Training difficulty determination method and device of training scheme, electronic equipment and storage medium

Abstract

The invention provides a training difficulty determination method and device of a training scheme, electronic equipment and a storage medium. The method comprises the following steps: for each target difficulty level combination in a target difficulty factor difficulty level combination set, executing a training scheme difficulty determination operation so as to determine the training difficulty of a training scheme, matched with the target difficulty level combination, of a target course theme; determining a difficulty score of the difficulty level of the target difficulty factor in the target difficulty level combination; a preset first corresponding relation table used for representing the corresponding relation between the difficulty factor pairs and the action types between the difficulty factors is obtained; generating a second corresponding relation table based on the first corresponding relation table; for each difficulty factor pair in each second corresponding relation table, generating a difficulty factor pair difficulty score of the difficulty factor pair; and according to each difficulty score and each difficulty factor pair difficulty score, determining the training difficulty of a training scheme matched with the target course theme and the target difficulty level combination.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a method, device, electronic device, and storage medium for determining the training difficulty of a training program. Background Art

[0002] People with autism and Asperger's syndrome often encounter many challenges in social learning, so accurately assessing the difficulty of the training program and providing them with appropriate training programs accordingly is crucial to improving their training results and promoting their growth and development in social skills.

[0003] In social learning scenarios for patients with autism and Asperger's syndrome, traditional training program difficulty assessments often only consider the impact of a single difficulty factor (such as language complexity) or a few difficulty factors on the overall training difficulty. To process these difficulty factors, a simple accumulation method or linear model is usually used to calculate the overall difficulty of the training program.

[0004] However, in actual social training programs, there are multiple difficulty factors that affect the overall difficulty of the training program. Moreover, these difficulty factors do not act independently, but rather interact with each other in a complex manner. The above approach may ignore the interactions between different difficulty factors and their multi-level impacts on the patient's training effect. Therefore, the traditional training program determination method may not be sufficient to fully and accurately reflect the true difficulty of the training program, thereby affecting the matching of the most suitable training program for the patient.

[0005] Therefore, it is necessary to propose a method for determining the training difficulty of a training program to solve at least one of the above technical problems. Summary of the Invention

[0006] The embodiments of the present disclosure propose a method, device, electronic device and storage medium for determining the training difficulty of a training program. On the basis of the independent impact of each difficulty factor on the training difficulty of the training program, the impact of the interaction between multiple difficulty factors on the training difficulty of the training program is also considered. This can more comprehensively and accurately reflect the actual difficulty of the training program, and thus match the most suitable training program for the patient.

[0007] In a first aspect, the present disclosure provides a method for determining the training difficulty of a training program, comprising:

[0008] Obtaining at least one target difficulty factor associated with a target course topic, wherein each target difficulty factor has at least one difficulty level;

[0009] For each target difficulty level combination in the target difficulty factor difficulty level combination set, a training program difficulty determination operation is performed to determine the training difficulty of a training program that matches the target course theme with the target difficulty level combination, wherein the target difficulty factor difficulty level combination set is formed by difficulty levels corresponding to the at least one target difficulty factor, and the training program difficulty determination operation includes:

[0010] For each target difficulty factor, determining the difficulty score corresponding to the difficulty level of the target difficulty factor in the target difficulty level combination according to a mapping relationship between the difficulty level corresponding to the target difficulty factor and the difficulty score;

[0011] Obtaining a preset first correspondence table for characterizing correspondences between difficulty factor pairs and interaction types between the difficulty factors;

[0012] generating a second correspondence table based on the first correspondence table, wherein the second correspondence table belongs to the first correspondence table and both difficulty factors in the difficulty factor pairs in the second correspondence table are target difficulty factors;

[0013] For each difficulty factor pair in the second correspondence table, determining a difficulty factor pair difficulty score for the difficulty factor pair based on the interaction type between the difficulty factors of the difficulty factor pair and the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination;

[0014] The training difficulty of the training program that matches the target course theme with the target difficulty level combination is determined based on the difficulty score of each target difficulty factor in the target difficulty level combination and the difficulty factor pair difficulty score of each difficulty factor pair.

[0015] In some optional embodiments, the interaction type between difficulty factors includes at least one of synergistic interaction and mutually exclusive interaction.

[0016] In some optional implementations, determining, for each difficulty factor pair in the second correspondence table, a difficulty factor pair difficulty score for the difficulty factor pair based on the interaction type between the difficulty factors of the difficulty factor pair and the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination includes:

[0017] For each difficulty factor pair in the second correspondence table, determining a difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair according to the interaction type between the difficulty factors of the difficulty factor pair;

[0018] The difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is used to determine the difficulty factor pair difficulty score of the difficulty factor pair based on the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination.

[0019] In some optional implementations, determining the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair based on the interaction type between the difficulty factors of the difficulty factor pair includes:

[0020] If the interaction type between the difficulty factors of the difficulty factor pair is synergistic, determining that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a collaborative difficulty assessment method, wherein, in the collaborative difficulty assessment method, the difficulty factor pair difficulty score of the difficulty factor pair is positively correlated with the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination;

[0021] If the interaction type between the difficulty factors of the difficulty factor pair is mutually exclusive, determine that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a mutually exclusive difficulty assessment method, wherein, in the mutually exclusive difficulty assessment method, the difficulty factor pair difficulty score of the difficulty factor pair is negatively correlated with the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination.

[0022] In some optional embodiments, the synergy includes first order synergy and second order synergy; and

[0023] If the interaction type between the difficulty factors of the difficulty factor pair is synergistic, determining the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair as a synergistic difficulty assessment method includes:

[0024] If the interaction type between the difficulty factors of the difficulty factor pair is first-level synergy, the difficulty factor pair is determined to be a high-difficulty factor pair or a low-difficulty factor pair based on the difficulty score of each difficulty factor in the target difficulty level combination;

[0025] When the difficulty factor pair is a high difficulty factor pair, determining that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a first collaborative difficulty assessment method, wherein in the first collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a first positive correlation degree;

[0026] When the difficulty factor pair is a low difficulty factor pair, determining that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a second collaborative difficulty assessment method, wherein in the second collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a second positive correlation degree, and the first positive correlation degree is greater than the second positive correlation degree;

[0027] If the interaction type between the difficulty factors of the difficulty factor pair is the second level synergistic interaction, determine that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is the third collaborative difficulty assessment method, wherein in the third collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a third positive correlation degree, wherein the second positive correlation degree is greater than the third positive correlation degree.

[0028] In some optional embodiments, after determining the training difficulty of the training program that matches the target course theme with the target difficulty level combination based on the difficulty score of each target difficulty factor in the target difficulty level combination and the difficulty factor pair difficulty score of each difficulty factor pair, the method further includes:

[0029] For each target difficulty level combination in the target difficulty factor difficulty level combination set, the following normalization operation is performed:

[0030] Based on the training difficulty of the training program matched with each target difficulty level combination in the target difficulty factor difficulty level combination set, a preset normalization method is used to normalize the training difficulty of the training program matched with the target difficulty level combination to obtain the normalized training difficulty of the training program matched with the target difficulty level combination.

[0031] In a second aspect, the present disclosure provides a device for determining the training difficulty of a training program, comprising:

[0032] a difficulty factor acquisition unit, configured to acquire at least one target difficulty factor associated with a target course topic, wherein each target difficulty factor has at least one difficulty level;

[0033] A training program difficulty determination unit is configured to perform a training program difficulty determination operation for each target difficulty level combination in a target difficulty factor difficulty level combination set, so as to determine the training difficulty of a training program that matches the target course theme with the target difficulty level combination, wherein the target difficulty factor difficulty level combination set is formed by the difficulty levels corresponding to the at least one target difficulty factor, and the training program difficulty determination operation includes:

[0034] For each target difficulty factor, determining the difficulty score corresponding to the difficulty level of the target difficulty factor in the target difficulty level combination according to a mapping relationship between the difficulty level corresponding to the target difficulty factor and the difficulty score;

[0035] Obtaining a preset first correspondence table for characterizing correspondences between difficulty factor pairs and interaction types between the difficulty factors;

[0036] generating a second correspondence table based on the first correspondence table, wherein the second correspondence table belongs to the first correspondence table and both difficulty factors in the difficulty factor pairs in the second correspondence table are target difficulty factors;

[0037] For each difficulty factor pair in the second correspondence table, determining a difficulty factor pair difficulty score for the difficulty factor pair based on the interaction type between the difficulty factors of the difficulty factor pair and the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination;

[0038] The training difficulty of the training program that matches the target course theme with the target difficulty level combination is determined based on the difficulty score of each target difficulty factor in the target difficulty level combination and the difficulty factor pair difficulty score of each difficulty factor pair.

[0039] In some optional embodiments, the interaction type between difficulty factors includes at least one of synergistic interaction and mutually exclusive interaction.

[0040] In some optional embodiments, the training scheme difficulty determination unit may be further configured to:

[0041] For each difficulty factor pair in the second correspondence table, determining a difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair according to the interaction type between the difficulty factors of the difficulty factor pair;

[0042] The difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is used to determine the difficulty factor pair difficulty score of the difficulty factor pair based on the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination.

[0043] In some optional embodiments, the training scheme difficulty determination unit may be further configured to:

[0044] If the interaction type between the difficulty factors of the difficulty factor pair is synergistic, determining that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a collaborative difficulty assessment method, wherein in the collaborative difficulty assessment method, the difficulty factor pair difficulty score of the difficulty factor pair is positively correlated with the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination;

[0045] If the interaction type between the difficulty factors of the difficulty factor pair is mutually exclusive, determine that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a mutually exclusive difficulty assessment method, wherein, in the mutually exclusive difficulty assessment method, the difficulty factor pair difficulty score of the difficulty factor pair is negatively correlated with the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination.

[0046] In some optional embodiments, the synergy includes first order synergy and second order synergy; and

[0047] The training program difficulty determination unit can be further configured to:

[0048] If the interaction type between the difficulty factors of the difficulty factor pair is first-level synergy, the difficulty factor pair is determined to be a high-difficulty factor pair or a low-difficulty factor pair based on the difficulty score of each difficulty factor in the target difficulty level combination;

[0049] When the difficulty factor pair is a high difficulty factor pair, determining that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a first collaborative difficulty assessment method, wherein in the first collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a first positive correlation degree;

[0050] When the difficulty factor pair is a low difficulty factor pair, determining that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a second collaborative difficulty assessment method, wherein in the second collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a second positive correlation degree, and the first positive correlation degree is greater than the second positive correlation degree;

[0051] If the interaction type between the difficulty factors of the difficulty factor pair is the second level synergistic interaction, determine that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is the third collaborative difficulty assessment method, wherein in the third collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a third positive correlation degree, wherein the second positive correlation degree is greater than the third positive correlation degree.

[0052] In some optional embodiments, the device further comprises:

[0053] The normalization unit is configured to perform the following normalization operation on the training difficulty of the training scheme matched with each target difficulty level combination in the target difficulty factor difficulty level combination set:

[0054] Based on the training difficulty of the training program matched with each target difficulty level combination in the target difficulty factor difficulty level combination set, a preset normalization method is used to normalize the training difficulty of the training program matched with the target difficulty level combination to obtain the normalized training difficulty of the training program matched with the target difficulty level combination.

[0055] In a third aspect, the present disclosure provides an electronic device, comprising:

[0056] one or more processors;

[0057] a storage device having one or more programs stored thereon,

[0058] When the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any embodiment of the first aspect of the present disclosure.

[0059] In a fourth aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by one or more processors, implements the method described in any embodiment of the first aspect of the present disclosure.

[0060] In a fifth aspect, the present disclosure provides a computer program product, comprising a computer program / instruction, which, when executed by a processor, implements the method described in any embodiment of the first aspect of the present disclosure.

[0061] The embodiments of the present disclosure provide a method, device, electronic device and storage medium for determining the training difficulty of a training program, which obtains at least one target difficulty factor associated with a target course theme, wherein each target difficulty factor has at least one difficulty level, and for each target difficulty level combination in a target difficulty factor difficulty level combination set, performs a training program difficulty determination operation to determine the training difficulty of a training program that matches the target course theme with the target difficulty level combination, wherein the target difficulty factor difficulty level combination set is formed by each difficulty level corresponding to at least one target difficulty factor, and the training program difficulty determination operation includes: for each target difficulty factor, determining the difficulty level corresponding to the target difficulty factor in the target difficulty level combination according to the mapping relationship between the difficulty level corresponding to the target difficulty factor and the difficulty score degree score; obtaining a preset first correspondence table for characterizing the correspondence between difficulty factor pairs and interaction types between difficulty factors; generating a second correspondence table based on the first correspondence table, wherein the second correspondence table belongs to the first correspondence table and both difficulty factors in the difficulty factor pairs in the second correspondence table are target difficulty factors; for each difficulty factor pair in each second correspondence table, generating a difficulty factor pair difficulty score for the difficulty factor pair based on the interaction type between the difficulty factors of the difficulty factor pair and the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination; determining the training difficulty of the training program that matches the target course theme with the target difficulty level combination based on the difficulty score of each target difficulty factor in the target difficulty level combination and the difficulty factor pair difficulty score of each difficulty factor pair. The present disclosure not only considers the impact of each difficulty factor associated with the target course theme on the training difficulty of the training program individually, but also considers the impact of the interaction between multiple difficulty factors on the training difficulty of the training program, which can more comprehensively and accurately reflect the actual difficulty of the training program, thereby matching the most suitable training program for the patient. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Other features, objects, and advantages of the present disclosure will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are for illustration purposes only and are not to be considered as limiting the present invention. In the drawings:

[0063] Figure 1 is a diagram of a system architecture in which an embodiment of a method for determining training difficulty of a training scheme according to the present disclosure may be applied;

[0064] Figure 2 is a flow chart of one embodiment of a method for determining training difficulty of a training program according to the present disclosure;

[0065] Figure 3is a decomposed flow chart of one embodiment of step 202 according to the present disclosure;

[0066] Figure 4 is a structural diagram of an embodiment of a device for determining training difficulty of a training program according to the present disclosure;

[0067] Figure 5 It is a schematic diagram of the structure of a computer system of an electronic device suitable for implementing the embodiments of the present disclosure. DETAILED DESCRIPTION

[0068] The present disclosure will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are intended only to illustrate the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, only portions relevant to the relevant invention are shown in the accompanying drawings.

[0069] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in the present disclosure may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0070] Figure 1 An exemplary system architecture 100 is shown to which embodiments of a training difficulty determination method, apparatus, electronic device, and storage medium of the training regimen of the present disclosure may be applied.

[0071] like Figure 1 As shown, system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. Network 104 is used to provide communication links between terminal devices 101, 102, 103 and server 105. Network 104 may include various communication connection types, such as wired communication links, wireless communication links, and the like.

[0072] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as training program difficulty determination applications, voice interaction applications, video conferencing applications, short video social networking applications, web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0073] Terminal devices 101, 102, 103 can be hardware or software. When terminal devices 101, 102, 103 are hardware, they can be various electronic devices with microphones and speakers, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III, Moving Picture Experts Compression Standard Audio Layer 3), MP4 players (Moving Picture Experts Group Audio Layer IV, Moving Picture Experts Compression Standard Audio Layer 4), portable computers and desktop computers, etc. When terminal devices 101, 102, 103 are software, they can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules (for example, obtaining at least one target difficulty factor associated with the target course topic), or it can be implemented as a single software or software module. No specific limitation is made here.

[0074] The server 105 may be a server that provides various services, such as a backend server that processes at least one target difficulty factor associated with the target course topic obtained by the terminal devices 101, 102, and 103. The backend server may perform corresponding processing based on the at least one target difficulty factor associated with the target course topic obtained by the terminal device.

[0075] In some cases, the training difficulty determination method of the training program provided by the present disclosure can be jointly performed by the terminal devices 101, 102, 103 and the server 105. For example, the step of "obtaining at least one target difficulty factor associated with the target course subject" can be performed by the terminal devices 101, 102, 103, and the step of "for each target difficulty factor, determining the difficulty score corresponding to the difficulty level of the target difficulty factor in the target difficulty level combination according to the mapping relationship between the difficulty level corresponding to the target difficulty factor and the difficulty score" can be performed by the server 105. The present disclosure does not limit this. Accordingly, the training difficulty determination device of the training program can also be respectively set in the terminal devices 101, 102, 103 and the server 105.

[0076] In some cases, the training difficulty determination method of the training program provided in the present disclosure can be executed by the server 105. Accordingly, the training difficulty determination device of the training program can also be set in the server 105. In this case, the system architecture 100 may also not include the terminal devices 101, 102, and 103.

[0077] In some cases, the training difficulty determination method of the training program provided in the present disclosure can be executed by the terminal devices 101, 102, and 103. Accordingly, the training difficulty determination device of the training program can also be set in the terminal devices 101, 102, and 103. In this case, the system architecture 100 may also not include the server 105.

[0078] It should be noted that the server 105 can be hardware or software. When the server 105 is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or it can be implemented as a single server. When the server 105 is software, it can be implemented as multiple software or software modules (for example, to provide distributed services), or it can be implemented as a single software or software module. No specific limitations are given here.

[0079] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0080] The information, data and signals involved in this disclosure are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data comply with the relevant laws, regulations and standards of relevant countries and regions.

[0081] Continue to refer Figure 2 , Figure 2 FIG2 shows a process 200 of an embodiment of a method for determining the training difficulty of a training program according to the present disclosure. Figure 2 The training difficulty determination method of the training program shown can be applied to Figure 1 The process 200 at least includes the following steps 201-202.

[0082] Step 201: Obtain at least one target difficulty factor associated with a target course topic.

[0083] In this embodiment, the course theme may refer to the core content around which each specific learning module for users with autism and Asperger's syndrome revolves.

[0084] In some optional embodiments, course topics may include exchanging information, two-way communication, choosing appropriate friends, starting and joining conversations, exiting conversations, using online communication and social media, using humor appropriately, teamwork, inviting friends, handling disagreements appropriately, changing public opinion, dealing with ridicule and embarrassment, handling rumors and gossip appropriately, and dealing with bullying.

[0085] In some optional implementations, the target course topic may refer to a course topic that is currently most suitable for the target user, determined based on the course topic priorities of each course topic.

[0086] In some optional implementations, difficulty factors may include topic depth, emotion / conflict intensity, language complexity, AI guidance and error correction intensity, time / response pressure, conversation dominance, and media presentation method, etc., without specific limitations here.

[0087] Among them, topic depth can indicate the complexity and depth of the course content corresponding to the course theme; emotion / conflict intensity can indicate the degree to which the course content corresponding to the course theme may cause emotional fluctuations or cognitive conflicts in users; language complexity can indicate the complexity and difficulty of the language used in the course content corresponding to the course theme, including vocabulary, grammatical structure, and the use of professional terms; AI guidance and error correction intensity can indicate the degree of guidance and support provided by AI in the course content corresponding to the course theme; time / response pressure can indicate the time limit or requirement for quick response required to complete tasks or answer questions in the course content corresponding to the course theme; conversation dominance can indicate who (AI or user) controls the rhythm and direction of the conversation in the course content corresponding to the course theme; media presentation method can indicate the various media forms used to deliver course content in the course theme, such as text, images, audio, video, etc.

[0088] Each course theme is associated with at least one target difficulty factor. The at least one target difficulty factor may refer to a difficulty factor among the above-mentioned difficulty factors that can affect the training difficulty of the training program of the course theme. The target difficulty factors associated with different course themes may be the same or different.

[0089] In some optional implementations, at least one target difficulty factor associated with the target course subject may be obtained based on a course subject-to-difficulty factor mapping relationship table.

[0090] The preset course theme and difficulty factor mapping relationship table may include each course theme and at least one target difficulty factor associated with the course theme.

[0091] Step 202: For each target difficulty level combination in the target difficulty factor difficulty level combination set, a training program difficulty determination operation is performed.

[0092] In this embodiment, each difficulty factor may have at least one difficulty level, and the difficulty levels may be divided according to the degree of influence of each difficulty factor on the difficulty of the course content.

[0093] For example, AI guidance and error correction intensity can be divided into five difficulty levels from low to high: Difficulty Level 1, Difficulty Level 2, Difficulty Level 3, Difficulty Level 4, and Difficulty Level 5. Conversation dominance can be divided into three difficulty levels from low to high: Difficulty Level 1, Difficulty Level 2, and Difficulty Level 3.

[0094] In some optional embodiments, for at least one target difficulty factor associated with the target course theme, different difficulty levels of each target difficulty factor can be combined in advance to generate a target difficulty factor difficulty level combination set formed for each difficulty level corresponding to the at least one target difficulty factor, wherein the target difficulty factor difficulty level combination set includes difficulty level combinations of different difficulty levels of each difficulty factor associated with the target course theme, and the target difficulty level combination can refer to any difficulty level combination in the target difficulty factor difficulty level combination set.

[0095] For example, there are N target difficulty factors associated with the target course topic, namely I1…I N , for difficulty factor I i There is C i difficulty level, then the target difficulty factor difficulty level combination set has target difficulty level combinations. Each target difficulty level combination includes each difficulty factor in the N difficulty factors and the corresponding difficulty level.

[0096] For example, the difficulty factors associated with the target course topic may include AI guidance and error correction intensity and conversation dominance. AI guidance and error correction intensity can be divided into 5 difficulty levels from low to high, namely difficulty level 1, difficulty level 2, difficulty level 3, difficulty level 4 and difficulty level 5. Conversation dominance can be divided into 3 difficulty levels from low to high, namely difficulty level 1, difficulty level 2 and difficulty level 3. By combining different difficulty levels of AI guidance and error correction intensity and conversation dominance, a target difficulty factor difficulty level combination set including 15 target difficulty level combinations can be obtained.

[0097] For example, for the target difficulty level combination {AI guidance and error correction strength: difficulty level 2, dialogue dominance: difficulty level 1}, the difficulty level of AI guidance and error correction strength is difficulty level 2, and the difficulty level of dialogue dominance is difficulty level 1. In some optional implementations, for each target difficulty level combination in the target difficulty factor difficulty level combination set formed by the difficulty levels corresponding to at least one target difficulty factor, a training program for the target course theme can be determined. In other words, the training program for the target course theme can be the course content after the course content corresponding to the target course theme is configured accordingly according to the difficulty level of each target difficulty factor in the target difficulty level combination.

[0098] In this embodiment, a training program difficulty determination operation is performed to determine the training difficulty of the training program that matches the target course subject with the target difficulty level combination.

[0099] In some optional implementations, step 202 may include the following steps 2021-2025.

[0100] Step 2021 : For each target difficulty factor, determine the difficulty score corresponding to the difficulty level of the target difficulty factor in the target difficulty level combination according to the mapping relationship between the difficulty level corresponding to the target difficulty factor and the difficulty score.

[0101] The difficulty level of the target difficulty factor in the target difficulty level combination may be the difficulty level of the target difficulty factor in the target difficulty level combination.

[0102] Generally, in the process of course design, difficulty factors are often simply graded according to the degree of influence of a single difficulty factor on the course content, and then each grade is mapped to a corresponding score, or the same difficulty grading method and score mapping method are used for each difficulty factor. However, each difficulty factor has its own unique characteristics, and a single difficulty level and difficulty score mapping method may not be able to fully capture these characteristics, which will lead to an inaccurate assessment of the training difficulty of the training program.

[0103] Therefore, in order to better quantify the difficulty level corresponding to each difficulty factor according to the characteristics of each difficulty factor, this embodiment can quantify the difficulty level corresponding to the difficulty factor into a difficulty score based on the mapping relationship between the difficulty level corresponding to the difficulty factor and the difficulty score (or difficulty conversion method). That is, different difficulty level and difficulty score mapping relationships can be adopted for different difficulty factors to quantify the difficulty level corresponding to the difficulty factor into a difficulty score.

[0104] In some optional implementations, (1) with respect to topic depth, a discrete graded difficulty conversion method may be used to convert the impact of topic depth on the training difficulty of the training program for the course theme into a quantifiable difficulty level and a difficulty score corresponding to the difficulty level.

[0105] Specifically, the topic depth can be divided into multiple difficulty levels according to the complexity and depth of the topic depth in the training plan from low to high, including difficulty level 1 (the complexity and depth of the topic depth are low), difficulty level 2 (the complexity and depth of the topic depth are slightly low), difficulty level 3 (the complexity and depth of the topic depth are medium), difficulty level 4 (the complexity and depth of the topic depth are high) and difficulty level 5 (the complexity and depth of the topic depth are very high).

[0106] Each difficulty level may also be mapped to a corresponding difficulty score according to a preset difficulty score mapping method, and the difficulty score may be in the range of 0-1.

[0107] For example, difficulty level 1 = 0.2 points, difficulty level 2 = 0.4 points, difficulty level 3 = 0.6 points, difficulty level 4 = 0.8 points, and difficulty level 5 = 1 point.

[0108] (2) With regard to language complexity, a discrete grading difficulty conversion method can be used to convert the impact of language complexity on the training difficulty of the training program of the course theme into a quantifiable difficulty level and a difficulty score corresponding to the difficulty level.

[0109] Specifically, the language complexity can be divided into multiple difficulty levels according to the language complexity from low to high in the training plan, including difficulty level 1 (low language complexity), difficulty level 2 (slightly low language complexity), difficulty level 3 (medium language complexity), difficulty level 4 (high language complexity) and difficulty level 5 (very high language complexity).

[0110] Each difficulty level may also be mapped to a corresponding difficulty score according to a preset difficulty score mapping method, and the difficulty score may be in the range of 0-1.

[0111] For example, difficulty level 1 = 0.2 points, difficulty level 2 = 0.4 points, difficulty level 3 = 0.6 points, difficulty level 4 = 0.8 points, and difficulty level 5 = 1 point.

[0112] By using the above-mentioned discrete grading method to divide the difficulty levels of topic depth and language complexity, when setting course content, the difficulty of the course content can be managed and adjusted intuitively without switching between infinite continuous values, avoiding repeated entanglement with subtle decimal values.

[0113] For example, an entry-level course might have a difficulty level of 1 for depth of topic and a difficulty level of 1 for complexity of language, while an advanced course might have a difficulty level of 5 for depth of topic and a difficulty level of 5 for complexity of language.

[0114] This method reduces the complexity of course content design, improves work efficiency, and makes the course content design and implementation process more concise and clear.

[0115] (3) Regarding the intensity of AI guidance and error correction, a proportional difficulty conversion method can be used to convert the impact of the intensity of AI guidance and error correction on the training difficulty of the training program of the course theme into a quantifiable difficulty level and a difficulty score corresponding to the difficulty level.

[0116] Specifically, the difficulty level of AI guidance and error correction intensity can be divided according to the ratio of AI assistance and user self-study in the training plan.

[0117] For example, the ratio of AI assistance to user self-study can be determined based on dimensions such as the relevance of the information provided by AI in the course content to the current learning task, the frequency of interaction between AI and students, and the degree of AI intervention in the problem-solving process. Furthermore, the difficulty level of AI guidance and error correction intensity can be divided according to the ratio of AI assistance to user self-study.

[0118] Among them, the ratio of AI assistance to user self-study can be used to indicate the intensity of AI guidance on the training program.

[0119] If the proportion of AI-guided content in the training plan is higher, it means that the AI ​​provides higher levels of guidance and support, and the corresponding course content is simpler; if the proportion of AI-guided content in the course content is lower, it means that the proportion of content that users need to learn on their own is higher, and the corresponding course content is more difficult.

[0120] For example, if the ratio of AI assistance to user self-study is 4:1, it means that the AI ​​guidance content accounts for more and the user self-exploration is less. If the ratio of AI assistance to user self-study is 1:4, it means that the user self-explores and the AI ​​guidance content is less.

[0121] Here, the ratio of AI assistance to user self-study can be multiple pre-set ratios.

[0122] In some optional implementations, the ratio of AI assistance to user self-study can be normalized first, and then the difficulty level of AI guidance and error correction intensity can be determined based on the normalized ratio.

[0123] For example, the following formula can be used to normalize the ratio of AI assistance to user self-study.

[0124] r=a / (a+b)

[0125] Among them, r represents the normalized ratio of AI-assisted to user self-study, a represents the proportion of AI-assisted course content in the entire training program, and b represents the proportion of user self-study course content in the entire training program.

[0126] For example, if the ratio of AI assistance to user self-study is 4:1, using the above normalization formula, the normalized ratio r of AI assistance to user self-study is 0.8.

[0127] In some optional implementations, the normalized ratio of AI assistance to user self-study can be determined as a difficulty score.

[0128] In some optional implementations, the normalized ratio of AI assistance to user self-study can be mapped to different difficulty levels according to a preset difficulty score mapping method.

[0129] For example, the normalized ratio of AI assistance to user self-study can be mapped to different difficulty levels according to the following difficulty score mapping method.

[0130]

[0131] Among them, when the normalized ratio r∈[0,0.3), the corresponding difficulty level can be difficulty level 3 (low AI assistance, high self-study ability requirement); when the normalized ratio r∈[0.3,0.7), the corresponding difficulty level can be difficulty level 2 (medium AI assistance, medium self-study difficulty); when the normalized ratio r∈[0.7,1), the corresponding difficulty level can be difficulty level 1 (high AI assistance, low self-study difficulty).

[0132] (4) With regard to the dialogue dominance, a proportional difficulty conversion method can be used to convert the impact of the dialogue dominance on the training difficulty of the training program of the course theme into a quantifiable difficulty level and a difficulty score corresponding to the difficulty level.

[0133] Specifically, the difficulty level of conversation control can be divided according to the ratio of the AI's speaking time to the user's speaking time in the training plan. The ratio of the AI's speaking time to the user's speaking time in the course content can indicate who (the AI ​​or the user) controls the rhythm and direction of the conversation.

[0134] If the AI ​​speaks longer in the course content, it means that the AI ​​dominates the rhythm and direction of the conversation, and the corresponding course content is simpler. If the user speaks longer in the course content, it means that the user dominates the rhythm and direction of the conversation, and the corresponding course content is more difficult.

[0135] For example, if the ratio of the AI's speaking time to the user's speaking time is 4:1, it means that the AI ​​dominates the rhythm and direction of the conversation more. If the ratio of the AI's speaking time to the user's speaking time is 1:4, it means that the user dominates the rhythm and direction of the conversation more.

[0136] Here, the ratio of the AI's speaking time to the user's speaking time can be multiple pre-set ratios.

[0137] In some optional implementations, the ratio of the AI's speaking time to the user's speaking time may be normalized first, and then the difficulty level of the conversation dominance may be divided according to the normalized ratio.

[0138] For example, the following formula can be used to normalize the ratio of the AI's speaking time to the user's speaking time.

[0139] s=c / (c+d)

[0140] Among them, s represents the ratio of the normalized AI speaking time to the user speaking time, c represents the proportion of the AI ​​speaking time in the entire training program, and d represents the proportion of the user speaking time in the entire training program.

[0141] For example, if the ratio of the AI's speaking time to the user's speaking time is 4:1, using the above normalization formula, the normalized ratio s of the AI's speaking time to the user's speaking time is 0.8.

[0142] In some optional implementations, the ratio of the normalized AI speaking time to the user speaking time may be determined as the difficulty score.

[0143] In some optional implementations, the normalized ratio of the AI ​​speaking time to the user speaking time may be mapped to different difficulty levels according to a preset difficulty score mapping method.

[0144] For example, the normalized ratio of the AI ​​speaking time to the user speaking time can be mapped to different difficulty levels according to the following difficulty score mapping method.

[0145]

[0146] Among them, when the normalized ratio s∈[0,0.3) is in the range, the corresponding difficulty level can be difficulty level 3 (the degree of user-dominated dialogue is very high, and the degree of AI-dominated dialogue is very low); when the normalized ratio s∈[0.3,0.7) is in the range, the corresponding difficulty level can be difficulty level 2 (the degree of dialogue dominance between AI and users is medium); when the normalized ratio s∈[0.7,1) is in the range, the corresponding difficulty level can be difficulty level 1 (the degree of AI-dominated dialogue is very high, and the degree of user-dominated dialogue is very low).

[0147] (5) With regard to the media presentation method, a proportional difficulty conversion method can be used to convert the impact of the media presentation method on the training difficulty of the training program of the course theme into a quantifiable difficulty level and a difficulty score corresponding to the difficulty level.

[0148] Specifically, the difficulty level of media presentation methods can be divided according to the proportion of different media forms (such as text, pictures, audio, and video) used in the training program.

[0149] For example, the difficulty level of media presentation can be divided according to the ratio of text content to multimedia content (pictures, audio, and video) used in the course content.

[0150] If the course content consists of a larger proportion of text content, users will need to understand the information more by reading text, which requires a higher level of abstract comprehension ability, and the corresponding course content will be more difficult. If the course content consists of a larger proportion of multimedia content, users can use images, sounds, videos and other sensory stimulations to assist in understanding, which lowers the threshold for understanding, and the corresponding course content will be relatively simple.

[0151] For example, if the ratio of text content to multimedia content is 4:1, it means that the course content is mainly text content and the course difficulty is relatively high; if the ratio of text content to multimedia content is 1:4, it means that the course content is mainly multimedia content and the course difficulty is relatively low.

[0152] In some optional implementations, the ratio of text content to multimedia content may be normalized first, and then the difficulty level of the media presentation method may be divided according to the normalized ratio.

[0153] For example, the following formula may be used to normalize the ratio of text content to multimedia content.

[0154] w=e / (e+f)

[0155] Among them, w represents the ratio of normalized text content to multimedia content, e represents the proportion of text content in the entire training program, and f represents the proportion of multimedia content in the entire training program.

[0156] For example, if the ratio of text content to multimedia content is 4:1, using the above normalization formula, the normalized ratio w of text content to multimedia content is 0.8.

[0157] In some optional implementations, the ratio of the normalized text content to the multimedia content may be determined as the difficulty score.

[0158] For example, the normalized ratio of text content to multimedia content may be mapped to different difficulty levels according to the following difficulty score mapping method.

[0159]

[0160] Among them, when the normalized ratio w∈[0,0.1), the corresponding difficulty level can be difficulty level 1 (less text content, more multimedia content, easy to understand); when the normalized ratio w∈[0.1,0.3), the corresponding difficulty level can be difficulty level 2 (slightly less text content, more multimedia content, easier to understand); when the normalized ratio w∈[0.3,0.5), the corresponding difficulty level can be difficulty level 3 (moderate ratio of text content and multimedia content, medium difficulty in understanding); when the normalized ratio w∈[0.5,0.7), the corresponding difficulty level can be difficulty level 4 (more text content, less multimedia content, more difficult to understand); when the normalized ratio w∈[0.7,1), the corresponding difficulty level can be difficulty level 5 (large text content, little multimedia content, very difficult to understand).

[0161] By adopting a proportional difficulty conversion method, the difficulty levels of AI guidance and error correction intensity, dialogue dominance, and media presentation methods are divided. Only by defining key boundaries and selecting appropriate proportional calculation methods can the difficulty level division be quickly implemented. Subsequently, the proportional boundaries can be fine-tuned or additional factors can be introduced based on feedback or new research findings without making large-scale modifications to the entire algorithm structure. The proportion can also be dynamically adjusted based on user profile information (such as learning history, interest preferences, ability level, etc.), thereby changing the difficulty level to adapt to individual differences. For example, if a user performs well in a certain aspect, the difficulty can be adjusted by reducing AI auxiliary information or increasing user-initiated challenging content to ensure that each user can get the learning experience that best suits them.

[0162] (6) Regarding the intensity of emotion / conflict, a difficulty conversion method based on logarithmic mapping and segmented threshold can be used to convert the impact of emotion / conflict intensity on the training difficulty of the training program of the course theme into a quantifiable difficulty level and a difficulty score corresponding to the difficulty level.

[0163] Specifically, the difficulty level of emotion / conflict intensity can be divided according to the degree to which the training program may induce emotional fluctuations or cognitive conflicts in the user.

[0164] In some optional embodiments, a scoring range for the intensity of emotions / conflicts that the course content may cause may be provided in advance. For example, the intensity of emotions / conflicts may be scored from 1 to 10, where 1 represents almost no intensity of emotions / conflicts and 10 represents the maximum intensity of emotions / conflicts imaginable.

[0165] Then, the emotion / conflict intensity can be mapped to a value between 0 and 1 by the following formula, and then the difficulty level of the emotion / conflict intensity can be determined according to the mapped value.

[0166]

[0167] Among them, the above formula can often be used to map continuous variables (intensity of emotion / conflict) to values ​​between 0 and 1, that is, f(C)∈[0,1], C can represent the intensity of emotion / conflict, and the range can be between [1,5]. M can represent the C value corresponding to when the function reaches the median (that is, 0.5). For example, M can be 2.5, which means that when C=2.5, f(C)=0.5. k can represent the steepness coefficient. The K value determines the flatness or steepness of the curve of the function f(C), and usually takes a value between 1 and 2. A larger k value will make the curve of the function f(C) steeper, and a smaller k value will make the curve of the function f(C) flatter.

[0168] When C is less than M, the value of function f(C) is close to 0, indicating that the emotional fluctuation or conflict intensity is weak; when C is greater than M, the value of function f(C) is close to 1, indicating that the emotional fluctuation or conflict intensity is extremely high; when C is equal to M, the value of function f(C) is 0.5, indicating that the emotional fluctuation or conflict intensity is moderate.

[0169] After obtaining the emotion / conflict intensity values ​​mapped to between 0 and 1, the emotion / conflict intensity values ​​in the 0-1 interval can be converted into different difficulty levels by means of segmented thresholds according to a preset difficulty score mapping method.

[0170] For example, the emotion / conflict intensity values ​​in the range of 0-1 may be mapped to different difficulty levels according to the following difficulty score mapping method.

[0171]

[0172] Among them, when f(C)∈[0,0.1), the corresponding difficulty level can be difficulty level 1 (the course content does not trigger user emotions and conflicts); when f(C)∈[0.1,0.3), the corresponding difficulty level can be difficulty level 2 (the course content slightly triggers user emotions and conflicts); when f(C)∈[0.3,0.5), the corresponding difficulty level can be difficulty level 3 (the course content moderately triggers user emotions and conflicts); when f(C)∈[0.5,0.7), the corresponding difficulty level can be difficulty level 4 (the course content strongly triggers user emotions and conflicts); when f(C)∈[0.7,1), the corresponding difficulty level can be difficulty level 5 (the course content strongly triggers user emotions and conflicts).

[0173] (7) For time / response pressure, the difficulty conversion method of logarithmic mapping and segmented threshold can be used to convert the impact of time / response pressure on the training difficulty of the training program of the course topic into a quantifiable difficulty level and a difficulty score corresponding to the difficulty level.

[0174] Specifically, the difficulty level of emotion / conflict intensity can be divided according to the time limit required to complete the task or answer the question or the requirement for quick response in the training program.

[0175] In some optional implementations, in actual conversations or interactions, the user's response time / response pressure may vary from a few milliseconds to a few seconds (or even longer). Here, the time range of the time / response pressure caused by the course content can be pre-set, for example, the time / response pressure can be 0-60 seconds. The shorter the time, the shorter the response time required to complete the task or answer the question, and the lower the response pressure; the longer the time, the longer the response time required to complete the task or answer the question, and the greater the response pressure.

[0176] Then, the time / response pressure can be mapped to a value between 0 and 1 by the following formula, and then the difficulty level of the time / response pressure can be determined according to the mapped value.

[0177]

[0178] Among them, this formula can often be used to map continuous variables (time / response pressure) to values ​​between 0 and 1, that is, f(t)∈[0,1], t represents the current time response value, t max Indicates the set maximum time boundary (unit: seconds), t min Indicates the set minimum time boundary (unit: seconds).

[0179] When t is less than or equal to t min When t is greater than or equal to t max When , the value of f(t) is equal to 0. When the value of f(t) is closer to 1, it means that the response time required to complete the task or answer the question in the course content is shorter and the response pressure is smaller. When the value of f(t) is closer to 0, it means that the response time required to complete the task or answer the question in the course content is longer and the response pressure is greater.

[0180] After obtaining the time / response pressure values ​​mapped to between 0 and 1, the time / response pressure values ​​in the 0-1 interval can be converted into different difficulty levels according to a preset difficulty score mapping method by means of segmented thresholds.

[0181] For example, the time / response pressure values ​​in the range of 0-1 may be mapped to different difficulty levels according to the following difficulty score mapping method.

[0182]

[0183] Among them, when f(t)∈[0,0.3), the corresponding difficulty level can be difficulty level 1 (long response time, high response pressure); when f(t)∈[0.3,0.7), the corresponding difficulty level can be difficulty level 2 (medium response time, medium response pressure); when f(t)∈[0.7,1), the corresponding difficulty level can be difficulty level 3 (short response time, low response pressure).

[0184] A wide range of numerical values ​​(such as response times from milliseconds to seconds, or from mild emotional fluctuations to intense conflicts) makes it inappropriate to directly use linear mapping for evaluation. By adopting a logarithmic mapping and segmented threshold difficulty conversion method to divide the difficulty levels of emotion / conflict intensity and time / response pressure, these large-scale values ​​can be "compressed" into a relatively balanced range, ensuring that even extreme values ​​can be reasonably evaluated. Within the common range (non-extreme values), this mapping method improves the discrimination of the ratings, making it easier to identify and classify users or situations of different levels. The logarithmic curve naturally provides a smooth transition between shorter and longer durations, and between low-intensity emotions and high-intensity emotions. This means that when the user's time increases slightly or the emotional intensity rises slightly, the rating will not drop suddenly, but will change gently, which is more in line with reality.

[0185] In this way, by selecting the most suitable difficulty conversion method according to the characteristics of each difficulty factor, we can ensure that the impact of each difficulty factor on the training difficulty of the training plan corresponding to the course theme can be accurately converted into quantifiable difficulty levels and difficulty scores in the form that best suits its characteristics, thereby providing a solid foundation for the formulation of scientific and reasonable training plans.

[0186] Through the above difficulty conversion methods, each difficulty level of each difficulty factor and the difficulty score corresponding to the difficulty level can be obtained, so that a mapping relationship between the difficulty level corresponding to each difficulty factor and the difficulty score can be established based on each difficulty level of each difficulty factor and the difficulty score corresponding to the difficulty level. For example, the mapping relationship between the difficulty level and the difficulty score can be a difficulty level and difficulty score mapping table.

[0187] In some optional implementations, for each target difficulty factor, the difficulty score corresponding to the difficulty level of the target difficulty factor in the target difficulty level combination may be determined according to a mapping table of difficulty levels and difficulty scores corresponding to the target difficulty factor.

[0188] In some optional embodiments, if there is a difficulty score corresponding to the difficulty level of the target difficulty factor that is in a difficulty score range, for example, [0.1, 0.3), then the difficulty score corresponding to the difficulty level can be determined as the minimum value in the difficulty score range, for example, 0.1, or the difficulty score corresponding to the difficulty level can be determined as the middle value in the difficulty score range, for example, 0.2, or the difficulty score corresponding to the difficulty level can be determined as any value in the difficulty score range, or the difficulty score corresponding to the difficulty level can be determined according to other methods, which are not limited here.

[0189] Step 2022: Obtain a preset first correspondence table for characterizing the correspondence between difficulty factor pairs and interaction types between the difficulty factors.

[0190] In this embodiment, the interaction type between difficulty factors may refer to the interaction pattern exhibited by different difficulty factors when they jointly influence the training difficulty of the training program.

[0191] A difficulty factor pair may refer to two difficulty factors that interact with each other when it comes to the training difficulty of a training program, wherein the difficulty factor pair may include a first difficulty factor and a second difficulty factor, the first difficulty factor may refer to one of the two difficulty factors that interact with each other when it comes to the training difficulty of a training program, and the second difficulty factor may refer to the other of the two difficulty factors that interact with each other when it comes to the training difficulty of a training program.

[0192] The first correspondence table includes all difficulty factor pairs that interact with each other in the training difficulty of the training program and interaction types between the difficulty factors corresponding to the difficulty factor pairs.

[0193] In some optional implementations, the interaction type between difficulty factors may include at least one of synergistic interaction and mutually exclusive interaction.

[0194] Among them, synergy can mean that when the difficulty levels of two difficulty factors in a difficulty factor pair are high at the same time, the degree of influence on the training difficulty of the training program is greater than the degree of influence of the simple sum of the difficulty scores corresponding to the difficulty levels of the two difficulty factors on the training difficulty of the training program.

[0195] Mutually exclusive effect may mean that when the difficulty levels of two difficulty factors in a difficulty factor pair are simultaneously high, the degree of impact on the training difficulty of the training program is less than the degree of impact of simply adding the difficulty scores corresponding to the difficulty levels of the two difficulty factors on the training difficulty of the training program.

[0196] Step 2023: Generate a second correspondence table based on the first correspondence table.

[0197] The second correspondence table belongs to the first correspondence table, and both difficulty factors in the difficulty factor pairs in the second correspondence table are target difficulty factors.

[0198] In other words, the second correspondence table is a subset of the first correspondence table, and the first difficulty factor and the second difficulty factor of the difficulty factor pairs in the second correspondence table are both target difficulty factors.

[0199] Step 2024: For each difficulty factor pair in the second correspondence table, determine the difficulty factor pair difficulty score of the difficulty factor pair based on the interaction type between the difficulty factors of the difficulty factor pair and the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination.

[0200] In this embodiment, based on each difficulty factor pair in the second correspondence table, a difficulty factor pair difficulty score of the difficulty factor pair can be generated based on the interaction type between the difficulty factors of the difficulty factor pair and the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination, so as to measure the impact of the interaction between the difficulty factor pair on the training difficulty of the training plan.

[0201] In some optional implementations, step 2024 may include the following A1-A2.

[0202] A1. For each difficulty factor pair in the second relationship correspondence table, determine a difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair according to the interaction type between the difficulty factors of the difficulty factor pair.

[0203] Here, according to the types of interactions between different difficulty factors, different difficulty factor-to-difficulty assessment methods can be used to more accurately assess the impact of different difficulty factors on the training difficulty of the training program.

[0204] In some optional implementations, in this embodiment, the types of interactions between different difficulty factors may correspond to different difficulty factor-to-difficulty assessment methods. By adopting different difficulty factor-to-difficulty assessment methods, the impact of each difficulty factor on the training difficulty of the training program can be more accurately measured, so as to more accurately obtain the overall training difficulty of the training program.

[0205] In some optional implementations, if the interaction type between the difficulty factor pair is a synergistic interaction, the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is determined to be a synergistic difficulty assessment method.

[0206] In the collaborative difficulty assessment method, the difficulty score of the difficulty factor pair is positively correlated with the difficulty score of each difficulty factor in the difficulty factor pair in the difficulty level.

[0207] In other words, in the collaborative difficulty assessment method, the degree of influence of the difficulty factor pair on the training difficulty of the training program is greater than the degree of influence of the simple sum of the difficulty scores corresponding to the difficulty levels of the two difficulty factors on the training difficulty of the training program. That is, the impact of the two difficulty factors in the difficulty factor pair on the overall difficulty of the training program will exceed linear expectations, and the difficulty impact of the two difficulty factors on the training difficulty of the training program is not just the result of the simple sum of the difficulty scores of the two difficulty factors, but produces a result that exceeds the simple sum of the difficulty scores of the two difficulty factors.

[0208] The synergistic difficulty assessment method is used to assess the impact of difficulty factors on the difficulty of a training program when the interaction type between difficulty factors is synergistic.

[0209] In some alternative embodiments, the synergy may include a first order synergy and a second order synergy.

[0210] Among them, the first level synergy (also called strong synergy) means that when two difficulty factors are at a high level at the same time, their impact on the overall difficulty of the training program will be significantly doubled or at least exceed linear expectations.

[0211] Example 1, for the difficulty factors emotion / conflict intensity and time / response pressure.

[0212] When conflict is high and users are required to respond within a very short timeframe, this significantly increases emotional tension and cognitive load. Combining high conflict with time pressure often results in a training scenario with an explosive increase in difficulty. This means that the combination of high conflict and time pressure is significantly more challenging for learners than either factor alone (conflict or time pressure).

[0213] For example, in a high-emotion / conflict situation such as a collaborative negotiation, adding the pressure of a countdown can cause the training difficulty of the training program to explode.

[0214] Example 2, for the difficulty factors language complexity and time / response pressure.

[0215] If, in a training program, complex language structures (such as advanced sentences and abstract vocabulary) are used in the conversation and the user is required to understand and respond in a short period of time, the user will feel extremely challenged. In this case, the user may feel unable to keep up with the rhythm of the conversation, leading to deep frustration or simply giving up trying. If the other party's words are complex in themselves and time is tight, the user's cognitive load will increase significantly. The highly complex language plus time pressure requires users to process a large amount of information in a short period of time, which greatly increases their psychological burden and causes the training difficulty of the training program to explode.

[0216] Example 3, for the difficulty factors emotion / conflict intensity and language complexity.

[0217] If a training scenario involves high levels of emotional volatility or intense conflict, and complex language structures (such as advanced sentence structures and specialized terminology) are used during communication, this can be a significant challenge for users. In this scenario, users not only have to cope with strong emotional impact and tense interpersonal interactions, but also need to expend additional cognitive resources on understanding complex language expressions. High levels of emotional / conflict intensity coupled with high language complexity mean that learners must simultaneously process complex information input and high-intensity emotional output. This combination significantly increases the overall difficulty of the training scenario. Compared to considering either factor alone (emotional / conflict intensity alone or language complexity alone), the combination of the two greatly increases the cognitive and emotional burden on users, resulting in a nonlinear increase in the training difficulty of the training scenario.

[0218] In some optional embodiments, if the interaction type between the difficulty factors of the difficulty factor pair is first-level synergy, the difficulty factor pair is determined to be a high-difficulty factor pair or a low-difficulty factor pair based on the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination.

[0219] In this embodiment, when the sum average of the difficulty scores of the difficulty factors in the difficulty factor pair in the target difficulty level combination is greater than a preset difficulty score threshold, the difficulty factor pair is determined to be a high difficulty factor pair.

[0220] When the sum average of the difficulty scores of the difficulty factors in the difficulty factor pair in the target difficulty level combination is less than or equal to the difficulty score threshold, the difficulty factor pair is determined to be a low difficulty factor pair.

[0221] Here, the preset difficulty score threshold can be adjusted according to actual conditions, for example, the difficulty score threshold can be 0.6.

[0222] When the difficulty factor pair is a high difficulty factor pair, the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is determined to be the first collaborative difficulty assessment method.

[0223] In the first collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a first positive correlation.

[0224] The first collaborative difficulty assessment method may be used to assess the impact of the difficulty factor pair on the difficulty of the training program when the difficulty factor pair is a high-difficulty factor pair.

[0225] When the difficulty factor pair is a low difficulty factor pair, the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is determined to be the second collaborative difficulty assessment method.

[0226] In the second collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is the second positive correlation, and the first positive correlation is greater than the second positive correlation.

[0227] The second collaborative difficulty assessment method may be used to assess the impact of the difficulty factor pair on the difficulty of the training program when the difficulty factor pair is a low-difficulty factor pair.

[0228] The degree of influence of the difficulty factor pair on the training difficulty of the training program in the first positive correlation is greater than the degree of influence on the training difficulty of the training program in the second positive correlation, that is, when the difficulty factor pair is a high-difficulty factor pair, the degree of influence on the training difficulty of the training program is greater than when the difficulty factor pair is a low-difficulty factor pair.

[0229] Level 2 synergy (also known as moderate synergy) refers to when two difficulty factors are simultaneously at high levels, there is a noticeable effect, but the effect is not as multiplicative as level 1 synergy. In other words, while the two difficulty factors do increase the overall difficulty, the increase is not exponential.

[0230] Example 1, for the difficulty factors Topic Depth and Emotion / Conflict Intensity.

[0231] In a training scenario, even if the topic is superficial, the emotional / conflict intensity still increases the training difficulty, which still places a certain amount of pressure on the user. However, since the topic itself is not deep, the user does not need to deal with complex concepts or logical reasoning. Therefore, although the emotional challenge is increased, the overall difficulty increase is limited. If the topic is very deep and the emotional / conflict intensity is also high, the difficulty of understanding and emotional negotiation will be greatly increased. However, this is not as direct as the impact of language complexity on emotional / conflict intensity, so it is considered a moderate synergistic effect.

[0232] Example 2, for the difficulty factors topic depth and language complexity.

[0233] In training scenarios, the deeper the topic (involving emotions / abstract thinking) and the more complex the language, the higher the difficulty of the training scenario, and the greater the challenge users face. This requires them to not only understand complex ideas but also parse difficult language expressions. However, in many scenarios, even if the topic is deep, it can often be conveyed through relatively approachable and emotional language. This means that even when dealing with profound content, the burden on users can be reduced by simplifying the language. While this combination increases the difficulty of the training scenario, it does not reach the level of exponential growth, and is considered a moderate synergy.

[0234] Example 3, regarding the difficulty factors of media presentation and language complexity.

[0235] In learning or communication scenarios where text is the main way to convey information, if the language complexity is high, it will usually lead to a significant increase in the difficulty of understanding. Although high language complexity will make the difficulty of understanding higher than a simple linear increase, this does not mean that its impact is unlimited or exponential. In fact, as the complexity of the language increases, the difficulty of understanding increases, but this increase is often gradual and bounded, and does not reach an extreme level. It is a moderate synergistic effect.

[0236] In some optional implementations, if the inter-difficulty factor interaction type of the difficulty factor is the second level synergistic interaction, the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is determined to be the third synergistic difficulty assessment method.

[0237] Among them, in the third collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a third positive correlation, wherein the second positive correlation is greater than the third positive correlation.

[0238] The degree of influence of the difficulty factor pair on the training difficulty of the training program in the second positive correlation is greater than the degree of influence on the training difficulty of the training program in the third positive correlation. That is to say, when the type of interaction between the difficulty factors of the difficulty factor pair is the second level of synergy, the degree of influence of the difficulty factor pair on the increase in the training difficulty of the training program is less than the degree of influence on the increase in the training difficulty of the training program when the type of interaction between the difficulty factors of the difficulty factor pair is the first level of synergy.

[0239] The third synergistic difficulty evaluation method is used to evaluate the impact of difficulty factors on the difficulty of training programs when the interaction type between difficulty factors is the second level of synergy.

[0240] If the inter-difficulty factor interaction type of the difficulty factor is mutually exclusive, the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is determined to be a mutually exclusive difficulty assessment method.

[0241] In the mutually exclusive difficulty assessment method, the difficulty score of the difficulty factor pair is negatively correlated with the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination.

[0242] In other words, in the mutually exclusive difficulty assessment method, the degree of influence of the difficulty factor pair on the training difficulty of the training plan is less than the degree of influence of the simple sum of the difficulty scores corresponding to the difficulty levels of the two difficulty factors on the training difficulty of the training plan. That is, the two difficulty factors in the difficulty factor pair have a lower impact on the overall difficulty of the training plan than the linear expectation. The difficulty impact of the two difficulty factors on the training difficulty of the training plan is not just the result of the simple sum of the difficulty scores of the two difficulty factors, but produces a result lower than the simple sum of the difficulty scores of the two difficulty factors. That is, the existence of one difficulty factor will weaken the training difficulty of the training plan brought by the other difficulty factor.

[0243] For example, difficulty factors include language complexity and the intensity of AI guidance and error correction.

[0244] Learners may experience difficulty understanding texts with high linguistic complexity. This includes complex sentence structures, specialized terminology, and uncommon vocabulary, all of which increase cognitive load and complicate information processing. However, AI guidance and error correction can alleviate these issues. For example, AI can provide real-time explanations of complex grammatical structures, simplify sentences, or directly translate them into more accessible language. As AI guidance and error correction become more robust, the barriers posed by language complexity to learners gradually decrease.

[0245] A2, using the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair, and based on the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination, determining a difficulty factor pair difficulty score for the difficulty factor pair.

[0246] In some optional implementations, if the inter-difficulty factor interaction type of the difficulty factor is a first-level synergy, the first synergy difficulty evaluation method and the second synergy difficulty evaluation method corresponding to the first-level synergy can be implemented by the following formula:

[0247]

[0248] Among them, when hour, (First collaborative difficulty assessment method)

[0249] when hour, (Second collaborative difficulty assessment method)

[0250] f i and fj Represents the difficulty score of one difficulty factor and the other difficulty factor in a difficulty factor pair respectively.

[0251] StrongSynergy(f i ,f j ) is the calculated difficulty factor f i and f j The difficulty factor to the difficulty score.

[0252] θ can represent the difficulty score threshold.

[0253] β1 is the synergy coefficient of the first synergy difficulty evaluation method, which is used to control the increase in the function formula corresponding to the first synergy difficulty evaluation method.

[0254] β1 can be, for example, 0.3, which is not limited here. By adjusting the value of β1, the sensitivity of the first collaborative difficulty assessment method to difficulty changes can be changed. If β1 is set high, even a small increase in the difficulty score will lead to a significant increase in the overall difficulty; conversely, a lower β1 value means that the overall difficulty changes more slowly with the difficulty score.

[0255] β2 may represent the coordination coefficient of the second coordination difficulty evaluation method, and is used to control the increase in the function formula corresponding to the second coordination difficulty evaluation method.

[0256] β2 can be, for example, 0.4, though this is not a limitation. By adjusting the value of β2, the sensitivity of the second collaborative difficulty assessment method to changes in difficulty can be altered. If β2 is set high, even a small increase in the difficulty score will result in a significant increase in the overall difficulty; conversely, a low β2 value means that the overall difficulty changes more gradually with the difficulty score.

[0257] γ can represent the nonlinear strength parameter, which is used to control the function growth rate.

[0258] γ can be 0.5, for example, and there is no specific limitation here. When γ is large, the function grows faster, which means that as the difficulty score increases, the overall difficulty will also increase rapidly; when γ is small, the function grows slower, which means that the overall difficulty will increase more gradually with the increase of the difficulty score.

[0259] D base It can represent the sum of the difficulty scores of each target difficulty factor associated with the target course topic in the target difficulty level combination.

[0260] Through the above formula, the difficulty factor pair difficulty score of each difficulty factor pair whose inter-factor interaction type is the first level synergy can be obtained.

[0261] In some optional implementations, if the inter-difficulty factor interaction type of the difficulty factor is a second-level synergy, the third synergy difficulty assessment method corresponding to the second-level synergy can be implemented by the following formula:

[0262]

[0263] Among them, f i and f j Represents the difficulty score of one difficulty factor and the other difficulty factor in a difficulty factor pair respectively.

[0264] MediumSynergy(f i ,f j ) is the calculated difficulty factor f i and f j The difficulty factor to the difficulty score.

[0265] D base It can represent the sum of the difficulty scores of each target difficulty factor associated with the target course topic in the target difficulty level combination.

[0266] η can represent the synergy coefficient of the third synergy difficulty evaluation method, and η can be 0.6, for example, without limitation, and is used to control the function A larger value of η will cause the value of the function to increase faster, thus affecting the final comprehensive difficulty.

[0267] k can represent a nonlinear index, which is used to determine The index of .

[0268] For example, k can be 2. Different values ​​of k can change the speed at which the comprehensive difficulty changes with the difficulty factor.

[0269] Through the above formula, the difficulty factor pair difficulty score of each difficulty factor pair whose inter-factor interaction type is the second-level synergy can be obtained.

[0270] In some optional implementations, if the interaction type between the difficulty factors of the difficulty factor pair is mutually exclusive, the mutually exclusive collaborative difficulty assessment method corresponding to the mutually exclusive interaction can be implemented by the following formula:

[0271]

[0272] Among them, f i and f j Represents the difficulty score of one difficulty factor and the other difficulty factor in a difficulty factor pair respectively.

[0273] Antagonistic(f i ,f j) is the calculated difficulty factor f i and f j The difficulty factor to the difficulty score.

[0274] D base It can represent the sum of the difficulty scores of each target difficulty factor associated with the target course topic in the target difficulty level combination.

[0275] α can represent the mutual exclusion coefficient of the mutually exclusive difficulty evaluation method, which is used to control the mutual exclusion effect in the mutually exclusive difficulty evaluation method.

[0276] α can be, for example, 0.1, and is not specifically limited here. When α is larger, the mutual exclusion effect is stronger, which means that the difficulty reduction effect between the two difficulty factors is more significant. When α is smaller, the mutual exclusion effect is weaker, which means that the difficulty reduction effect between the two difficulty factors is weaker.

[0277] Through the above formula, the difficulty factor pair difficulty score of each difficulty factor pair with mutually exclusive interaction between factors can be obtained.

[0278] Step 2025: Determine the training difficulty of the training program that matches the target course theme with the target difficulty level combination based on the difficulty score of each target difficulty factor in the target difficulty level combination and the difficulty factor pair difficulty score of each difficulty factor pair.

[0279] In some optional implementations, the difficulty score of each target difficulty factor in the target difficulty level combination and the difficulty score of each difficulty factor pair can be added together, and the result of the addition can be determined as the training difficulty of the training program that matches the target course theme with the target difficulty level combination.

[0280] For example, the training difficulty of the training program for the target course topic can be obtained by the following formula.

[0281] D total =D base +D synergy

[0282] Among them, D total It can represent the training difficulty of the training program of the target course theme, D base It can represent the sum of the difficulty scores of each target difficulty factor associated with the target course topic in the target difficulty level combination, D synergy The sum of the difficulty factor pair difficulty scores of each difficulty factor pair can be expressed.

[0283] In some optional implementations, after step 205 , step 203 may be further included.

[0284] Step 203 : performing a normalization operation on the training difficulty of the training program matched with each target difficulty level combination in the target difficulty factor difficulty level combination set.

[0285] Specifically, based on the training difficulty of the training program matched with each target difficulty level combination in the target difficulty factor difficulty level combination set, a preset normalization method is used to normalize the training difficulty of the training program matched with the target difficulty level combination to obtain the normalized training difficulty of the training program matched with the target difficulty level combination.

[0286] The default normalization method can be achieved by the following formula:

[0287] Dnormalized=(D total -D min ) / (D max -D min )

[0288] Among them, Dnormalized is the training difficulty of the training program matching the target difficulty level combination after normalization, D total is the training difficulty of the training program that matches the target difficulty level combination before normalization, D min The minimum training difficulty among the training difficulties of the training schemes matched with each target difficulty level combination in the target difficulty factor difficulty level combination set before normalization, D max The maximum training difficulty among the training difficulties of the training plans matched with each target difficulty level combination in the target difficulty factor difficulty level combination set before normalization.

[0289] The training difficulty determination method of the training program provided by the embodiment of the present disclosure obtains at least one target difficulty factor associated with the target course theme, wherein each target difficulty factor has at least one difficulty level, and for each target difficulty level combination in the target difficulty factor difficulty level combination set, performs a training program difficulty determination operation to determine the training difficulty of the training program that matches the target course theme with the target difficulty level combination, the target difficulty factor difficulty level combination set is formed by each difficulty level corresponding to at least one target difficulty factor, and the training program difficulty determination operation includes: for each target difficulty factor, determining the difficulty score corresponding to the difficulty level of the target difficulty factor in the target difficulty level combination according to the mapping relationship between the difficulty level corresponding to the target difficulty factor and the difficulty score; obtaining a predetermined difficulty score. A first correspondence table is provided for characterizing the correspondence between difficulty factor pairs and interaction types between difficulty factors; a second correspondence table is generated based on the first correspondence table, wherein the second correspondence table belongs to the first correspondence table and both difficulty factors in the difficulty factor pairs in the second correspondence table are target difficulty factors; for each difficulty factor pair in each second correspondence table, a difficulty factor pair difficulty score is generated according to the interaction type between the difficulty factors of the difficulty factor pair and the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination; based on the difficulty score of each target difficulty factor in the target difficulty level combination and the difficulty factor pair difficulty score of each difficulty factor pair, the training difficulty of the training program that matches the target course theme with the target difficulty level combination is determined. The present disclosure not only considers the impact of each difficulty factor associated with the target course theme on the training difficulty of the training program individually, but also considers the impact of the interaction between multiple difficulty factors on the training difficulty of the training program, which can more comprehensively and accurately reflect the actual difficulty of the training program, thereby matching the most suitable training program for the patient.

[0290] Further references Figure 4 As an implementation of the methods shown in the above figures, the present disclosure provides an embodiment of a device for determining the training difficulty of a training program. Figure 4 Corresponding to the method embodiment shown, the apparatus can be specifically applied to various terminal devices.

[0291] like Figure 4As shown, the training difficulty device of the training program of this embodiment includes: a difficulty factor acquisition unit 401 and a training program difficulty determination unit 402. The difficulty factor acquisition unit 401 is used to acquire at least one target difficulty factor associated with the target course theme, wherein each target difficulty factor has at least one difficulty level; the training program difficulty determination unit 402 is used to perform a training program difficulty determination operation for each target difficulty level combination in the target difficulty factor difficulty level combination set to determine the training difficulty of the training program that matches the target course theme with the target difficulty level combination, wherein the target difficulty factor difficulty level combination set is formed by each difficulty level corresponding to at least one target difficulty factor, and the training program difficulty determination operation includes: for each target difficulty factor, determining the difficulty score corresponding to the difficulty level of the target difficulty factor in the target difficulty level combination according to the mapping relationship between the difficulty level corresponding to the target difficulty factor and the difficulty score; acquiring a preset first correspondence relationship table for characterizing the correspondence between difficulty factor pairs and the action type between difficulty factors; generating a second correspondence relationship table based on the first correspondence relationship table, wherein the second correspondence relationship table belongs to the first correspondence relationship table and both difficulty factors in the difficulty factor pairs in the second correspondence relationship table are target difficulty factors;

[0292] For each difficulty factor pair in the second correspondence table, the difficulty score of the difficulty factor pair is determined according to the type of interaction between the difficulty factors of the difficulty factor pair and the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination; according to the difficulty score of each target difficulty factor in the target difficulty level combination and the difficulty score of the difficulty factor pair of each difficulty factor pair, the training difficulty of the training plan that matches the target course theme with the target difficulty level combination is determined.

[0293] In this embodiment, the specific processing of the difficulty factor acquisition unit 401 and the training program difficulty determination unit 402 and the technical effects thereof can be referred to respectively. Figure 2 The relevant descriptions of step 201 to step 202 in the corresponding embodiment are not repeated here.

[0294] In some optional embodiments, the interaction type between difficulty factors includes at least one of synergistic interaction and mutually exclusive interaction.

[0295] In some optional implementations, the training program difficulty determination unit 402 may be further configured to:

[0296] For each difficulty factor pair in the second correspondence table, determining a difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair according to the interaction type between the difficulty factors of the difficulty factor pair;

[0297] According to the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair, based on the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination, a difficulty factor pair difficulty score of the difficulty factor pair is determined.

[0298] In some optional implementations, the training program difficulty determination unit 402 may be further configured to:

[0299] If the interaction type between the difficulty factors of the difficulty factor pair is synergistic, determining that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a synergistic difficulty assessment method, wherein in the synergistic difficulty assessment method, the difficulty factor pair difficulty score of the difficulty factor pair is positively correlated with the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination;

[0300] If the interaction type between the difficulty factors of the difficulty factor pair is mutually exclusive, the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is determined to be a mutually exclusive difficulty assessment method, wherein, in the mutually exclusive difficulty assessment method, the difficulty factor pair difficulty score of the difficulty factor pair is negatively correlated with the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination.

[0301] In some optional embodiments, the synergy includes a first-level synergy and a second-level synergy, and the training program difficulty determination unit 402 may be further configured to:

[0302] If the interaction type between the difficulty factors of the difficulty factor pair is first-level synergy, the difficulty factor pair is determined to be a high-difficulty factor pair or a low-difficulty factor pair based on the difficulty score of each difficulty factor in the target difficulty level combination;

[0303] When the difficulty factor pair is a high difficulty factor pair, determining that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a first collaborative difficulty assessment method, wherein in the first collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a first positive correlation degree;

[0304] When the difficulty factor pair is a low difficulty factor pair, determining that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a second collaborative difficulty assessment method, wherein in the second collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a second positive correlation degree, and the first positive correlation degree is greater than the second positive correlation degree;

[0305] If the interaction type between the difficulty factors of the difficulty factor pair is the second level synergistic interaction, the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is determined to be the third synergistic difficulty assessment method, wherein in the third synergistic difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is the third positive correlation degree, wherein the second positive correlation degree is greater than the third positive correlation degree.

[0306] In some optional embodiments, the apparatus 400 further includes:

[0307] Normalization unit 403 ( Figure 4 (not shown) for performing the following normalization operation on each target difficulty level combination in the target difficulty factor difficulty level combination set:

[0308] Based on the training difficulty of the training program matched with each target difficulty level combination in the target difficulty factor difficulty level combination set, a preset normalization method is used to normalize the training difficulty of the training program matched with the target difficulty level combination to obtain the normalized training difficulty of the training program matched with the target difficulty level combination.

[0309] It should be noted that the implementation details and technical effects of each unit in the training difficulty determination device of the training program provided in the embodiment of the present disclosure can be referred to the description of other embodiments in the present disclosure and will not be repeated here.

[0310] Reference below Figure 5 , which shows a schematic structural diagram of a computer system 500 suitable for implementing a terminal device of the present disclosure. Figure 5 The computer system 500 shown is only an example and should not bring any limitation to the functions and usage scope of the embodiments of the present disclosure.

[0311] like Figure 5 As shown, the computer system 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. Various programs and data required for the operation of the computer system 500 are also stored in the RAM 503. The processing device 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 405 is also connected to the bus 504.

[0312] Typically, the following devices may be connected to the I / O interface 505: an input device 506 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the computer system 500 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 5 The computer system 500 of the electronic device having various devices is shown, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0313] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network via the communication device 509, or installed from the storage device 508, or installed from the ROM 502. When the computer program is executed by the processing device 501, the above-mentioned functions defined in the method of the embodiment of the present disclosure are performed.

[0314] It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or component. In the present disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0315] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0316] The computer readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device can realize the following operation: Figure 2 The illustrated embodiment and its optional implementations illustrate a method for determining the training difficulty of a training program.

[0317] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, Python, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0318] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0319] The units involved in the embodiments described in this disclosure may be implemented in software or hardware. In some cases, the name of a unit does not limit the unit itself. For example, the difficulty factor acquisition unit may also be described as an "acquisition unit."

[0320] The above description is merely a preferred embodiment of the present disclosure and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also includes other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned disclosed concepts. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this disclosure.

Claims

1. A method for determining the training difficulty of a training program, characterized in that: The method comprises: Obtaining at least one target difficulty factor associated with a target course topic, wherein each target difficulty factor has at least one difficulty level; For each target difficulty level combination in the target difficulty factor difficulty level combination set, a training program difficulty determination operation is performed to determine the training difficulty of a training program that matches the target course theme with the target difficulty level combination, wherein the target difficulty factor difficulty level combination set is formed by difficulty levels corresponding to the at least one target difficulty factor, and the training program difficulty determination operation includes: For each target difficulty factor, determining the difficulty score corresponding to the difficulty level of the target difficulty factor in the target difficulty level combination according to a mapping relationship between the difficulty level corresponding to the target difficulty factor and the difficulty score; Obtaining a preset first correspondence table for characterizing correspondences between difficulty factor pairs and interaction types between the difficulty factors; generating a second correspondence table based on the first correspondence table, wherein the second correspondence table belongs to the first correspondence table and both difficulty factors in the difficulty factor pairs in the second correspondence table are target difficulty factors; For each difficulty factor pair in the second correspondence table, determining a difficulty factor pair difficulty score for the difficulty factor pair based on the interaction type between the difficulty factors of the difficulty factor pair and the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination; The training difficulty of the training program that matches the target course theme with the target difficulty level combination is determined based on the difficulty score of each target difficulty factor in the target difficulty level combination and the difficulty factor pair difficulty score of each difficulty factor pair.

2. The method according to claim 1, characterized in that The interaction type between difficulty factors includes at least one of synergistic effect and mutually exclusive effect.

3. The method according to claim 2, characterized in that The step of determining, for each difficulty factor pair in the second correspondence table, a difficulty factor pair difficulty score of the difficulty factor pair according to the interaction type between the difficulty factors of the difficulty factor pair and the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination includes: For each difficulty factor pair in the second correspondence table, determining a difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair according to the interaction type between the difficulty factors of the difficulty factor pair; The difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is used to determine the difficulty factor pair difficulty score of the difficulty factor pair based on the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination.

4. The method according to claim 3, characterized in that The determining of a difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair based on the interaction type between the difficulty factors of the difficulty factor pair includes: If the interaction type between the difficulty factors of the difficulty factor pair is synergistic, determining that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a collaborative difficulty assessment method, wherein in the collaborative difficulty assessment method, the difficulty factor pair difficulty score of the difficulty factor pair is positively correlated with the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination; If the interaction type between the difficulty factors of the difficulty factor pair is mutually exclusive, determine that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a mutually exclusive difficulty assessment method, wherein, in the mutually exclusive difficulty assessment method, the difficulty factor pair difficulty score of the difficulty factor pair is negatively correlated with the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination.

5. The method according to claim 4, characterized in that Synergy includes first-level synergy and second-level synergy; as well as If the interaction type between the difficulty factors of the difficulty factor pair is synergistic, determining the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair as a synergistic difficulty assessment method includes: If the interaction type between the difficulty factors of the difficulty factor pair is first-level synergy, the difficulty factor pair is determined to be a high-difficulty factor pair or a low-difficulty factor pair based on the difficulty score of each difficulty factor in the target difficulty level combination; When the difficulty factor pair is a high difficulty factor pair, determining that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a first collaborative difficulty assessment method, wherein in the first collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a first positive correlation degree; When the difficulty factor pair is a low difficulty factor pair, determining that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is a second collaborative difficulty assessment method, wherein in the second collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a second positive correlation degree, and the first positive correlation degree is greater than the second positive correlation degree; If the interaction type between the difficulty factors of the difficulty factor pair is the second level synergistic interaction, determine that the difficulty factor pair difficulty assessment method corresponding to the difficulty factor pair is the third collaborative difficulty assessment method, wherein in the third collaborative difficulty assessment method, the degree of positive correlation between the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination and the difficulty score of the difficulty factor pair of the difficulty factor pair is a third positive correlation degree, wherein the second positive correlation degree is greater than the third positive correlation degree.

6. The method according to claim 1, characterized in that After determining the training difficulty of the training program that matches the target course theme with the target difficulty level combination based on the difficulty score of each target difficulty factor in the target difficulty level combination and the difficulty factor pair difficulty score of each difficulty factor pair, the method further includes: For the training difficulty of the training program matched with each target difficulty level combination in the target difficulty factor difficulty level combination set, the following normalization operation is performed: Based on the training difficulty of the training program matched with each target difficulty level combination in the target difficulty factor difficulty level combination set, a preset normalization method is used to normalize the training difficulty of the training program matched with the target difficulty level combination to obtain the normalized training difficulty of the training program matched with the target difficulty level combination.

7. A device for determining the training difficulty of a training program, characterized in that: include: a difficulty factor acquisition unit, configured to acquire at least one target difficulty factor associated with a target course topic, wherein each target difficulty factor has at least one difficulty level; A training program difficulty determination unit is configured to perform a training program difficulty determination operation for each target difficulty level combination in a target difficulty factor difficulty level combination set, so as to determine the training difficulty of a training program that matches the target course theme with the target difficulty level combination, wherein the target difficulty factor difficulty level combination set is formed by the difficulty levels corresponding to the at least one target difficulty factor, and the training program difficulty determination operation includes: For each target difficulty factor, determining the difficulty score corresponding to the difficulty level of the target difficulty factor in the target difficulty level combination according to a mapping relationship between the difficulty level corresponding to the target difficulty factor and the difficulty score; Obtaining a preset first correspondence table for characterizing correspondences between difficulty factor pairs and interaction types between the difficulty factors; generating a second correspondence table based on the first correspondence table, wherein the second correspondence table belongs to the first correspondence table and both difficulty factors in the difficulty factor pairs in the second correspondence table are target difficulty factors; For each difficulty factor pair in the second correspondence table, determining a difficulty factor pair difficulty score for the difficulty factor pair based on the interaction type between the difficulty factors of the difficulty factor pair and the difficulty score of each difficulty factor in the difficulty factor pair in the target difficulty level combination; The training difficulty of the training program that matches the target course theme with the target difficulty level combination is determined based on the difficulty score of each target difficulty factor in the target difficulty level combination and the difficulty factor pair difficulty score of each difficulty factor pair.

8. An electronic device, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon, When one or more programs are executed by one or more processors, the one or more processors are caused to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that A computer program is stored thereon, wherein when the computer program is executed by one or more processors, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The method comprises a computer program / instruction, which implements the method according to any one of claims 1 to 6 when the computer program / instruction is executed by a processor.

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