CN116664013A - Effect evaluation method for collaborative learning mode, ubiquitous intelligent learning system and medium - Google Patents
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Abstract
The invention relates to the technical field of data processing, in particular to an effect evaluation method of a collaborative learning mode, a ubiquitous intelligent learning system and a medium. The method comprises the following steps: acquiring target learning track data and/or target scale data recorded by a target learner in a collaborative learning mode, wherein the target learning track data is associated with learning track data between at least two other learners, and the reliability of the target scale data is greater than a preset reliability threshold; determining a collaborative learning evaluation value corresponding to the target learner according to the target learning track data and/or the target scale data; and determining an evaluation result according to the collaborative learning evaluation scores corresponding to at least two learners in the collaborative learning mode. The method and the device realize evaluation of the effect in the collaborative learning mode from multiple dimensions, and solve the problem of how to evaluate the learning effect in the collaborative learning mode.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an effect evaluation method of a collaborative learning mode, a ubiquitous intelligent learning system and a medium.
Background
With the development of computer and internet technologies, learning modes are gradually changed from off-line learning modes to on-line learning. The on-line learning can provide a learner with more comprehensive course resources and more diversified learning modes than the off-line learning. However, the difficulty to be overcome in online learning is how to evaluate the learning effect of the learner, and ensure the effectiveness of online learning of the learner.
In a related technical scheme, the chinese patent document of patent number CN202110756827.5 discloses a method, a device, equipment and a storage medium for evaluating learning effect, and learning data of students in a set learning stage is obtained; processing the learning data to obtain a first evaluation parameter; wherein the first evaluation parameter comprises: time management ability evaluation parameters, progress potential evaluation parameters, accuracy grasping ability evaluation parameters, and learning stability evaluation parameters; determining a learning effect index according to the first evaluation parameter; and generating a set evaluation map according to the first evaluation parameter and the learning effect index, and displaying the set evaluation map.
However, the learning effect evaluation method disclosed above aims at the learning effect evaluation of students in the personal learning mode, and cannot be evaluated for the collaborative learning modes such as class, grade and the like, that is, cannot be evaluated for the collaborative learning mode.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
The invention mainly aims to provide an effect evaluation method of a collaborative learning mode, which aims to solve the problem of how to evaluate learning effects in the collaborative learning mode.
In order to achieve the above object, the present invention provides a method for evaluating the effect of a collaborative learning mode, the method comprising:
acquiring target learning track data and/or target scale data recorded by a target learner in a collaborative learning mode, wherein the target learning track data is associated with learning track data between at least two other learners, and the reliability of the target scale data is greater than a preset reliability threshold;
determining a collaborative learning evaluation value corresponding to the target learner according to the target learning track data and/or the target scale data;
and determining an evaluation result according to the collaborative learning evaluation scores corresponding to at least two learners in the collaborative learning mode.
Optionally, the collaborative learning evaluation score includes a system evaluation score and/or a learner evaluation score, and the step of determining, according to the target learning trajectory data and/or the target scale data, the collaborative learning evaluation score corresponding to the target learner includes:
Determining the system assessment score according to the target learning track data and/or determining the learner assessment score according to the target scale data;
and determining the collaborative learning evaluation value according to the system evaluation value and/or the learner evaluation value.
Optionally, the step of determining the system assessment score according to the target learning trajectory data and/or determining the learner assessment score according to the target scale data comprises:
determining the system evaluation value according to at least one of the number of learning data nodes, the learning data node intervals and the learning score data in the target learning track data; and/or the number of the groups of groups,
and determining the learner evaluation value according to at least one of the cooperative learning environment evaluation value, the cooperative learning activity evaluation value and the cooperative learning effect evaluation value in the target scale data.
Optionally, the pearson correlation coefficient corresponding to the cooperative learning environment assessment value, the cooperative learning activity assessment value and the cooperative learning effect assessment value are all greater than a preset pearson correlation coefficient threshold.
Optionally, the step of determining the collaborative learning assessment score according to the system assessment score and/or the learner assessment score comprises:
Acquiring a first evaluation weight coefficient corresponding to the system evaluation value and/or a second evaluation weight coefficient corresponding to the learner evaluation value;
and determining the collaborative learning evaluation value according to the system evaluation value and the first evaluation weight coefficient and/or the learner evaluation value and the second evaluation weight coefficient.
Optionally, before the step of obtaining the target learning track data and/or the target scale data recorded by the target learner in the collaborative learning mode, the method further includes:
determining the credibility of the scale data according to the clone Bach coefficient corresponding to each scale data of the target learner;
and determining the scale data with the clone Bach coefficient larger than the standard value of the preset clone Bach coefficient as the target scale data.
Optionally, before the step of determining the evaluation result according to the collaborative learning evaluation scores corresponding to at least two learners in the collaborative learning mode, the method further includes:
determining a KMO value of the collaborative learning assessment score based on a bateride sphere test algorithm;
and when the KMO value is in a preset check interval, executing the step of determining an evaluation result according to the collaborative learning evaluation values corresponding to at least two learners in the collaborative learning mode.
Optionally, the step of determining an evaluation result according to the collaborative learning evaluation scores corresponding to at least two learners in the collaborative learning mode includes:
determining a collaborative learning evaluation mean value according to at least two collaborative learning evaluation scores;
when the collaborative learning evaluation mean value is in a first preset range, determining the evaluation result as a first evaluation result;
when the collaborative learning evaluation mean value is in a second preset range, determining the evaluation result as a second evaluation result;
when the collaborative learning evaluation mean value is in a third preset range, determining that the evaluation result is a third evaluation result;
when the collaborative learning evaluation mean value is in a fourth preset range, determining that the evaluation result is a fourth evaluation result;
and when the collaborative learning evaluation mean value is in a fifth preset range, determining the evaluation result as a fifth evaluation result.
In addition, in order to achieve the above object, the present invention also provides a ubiquitous intelligent learning system, which includes: the device comprises a memory, a processor and a collaborative learning mode effect evaluation program stored on the memory and capable of running on the processor, wherein the collaborative learning mode effect evaluation program realizes the steps of the collaborative learning mode effect evaluation method when being executed by the processor.
In addition, in order to achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon an effect evaluation program of a cooperative learning mode, which when executed by a processor, implements the steps of the effect evaluation method of the cooperative learning mode as described above.
The embodiment of the invention provides an effect evaluation method, a ubiquitous intelligent learning system and a medium for a collaborative learning mode, wherein the evaluation value of a target learner on the collaborative learning mode is calculated by acquiring at least one of target learning track data and target scale data recorded by the target learner in the collaborative learning mode of the ubiquitous intelligent learning system, and the evaluation result of the collaborative learning mode is jointly determined according to the evaluation values of at least two learners, so that the effect under the collaborative learning mode is evaluated.
Drawings
FIG. 1 is a schematic diagram of a hardware operating environment of a ubiquitous intelligent learning system according to an embodiment of the present invention;
FIG. 2 is a flowchart of a first embodiment of a method for evaluating effects of collaborative learning mode according to the present invention;
FIG. 3 is a flowchart of a second embodiment of an effect evaluation method for collaborative learning mode according to the present invention;
FIG. 4 is a flowchart of a third embodiment of a method for evaluating effects of collaborative learning mode according to the present application;
fig. 5 is a flowchart of a fourth embodiment of an effect evaluation method of a collaborative learning mode according to the present application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
According to the application, the evaluation value of the target learner on the cooperative learning mode is calculated by acquiring at least one of the target learning track data and the target scale data recorded by the target learner in the cooperative learning mode of the ubiquitous intelligent learning system, and the evaluation result of the cooperative learning mode is jointly determined according to the evaluation values of at least two learners, so that the effect in the cooperative learning mode is evaluated.
In order to better understand the above technical solution, exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
As an implementation scheme, fig. 1 is a schematic architecture diagram of a hardware operating environment of a ubiquitous intelligent learning system according to an embodiment of the present invention.
As shown in fig. 1, the ubiquitous intelligent learning system may include: a processor 1001, such as a CPU, memory 1005, user interface 1003, network interface 1004, communication bus 1002. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
Those skilled in the art will appreciate that the ubiquitous intelligent learning system architecture shown in fig. 1 is not limiting of the ubiquitous intelligent learning system, and may include more or fewer components than illustrated, or certain components may be combined, or a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and an effect evaluation program of the cooperative learning mode may be included in the memory 1005 as one storage medium. The operating system is a program for managing and controlling hardware and software resources of the ubiquitous intelligent learning system, and an effect evaluation program of the collaborative learning mode and other software or program operations.
In the ubiquitous intelligent learning system shown in fig. 1, the user interface 1003 is mainly used for connecting a terminal, and performs data communication with the terminal; the network interface 1004 is mainly used for a background server and is in data communication with the background server; the processor 1001 may be configured to call an effect evaluation program of the cooperative learning mode stored in the memory 1005.
In this embodiment, the ubiquitous intelligent learning system includes: a memory 1005, a processor 1001, and an effect evaluation program of a cooperative learning mode stored on the memory and executable on the processor, wherein:
when the processor 1001 invokes the effect evaluation program of the cooperative learning mode stored in the memory 1005, the following operations are performed:
acquiring target learning track data and/or target scale data recorded by a target learner in a collaborative learning mode, wherein the target learning track data is associated with learning track data between at least two other learners, and the reliability of the target scale data is greater than a preset reliability threshold;
Determining a collaborative learning evaluation value corresponding to the target learner according to the target learning track data and/or the target scale data;
and determining an evaluation result according to the collaborative learning evaluation scores corresponding to at least two learners in the collaborative learning mode.
When the processor 1001 invokes the effect evaluation program of the cooperative learning mode stored in the memory 1005, the following operations are performed:
determining the system assessment score according to the target learning track data and/or determining the learner assessment score according to the target scale data;
and determining the collaborative learning evaluation value according to the system evaluation value and/or the learner evaluation value.
When the processor 1001 invokes the effect evaluation program of the cooperative learning mode stored in the memory 1005, the following operations are performed:
determining the system evaluation value according to at least one of the number of learning data nodes, the learning data node intervals and the learning score data in the target learning track data; and/or the number of the groups of groups,
and determining the learner evaluation value according to at least one of the cooperative learning environment evaluation value, the cooperative learning activity evaluation value and the cooperative learning effect evaluation value in the target scale data.
When the processor 1001 invokes the effect evaluation program of the cooperative learning mode stored in the memory 1005, the following operations are performed:
acquiring a first evaluation weight coefficient corresponding to the system evaluation value and/or a second evaluation weight coefficient corresponding to the learner evaluation value;
and determining the collaborative learning evaluation value according to the system evaluation value and the first evaluation weight coefficient and/or the learner evaluation value and the second evaluation weight coefficient.
When the processor 1001 invokes the effect evaluation program of the cooperative learning mode stored in the memory 1005, the following operations are performed:
determining the credibility of the scale data according to the clone Bach coefficient corresponding to each scale data of the target learner;
and determining the scale data with the clone Bach coefficient larger than the standard value of the preset clone Bach coefficient as the target scale data.
When the processor 1001 invokes the effect evaluation program of the cooperative learning mode stored in the memory 1005, the following operations are performed:
determining a KMO value of the collaborative learning assessment score based on a bateride sphere test algorithm;
and when the KMO value is in a preset check interval, executing the step of determining an evaluation result according to the collaborative learning evaluation values corresponding to at least two learners in the collaborative learning mode.
When the processor 1001 invokes the effect evaluation program of the cooperative learning mode stored in the memory 1005, the following operations are performed:
determining a collaborative learning evaluation mean value according to at least two collaborative learning evaluation scores;
when the collaborative learning evaluation mean value is in a first preset range, determining the evaluation result as a first evaluation result;
when the collaborative learning evaluation mean value is in a second preset range, determining the evaluation result as a second evaluation result;
when the collaborative learning evaluation mean value is in a third preset range, determining that the evaluation result is a third evaluation result;
when the collaborative learning evaluation mean value is in a fourth preset range, determining that the evaluation result is a fourth evaluation result;
and when the collaborative learning evaluation mean value is in a fifth preset range, determining the evaluation result as a fifth evaluation result.
Based on the hardware architecture of the ubiquitous intelligent learning system based on the data processing technology, the embodiment of the effect evaluation method of the collaborative learning mode is provided.
Referring to fig. 2, in a first embodiment, the effect evaluation method of the cooperative learning mode includes the steps of:
step S10, acquiring target learning track data and/or target scale data recorded by a target learner in a collaborative learning mode;
In the present embodiment, the target learner is selected from the respective learners in the cooperative learning mode by a ubiquitous intelligent learning system (hereinafter referred to as system).
Optionally, the selection of the target learner may be selected randomly by the system, or may be selected based on a certain rule. Alternatively, if based on a certain rule, a learner whose learning duration recorded in the collaborative learning mode exceeds a preset duration threshold may be selected as the target learner.
In this embodiment, the collaborative learning mode refers to a learning mode in which collaborative learning is performed among one or more learners in a system in a group or team manner. The group may be composed of classmates, learning partners with the same learning objectives or similar learning interests, or learners in the same open place (e.g., a real base, a mall, a community, etc.).
Optionally, the implementation flow of the collaborative learning mode can comprise a flexible group unified goal, a clear task formation plan, intelligent division of work for collaboration and shared result collective evaluation.
In this embodiment, the collaborative learning mode refers to a learning mode in which collaborative learning is performed among one or more learners in a system in a group or team manner. The group may be composed of classmates, learning partners with the same learning objectives or similar learning interests, or learners in the same open place (e.g., a real base, a mall, a community, etc.).
Optionally, the implementation flow of the collaborative learning mode can comprise a flexible group unified goal, a clear task formation plan, intelligent division of work for collaboration and shared result collective evaluation.
In this embodiment, the system can provide a flexible group construction manner for users, not only can automatically form groups according to an organization architecture, but also can freely combine according to learning needs or project demands or interest and hobbies, especially, can pull instruction teachers or expert students into the groups, solves the problem of the traditional collaborative learning that the grouping space is blocked, and the grouping difficulty is brought by the demands and the feature complexity of learners, and can realize more efficient, scientific and reasonable grouping. After the group division is completed, a group learning target needs to be unified. Due to the complexity and large scale of the population, it is difficult to develop consistent learning objectives with each other. Therefore, the functions of the USLS (Ubiquitous Smart Learning Space, ubiquitous intelligent learning space) collaborative space are required to be fully exerted, the learning targets are discussed collectively through methods such as mind-guide diagrams, online documents, project designs and the like, and then the unified group learning targets are formed through functions such as video conferences and member voting of the interactive space.
In this embodiment, the learning trajectory data refers to data generated when the system records that the target learner uses various functions in the collaborative learning mode, or data generated when the target learner performs corresponding operations, and the target learning trajectory data refers to learning data trajectories associated with at least two other learners in the same collaborative learning mode.
In this embodiment, the target learner performs various operations related to collaborative learning in the collaborative learning mode to generate corresponding learning data nodes, and the system constructs learning track data from each learning data node of the target learner recorded in a period of history duration.
For easier understanding, the following exemplifies the construction process of the target learning trajectory data.
Illustratively, when a target learner votes on a learning objective established by a learning team in which the target learner is located in a collaborative learning mode, a member voting function in the system is used to allow the team members to jointly decide on a learning objective of a person, and the system regards the member voting function as a collaborative learning-related operation because a plurality of learners are involved in the member voting function, at this time, the system records that the target learner uses the member voting action as an initiator of the action, the system generates a main learning data node, and other learners who will vote as participants also generate a sub learning data node, and the sub learning data node is used as a node associated with the main learning data node.
Then, in a history period (for example, one week in the past), the target learner also uses the "video conference" function, the "activity planning" function, the "project planning" function and the "drawing conceptual diagram" function in the collaborative learning mode, each time these functions are used to generate a corresponding main learning data node, the system generates a plurality of pieces of function usage trajectory data according to each generated main learning data node in the history period, and since these function usage trajectory data are trajectory data generated by the target learner in the collaborative learning mode, the function usage trajectory data can be used as learning trajectory data.
In the process, the learning track data can be generated by the learners who participate in the video conference function, the activity planning function, the project planning table setting function and the concept drawing function, and the learning data nodes generated among the learners are associated, so that the association among the learning track data correspondingly generated among the learners exists, and when the learning data track of the target learner exists, the learning track data is used as the target learning track data corresponding to the target learner.
In this embodiment, the scale data is scoring evaluation data of a learner on the collaborative learning mode, which is received by the system, and the target scale data is the scale data with higher reliability, which is selected from the scale data after the system performs reliability calculation on the scale data, wherein the reliability of the data is greater than a preset reliability threshold.
Alternatively, the scale data may be issued by the system to the learner at regular intervals, and the scale data may be generated according to the received learner-fed back by the learner, which includes the evaluation level.
It will be appreciated that in some embodiments, only the target learning track data may be acquired to perform the subsequent effect evaluation, only the target table data may be acquired, or the target table data may be acquired simultaneously or sequentially based on a certain order, and in the subsequent steps, what kind of acquisition mode is adopted, the subsequent execution steps correspondingly execute the data obtained by the acquisition mode.
Step S20, determining a collaborative learning evaluation value corresponding to the target learner according to the target learning track data and/or the target scale data;
in this embodiment, the cooperative learning evaluation score corresponding to the target learner is determined according to the target learning trajectory data and/or the target scale data. For evaluation of the collaborative learning mode of the system by the target learner, the evaluation can be performed from three dimensions:
1. The system evaluates the dimension, and the system judges the satisfaction of the target learner to the collaborative learning mode according to the target learning track data of the target learner;
2. the learner evaluates the dimension, and the learner sends scoring table data to enable the background system to know the satisfaction of the learner to the collaborative learning mode;
3. and meanwhile, the system evaluation dimension and the learner evaluation dimension are included, namely, the satisfaction condition of the learner on the collaborative learning mode is comprehensively evaluated according to the target learning track data and the scoring table data.
The determination of the specific collaborative learning evaluation value will be described in the following embodiments, and will not be described herein.
And step S30, determining an evaluation result according to the collaborative learning evaluation values corresponding to at least two learners in the collaborative learning mode.
In the present embodiment, the previous step calculates the collaborative learning evaluation score of the learner for the collaborative learning mode in a single learner dimension. In this step, the evaluation result of the cooperative learning mode is determined by the cooperative learning evaluation values of at least two learners.
It is understood that the higher the cooperative learning evaluation value, the more satisfied the learner's evaluation of the cooperative learning mode.
Alternatively, as to how to determine the evaluation result, first, a cooperative learning evaluation mean value of each cooperative learning evaluation score is calculated, and then it is determined in which preset range the cooperative learning evaluation mean value is located. Alternatively, the method may be divided into five preset ranges, that is, a first preset range, a second preset range, a third preset range, a fourth preset range, and a fifth preset range, where the evaluation results corresponding to the respective ranges are a first evaluation result, a second evaluation result, a third evaluation result, a fourth evaluation result, and a fifth evaluation result, respectively.
Optionally, in some embodiments, the first preset range is smaller than the second preset range and smaller than the third preset range and smaller than the fourth preset range and smaller than the fifth preset range, and the first evaluation result indicates that the learner is very dissatisfied with the evaluation result of the collaborative learning mode, the second evaluation result indicates that the learner is relatively dissatisfied with the evaluation result of the collaborative learning mode, the third evaluation result indicates that the learner is relatively dissatisfied with the evaluation result of the collaborative learning mode, the fourth evaluation result indicates that the learner is satisfied with the evaluation result of the collaborative learning mode, and the fifth evaluation result indicates that the learner is very satisfied with the evaluation result of the collaborative learning mode.
Alternatively, in other embodiments, if the first preset range is greater than the second preset range and greater than the third preset range and greater than the fourth preset range and greater than the fifth preset range, then the respective corresponding evaluation results are opposite to those described above.
In the technical scheme provided by the embodiment, the evaluation score of the target learner on the collaborative learning mode is calculated by acquiring at least one of the target learning track data and the target scale data recorded by the target learner in the collaborative learning mode of the system, wherein the target learning track data is the user satisfaction calculated by the system according to the operation data of the learner, the target scale data is the user satisfaction actually fed back by the user, the evaluation score of the learner is calculated according to one or two dimensions, and the evaluation result of the collaborative learning mode is jointly determined according to the evaluation scores of at least two learners, so that the effect under the collaborative learning mode is evaluated.
Referring to fig. 3, in the second embodiment, based on any one of the embodiments, the step S20 includes:
step S21, determining the system evaluation value according to the target learning track data and/or determining the learner evaluation value according to the target scale data;
And step S22, determining the collaborative learning evaluation value according to the system evaluation value and/or the learner evaluation value.
As an alternative embodiment, in this embodiment, for the evaluation of the collaborative learning mode of the system by the target learner, the evaluation may be performed from three dimensions:
1. the system evaluates the dimension, and the system judges the satisfaction of the target learner to the collaborative learning mode according to the target learning track data of the target learner;
2. the learner evaluates the dimension, and the learner sends scoring table data to enable the background system to know the satisfaction of the learner to the collaborative learning mode;
3. and meanwhile, the system evaluation dimension and the learner evaluation dimension are included, namely, the satisfaction condition of the learner on the collaborative learning mode is comprehensively evaluated according to the target learning track data and the scoring table data.
Optionally, the system determines a system evaluation score obtained by system evaluation according to the target learning track data, and/or determines a learner evaluation score obtained by learner feedback result calculation according to the target scale data. The collaborative learning assessment score is then determined based on the system assessment score and/or the learner assessment score.
Further, the step S21 includes:
step S211, determining the system evaluation value according to at least one of the number of learning data nodes, the intervals of the learning data nodes and the learning score data in the target learning track data;
and/or, step S212, determining the learner evaluation value according to at least one of the collaborative learning environment evaluation value, the collaborative learning activity evaluation value and the collaborative learning effect evaluation value in the target scale data.
Alternatively, in the present embodiment, for how to calculate the system evaluation value, calculation may be performed in accordance with at least one of the number of learning data nodes, the learning data node interval, and the learning score data in the target learning trajectory data. The number of the learning data nodes is characterized as the function times of the target learner in the collaborative learning mode, the learning data node interval is characterized as the function frequency of the target learner in the collaborative learning mode, the number of the learning data nodes and the learning data node interval are used for representing the activity degree of the user in the collaborative learning mode, and the higher the activity degree is, the higher the system evaluation score is. The learning score data is characterized in that when the user uses the examination related function of the collaborative learning mode, the system obtains examination scores according to examination answers input by the user, and it can be understood that the higher the examination scores obtained by the user in the examination, the better the learning effect of the user in the collaborative learning mode is represented, so that the learning effect of the user in the collaborative learning mode can be reflected based on the learning score data, namely, the higher the learning score data is, the better the learning effect of the user in the collaborative learning mode is.
Alternatively, in this embodiment, as to how to determine the learner evaluation value, when the learner performs scoring on the collaborative learning mode, the learner may score based on three dimensions of the collaborative learning environment, the collaborative learning activity value, and the collaborative learning effect, obtain a collaborative learning environment evaluation value, a collaborative learning activity evaluation value, and a collaborative learning effect evaluation value, respectively, and determine the learner evaluation value according to at least one dimension of the collaborative learning environment evaluation value, the collaborative learning activity evaluation value, and the collaborative learning effect evaluation value.
It should be noted that, the specific technical means adopted in implementing the technical features not described in the embodiments of the present application may be obtained by the prior art, and are not the key points of disclosure of the present application, and the present application aims to propose a technical solution including the technical features to solve the technical problems to be solved by the present application.
It should be noted that, the pearson correlation coefficient corresponding to the cooperative learning environment evaluation value, the cooperative learning activity evaluation value and the cooperative learning effect evaluation value are all greater than a preset pearson correlation coefficient threshold, that is, all the learner evaluation value and the cooperative learning environment, the cooperative learning activity and the cooperative learning effect show significance. Optionally, the preset pearson correlation coefficient threshold is 0.9.
Further, the step S22 includes:
step S221, obtaining a first evaluation weight coefficient corresponding to the system evaluation value and/or a second evaluation weight coefficient corresponding to the learner evaluation value;
step S222, determining the collaborative learning evaluation score according to the system evaluation score and the first evaluation weight coefficient, and/or the learner evaluation score and the second evaluation weight coefficient.
Optionally, in this embodiment, the system evaluation score and the learner evaluation score correspond to different weight coefficients, respectively, the weight coefficient corresponding to the system evaluation score is a first evaluation weight coefficient, and the weight coefficient corresponding to the learner evaluation score is a second evaluation weight coefficient. And when calculating the collaborative learning evaluation value, calculating the collaborative learning evaluation value according to the system evaluation value and the first evaluation weight coefficient and/or the learner evaluation value and the second evaluation weight coefficient.
Illustratively, the collaborative learning assessment score may be calculated as follows:
collaborative learning assessment score = first assessment weight coefficient system assessment score;
collaborative learning assessment score = second assessment weight coefficient learner assessment score;
Collaborative learning evaluation score= (first evaluation weight coefficient system evaluation score) + (second evaluation weight coefficient learner evaluation score).
In the technical solution provided in this embodiment, in order to more accurately determine satisfaction of a learner to a collaborative learning mode, evaluation may be performed from a system evaluation dimension and/or a learner evaluation dimension, and evaluation values corresponding to different dimensions are different, and a collaborative learning evaluation value is calculated according to the evaluation values of different dimensions, so that evaluation of effects in the collaborative learning mode is more accurately achieved.
Referring to fig. 4, in a third embodiment, before step S10, based on any embodiment, the method further includes:
step S40, determining the credibility of the scale data according to the clone Bach coefficients corresponding to the scale data of the target learner;
and S50, determining the scale data with the clone Bach coefficient larger than the standard value of the preset clone Bach coefficient as the target scale data.
As an alternative embodiment, in this embodiment, the certainty of the scale data may be determined based on the cloned Bach (Cronbach) coefficient.
Specifically, the scoring value of each target learner on the scale data is set as X, and then, the difference d of the scoring values of the target learners in the adjacent two scale data is set. The calculation formula of the clone Bach coefficient K is as follows:
Where n represents the number of scoring times of the target learner, Σd2 represents the sum of squares of the difference of the scoring scores of the target learner at different times, Σx2 represents the sum of squares of the total score of the target learner's data per scale.
Setting a preset clone Bach coefficient standard value K 0 0.8, K>0.8, and is determined as target scale data.
In the technical scheme provided by the embodiment, in order to ensure the credibility of the learner to score the collaborative learning mode, the scale data of the target learner (namely, the target learner is collected to score the collaborative learning mode for multiple times) are collected, if the cloned Bach coefficient of the scale data after multiple times of scoring is larger than a threshold value, the evaluation scoring credibility is higher, the data which are not randomly filled by the target learner are used as the target scale data, and the collaborative learning mode of the system is evaluated, so that the effect under the collaborative learning mode is evaluated more accurately.
Referring to fig. 5, in the fourth embodiment, before step S30, based on any embodiment, the method further includes:
step S60, determining the KMO value of the cooperative learning evaluation value based on a Bartlite sphere test algorithm;
and step S70, when the KMO value is in a preset check interval, executing the step of determining an evaluation result according to the collaborative learning evaluation values corresponding to at least two learners in the collaborative learning mode.
As an alternative embodiment, in this embodiment, in order to ensure that the obtained evaluation result is accurate, a patricide sphere test algorithm is used to verify the collaborative learning evaluation value.
Specifically, the KMO (Kaiser-Meyer-Olkin) value is calculated as follows:
wherein P is the collaborative learning evaluation value, and Q is the approximation coefficient of the collaborative learning evaluation value.
Alternatively, the preset check interval may be [0.7,0.8].
In this embodiment, when the KMO value is within the interval, it is determined that the obtained collaborative learning evaluation value is checked accurately, and the evaluation result determining step is performed.
It will be appreciated that when the KMO value is not within the interval, meaning that the resulting collaborative learning assessment score is inaccurate, the associated step of re-executing the determining of the collaborative learning assessment score is returned.
In the technical scheme provided by the embodiment, the cooperative learning evaluation value is checked by adopting the Bartlite sphere checking algorithm, and when the KMO value of the cooperative learning evaluation value is in a preset interval, the obtained cooperative learning evaluation value is judged to be accurate, so that the effect in the cooperative learning mode is evaluated more accurately.
Furthermore, it will be appreciated by those of ordinary skill in the art that implementing all or part of the processes in the methods of the above embodiments may be accomplished by computer programs to instruct related hardware. The computer program comprises program instructions, and the computer program may be stored in a storage medium, which is a computer readable storage medium. The program instructions are executed by at least one processor in a smart learning system to implement the flow steps of the embodiments of the method described above.
Accordingly, the present application also provides a computer-readable storage medium storing an effect evaluation program of a cooperative learning mode, which when executed by a processor, implements the respective steps of the effect evaluation method of a cooperative learning mode as described in the above embodiments.
The computer readable storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk, etc. which may store the program code.
It should be noted that, the specific technical means adopted in implementing the technical features not described in the embodiments of the present application may be obtained by the prior art, and are not the key points of disclosure of the present application, and the present application aims to propose a technical solution including the technical features to solve the technical problems to be solved by the present application.
It should be noted that, because the storage medium provided in the embodiments of the present application is a storage medium used for implementing the method in the embodiments of the present application, based on the method described in the embodiments of the present application, a person skilled in the art can understand the specific structure and the modification of the storage medium, and therefore, the description thereof is omitted herein. All storage media adopted by the method of the embodiment of the application belong to the scope of protection of the application.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. The effect evaluation method of the collaborative learning mode is characterized by being applied to a ubiquitous intelligent learning system, and comprises the following steps of:
acquiring target learning track data and/or target scale data recorded by a target learner in a collaborative learning mode, wherein the target learning track data is associated with learning track data between at least two other learners, and the reliability of the target scale data is greater than a preset reliability threshold;
Determining a collaborative learning evaluation value corresponding to the target learner according to the target learning track data and/or the target scale data;
and determining an evaluation result according to the collaborative learning evaluation scores corresponding to at least two learners in the collaborative learning mode.
2. The method for evaluating the effect of a cooperative learning mode according to claim 1, wherein the cooperative learning evaluation score includes a system evaluation score and/or a learner evaluation score, and the step of determining the cooperative learning evaluation score corresponding to the target learner based on the target learning trajectory data and/or the target scale data includes:
determining the system assessment score according to the target learning track data and/or determining the learner assessment score according to the target scale data;
and determining the collaborative learning evaluation value according to the system evaluation value and/or the learner evaluation value.
3. The effect evaluation method of a cooperative learning mode according to claim 2, wherein the step of determining the system evaluation score from the target learning trajectory data and/or determining the learner evaluation score from the target scale data includes:
Determining the system evaluation value according to at least one of the number of learning data nodes, the learning data node intervals and the learning score data in the target learning track data; and/or the number of the groups of groups,
and determining the learner evaluation value according to at least one of the cooperative learning environment evaluation value, the cooperative learning activity evaluation value and the cooperative learning effect evaluation value in the target scale data.
4. The method for evaluating the effect of a cooperative learning mode according to claim 3, wherein the cooperative learning environment evaluation value, the cooperative learning activity evaluation value, and the pearson correlation coefficient corresponding to the cooperative learning effect evaluation value are all greater than a preset pearson correlation coefficient threshold.
5. The effect evaluation method of a cooperative learning mode according to claim 2, wherein the step of determining the cooperative learning evaluation score based on the system evaluation score and/or the learner evaluation score includes:
acquiring a first evaluation weight coefficient corresponding to the system evaluation value and/or a second evaluation weight coefficient corresponding to the learner evaluation value;
and determining the collaborative learning evaluation value according to the system evaluation value and the first evaluation weight coefficient and/or the learner evaluation value and the second evaluation weight coefficient.
6. The method for evaluating the effect of a cooperative learning mode according to claim 1, wherein the step of acquiring target learning trajectory data and/or target scale data recorded by a target learner in the cooperative learning mode further comprises:
determining the credibility of the scale data according to the clone Bach coefficient corresponding to each scale data of the target learner;
and determining the scale data with the clone Bach coefficient larger than the standard value of the preset clone Bach coefficient as the target scale data.
7. The method for evaluating the effect of a cooperative learning mode according to claim 1, wherein the step of determining an evaluation result according to the cooperative learning evaluation scores corresponding to at least two learners in the cooperative learning mode further comprises, before:
determining a KMO value of the collaborative learning assessment score based on a bateride sphere test algorithm;
and when the KMO value is in a preset check interval, executing the step of determining an evaluation result according to the collaborative learning evaluation values corresponding to at least two learners in the collaborative learning mode.
8. The effect evaluation method of a cooperative learning mode according to claim 1, wherein the step of determining an evaluation result from the cooperative learning evaluation scores corresponding to at least two learners in the cooperative learning mode includes:
Determining a collaborative learning evaluation mean value according to at least two collaborative learning evaluation scores;
when the collaborative learning evaluation mean value is in a first preset range, determining the evaluation result as a first evaluation result;
when the collaborative learning evaluation mean value is in a second preset range, determining the evaluation result as a second evaluation result;
when the collaborative learning evaluation mean value is in a third preset range, determining that the evaluation result is a third evaluation result;
when the collaborative learning evaluation mean value is in a fourth preset range, determining that the evaluation result is a fourth evaluation result;
and when the collaborative learning evaluation mean value is in a fifth preset range, determining the evaluation result as a fifth evaluation result.
9. A ubiquitous intelligent learning system, characterized in that the ubiquitous intelligent learning system comprises: a memory, a processor, and a cooperative learning mode effect evaluation program stored on the memory and executable on the processor, which when executed by the processor, implements the steps of the cooperative learning mode effect evaluation method according to any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon an effect evaluation program of a cooperative learning mode, which when executed by a processor, implements the steps of the effect evaluation method of a cooperative learning mode according to any one of claims 1 to 8.
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