TOOL FOR AUTOMATED GENERATION OF CUSTOM MATHEMATICS PRACTICE PROBLEMS

Abstract

The present disclosure provides a system for automated generation of custom mathematics practice problems. Said system comprises a processor configured to execute instructions, a memory storing a database of mathematical concepts and problem templates, an input interface for receiving user-specific criteria related to difficulty level, problem type, and concept focus, and a problem generator for generating a plurality of practice problems by selecting a problem template from said database and adjusting problem parameters. Said system also includes an output interface to display said practice problems to a user and a feedback component to evaluate user responses and provide performance-based feedback.

Specification

Description:Field of the Invention


The present disclosure generally relates to educational tools. Further, the present disclosure particularly relates to a system for automated generation of custom mathematics practice problems.
Background
The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
Mathematics education has traditionally relied on standardised textbooks and problem sets to teach students various mathematical concepts. Such methods often provide a static set of problems for practice, with little or no flexibility in adjusting problem difficulty levels or customising problems based on the specific needs of individual students. Textbooks and conventional problem sets are limited in providing personalised practice or dynamic problem generation based on user progress and understanding.
One commonly known approach involves the manual selection of problems from pre-designed sets available in printed materials or fixed digital databases. Educators or students typically select problems from such sets without any form of automatic adjustment or customisation. As a result, such a system does not cater to individual learning paces or provide feedback based on the performance of a student. Moreover, static problems presented in textbooks fail to adjust to a student's progression, which limits the effectiveness of problem-solving exercises for different proficiency levels.
Another known system involves the use of basic problem generation software. Such software relies on pre-designed templates for specific mathematical topics but often lacks the capability to dynamically adjust or customise the difficulty level or scope of problems according to the user. Moreover, such systems provide minimal feedback on the performance of users, leading to an incomplete learning experience. The absence of interactive feedback mechanisms results in reduced guidance for students, particularly in identifying mistakes or understanding the steps needed to solve problems. This gap in feedback limits the effectiveness of known systems in helping students to enhance their problem-solving skills.
Further, conventional systems generally do not integrate any form of advanced feedback mechanisms based on user performance. Such systems typically provide problems for students to solve but lack the capacity to evaluate the responses and generate meaningful, personalised feedback. As a result, users are not able to effectively gauge progress or understand specific areas that require further practice. The absence of such dynamic feedback further exacerbates the issue of tailoring problem sets to individual learning needs, limiting the effectiveness of conventional learning tools.
Additionally, some existing systems involve static problem types or limited problem variations, which do not account for the need for diversity in practice problems. Such systems typically provide repetitive problems, leading to a lack of engagement and a reduced ability to assess different facets of problem-solving skills. This static nature fails to address different learning needs, particularly when students require more challenging or varied types of practice problems to fully grasp mathematical concepts.
Moreover, existing systems often focus on delivering problems without providing users with relevant visual aids or real-world contexts, which limits student engagement and their ability to relate problems to practical scenarios. The absence of visual or contextual elements reduces interest in solving problems and hinders the application of mathematical concepts to real-life situations. In many cases, this lack of contextual learning diminishes the overall learning experience and prevents students from understanding the practical implications of mathematical concepts.
In light of the above discussion, there exists an urgent need for solutions that overcome the problems associated with conventional systems and/or techniques for generating and delivering mathematics practice problems.
Summary
The following presents a simplified summary of various aspects of this disclosure in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements nor delineate the scope of such aspects. Its purpose is to present some concepts of this disclosure in a simplified form as a prelude to the more detailed description that is presented later.
The following paragraphs provide additional support for the claims of the subject application.
An objective of the present disclosure is to provide a system to enable automated generation of customised mathematics practice problems based on user-specific criteria, including difficulty level, problem type, and concept focus. Said system further aims to dynamically adjust the problem parameters and deliver feedback to enhance the learning experience of a user.
In an aspect, the present disclosure provides a system comprising a processor to execute instructions, a memory storing a database of mathematical concepts and problem templates, an input interface to receive user-specific criteria, and a problem generator to generate a plurality of practice problems by selecting templates from said database and adjusting parameters based on said criteria. Said system further includes an output interface to display generated problems and a feedback component to evaluate user responses and provide performance-based feedback.
Moreover, the system aims to provide enhanced learning experiences by adjusting the difficulty level of subsequent problems based on performance metrics, integrating real-world applications into problem sets, and incorporating step-by-step hints or visual aids in the displayed problems.

Brief Description of the Drawings


The features and advantages of the present disclosure would be more clearly understood from the following description taken in conjunction with the accompanying drawings in which:
FIG. 1 illustrates a system for automated generation of custom mathematics practice problems, in accordance with the embodiments of the present disclosure.
FIG. 2 illustrates several interconnected components of the system for automated generation of custom mathematics practice problems, in accordance with the embodiments of the present disclosure.
Detailed Description
In the following detailed description of the invention, reference is made to the accompanying drawings that form a part hereof, and in which is shown, by way of illustration, specific embodiments in which the invention may be practiced. In the drawings, like numerals describe substantially similar components throughout the several views. These embodiments are described in sufficient detail to claim those skilled in the art to practice the invention. Other embodiments may be utilized and structural, logical, and electrical changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims and equivalents thereof.
The use of the terms "a" and "an" and "the" and "at least one" and similar referents in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The use of the term "at least one" followed by a list of one or more items (for example, "at least one of A and B") is to be construed to mean one item selected from the listed items (A or B) or any combination of two or more of the listed items (A and B), unless otherwise indicated herein or clearly contradicted by context. The terms "comprising," "having," "including," and "containing" are to be construed as open-ended terms (i.e., meaning "including, but not limited to,") unless otherwise noted. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., "such as") provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.
Pursuant to the "Detailed Description" section herein, whenever an element is explicitly associated with a specific numeral for the first time, such association shall be deemed consistent and applicable throughout the entirety of the "Detailed Description" section, unless otherwise expressly stated or contradicted by the context.
As used herein, the term "processor" refers to any central processing unit or computing device capable of executing instructions provided by software or hardware in a system. Such a processor may be responsible for handling a variety of computational tasks required to generate and deliver custom mathematics practice problems. Said processor is responsible for interpreting input criteria, executing problem generation logic, and managing the interactions between various components of the system. In some embodiments, the processor may consist of multiple cores or units working in parallel to enhance the system's performance. The processor may also interact with external databases or cloud-based systems to retrieve additional mathematical concepts or problem templates. In other embodiments, the processor may be integrated with auxiliary devices or systems to facilitate faster execution of tasks. The processor may further handle tasks related to data storage, retrieval, and overall system management in response to user interactions or system demands.
As used herein, the term "memory" refers to any type of non-volatile or volatile storage medium used for retaining data and software instructions in a system. Such memory may communicate with the processor and store a database comprising mathematical concepts and problem templates. Said memory is responsible for retaining both static and dynamic data, which can be accessed and modified by the system during operation. The memory may store a wide range of mathematical content, including formulas, equations, and problem-solving techniques. The memory may also store data related to user progress, preferences, and performance history, enabling the system to adapt its problem generation to user needs. In some embodiments, memory may include multiple layers or types, such as RAM for short-term data access and a database for long-term storage. Such memory may be expandable or connected to external storage for additional capacity.
As used herein, the term "input interface" refers to any device or mechanism through which user-specific criteria may be received in a system. Said input interface may include physical input devices such as keyboards, touchscreens, or any other hardware that facilitates the entry of user data. In some embodiments, said input interface may also consist of software interfaces that allow users to input criteria such as difficulty level, problem type, and concept focus. The input interface may receive input from a single user or multiple users, depending on system configuration. In other embodiments, the input interface may allow for integration with third-party devices or applications, enhancing data entry flexibility. The input interface processes such data, enabling further components of the system to generate custom problems based on user preferences or needs. Input methods may also include voice commands or gesture-based interactions.
As used herein, the term "problem generator" refers to a component that dynamically generates practice problems based on user-specific criteria. Said problem generator selects templates from a database of mathematical concepts and modifies the parameters of said templates to create a variety of problems. The problem generator processes input criteria such as difficulty level, problem type, and concept focus to produce problems tailored to the user's requirements. In some embodiments, the problem generator may also incorporate multiple mathematical concepts into single problems, enhancing the complexity and variety of generated exercises. Said problem generator may access stored data or formulas and adjust problem structures accordingly. Further, the problem generator may employ randomisation techniques or predefined parameters to ensure uniqueness in each generated problem set, while maintaining adherence to the user's input criteria.
As used herein, the term "output interface" refers to any display mechanism that presents generated practice problems to a user in a system. Said output interface may include screens, monitors, projectors, or any other visual output device capable of conveying mathematical problems and their associated data. In some embodiments, the output interface may also provide interactive elements such as buttons or touch-sensitive areas, allowing users to directly engage with the presented problems. Said output interface may display problems in various formats, including step-by-step problem-solving hints or visual aids, enhancing the user's engagement with the material. The output interface may also present multiple problems simultaneously or allow for switching between problem sets. In other embodiments, the output interface may integrate with external devices or platforms, enabling remote display or collaboration.
As used herein, the term "feedback module" refers to a system component responsible for evaluating user responses to generated practice problems and providing performance-based feedback. Said feedback module processes user inputs, compares them against correct answers, and generates detailed feedback based on user performance. In some embodiments, the feedback module may identify specific areas of weakness, offering suggestions for improvement or further practice. Said feedback module may also dynamically adjust subsequent problems, modifying their difficulty level based on the user's progress or areas of difficulty. In other embodiments, the feedback module may store data related to user performance and use it to generate reports or summaries of progress over time. Feedback provided by said module may include immediate corrections, explanations, or next-step recommendations.
FIG. 1 illustrates a system for automated generation of custom mathematics practice problems, in accordance with the embodiments of the present disclosure. In an embodiment, a processor is provided to execute instructions within the system for automated generation of custom mathematics practice problems. Said processor may receive data from an input interface, process said data by executing stored instructions, and manage the operation of other system components. The processor can perform calculations, execute problem generation logic, and retrieve or store information as required by the system. In some embodiments, the processor may execute tasks in real time, dynamically adjusting operations based on received input or performance data. In further embodiments, the processor may manage multiple tasks simultaneously, coordinating the generation of practice problems and processing of user responses. The processor may also interact with external systems or devices through communication interfaces, enabling updates or integration of external resources. Additionally, the processor may be implemented using various technologies such as microprocessors, multicore processors, or distributed computing environments, depending on the specific system configuration.
In an embodiment, the system includes a memory in communication with said processor. Said memory stores a database that includes mathematical concepts and problem templates. Such memory may be implemented using various types of storage, including but not limited to non-volatile storage, dynamic memory, and cloud-based storage. The database stored within the memory contains predefined problem structures, formulas, equations, and concept-specific elements that the system accesses during operation. Said memory is responsible for maintaining the integrity of stored data and may allow retrieval and updates of mathematical content as needed. In some embodiments, the memory may also store user performance data, history of completed problems, and other relevant information that assists in customising practice problems. Said memory may operate in conjunction with external storage devices or cloud platforms to expand storage capacity and ensure that up-to-date mathematical content is available for problem generation.
In an embodiment, the system provides an input interface for receiving user-specific criteria, such as difficulty level, problem type, and concept focus. Said input interface can consist of physical devices such as a keyboard, mouse, or touchscreen that allow users to input data manually. In some embodiments, the input interface may also include a graphical user interface or software interface that facilitates the selection of problem parameters through dropdown menus, sliders, or text fields. The input interface processes the user's input and transmits said data to the processor for further action. In certain embodiments, said input interface may allow the input of multiple criteria simultaneously, providing a more flexible and personalised problem selection process. The input interface may also enable communication with external devices, such as mobile phones or tablets, which allow remote access to the system for data entry or integration with external educational tools.
In an embodiment, a problem generator is provided within the system, responsible for generating a plurality of practice problems based on user-specific criteria. Said problem generator selects a problem template from the database stored in the memory and dynamically adjusts parameters, such as numbers, values, or steps, to create a custom problem for the user. The problem generator processes data received through the input interface and applies said criteria to produce problems that match the user's requirements. In some embodiments, the problem generator may combine multiple mathematical concepts into a single problem, increasing complexity or variety in generated problem sets. Said problem generator may incorporate randomisation techniques to ensure that each problem is unique while adhering to the selected template. Further, the problem generator may be designed to operate continuously or on-demand, responding in real-time to user input and generating problems as needed.
In an embodiment, the system includes an output interface for displaying a plurality of generated practice problems to a user. Said output interface may consist of a variety of display technologies, such as computer monitors, touchscreens, or projectors, capable of presenting problems visually. In some embodiments, the output interface may allow users to interact directly with the displayed problems, such as by inputting answers, selecting options, or viewing hints. The output interface may support the display of both individual problems and problem sets, depending on user preferences or system settings. In certain embodiments, said output interface may also present step-by-step hints or visual aids to assist users in solving problems. The interface can be configured to adapt the display format based on the type of problem or user settings, ensuring clarity and ease of use in a variety of educational environments.
In an embodiment, the system includes a feedback module that evaluates user responses and provides performance-based feedback. Said feedback module processes user-submitted answers and compares them with the correct solutions stored in the system database. Upon evaluation, the feedback module may generate feedback tailored to the user's performance, identifying correct answers, mistakes, and areas for improvement. In some embodiments, said feedback module may also track user progress over time, adjusting subsequent problems or suggestions based on past performance. The feedback may be presented in various formats, such as text-based explanations, corrective feedback, or performance summaries. Additionally, said feedback module may interact with other system components to store performance data or generate customised reports for users or educators.
In an embodiment, the system's problem generator is further configured to generate multi-step problems that combine mathematical concepts from different categories. Said problem generator can access various problem templates stored in memory and dynamically integrate multiple mathematical concepts such as algebra, geometry, and calculus into a single multi-step problem. Each step of the problem requires the user to apply a different concept, promoting deeper understanding and problem-solving skills. In some embodiments, the system may present problems where the first step involves solving a linear equation, and the subsequent step requires applying the result to a geometric figure. This structure encourages users to think critically and apply multiple mathematical disciplines in sequence. The problem generator may also vary the complexity of each step based on user-specific criteria such as difficulty level, ensuring that each problem set is appropriate for the user's proficiency. Further, the system may introduce intermediate challenges that guide the user through progressively more complex concepts within a single problem-solving session, ensuring comprehensive practice across different mathematical areas.
In an embodiment, the feedback module is further configured to dynamically adjust the difficulty level of subsequent problems based on the performance metrics of the user. Said feedback module evaluates user responses, including correct answers, mistakes, and time taken to solve problems, and uses this information to modify future problems. If a user performs well, the system may increase the complexity of the following problems, introducing more challenging steps or advanced concepts. Conversely, if the user struggles, the feedback module may lower the difficulty, providing simpler problems that reinforce foundational concepts. The feedback module continuously monitors user performance throughout the problem-solving session and adapts future problems to ensure the user's progress is neither too slow nor too fast. In some embodiments, the system may also adjust other parameters such as the number of steps in multi-step problems or the inclusion of hints based on user performance. This dynamic adjustment of problem difficulty helps maintain user engagement and promotes optimal learning progression.
In an embodiment, the system further comprises a recommendation engine configured to suggest targeted problem sets to the user based on previously completed problems and identified areas of difficulty. Said recommendation engine analyses user performance data, which is stored in the system's memory, and identifies specific concepts where the user has demonstrated weaknesses or needs additional practice. Based on such analysis, the recommendation engine selects appropriate problem sets from the database that focus on the identified areas of difficulty. In some embodiments, the recommendation engine may also factor in user preferences, such as the desired problem type or difficulty level, when suggesting problem sets. The recommendation engine operates automatically, continuously updating its suggestions as the user completes more problems and progresses through the system. Additionally, the system may allow users to manually request recommendations, enabling focused practice on specific concepts that the user wishes to improve.
In an embodiment, the problem generator is further configured to incorporate real-world context or applications into said practice problems to enhance engagement with the user. Said problem generator retrieves problem templates from the memory and adjusts parameters to frame mathematical problems within practical scenarios. For example, a problem might require the user to calculate the area of a garden or the volume of a water tank, making abstract concepts more relatable by linking them to real-life situations. The system may incorporate a variety of real-world contexts, including financial calculations, engineering principles, and everyday measurements, ensuring that users understand the practical relevance of the mathematical concepts they are practicing. In some embodiments, the system allows users to select specific contexts of interest, further personalising the problem sets. Incorporating real-world applications into problem generation not only reinforces understanding but also motivates users by showing how mathematics is used in daily life.
In an embodiment, the output interface is further configured to display visual aids or step-by-step problem-solving hints alongside said practice problems. Said output interface can present visual elements such as graphs, charts, geometric figures, or illustrations that help users visualise mathematical problems. The system may display visual aids directly beside the text-based problem or allow users to toggle such aids on or off according to preference. In addition to visual aids, the output interface may provide hints in a step-by-step format, guiding users through the solution process without giving away the final answer. Such hints may be presented as optional steps that users can view if they encounter difficulty solving the problem independently. The system may also allow users to customise the level of detail provided in the hints, enabling flexibility based on individual learning needs. By integrating visual and step-by-step aids, the output interface enhances user comprehension and facilitates effective problem-solving.
In an embodiment, the input interface is further configured to allow customisation of problem presentation, including time limits, number of problems, and problem-solving format. Said input interface receives user preferences regarding how problems are presented and processed. Users can specify a desired time limit for each problem, challenging themselves to solve problems within a defined time frame, or opt for untimed sessions to focus on accuracy. The input interface also allows users to set the number of problems per session, providing flexibility in adjusting the length of practice sessions. In some embodiments, users may customise the problem-solving format, choosing between multiple-choice, fill-in-the-blank, or step-by-step problem-solving formats, depending on their preferences. The input interface communicates such preferences to the processor, which then adjusts the presentation of problems accordingly. This level of customisation allows users to tailor the problem-solving experience to suit their specific learning needs and preferences.
In an embodiment, the memory is further configured to store user progress data and generate reports summarising user performance trends over a predetermined time period. Said memory stores detailed records of each problem a user completes, including the time taken to solve the problem, the accuracy of responses, and any hints accessed during the problem-solving process. Such data may be used to track user improvement and identify long-term trends in performance. The system may generate periodic reports summarising user progress, presenting data in various formats such as graphs, charts, or tables. These reports can highlight areas of improvement or concepts that require further practice. In some embodiments, the system may allow users or educators to customise the reporting period and focus on specific metrics of interest, such as speed or accuracy. The stored data ensures that users have a comprehensive record of their learning progress, enabling informed decision-making about future practice needs.
In an embodiment, the problem generator is further configured to generate problems that require alternative methods of solution, promoting flexible thinking and problem-solving approaches. Said problem generator selects problem templates from the memory that are specifically designed to have more than one valid solution method. For example, a problem involving a geometric figure may be solvable through both algebraic manipulation and geometric reasoning. The problem generator presents such problems to users, encouraging them to explore different approaches and compare results. In some embodiments, the system may provide hints or suggestions about alternative solution methods if users are struggling to find multiple ways to solve the problem. This feature is particularly useful in helping users develop flexible thinking and adaptability in their problem-solving strategies, enhancing their overall mathematical proficiency.
In an embodiment, the system further comprises an analytics component configured to track and store detailed data on response times, accuracy rates, and problem-solving strategies for future analysis. Said analytics component collects performance data as users engage with the practice problems and stores such data in the system's memory for long-term analysis. The analytics component processes the data to generate insights into user behavior, including how quickly users respond to problems, how often mistakes are made, and which problem-solving strategies are most commonly used. In some embodiments, the analytics component may generate custom reports for users or educators, highlighting specific areas of strength or weakness. The data tracked by the analytics component can be used to optimise future problem sets or adjust the system's difficulty settings, ensuring that users receive appropriate levels of challenge as they progress through their mathematical practice.
FIG. 2 illustrates several interconnected components of the system for automated generation of custom mathematics practice problems, in accordance with the embodiments of the present disclosure. The system for automated generation of custom mathematics practice problems can be illustrated as comprising several interconnected components. At the core of the system is a processor that executes instructions and communicates with a memory storing a database of mathematical concepts and problem templates. The input interface allows the user to specify criteria such as difficulty level, problem type, and concept focus. Based on the criteria, the processor coordinates with the problem generator to select relevant templates from the memory and dynamically adjust parameters to create a variety of custom practice problems. These problems are then displayed to the user via the output interface. After the user interacts with the problems, submitting answers or responses, the feedback module evaluates the user's performance. The feedback module sends performance data to the processor and provides feedback to the user, enabling dynamic adjustment of future problems. This integration ensures a personalized learning experience tailored to user needs.
In an embodiment, the processor configured to execute instructions enables real-time processing of user input, problem generation, and feedback evaluation within the system for automated generation of custom mathematics practice problems. The processor communicates with various system components to process user-specific criteria, retrieve data from memory, and manage the problem generation process. By dynamically executing instructions based on input from the user and other system components, the processor allows for continuous interaction and seamless transitions between tasks. This real-time processing capability allows the system to respond efficiently to user inputs, thereby minimizing delays in problem generation and feedback delivery. The processor can handle multiple computational tasks simultaneously, such as adjusting problem parameters and analyzing user performance metrics, resulting in a flexible and responsive system that adapts to various educational needs.
In an embodiment, the memory in communication with the processor stores a database of mathematical concepts and problem templates, ensuring that a wide range of problems can be dynamically generated and personalized according to user-specific criteria. Said memory allows for the retrieval of complex problem structures and mathematical formulas, which are necessary for tailoring the practice problems to individual users. By facilitating efficient data storage and retrieval, the memory ensures that a large repository of mathematical content is readily available for problem generation. Moreover, the memory's ability to store user performance data enables long-term tracking of progress, allowing the system to adapt problem sets over time based on the user's learning curve. This interaction between the memory and other system components supports the continuous personalization of educational content.
In an embodiment, the input interface for receiving user-specific criteria related to difficulty level, problem type, and concept focus enables personalized interaction between the user and the system. Said input interface processes data entered by the user, allowing for the selection of specific problem parameters that cater to individual learning goals. This customization allows the system to generate problems that align with the user's proficiency level and areas of interest. By providing flexibility in how criteria are input, the system ensures that a diverse range of user needs can be addressed. The input interface can support various forms of input, including manual entry via keyboard or touch-based selection through a graphical interface, further expanding its usability across different devices. This enhances the system's adaptability for different learning environments.
In an embodiment, the problem generator is configured to generate a plurality of practice problems based on user-specific criteria by selecting a problem template from the database and dynamically adjusting problem parameters. Said problem generator tailors each problem according to user preferences, such as difficulty level or specific mathematical concepts, ensuring that the generated problems are relevant to the user's learning objectives. By selecting appropriate problem templates and adjusting numerical values or operations within those templates, the problem generator provides a unique set of problems for each practice session. This dynamic adjustment prevents redundancy and promotes continued engagement by offering new challenges. The problem generator can also incorporate different types of problems, such as multiple-choice questions or fill-in-the-blank formats, enhancing the system's versatility.
In an embodiment, the output interface displays the generated practice problems to the user, providing a clear and interactive medium for solving said problems. Said output interface may present problems in various formats, including text-based questions or interactive elements that allow the user to input answers directly. The interface also supports the display of visual aids, such as graphs or diagrams, that complement the problem-solving process. By presenting problems in a user-friendly manner, the output interface facilitates seamless engagement with the educational content. Additionally, the system may allow the user to adjust the display settings, such as font size or contrast, ensuring accessibility for a wide range of users. This flexibility makes the output interface suitable for various educational contexts, from individual learning to classroom use.
In an embodiment, the feedback module is configured to evaluate user responses and provide performance-based feedback, promoting adaptive learning. Said feedback module processes user inputs, comparing responses to correct solutions stored in the system. Upon detecting errors, the module can provide corrective suggestions or explanations, helping users understand where they went wrong and how to improve. By tailoring feedback to the user's specific performance, the system fosters a personalized learning environment that adapts to individual needs. Furthermore, the feedback module can track performance over time, adjusting future problems based on recurring errors or weaknesses in the user's approach. This dynamic feedback mechanism enhances learning outcomes by focusing on the user's progress and providing guidance based on real-time analysis.
In an embodiment, the problem generator is further configured to generate multi-step problems that combine mathematical concepts from different categories. Said generator selects templates that incorporate multiple disciplines, such as algebra and geometry, within a single problem. By requiring the user to apply different mathematical techniques in succession, the system promotes deeper comprehension and problem-solving skills. Multi-step problems challenge the user to understand how different concepts interrelate and develop strategies for solving complex problems. The dynamic generation of these problems ensures that they are customized to the user's proficiency level while providing appropriate levels of difficulty. This encourages the user to think critically and improves their ability to approach multifaceted mathematical scenarios.
In an embodiment, the feedback module is further configured to dynamically adjust the difficulty level of subsequent problems based on the user's performance metrics. Said module monitors user progress during problem-solving sessions, tracking accuracy, time taken, and frequency of errors. Based on this data, the system modifies the complexity of future problems, ensuring that the user is neither overwhelmed nor under-challenged. For instance, if the user consistently solves problems correctly, the system may present more advanced problems. Conversely, if errors are frequent, the system may simplify












I/We Claims


A system for automated generation of custom mathematics practice problems, said system comprising:
a processor configured to execute instructions;
a memory in communication with said processor, said memory storing a database of mathematical concepts and problem templates;
an input interface for receiving user-specific criteria related to difficulty level, problem type, and concept focus;
a problem generator configured to generate a plurality of practice problems based on said user-specific criteria by selecting a problem template from said database and dynamically adjusting problem parameters;
an output interface for displaying said plurality of generated practice problems to a user;
and a feedback module configured to evaluate user responses and provide performance-based feedback to said user.
The system of claim 1, wherein said problem generator is further configured to generate multi-step problems that combine mathematical concepts from different categories.
The system of claim 1, wherein said feedback module is further configured to dynamically adjust the difficulty level of subsequent problems based on performance metrics of said user.
The system of claim 1, further comprising a recommendation engine configured to suggest targeted problem sets to said user based on previously completed problems and identified areas of difficulty.
The system of claim 1, wherein said problem generator is further configured to incorporate real-world context or applications into said practice problems to enhance engagement with said user.
The system of claim 1, wherein said output interface is further configured to display visual aids or step-by-step problem-solving hints alongside said practice problems.
The system of claim 1, wherein said input interface is further configured to allow customization of problem presentation, including time limits, number of problems, and problem-solving format.
The system of claim 1, wherein said memory is further configured to store user progress data and generate reports summarizing user performance trends over a predetermined time period.
The system of claim 1, wherein said problem generator is further configured to generate problems that require alternative methods of solution, promoting flexible thinking and problem-solving approaches.
The system of claim 1, further comprising an analytics component configured to track and store detailed data on response times, accuracy rates, and problem-solving strategies for future analysis.




The present disclosure provides a system for automated generation of custom mathematics practice problems. Said system comprises a processor configured to execute instructions, a memory storing a database of mathematical concepts and problem templates, an input interface for receiving user-specific criteria related to difficulty level, problem type, and concept focus, and a problem generator for generating a plurality of practice problems by selecting a problem template from said database and adjusting problem parameters. Said system also includes an output interface to display said practice problems to a user and a feedback component to evaluate user responses and provide performance-based feedback.

, Claims:I/We Claims


A system for automated generation of custom mathematics practice problems, said system comprising:
a processor configured to execute instructions;
a memory in communication with said processor, said memory storing a database of mathematical concepts and problem templates;
an input interface for receiving user-specific criteria related to difficulty level, problem type, and concept focus;
a problem generator configured to generate a plurality of practice problems based on said user-specific criteria by selecting a problem template from said database and dynamically adjusting problem parameters;
an output interface for displaying said plurality of generated practice problems to a user;
and a feedback module configured to evaluate user responses and provide performance-based feedback to said user.
The system of claim 1, wherein said problem generator is further configured to generate multi-step problems that combine mathematical concepts from different categories.
The system of claim 1, wherein said feedback module is further configured to dynamically adjust the difficulty level of subsequent problems based on performance metrics of said user.
The system of claim 1, further comprising a recommendation engine configured to suggest targeted problem sets to said user based on previously completed problems and identified areas of difficulty.
The system of claim 1, wherein said problem generator is further configured to incorporate real-world context or applications into said practice problems to enhance engagement with said user.
The system of claim 1, wherein said output interface is further configured to display visual aids or step-by-step problem-solving hints alongside said practice problems.
The system of claim 1, wherein said input interface is further configured to allow customization of problem presentation, including time limits, number of problems, and problem-solving format.
The system of claim 1, wherein said memory is further configured to store user progress data and generate reports summarizing user performance trends over a predetermined time period.
The system of claim 1, wherein said problem generator is further configured to generate problems that require alternative methods of solution, promoting flexible thinking and problem-solving approaches.
The system of claim 1, further comprising an analytics component configured to track and store detailed data on response times, accuracy rates, and problem-solving strategies for future analysis.

Documents