Training support evaluation system for disabled people

Abstract

The invention discloses a disabled training support evaluation system, and relates to the technical field of disabled training, and the system comprises a multi-dimensional evaluation module, a quantitative evaluation module, a qualitative evaluation module, and a visual report module. According to the system, a multi-dimensional comprehensive evaluation system including knowledge mastering, skill application, learning attitude and emotion development is constructed, the learning effect of the disabled students is comprehensively covered, and the multi-dimensional evaluation not only pays attention to the knowledge and skill levels of the students, but also deeply investigates the learning attitude and emotion development conditions of the students, so that the learning efficiency of the disabled students is improved. Therefore, one-sidedness possibly brought by single-dimension evaluation is avoided, meanwhile, the system adopts a qualitative and quantitative combined mode, interference of subjective judgment is reduced, objectivity and accuracy of evaluation results are ensured, the comprehensive and objective evaluation system provides more accurate and reliable feedback for trainees and trainees, and the training efficiency is improved. And the two parties can better understand the learning progress.

Description

Technical Field

[0001] The present invention relates to the technical field of disabled people's training, and in particular to a disabled people's training support and evaluation system. Background Art

[0002] With the development of information technology, modern education and training pay more and more attention to personalization and intelligence, especially for special groups such as people with disabilities. It is emphasized that the learning effects of students should be evaluated from multiple angles. Due to their special physical and psychological conditions, people with disabilities face many challenges in the learning process. They need more personalized and comprehensive training support and evaluation systems to help them give full play to their potential, improve their employment ability and quality of life. It is urgent to introduce a more comprehensive evaluation mechanism to promote the all-round development of students. In this context, it is particularly important to establish a multi-dimensional comprehensive evaluation system.

[0003] However, most of the existing evaluation systems for people with disabilities focus on the two traditional dimensions of knowledge mastery and skill application, and pay insufficient attention to the learning attitude and emotional development of people with disabilities during the learning process. Learning attitude directly affects the enthusiasm and persistence of people with disabilities in learning, while emotional development is related to their mental health and self-confidence. The lack of consideration of these dimensions makes the evaluation results incomplete and unable to accurately reflect the comprehensive learning outcomes of people with disabilities. In terms of evaluation methods, the existing system mainly relies on quantitative evaluation, which makes it difficult to gain an in-depth understanding of the learning process and inner experience of people with disabilities. The lack of qualitative evaluation makes it impossible to conduct in-depth analysis of the learning attitude and emotional development of people with disabilities, discover the specific problems and needs they face in learning, and provide sufficient basis for personalized training support.

[0004] To sum up, the existing training evaluation system for people with disabilities has the problems of single evaluation dimension and incomplete and objective evaluation method. Therefore, developing a comprehensive evaluation system for people with disabilities covering multiple aspects such as knowledge mastery, skill application, learning attitude and emotional development will further promote the intelligent and personalized development of the training support evaluation system for people with disabilities, and provide more efficient and accurate learning support services for disabled students. Summary of the invention

[0005] The purpose of the present invention is to make up for the shortcomings of the existing technology and provide a training support evaluation system for the disabled. It can use a comprehensive evaluation system of knowledge mastery, skill application, learning attitude, and emotional development in multiple dimensions, and adopt a combination of qualitative and quantitative methods for evaluation. It can comprehensively and objectively reflect the learners' learning outcomes, and can also provide detailed data support for trainers to carry out targeted teaching adjustments and optimizations, realize quantitative analysis of qualitative data and intelligent integration and feedback of multi-dimensional evaluation results, and provide strong support and guarantee for the training of the disabled.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a support and evaluation system for disabled people's training, the components of which include: a multi-dimensional evaluation module, a quantitative evaluation module, a qualitative evaluation module, and a visual report module;

[0007] The multi-dimensional evaluation module constructs a comprehensive evaluation system of multiple sub-dimensions including knowledge mastery, skill application, learning attitude, and emotional development;

[0008] The quantitative evaluation module uses data statistics and analysis methods to conduct quantitative evaluation of knowledge mastery and skill application sub-dimensions to reflect the overall level and individual differences of trainees;

[0009] The qualitative evaluation module uses expert evaluation, student peer evaluation, and self-evaluation to conduct qualitative analysis of learning attitudes and emotional development dimensions;

[0010] The visualization report module visualizes the students' evaluation data in the form of charts, intuitively reflecting the students' performance in various dimensions. Based on the visualization data, the system automatically generates a detailed learning effectiveness report. The report content includes the students' basic information, evaluation results in each dimension, progress trajectory, and potential improvement points.

[0011] Furthermore, the multi-dimensional evaluation module specifically includes:

[0012] Knowledge mastery sub-dimension: evaluate the mastery of theoretical knowledge of disabled trainees in the training courses through online tests and homework submission;

[0013] Skill application sub-dimension: Introduce virtual reality (VR) and augmented reality (AR) technologies to simulate real life and work scenarios, set practical operation tasks and simulation scenarios, and examine the ability of disabled trainees to apply the skills they have learned to practice;

[0014] Learning attitude sub-dimension: Using sensors and data analysis, we monitor students’ learning time, participation, and question frequency to assess their learning attitudes. We also record students’ viewing time and number of interactions in online courses to determine their learning enthusiasm.

[0015] Emotional development sub-dimension: Through questionnaire surveys and interviews, we understand the emotional changes and psychological states of disabled trainees during the training process, and ask trainees about their feelings about their improved self-confidence and expectations for the future to assess their emotional development.

[0016] Furthermore, the specific steps of the knowledge mastery sub-dimension are:

[0017] Course content decomposition: The training course is carefully decomposed according to the knowledge points, and the importance and difficulty of each knowledge point are clearly defined;

[0018] Online test design: Design a variety of online test questions based on knowledge points, including multiple-choice questions, fill-in-the-blank questions, and short-answer questions to ensure that the disabled students' mastery of theoretical knowledge can be fully examined;

[0019] Homework assignments: Assign targeted homework tasks based on the course content, requiring students to apply the knowledge they have learned to answer questions and perform practical operations;

[0020] Test and homework grading: The system automatically grades online test questions and performs preliminary screening and classification of homework tasks. For complex homework, trainers will manually grade it.

[0021] Knowledge mastery assessment: Calculate students’ knowledge mastery based on test scores and question difficulty, and analyze students’ weaknesses in each knowledge point.

[0022] Furthermore, the knowledge mastery sub-dimension collects the student's online test scores, and calculates the knowledge mastery score K by combining the weighted score with the difficulty coefficient according to the question weight and difficulty coefficient, as well as the student's actual score. knowledge ,Right now S i is the score of the ith test question, W i It is set according to the importance of the topic. i is the difficulty coefficient of the question, n is the total number of test questions, and the calculation results are saved in the student's learning file to more accurately reflect the student's mastery of key knowledge and for subsequent analysis and report generation.

[0023] Furthermore, the specific steps of the skill application sub-dimension are:

[0024] Scene construction: Use virtual reality (VR) and augmented reality (AR) technologies to build real life and work scenes, including different environments such as offices, factory workshops, and stores;

[0025] Task setting: Setting actual operation tasks according to the scenario, i.e., document processing and meeting organization in the office scenario, and equipment operation and product assembly in the factory workshop scenario;

[0026] Determination of skill evaluation indicators: Determine the evaluation indicators for skill application, namely, time efficiency of task completion, degree of quasi-task completion, and error rate;

[0027] Simulation task execution: Trainees perform actual operation tasks in a virtual scene, and the system records the trainees' operation process through sensors and data analysis technology;

[0028] Skill application assessment: Conduct a quantitative assessment of the trainees’ task execution based on the assessment indicators. Combined with expert evaluation and trainee peer evaluation, conduct a comprehensive assessment of the trainees’ skill application capabilities.

[0029] Furthermore, the skill application sub-dimension uses VR / AR technology to design simulation scenarios close to real life and work according to the training objectives, including daily life scenarios and work environment simulations. Specific operation tasks are set in the simulation scenarios and trainees are required to complete them within the specified time. The operation process of trainees in the simulation scenarios is recorded in real time, including operation steps, time, and number of errors. The skill application is comprehensively evaluated using the three dimensions of task completion, time efficiency, and error rate. The skill application score S skill The calculation formula is C is the task completion, T is the time required to complete the task, E is the error rate, and C max is the maximum completion degree of the task, T min This is the fastest completion time among all the students.

[0030] Furthermore, the quantitative evaluation module automatically adjusts the scoring weight based on the performance changes of the students in different time periods, and the specific steps are as follows:

[0031] Initial weight setting: Set initial weight values ​​for the two dimensions of knowledge mastery and skill application. and

[0032] Performance data collection: During each evaluation cycle, students’ performance data on knowledge mastery and skill application are collected, i.e. test scores, assignment scores, and practical operation scores;

[0033] Dynamic weight adjustment: Based on the student's performance data in the current evaluation cycle, compare it with the performance data in the previous cycle, calculate the performance change rate r, and adjust the weight accordingly. If the student's performance improves, the weight of the dimension will be increased accordingly, otherwise the weight will be reduced. The calculation formula for the performance change rate r is: Where X current represents the total performance score of the current period, X previous Represents the sum of performance scores for the previous period;

[0034] Weight update: Update the weights of knowledge mastery and skill application according to the performance change rate r, that is, Among them, α and β are adjustment factors used to control the speed of weight change;

[0035] Comprehensive score calculation: Use the updated weight values ​​to recalculate the student's comprehensive score, that is, Where Kknowledge and S skill Respectively represent the students’ scores in knowledge mastery and skill application;

[0036] Continuous iteration: Repeat the steps to dynamically adjust the weights to calculate the comprehensive score, update the weights after each evaluation cycle, and recalculate the comprehensive score until the end of the evaluation cycle.

[0037] Furthermore, the learning attitude sub-dimension uses the student learning time, participation, and question frequency data recorded by the system as basic data, and uses an algorithm to quantify participation and enthusiasm. The algorithm formula is: Among them, T act is the time that students actually participate in learning, T tot is the total learning time, F ques It is the frequency of students asking questions, A is the participation and enthusiasm index. The A value is standardized to eliminate the impact of the difference in total learning time between different students, and the standardized participation and enthusiasm index SA is obtained.

[0038] Furthermore, the emotional development sub-dimension is designed to include a multi-dimensional emotional questionnaire including self-confidence, expectations, and emotional changes. The emotional state data of the trainees is obtained through questionnaire collection. For each emotional question in the questionnaire, the score of positive answers is set to be higher than that of negative answers. The calculation formula is: Among them, S i is the benchmark score for this problem, P i is the number of people who choose the positive answer, N i is the number of people who chose negative answers, ELS i is the emotional tendency score, which combines all emotional questions into an ELS i The weighted sum is used to obtain the comprehensive sentiment index, and the calculation formula is: Where m is the total number of emotional questions, W i It is the weight of each question. By adjusting self-confidence, emotional state and expectations for the future, the comprehensive emotional index can be reasonably determined according to the training objectives and the characteristics of the trainees.

[0039] Furthermore, the qualitative evaluation module collects unstructured data generated by trainees during the training process and assigns a sentiment index CEI to positive and negative sentiment words. i ,For each student, track the changes of their comprehensive emotional index at different time points t, draw the emotional change curve, smooth the emotional change curve to eliminate the impact of short-term fluctuations, and obtain a more stable emotional development trend, that is, m is the total number of emotional problems, CEI jis the emotional index at the jth time point. According to the trend of emotional change, the emotional development of each student is scored. The calculation formula of the emotional development score D is: Where T is the total number of time points in the evaluation period, E m (t) is the comprehensive emotion index at the tth time point. The calculated emotion development score is compared with the expert manual review result, and revised according to the expert opinions and historical data. The final emotion development score is integrated into the qualitative evaluation report and presented to the trainees and trainers together with the engagement and motivation indicators.

[0040] Compared with the existing technology, the disabled training support and evaluation system has the following beneficial effects:

[0041] 1. This system achieves comprehensive coverage of the learning outcomes of disabled students by constructing a multi-dimensional comprehensive evaluation system that includes knowledge mastery, skill application, learning attitude, and emotional development. This multi-dimensional evaluation not only focuses on the students' knowledge and skill levels, but also deeply examines their learning attitudes and emotional development, thereby avoiding the one-sidedness that may be caused by a single-dimensional evaluation. At the same time, the system adopts a combination of qualitative and quantitative methods to reduce the interference of subjective judgment and ensure the objectivity and accuracy of the evaluation results. This comprehensive and objective evaluation system provides trainers and trainees with more accurate and reliable feedback, which helps both parties better understand the learning progress and formulate more appropriate learning plans.

[0042] 2. This system focuses on customized evaluation based on the individual differences and special needs of disabled students. By collecting and analyzing various data of students during the learning process, the system can automatically identify their learning characteristics and areas of strength, and then provide each student with personalized learning suggestions and feedback. It can also automatically summarize the multi-dimensional evaluation results into a comprehensive report and present it to students and trainers in an intuitive and easy-to-understand manner. This highly personalized evaluation and intelligent feedback mechanism not only improves the evaluation efficiency, but also promotes students' independent learning and active development, providing strong support for the vocational training and future development of disabled students.

[0043] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 Operational flow chart of the training support evaluation system for people with disabilities.

[0046] Figure 2 Schematic diagram of different sub-dimensions of the multidimensional assessment module in the training support evaluation system for people with disabilities. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] Embodiment 1

[0049] This embodiment describes in detail the specific implementation process of the disability training support evaluation system. The system comprehensively and objectively evaluates the learning outcomes of disabled trainees in terms of knowledge mastery, skill application, learning attitude and emotional development through the comprehensive use of multi-dimensional evaluation modules, quantitative evaluation modules, qualitative evaluation modules and visual reporting modules, and generates detailed visual reports, providing strong data support and personalized learning suggestions for trainers and trainees.

[0050] In the specific implementation, first, the disabled training support and evaluation system is deployed on a stable server, and the local area network is used to ensure that trainees and trainers can use the system smoothly. Disabled trainees register in the system and enter their basic personal information in detail, including name, age, disability type, and degree of disability. At the same time, trainees are also required to provide relevant background information, such as education level, work experience, etc., so that the system can better understand the trainees' starting point and needs. Trainers develop personalized training plans for each trainee based on the information provided by the trainees and the goals and requirements of the training program. For example, for trainees with severe physical disabilities, the training plan may focus on training in computer skills and other aspects to reduce the impact of physical inconvenience on learning; for visually impaired trainees, the proportion of speech recognition and audio learning resources may be increased.

[0051] Then, the multi-dimensional assessment module implements the outline of the training course, breaks down the knowledge system into specific knowledge points, and clarifies the importance and difficulty of each knowledge point. The online test questions cover multiple-choice questions, fill-in-the-blank questions, short-answer questions and other forms, which comprehensively examine the students' understanding and mastery of theoretical knowledge. The homework tasks are closely integrated with the course content, requiring students to use the knowledge they have learned to solve or operate practical problems. The system automatically corrects the online test questions and conducts preliminary screening and classification of the homework tasks. For some complex homework tasks that require in-depth analysis, the trainers will manually correct and evaluate them. Comprehensive analysis of the completion of homework, calculate the students' knowledge mastery, and find out the weak links of students in various knowledge points, provide a basis for subsequent targeted tutoring, and use virtual reality (VR) and augmented reality (AR) technology to build highly realistic real-life and work scenes, such as offices, factory workshops, stores, etc. According to the characteristics of different scenes, set corresponding actual operation tasks and simulation scenes. For example, in the office scene, students need to complete tasks such as document processing and meeting organization; in the factory workshop scene, students need to perform equipment operation, product assembly and other tasks. In the process of students performing tasks, The system uses sensors and data analysis technology to record the trainees' operation process in real time, including details such as operation steps, time taken, errors, etc. After completing the task, the system conducts a quantitative assessment of the trainees' skill application ability based on pre-determined skill evaluation indicators, such as task completion time efficiency, quasi-task completion, error rate, etc. At the same time, it conducts a comprehensive evaluation of the trainees' skill application ability by combining expert evaluation and trainee mutual evaluation. Experts will give professional opinions and suggestions based on the trainees' operation performance, and trainees will also evaluate each other and share each other's experiences and opinions, so as to comprehensively evaluate the trainees' skill application level from multiple perspectives. It also uses sensors and data analysis technology to continuously monitor the trainees' learning time, participation, and question frequency. The learning time includes the total time the trainees log in to the system to learn and the time spent on each learning module; the participation is measured by the trainees' activeness in speaking in the course discussion area and the degree of their enthusiasm in participating in group activities; the question frequency records the number of questions the trainees ask the trainer or classmates during the learning process. By analyzing these data, the trainees' learning attitude is evaluated. For example, if the trainees watch the online course for a long time, actively participate in the interaction, and ask questions frequently, it means that they are highly motivated to learn.On the contrary, if the students spend a short time studying, have low participation, and rarely ask questions, it may indicate that their learning attitude needs to be improved. In order to more accurately evaluate the learning attitude, the system will also record the students' specific interactive behaviors in the online course, such as whether they complete the exercises in the course carefully and whether they actively participate in the discussion. The system also designs detailed questionnaires and in-depth interviews to understand the emotional changes and psychological states of disabled students during the training process. The questionnaires cover questions on self-confidence improvement, emotional state, and expectations for the future. For example, students are asked whether they feel more confident after the training, their emotional reactions when facing difficulties, and their expectations for future career development. Interviews are conducted by professional psychological counselors or trainers, who communicate with students face to face to gain an in-depth understanding of their inner feelings and experiences during the training process. When analyzing the questionnaire and interview results, each emotional question is classified according to the student's answer. For example, for the question of self-confidence improvement, the answer is divided into positive (such as "I feel that I have become more confident") and negative (such as "I still lack confidence in myself"), and the corresponding score is given according to the tendency of the answer. Then, the scores of all emotional questions are weighted and summed to obtain a comprehensive emotional index to comprehensively evaluate the emotional development of the students. ;

[0052] Subsequently, initial weight values ​​are set for the two dimensions of knowledge mastery and skill application, for example, knowledge mastery accounts for 60% and skill application accounts for 40%. In each evaluation cycle, the system automatically collects students' knowledge test scores, homework scores, actual operation scores and other data, and calculates the performance change rate by comparing the performance data of the current cycle with the previous cycle, and adjusts the weight accordingly. If the student's performance improves, the weight of the corresponding dimension is increased, otherwise it is reduced. The weights of knowledge mastery and skill application are adjusted according to the performance change rate to reflect the student's latest learning situation, and the updated weights are used to recalculate the student's comprehensive score. Repeat the iterative calculation throughout the evaluation cycle to ensure that the score can reflect the student's progress in a timely manner.

[0053] Next, the qualitative evaluation module adopts a combination of expert evaluation, student mutual evaluation and self-evaluation. The expert evaluation is carried out by experts with rich teaching experience and professional knowledge. They give comprehensive and objective evaluation based on the students' performance in the training process, including learning attitude, proficiency in skill application, problem-solving ability, etc. Student mutual evaluation is achieved through mutual evaluation among students. Students evaluate other students' learning attitude, teamwork ability, etc. based on each other's performance in group activities and cooperative tasks. Self-evaluation requires students to reflect on and evaluate their learning gains, progress, strengths and weaknesses in the training process. Through the combination of these three evaluation methods, we can conduct in-depth analysis of students' learning attitudes and emotional development dimensions from multiple angles, and provide students with comprehensive and three-dimensional evaluation feedback.

[0054] Finally, the visualization report module visualizes the students' evaluation data in the form of various charts, such as bar charts, line charts, pie charts, etc. In terms of knowledge mastery, the bar charts are used to show the students' scores on various knowledge points, which intuitively reflect the students' strengths and weaknesses; in terms of skill application, the line charts are used to show the students' skill improvement at different stages, as well as the comparison with other students; in terms of learning attitude, the pie charts are used to show the proportion of students' learning time distribution, participation, and question frequency. Based on the visualized data, the system automatically generates a detailed learning effectiveness report. The report content includes not only the students' basic information, such as name, age, disability type, etc., but also covers the evaluation results of various dimensions, such as knowledge mastery, skill application score, learning attitude score, emotional development score, etc. In addition, the report also shows the students' progress trajectory, and presents the students' learning progress by comparing the students' evaluation data at different stages. At the same time, the report points out the students' potential improvement points, analyzes the areas where the students need to further improve based on their performance in each dimension, and gives corresponding suggestions and improvement measures.

[0055] In addition, the system will provide timely feedback to trainees and trainers on the generated visual reports. Through the reports, trainees can clearly understand their performance and progress in the training process, discover their strengths and weaknesses, and thus adjust their learning strategies in a targeted manner and strengthen the learning of weak links. Trainers can use the reports to fully understand the overall situation of the trainees, including their learning progress, learning attitude, and skill level. Based on this information, trainers can adjust teaching strategies in a timely manner and optimize training content and methods. Trainees and trainers can also jointly formulate the next learning plan and goals based on the progress trajectory and potential improvement points in the report.

[0056] To sum up, through the application of this embodiment, the disabled training support evaluation system gives full play to its advantages of multi-dimensional evaluation, combination of quantitative and qualitative, and visual report generation, providing disabled students with comprehensive, objective evaluation and personalized training support. Students can clearly understand their learning situation and clarify their direction of efforts through the system; trainers can adjust teaching strategies in time according to the information fed back by the system to improve the quality and effectiveness of training. The application of this system helps to enhance the learning enthusiasm and self-confidence of disabled students, promote their better integration into society, and realize their own value.

[0057] Embodiment 2

[0058] This embodiment provides a training support and evaluation system for people with disabilities. The system generates a personalized learning report for each trainee through a multi-dimensional assessment of knowledge mastery, skill application, learning attitude, and emotional development, combining quantitative analysis with qualitative evaluation. The system aims to help trainees understand their own strengths and weaknesses, while assisting trainers in optimizing teaching.

[0059] In the specific implementation, a comprehensive evaluation system including knowledge mastery, skill application, learning attitude, and emotional development is constructed to comprehensively cover the students' learning process. In the sub-dimension of knowledge mastery, the system subdivides the knowledge points of the training course, and evaluates the students' knowledge mastery through online tests (including multiple-choice questions, fill-in-the-blank questions, short-answer questions, etc.) and homework submission. According to the test scores and the difficulty of the questions, the students' knowledge mastery is calculated by combining weighted scores with difficulty coefficients. The calculation formula is: S i is the score of the ith test question, W i It is set according to the importance of the topic. i is the difficulty coefficient of the question, n is the total number of test questions, and in terms of skill application, VR / AR technology is used to create a simulation scene. Trainees perform specific tasks in the simulation environment, and the system records their operation process and uses task completion C, error rate E, and maximum task completion C max , to quantify the skill level, and at the same time combine expert evaluation and student mutual evaluation to comprehensively evaluate the student's skill application ability. The skill application score calculation formula is:

[0060] Then, the scoring weights are automatically adjusted based on the student's performance changes in different time periods, and the weights of knowledge mastery and skill application are initially set. and After that, the student's performance data, such as test scores and homework scores, is collected in each evaluation cycle, and the performance change rate is calculated by comparing the data of the current cycle with the data of the previous cycle. Where X current represents the total performance score of the current period, X previous It represents the sum of the performance scores of the previous cycle. The weight is adjusted according to the performance change rate. If the student's performance improves, the weight of this dimension will be increased accordingly, otherwise the weight will be reduced. The weight update formula is: Where K knowledge and S skill They represent the students' scores in knowledge mastery and skill application respectively.

[0061] Secondly, we conduct a qualitative analysis of learning attitudes by combining expert evaluation, mutual evaluation and self-evaluation, evaluate students’ learning attitudes and emotional development, collect unstructured data of students during the training process, including online interactions, question frequency, etc., and use algorithms to quantify participation and enthusiasm. The formula is: Among them, T act is the time that students actually participate in learning, T tot is the total learning time, F ques is the frequency of students' questions, A is the participation and enthusiasm index, and the A value is standardized to eliminate the impact of the total learning time differences between different students, and the standardized participation and enthusiasm index SA is obtained. Experts give professional evaluations based on students' learning performance, participation, etc. Students evaluate each other's learning attitude and enthusiasm; students conduct self-evaluation and reflect on their attitude and effort in the learning process. The emotional state data of students are obtained through questionnaires and interviews, and emotional indexes CEI are given to positive and negative emotional words. i ,Right now For each student, track the changes in the comprehensive emotional index at different time points t, draw the emotional change curve, and smooth the emotional change curve to eliminate the impact of short-term fluctuations to obtain a more stable emotional development trend. The calculation formula is: m is the total number of emotional problems, CEI j is the emotional index at the jth time point. According to the trend of emotional change, the emotional development of each student is scored. The calculation formula of the emotional development score D is: Where T is the total number of time points in the evaluation period, E m (t) is the comprehensive emotion index at the tth time point. The calculated emotion development score is compared with the expert manual review result, and revised according to the expert opinions and historical data. The final emotion development score is integrated into the qualitative evaluation report and presented to the trainees and trainers together with the engagement and motivation indicators.

[0062] Finally, the visual report module visualizes the students' evaluation data in the form of charts, intuitively reflecting the students' performance in various dimensions. Based on the visualized data, the system automatically generates a detailed learning effectiveness report. The report content includes the students' basic information, evaluation results in each dimension, progress trajectory, potential improvement points, etc. Students and trainers can use the visual report to clearly understand the students' learning situation, discover the students' strengths and weaknesses, and thus formulate targeted learning plans and teaching strategies.

[0063] To summarize, this implementation provides data support for qualitative evaluation through the results of quantitative evaluation module, while qualitative evaluation conducts in-depth analysis and interpretation of the results of quantitative evaluation. For example, the quantitative scoring of knowledge mastery can be combined with the qualitative evaluation of learning attitude to jointly reflect the trainees' situation in knowledge learning. The sub-dimensions of the multidimensional evaluation module are interrelated to provide comprehensive information for the comprehensive evaluation of trainees. The evaluation of skill application ability can be combined with the knowledge mastery to examine whether trainees can effectively apply what they have learned to practical operations. The expert evaluation and trainee mutual evaluation of the qualitative evaluation module can provide multi-angle views for the evaluation of learning attitude and emotional development, making the evaluation more comprehensive and objective, which not only helps trainees clarify their own learning advantages and disadvantages, but also provides trainers with specific teaching optimization directions, thereby effectively improving the training effect and personal development of people with disabilities.

[0064] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A training support and evaluation system for people with disabilities, characterized in that: The components of the support evaluation system include: multi-dimensional evaluation module, quantitative evaluation module, qualitative evaluation module, and visual report module; The multi-dimensional evaluation module constructs a comprehensive evaluation system of multiple sub-dimensions including knowledge mastery, skill application, learning attitude, and emotional development; The quantitative evaluation module uses data statistics and analysis methods to conduct quantitative evaluation of knowledge mastery and skill application sub-dimensions to reflect the overall level and individual differences of trainees; The qualitative evaluation module uses expert evaluation, student peer evaluation, and self-evaluation to conduct qualitative analysis of learning attitudes and emotional development dimensions; The visualization report module visualizes the students' evaluation data in the form of charts, intuitively reflecting the students' performance in various dimensions. Based on the visualization data, the system automatically generates a detailed learning effectiveness report. The report content includes the students' basic information, evaluation results in various dimensions, progress trajectory, and potential improvement points.

2. The disabled person training support evaluation system according to claim 1, characterized in that: The multi-dimensional evaluation module specifically includes: Knowledge mastery sub-dimension: evaluate the disabled trainees’ mastery of theoretical knowledge in the training courses through online tests and homework submission; Skill application sub-dimension: Introduce virtual reality (VR) and augmented reality (AR) technologies to simulate real life and work scenarios, set practical operation tasks and simulation scenarios, and examine the ability of disabled trainees to apply the skills they have learned to practice; Learning attitude sub-dimension: Using sensors and data analysis, we monitor students’ learning time, participation, and question frequency to assess their learning attitudes. We also record students’ viewing time and number of interactions in online courses to determine their learning enthusiasm. Emotional development sub-dimension: Through questionnaires and interviews, we understand the emotional changes and psychological states of disabled trainees during the training process, and ask trainees about their feelings about their improved self-confidence and expectations for the future to assess their emotional development.

3. The disabled person training support evaluation system according to claim 2, characterized in that: The specific steps of the knowledge mastery sub-dimension are: Course content decomposition: The training course is carefully decomposed according to the knowledge points, and the importance and difficulty of each knowledge point are clearly defined; Online test design: Design a variety of online test questions based on knowledge points, including multiple-choice questions, fill-in-the-blank questions, and short-answer questions to ensure that the disabled students' mastery of theoretical knowledge can be fully examined; Homework assignments: Assign targeted homework tasks based on the course content, requiring students to apply the knowledge they have learned to answer questions and perform practical operations; Test and homework grading: The system automatically grades online test questions and performs preliminary screening and classification of homework tasks. For complex homework, trainers will manually grade it. Knowledge mastery assessment: Calculate students’ knowledge mastery based on test scores and question difficulty, and analyze students’ weaknesses in each knowledge point.

4. The disabled person training support and evaluation system according to claim 3, characterized in that: The knowledge mastery sub-dimension collects the student's online test scores, and calculates the knowledge mastery score K by combining the weighted score with the difficulty coefficient according to the question weight and difficulty coefficient, as well as the student's actual score. knowledge ,Right now S i is the score of the ith test question, W i It is set according to the importance of the topic. i is the difficulty coefficient of the question, n is the total number of test questions, and the calculation results are saved in the student's learning file to more accurately reflect the student's mastery of key knowledge and for subsequent analysis and report generation.

5. The disabled person training support evaluation system according to claim 2, characterized in that: The specific steps of the skill application sub-dimension are: Scene construction: Use virtual reality (VR) and augmented reality (AR) technologies to build real life and work scenes, including different environments such as offices, factory workshops, and stores; Task setting: Setting actual operation tasks according to the scenario, i.e., document processing and meeting organization in the office scenario, and equipment operation and product assembly in the factory workshop scenario; Determination of skill evaluation indicators: Determine the evaluation indicators for skill application, namely, time efficiency of task completion, degree of quasi-task completion, and error rate; Simulation task execution: Trainees perform actual operation tasks in a virtual scene, and the system records the trainees' operation process through sensors and data analysis technology; Skill application assessment: Conduct a quantitative assessment of the trainees’ task execution based on the assessment indicators. Combined with expert evaluation and trainee peer evaluation, conduct a comprehensive assessment of the trainees’ skill application capabilities.

6. The disabled person training support and evaluation system according to claim 5, characterized in that: The skill application sub-dimension uses VR / AR technology to design simulation scenarios close to real life and work according to the training objectives, including daily life scenarios and work environment simulations. Specific operation tasks are set in the simulation scenarios and trainees are required to complete them within the specified time. The operation process of trainees in the simulation scenarios is recorded in real time, including operation steps, time, and number of errors. The skill application is comprehensively evaluated using the three dimensions of task completion, time efficiency, and error rate. The skill application score S skill The calculation formula is C is the task completion, T is the time required to complete the task, E is the error rate, and C max is the maximum completion degree of the task, T min This is the fastest completion time among all the students.

7. The disabled person training support and evaluation system according to claim 1, characterized in that: The quantitative evaluation module automatically adjusts the scoring weight based on the student's performance changes in different time periods. The specific steps are as follows: Initial weight setting: Set initial weight values ​​for the two dimensions of knowledge mastery and skill application. and Performance data collection: During each evaluation cycle, students’ performance data on knowledge mastery and skill application are collected, i.e. test scores, assignment scores, and practical operation scores; Dynamic weight adjustment: Based on the student's performance data in the current evaluation cycle, compare it with the performance data in the previous cycle, calculate the performance change rate r, and adjust the weight accordingly. If the student's performance improves, the weight of the dimension will be increased accordingly, otherwise the weight will be reduced. The calculation formula for the performance change rate r is: Where X current represents the total performance score of the current period, X previous Represents the sum of performance scores for the previous period; Weight update: Update the weights of knowledge mastery and skill application according to the performance change rate r, that is, Among them, α and β are adjustment factors used to control the speed of weight change; Comprehensive score calculation: Use the updated weight values ​​to recalculate the student's comprehensive score, that is, Where K knowledge and S skill Respectively represent the students’ scores in knowledge mastery and skill application; Continuous iteration: Repeat the steps to dynamically adjust the weights to calculate the comprehensive score, update the weights after each evaluation cycle, and recalculate the comprehensive score until the end of the evaluation cycle.

8. The disabled person training support and evaluation system according to claim 2, characterized in that: The learning attitude sub-dimension uses the student learning time, participation, and question frequency data recorded by the system as basic data, and uses an algorithm to quantify participation and enthusiasm. The algorithm formula is: Among them, T act is the time that students actually participate in learning, T tot is the total learning time, F ques It is the frequency of students asking questions, A is the participation and enthusiasm index. The A value is standardized to eliminate the impact of the difference in total learning time between different students, and the standardized participation and enthusiasm index SA is obtained.

9. The disabled person training support and evaluation system according to claim 2, characterized in that: The emotional development sub-dimension design includes a multi-dimensional emotional questionnaire including self-confidence, expectations, and emotional changes. The emotional state data of the trainees are obtained through questionnaire collection. For each emotional question in the questionnaire, the score of positive answers is set to be higher than that of negative answers. The calculation formula is: Among them, S i is the benchmark score for this problem, P i is the number of people who choose the positive answer, N i is the number of people who chose negative answers, ELS i is the emotional tendency score, which combines all emotional questions into an ELS i The weighted sum is used to obtain the comprehensive sentiment index, and the calculation formula is: Where m is the total number of emotional questions, W i It is the weight of each question. By adjusting self-confidence, emotional state and expectations for the future, the comprehensive emotional index can be reasonably determined according to the training objectives and the characteristics of the trainees.

10. The disabled person training support and evaluation system according to claim 1, characterized in that: The qualitative evaluation module collects unstructured data generated by trainees during the training process and assigns a sentiment index CEI to positive and negative sentiment words. i ,For each student, track the changes of their comprehensive emotional index at different time points t, draw the emotional change curve, smooth the emotional change curve to eliminate the impact of short-term fluctuations, and obtain a more stable emotional development trend, that is, m is the total number of emotional problems, CEI j is the emotional index at the jth time point. According to the trend of emotional change, the emotional development of each student is scored. The calculation formula of the emotional development score D is: Where T is the total number of time points in the evaluation period, E m (t) is the comprehensive emotion index at the tth time point. The calculated emotion development score is compared with the expert manual review result, and revised according to the expert opinions and historical data. The final emotion development score is integrated into the qualitative evaluation report and presented to the trainees and trainers together with the engagement and motivation indicators.

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