grade values ​​into a continuous numerical scale to enable consistent comparison and calculation across different subjects and study phases.

[0060] After capturing and storing the curriculum mapping information and semester grade data, the system activates a unit for calculating subject contributions. This generates a subject contribution matrix that represents the proportional contributions of subjects to the respective areas of study within the graduate profile. The subject contribution matrix is ​​structured as a two-dimensional data structure, with subject codes arranged along the first dimension and area codes along the second. Each matrix element represents a proportional contribution coefficient that indicates the extent to which a particular subject contributes to the development of a corresponding area of ​​competence.

[0061] The contribution coefficients stored in the subject contribution matrix can be determined based on the distribution of courses across the competency areas defined in the graduate profile. In one implementation, the coefficient for a specific subject and training area pair can be calculated using a proportional distribution method, where the contribution value is defined as the inverse of the number of subjects assigned to the training area. If a total of (N) courses are assigned to a training area, each course contributes proportionally (1 / N) to that training area. In alternative implementations, the contribution coefficients can take into account additional weighting factors such as credit points, teaching hours, or competency priorities defined within the framework of curriculum development.

[0062] Once the subject contribution matrix is ​​created, the system performs the semester assessment. For this, it uses a semester assessment unit configured to determine the performance values ​​for each area of ​​study within the respective degree program during the semester. The semester assessment unit retrieves the normalized subject grades from the semester grade dataset and multiplies them by the corresponding contribution coefficients from the subject contribution matrix. This distributes the subject grades according to the respective influence of each subject on the competency areas.

[0063] The calculated semester performance scores are stored in memory as part of a competency area vector, which represents the competency scores achieved in the study segment. The system can repeat this evaluation process for each semester of the degree program, thus generating a sequence of competency area vectors that map competency acquisition across multiple study segments.

[0064] A control unit is configured to aggregate semester performance scores across multiple semesters to determine the cumulative conformance scores of the graduate profile. The control unit retrieves the performance vectors stored for each semester in the individual areas of study and performs a sequential accumulation of the performance scores for each competency area. The cumulative conformance score for each area of ​​study is thus the sum of the semester performance scores assigned to that area across all semesters of the degree program.

[0065] The control unit can also generate a multi-semester conformance vector that represents the cumulative competency achievement values ​​for all areas of study in the graduate profile. The conformance vector provides a quantitative representation of the degree to which each competency area defined in the graduate profile has been achieved, based on the academic performance recorded throughout the entire study program.

[0066] To determine whether the graduate profile requirements are met, the control unit compares the cumulative conformance scores with predefined threshold ranges stored in memory. These threshold ranges represent classification boundaries corresponding to different competency levels, such as minimum performance, satisfactory performance, or advanced performance. If the cumulative conformance score for a specific training area exceeds the predefined threshold for that competency area, the system assumes that the competency requirement is met.

[0067] In certain embodiments, the system may further include a parallel processing unit configured to perform matrix operations simultaneously for multiple educational areas using parallel processing circuits. This parallel processing capability significantly improves computational efficiency when assessing extensive academic programs with numerous subjects and competency areas.

[0068] The system can additionally include a visualization interface that generates graphical or analytical representations of the calculated conformance values. This interface can create charts or data tables that depict the percentage contributions of individual subjects, the semester achievements in the respective competency areas, and the cumulative conformance indicators of the graduate profile across the entire degree program.

[0069] By integrating a communication interface, storage, profile processing, curriculum mapping, grade processing, contribution calculation, semester assessment, and control unit, the present invention provides a structured, machine-based device that can determine compliance with the graduate profile based on academic performance data. The processing technology implemented in the system ensures that academic achievements at the subject level are systematically converted into measurable competency values ​​that correspond to the graduate profile defined for the degree program.

[0070] In certain embodiments, the system includes a network communication interface configured to receive academic data from institutional terminals.

[0071] A structured storage system stores information about the graduate's profile and the course content.

[0072] A profile processing unit creates competency area matrices that represent the profile structures of university graduates.

[0073] A curriculum map assigns subjects from a curriculum to competency areas.

[0074] A grade recording unit stores the subject grades obtained from academic assessment documents.

[0075] A calculation procedure for the contributions generates a contribution matrix of the individual persons, which represents the weighted participation of the persons within the areas of competence.

[0076] A semester evaluation meeting determines the performance values ​​for competency areas using matrix-based calculations.

[0077] A control unit generates cumulative conformity indicators and classification results that represent the achievement of the graduate profile.

[0078] The system for determining graduate profile conformity based on academic performance data includes an integrated computing device consisting of a variety of interconnected hardware modules and configured for the structured evaluation of academic data.

[0079] In one embodiment, the system comprises a communication interface configured to connect data via a communication network to remote academic endpoints such as lecturer input stations, institutional database servers, or curriculum management systems. The communication interface receives information on the academic grades for the subjects taught within a degree program.

[0080] A storage unit is operationally connected to the communication interface unit and serves as a structured digital storage for storing graduate profile definitions, competence area identifiers, curriculum subject identifiers, semester identifiers and grade values ​​assigned to the individual subjects.

[0081] A profile processing unit is connected to the storage unit and configured to generate a training area matrix representing a variety of competency areas of the graduate's profile. Each competency area represents a defined training area associated with the completion of the academic program.

[0082] A curriculum mapping unit is operationally coupled to the storage unit and configured to generate a relational association table that links curriculum subjects to one or more areas of expertise in the graduate profile. The relational mapping structure establishes the relationship between subject-specific teaching and the competency areas defined in the graduate profile.

[0083] A grade recording unit receives subject grade values ​​that correspond to the subjects in the curriculum and stores the grade values ​​together with associated subject and semester identifiers in memory.

[0084] A module for calculating contributions generates a subject contribution matrix that represents the proportional contribution values ​​of subjects in relation to the respective training areas of the graduate profile. In one implementation, the contribution matrix is ​​created by storing subject identifiers in the first dimension and training area identifiers in the second dimension. Each matrix element contains a proportional contribution coefficient that indicates the influence of a particular subject on a specific competency area.

[0085] A semester assessment module is configured to determine performance scores for each competency area during a specific semester. The assessment module performs structured calculations based on the subject contribution matrix and the subject grades stored in memory.

[0086] A control unit aggregates semester performance scores across multiple semesters of the degree program to generate cumulative conformance indicators that represent the overall performance of the graduate profile. The control unit then compares these cumulative conformance scores with predefined threshold ranges stored in memory to determine a conformance classification of the graduate profile.

[0087] In some embodiments, the system includes a grade normalization module configured to convert subject grades into normalized numerical values ​​within a predefined computational range to enable consistent assessment across multiple academic grading scales.

[0088] In certain implementations, a module for parallel calculations is integrated into the system architecture to simultaneously perform matrix operations for multiple competence areas and thus accelerate the calculation of semester performance values.

[0089] The system may also include a visualization interface configured to generate graphical representations of competency achievement levels, subject contribution percentages, and cumulative graduate profile conformance scores.

[0090] By integrating these hardware modules and matrix generation mechanisms, the system provides a technical device for determining graduate profile conformity based on curriculum grade data stored throughout the academic program.

[0091] The system is realized through concrete technological structures, not merely through abstract data processing. Each functional element of the system is implemented through hardware-based electronic circuits and computing components integrated into a computer-based architecture. The communication interface is implemented as a hardware communication subsystem and comprises network interface circuits, transceiver circuits, input / output controllers, and communication ports configured for electronic connection to remote computer terminals in various departments via a wired or wireless communication network. The communication interface receives digital academic data sets from remote terminals and converts the received signals into machine-readable digital data streams, which are then transmitted via the system's internal data buses.The storage unit uses non-volatile electronic storage media such as semiconductor memory, magnetic storage, or solid-state storage, which can permanently store structured data sets such as graduate profiles, study area, subject and semester codes, subject grades, course contribution matrices, and other intermediate results required for system operation. The storage unit comprises addressable memory locations that internal processors can access via memory controllers and data buses. This enables the retrieval and modification of stored data structures during the execution of computational operations.

[0092] The profile processing unit, curriculum mapping processing unit, grade processing unit, contribution calculation unit, semester assessment unit, control unit, grade normalization unit, parallel processing unit, data aggregation unit, and comparison unit are each implemented by one or more electronic processing circuits. These consist of programmable microprocessors, digital signal processors, or application-specific integrated circuits (ASICs) configured to execute stored instruction sets retrieved from memory. The processing circuits include arithmetic logic units, instruction decoding circuits, internal registers, and clock-driven control logic that enables the execution of mathematical and logical operations on stored data.Using these hardware circuits, the profile processing unit physically generates a data matrix for the study areas by writing study area identifiers to the designated memory addresses. The curriculum mapping processing unit creates the mapping table between subjects and study areas by storing relational mapping records that link subject identifiers with study area identifiers and semester identifiers in indexed data structures in memory. The grade processing unit receives grade values ​​via the communication interface and stores them in a semester grade record. Memory addressing operations are used to link each grade value with the corresponding subject and semester identifiers.The unit for calculating contributions includes a matrix generation circuit that assigns subject identifiers along a first matrix dimension and training area identifiers along a second matrix dimension. This generates the subject contribution matrix in memory, while the arithmetic logic circuit calculates the proportional contribution values ​​representing each subject's participation in the respective training areas.

[0093] The semester assessment unit utilizes the hardware's computing circuitry to perform matrix-based calculations. Normalized or raw subject grades from the semester grade dataset are multiplied by the corresponding contribution values ​​from the subject contribution matrix to generate semester performance scores for each area of ​​study. The parallel processing unit, where available, is implemented with multi-core processors or parallel computers capable of performing matrix operations simultaneously across multiple area datasets. This accelerates the determination of semester performance scores. The data aggregation unit performs sequential accumulation operations by retrieving semester performance scores from memory and generating cumulative, cross-semester performance datasets that represent the overall performance of the graduate's profile.The control unit is implemented as a higher-level processing unit that executes decision logic instructions from memory to determine cumulative conformance values ​​and classify them into predefined conformance levels based on threshold ranges stored in memory. The comparison unit performs hardware-based numerical comparison operations to determine the differences between calculated conformance values ​​and predefined target values.

[0094] The visualization interface is implemented using hardware display controllers and a graphics output circuit that sends graphical display commands to display devices, thus enabling visual representations of the percentage contributions of individual subjects, semester grades, and cumulative completion values. Internal system communication between the various units takes place via electrical connections such as system, data, address, and control buses, which ensure coordinated data exchange between the processing circuitry and storage hardware.Through this arrangement of communication interfaces, storage hardware, processing circuitry and display control electronics, the described system provides a feasible computer device that can receive academic data, perform a matrix-based computer-aided evaluation of academic performance and generate measurable indicators for the fulfillment of study requirements over several semesters of a degree program.

[0095] The drawing and the preceding description illustrate embodiments. Those skilled in the art will recognize that one or more of the described elements can be combined to form a single functional element. Alternatively, certain elements can be divided into several functional elements. Elements of one embodiment can be added to another. For example, the process flows described here can be modified and are not limited to the manner described herein. Furthermore, the actions of a flowchart need not be performed in the sequence shown; nor do all actions necessarily need to be carried out. Actions that do not depend on other actions can be performed in parallel with the other actions. The scope of protection of the embodiments is in no way limited by these specific examples. Numerous variations, whether explicitly stated in the description or not, such as...Differences in structure, dimensions, and materials are possible. The scope of protection of the embodiments is at least as comprehensive as described by the following claims.

[0096] The advantages, other benefits, and problem solutions have been described above with reference to specific embodiments. However, the advantages, benefits, problem solutions, and any components that can effect or enhance an advantage, benefit, or solution are not to be construed as critical, necessary, or essential features or components of the claims. REFERENCES 100 A computer-aided system for determining the degree of conformity with the graduate profile of an academic program based on data on the curriculum grades. 102 Communication interface unit 104 storage units 106 Profile processing unit 108 Processing Units for Curriculum Assignment 110 sorting system 112 Processing unit for contribution calculation 114 Semester assessment processing unit 116 Control unit

Claims

A computer-based system for determining the degree of conformity with a graduate profile of an academic program based on academic performance data, wherein the system comprises: a communication interface unit configured to receive academic data from remote computer terminals connected to an academic unit via a communication network; a storage unit operationally connected to the communication interface unit and configured to store graduate profile data, field of study identifiers, subject identifiers, semester identifiers, and subject grade values;a profile processing unit connected to the storage unit and configured to generate a training area data matrix by storing a variety of training areas for graduate profiles in the storage unit, each training area corresponding to a competency area associated with the completion of the academic program; a curriculum mapping processing unit coupled to the storage unit and configured to generate a subject-to-training area mapping table by mapping each subject of a curriculum to at least one training area for graduate profiles stored in the storage unit;a grade processing unit connected to the communication interface unit and the storage unit, configured to receive semester grade values ​​corresponding to subjects in the curriculum and to generate a semester grade record by storing the received grade values ​​in the storage unit along with subject and semester identifiers; a contribution calculation unit connected to and configured with the storage unit to generate a student contribution matrix representing the proportional contribution values ​​of the students in relation to the respective fields of study within the university profile; a semester assessment unit configured to determine a semester performance value for each field of study within the graduate profile based on the subject contribution matrix and the semester grade record;and a control unit connected to the semester assessment unit and configured to determine a cumulative conformance score representing the overall degree of attainment of the graduate profile over several semesters, wherein the contribution calculation unit is configured to generate the subject contribution matrix using a matrix generation circuit that stores subject identifiers along a first dimension and identifiers of the graduate profile's areas of study along a second dimension of the matrix, each matrix element representing a proportional contribution value corresponding to a subject's participation in a respective area of ​​study, and wherein the control unit is configured to classify the cumulative conformance score into a variety of predefined conformance levels based on stored threshold ranges representing the graduate profile's performance categories. System according to claim 1, further comprising a grade normalization unit coupled to the grade processing unit, which is configured to generate a normalized grade data set by converting the grade values ​​of the individual pupils into normalized numerical values ​​within a predefined computational range stored in the storage unit. System according to claim 1, wherein the storage unit stores the subject contribution matrix in a two-dimensional indexed data structure and the processing unit is configured to access matrix elements by using training area identifiers and subject identifiers as indexing parameters for retrieving proportional contribution values. System according to claim 1, further comprising: a parallel computing unit coupled to the semester assessment processing unit and configured to simultaneously determine semester performance values ​​for a plurality of training areas of the graduate profile using parallel matrix operations performed on the subject contribution matrix and the semester grade data set; a data aggregation processing unit configured to generate a multi-semester performance data set by sequentially combining semester performance values ​​stored in the storage unit to generate cumulative graduate profile conformance values ​​over several semesters. System according to claim 1, wherein the profile processing unit generates the training area data matrix with identifiers representing disciplinary competencies, professional competencies and behavioral competencies related to the completion of the academic program, and wherein the curriculum mapping processing unit generates the subject-training area assignment table with subject identifiers, semester identifiers and training area identifiers forming a relational assignment structure. System according to claim 1, wherein the grade processing unit records the subject grade values ​​on a numerical scale between 1.0 and 7.0 and the contribution calculation unit determines the proportional contribution values ​​for each subject on the basis of a ratio between the number of subjects assigned to a training area and the total number of subjects in the curriculum. System according to claim 1, wherein the processing unit for contribution calculation generates the subject contribution matrix representing the weighted participation of subjects across the training areas of the graduate profile, and wherein the processing unit for semester assessment determines the semester performance value for each training area using weighted combinations of subject grades and corresponding contribution values. The system according to claim 1 further comprises a comparison processing unit configured to compare the cumulative fulfillment value with a predefined target achievement value stored in memory, wherein the comparison processing unit divides the degree of fulfillment of the graduate profile into predefined categories, including achieved, achieved with merit and achieved with distinction. The system according to claim 1 further comprises a visualization interface configured to generate graphical outputs that represent the percentage contributions of the individual subjects, the semester successes and the cumulative values ​​for compliance with the graduate profile, wherein the semester evaluation processing unit generates a training area success vector that represents the semester-wise performance values ​​for the respective training areas of the graduate profile. System according to claim 1, wherein the control unit generates a multi-semester conformity vector representing the cumulative graduate profile success values ​​over successive semesters of the curriculum. System according to claim 1, wherein the processing unit for contribution calculation determines a deviation value representing the difference between the cumulative fulfillment value and an ideal graduate profile achievement value stored in memory, and wherein the memory stores curriculum structure data representing the semester-by-semester allocation of subjects within the academic program.

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