CN117808641A - Collaborative problem solving capability evaluation system and method oriented to group interaction - Google Patents
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Abstract
The invention relates to a collaborative problem solving capability evaluation system and method facing group interaction, wherein the system comprises the following steps: and a user terminal module: the user logs in a teacher role or a student role through the terminal equipment; implementing a collaborative problem resolution capability assessment module: creating a collaboration task and grouping students by a teacher, collecting and analyzing multi-mode data when the students solve the collaboration task, evaluating group collaboration problem solving capability of analyzing group interaction behaviors, and generating an evaluation report in real time; and the data center module is used for storing the data table. The system provided by the invention is suitable for online collaborative learning and evaluation activities, can evaluate the group collaborative problem solving capability based on group interactive behavior analysis, and is used for guiding teachers to take targeted intervention measures to improve collaborative learning efficiency and promote the group collaborative problem solving capability.
Description
Technical Field
The invention relates to the field of core literacy and high-order capability assessment, in particular to a collaborative problem solving capability assessment system and method for group interaction.
Background
The ability to solve collaborative problems is considered an indispensable important skill for people to realize life-long learning and occupational sustainable development. According to social culture learning theory, the individual wants to promote the collaborative problem solving capability to participate in social interaction, and the collaborative problem solving capability assessment developed in the interaction process among individuals can help teachers and students to comprehensively master the overall situation of the group collaborative problem solving problem, help the teachers and students to better master and understand the collaborative problem solving process, guide teachers to take targeted intervention measures, promote the individual to perform self-thinking and social adjustment, and provide powerful support for promoting efficient collaborative groups and promoting the individual collaborative problem solving capability. Currently, existing collaborative problem resolution assessment projects focus only on individual performance and team task completion results, such as the internationally initiated large scale computer-based collaborative problem resolution assessment projects—pisa2015 (Programme for International Student Assessment) and ATC21S (Assessment and Teaching of st Century Skills). The system or the method for supporting the collaborative problem solving capability assessment mainly focuses on the performance of the individual, can evaluate the comprehensive performance of the group collaborative problem solving at an overall view angle, only gives the capability level of the individual according to the evaluation result, does not stand at the view angle of interaction between groups and analyze the comprehensive level of the group collaborative problem solving in a dynamic change-oriented process, is not beneficial to teachers and students to integrally grasp the group collaborative problem solving process, cannot accurately know the advantages and disadvantages of the interaction between the individuals, and cannot effectively intervene and provide guidance. In addition, tasks provided by the existing assessment projects or systems cannot be modified and customized, so that a teacher can be supported to edit the collaborative tasks and develop assessment activities independently, and the assessment activities for the normalized collaborative problem solving ability are difficult to support and develop, and the cultivation of the collaborative problem solving ability of students is not facilitated. Moreover, the computer-based evaluation system or method can realize less automatic acquisition, processing and analysis of the multi-modal behavior data, so that the evaluation evidence is incomplete and the evaluation accuracy is affected. Therefore, how to overcome the problems that the current group cooperation problem solving capability evaluating system has single visual angle, incomplete evaluating evidence, untimely evaluating report generation and no support for teachers to develop normalized evaluating activities becomes a urgent problem to be solved.
Disclosure of Invention
In order to solve the technical problems, the invention provides a collaborative problem solving capability evaluation system and method for group interaction.
The technical scheme of the invention is as follows: a group interaction-oriented collaborative problem resolution capability assessment system, comprising:
and a user terminal module: the user logs in a teacher role or a student role through terminal equipment, and the terminal equipment comprises: a mobile phone, a tablet, a computer and data acquisition equipment;
implementing a collaborative problem resolution capability assessment module: creating a collaboration task by a teacher, grouping students, collecting multi-mode data when the students solve the collaboration task, evaluating the group collaboration problem solving capability facing group interaction behavior analysis, and generating an evaluation report in real time; the method comprises the following steps of: the system comprises a collaborative task editing module, a behavior data acquisition module, an individual behavior coding module, a group interaction analysis module and an evaluation result output module;
and the data center module is used for storing the data table.
Compared with the prior art, the invention has the following advantages:
1. the invention discloses a group interaction-oriented collaborative problem solving capability assessment system, which designs a function for supporting teachers to independently create collaborative tasks, can generate diversified collaborative problem scenes and custom group scales, can trigger individuals to generate a large amount of process behavior data for characterizing collaborative problem solving capability by enabling students to conduct online problem exploration and real-time communication negotiation with groups, and pre-establishes mapping relations between different types of behavior data and behavior evidences, so as to realize automatic processing and coding of the behavior data, realize 'problem-finding-evaluating-reporting' integrated assessment flow, reduce complex work of manual coding, improve assessment efficiency and facilitate the use of teachers in daily teaching activities.
2. The invention provides a universal data interface which can be connected with different types of mobile intelligent equipment, so that multimode behavior data generated by individuals in different scenes can be conveniently collected, synchronization and alignment of the different types of data are realized through a time phase detection and time normalization method, semantic features are further extracted based on a deep learning model, fusion of the multimode data in a feature layer is realized, and sources of evaluation evidences are further enriched.
3. According to the invention, the group capacity level is calculated based on group interaction behavior analysis, the interaction activities among individuals are converted into interaction behavior indexes with evaluation significance by adopting a sliding time pane coding mode, the scores of the groups in different sub-dimensions are calculated, and on the basis, the group collaboration problem solving capacity level is judged by utilizing a Euclidean distance calculation formula, so that the comprehensive evaluation of the group collaboration problem solving capacity facing the group interaction behavior analysis is realized. The problem that an existing collaborative problem solving capability evaluating system only focuses on individual performance and lacks evaluation of a group-oriented collaborative level is solved.
4. The invention provides capability assessment reports for different roles of teachers and students, students can check the capability assessment reports of a group of a certain cooperative task participated in by the students, screening conditions are added to the role of the teachers, the teacher can select the assessment report of a certain group participated in a certain task, and the attention points of users are considered more.
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FIG. 1 is a block diagram of a collaborative problem resolution capability assessment system for group interaction in an embodiment of the present invention;
FIG. 2 is a schematic diagram of an interface showing a generic task template in an embodiment of the present invention;
FIG. 3 is an interface diagram of various types of problem templates in accordance with an embodiment of the present invention;
FIG. 4 is a diagram of an interface of a task data template according to an embodiment of the present invention;
FIG. 5 is an interface schematic of a distribution module according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of an interface of a grouping module according to an embodiment of the present invention;
fig. 7 is an interface schematic diagram of a data acquisition module according to an embodiment of the present invention.
Detailed Description
The invention provides a group interaction-oriented collaborative problem solving capability assessment system which is suitable for online collaborative learning and assessment activities, can assess group collaborative problem solving capability based on group interaction behavior analysis, and is used for guiding teachers to take targeted intervention measures to improve collaborative learning efficiency and promote the improvement of group collaborative problem solving capability.
The present invention will be further described in detail below with reference to the accompanying drawings by way of specific embodiments in order to make the objects, technical solutions and advantages of the present invention more apparent.
Example 1
As shown in fig. 1, the collaborative problem solving capability evaluation system for group interaction provided by the embodiment of the invention includes the following modules:
and a user terminal module: the user logs in teacher role or student role through the terminal equipment, and the terminal equipment includes: a mobile phone, a tablet, a computer and data acquisition equipment;
implementing a collaborative problem resolution capability assessment module: creating a collaboration task and grouping students by a teacher, collecting and analyzing multi-mode data when the students solve the collaboration task, evaluating the group collaboration problem solving capability of the analysis of the interaction behaviors of the face groups, and generating an evaluation report in real time; the method comprises the following steps of: the system comprises a collaborative task editing module, a behavior data acquisition module, an individual behavior coding module, a group interaction analysis module and an evaluation result output module;
and the data center module is used for storing the data table.
In one embodiment, the client module is: the user logs in teacher role or student role through the terminal equipment, and the terminal equipment includes: cell-phone, tablet, computer, data acquisition equipment specifically include:
a user can log in the system from the user side through a smart phone, a tablet, a computer and data acquisition equipment (such as intelligent wearable equipment and the like), a user side module provides a teacher role and a student role entrance, and corresponding functional modules are provided according to different roles.
In one embodiment, the collaborative task editing module specifically includes:
the question setting module: a template creation task and topic for a teacher, wherein the template comprises: a general task template, a plurality of types of problem templates and a task data template;
wherein, the general task template needs to be edited by a teacher as follows: { topic mode (topic symmetric mode/topic asymmetric mode), task title, task cover, task duration, task profile, task description };
various types of problem templates require the teacher to edit the following information: { topic title, topic keyword, topic type (single choice topic, multiple choice topic, gap filling topic, subjective topic, interaction topic, novel topic), topic stem content, answer setting, evaluation rule setting }; the data embedded points are preset in the template, and operation behavior data generated by interaction of students and problems are specified;
the task material template needs to be edited by a teacher as follows: { data header, data cover, data key, data description, data content, task map }, and provide data upload function;
the distribution module: for the teacher to select test classes;
and a grouping module: the method is used for teachers to group testers and determine the collaboration companion of each tester.
In the embodiment of the invention, after a teacher logs in a system, clicking a 'I want to create a' can enter 'collaborative task editing module', firstly editing the basic information of a collaborative task by using a universal task template provided by a question setting module, and determining a question mode, a task title, a task cover, a task duration, a task brief introduction and a task description; as shown in fig. 2, an interface schematic diagram of a general task template in different question modes is shown, and it should be noted that, according to the choice of the question mode, there are mainly the following cases:
when the "topic mode" is the "topic asymmetric mode", as shown in the left side of fig. 2, the number of people in each group is fixed to 2;
when the "topic mode" is the "topic symmetric mode", as shown on the right side of FIG. 2, each group may be 2,3, or 4 people. The panelist was further determined by setting "number of roles": when the number of the roles is 0, the information seen by the data centers of all the members in the group is the same, the number of the group is more flexible, and the number of the groups can be 2,3 or 4, and the data in the data centers of all the members in the group is the same; when the "number of roles" is "2,3 or 4", the number of group persons is fixed as the number of roles, and the data in the "data center" of each member in the group is different.
Then, adding different types of questions by using a plurality of types of question templates, and editing information of preset variables, setting answers and defining scoring rules after a teacher selects a certain type of question template; adding relevant or irrelevant reference data for each question by using a data template, storing all the reference data in a data center of a task area, and automatically storing preset data embedded points in the corresponding template into the task after the task editing is completed; FIG. 3 illustrates an interface schematic diagram of a question template for "single choice questions" including: title, keyword, type of title, content of stem, options and correct answer.
FIG. 4 illustrates an interface schematic of a task material template, including: data title, data cover, data key, data description, data content, task map. Wherein if a "task map" is set for a material, i.e., it is determined which problem the material is associated with, the material is "related material" related to problem resolution; if the "task map" is not set, it is indicated that the data is "interference data" regardless of the problem resolution.
The teacher finishes task editing and clicks a 'task release' button to enter a task simulation test, the task is successfully released after the test is finished, the teacher selects an object participating in the test by using the allocation module, the object is checked by taking a class or a group as a unit, and an interface schematic diagram of the allocation module is shown in fig. 5.
The teacher uses the grouping module to group the test objects, determines the cooperation companion of each tester in two ways, namely random grouping and custom grouping, the number of people in each group is about 2-4, the corresponding requirement is provided for the number of people in the group according to the task 'cooperation type' selected before, after submitting the grouping scheme, the teacher can check the own task after logging in, and FIG. 6 shows the interface schematic diagram of the grouping module, including random grouping and custom grouping.
In one embodiment, the behavior data acquisition module specifically includes:
the students are used as testers to check tasks and participate in the tasks, the testers and the panelists thereof communicate with the task area in real time and complete the tasks through the communication area, and the multi-mode behavior data of each tester are collected in real time and uploaded to a data center;
the communication area is used for real-time online discussion of testers and members thereof and receiving system messages; for example, students may send text-like, picture-like information, select preset messages or send voice messages directly, receive companion messages and system messages;
the task area is used for presenting task information and a response area;
the multimodal behavior data includes: interaction behavior data of a tester in an exchange area and a task area, and physiological data and physical sign data of the tester recorded by data acquisition equipment, and the multi-modal behavior data MBD= { conversation content, click behavior, head motion, limb motion, eye movement behavior, facial expression, brain electrical data, heart rate and blood pressure }, which are defined in the embodiment of the invention.
Students can check collaborative tasks issued by teachers in advance through a behavior data acquisition module as testers, enter a designated virtual collaboration group first page according to a predefined grouping scheme after clicking a 'entering task', can see the login state of other group members of the group, highlight a 'start test' button if all the group members are online, click to enter a formal test task, and put ash on the 'start test' button if the group members are not logged in;
after the test task starts, students can see a task area and an exchange area, the task area comprises a problem area and a data center, the problem area displays problem information added by a teacher, response requirements and the like, the data center displays related information or interference information added by the teacher in advance, the exchange area supports online discussion of testers and peers, and can send messages such as texts and pictures, or select preset messages or send voice messages. According to the preset data embedded points, the system records the operation behavior data of students in the task area and the conversation behavior data of the communication area. In the test process, for each question in the task, the system randomly selects one member in the group to be responsible for submitting the answer after the whole group discussion, after the member submits the answer, the communication area prompts other members to check the answer and vote in the form of a system message, if all the votes agree, the next question is entered, and if one member does not agree, the answer needs to be submitted again.
When students execute tasks, the multi-mode behavior data generated by each student in executing the tasks are recorded in real time by combining with an external intelligent wearable device, synchronization and alignment are realized by using a time phase detection and time normalization method on the multi-mode behavior data, then semantic features are further extracted, for example, audio data are identified and extracted by using a DFSMN model, video data are acquired by taking frames at intervals, the data are uniformly processed to 224 multiplied by 224, and each image is standardized and input into a ResNet network in a matrix form to extract the semantic features. The processed data is passed into the data center along with the recorded operational behavior data and session behavior data. All process behavior data is stored in the data center based on the xAPI specification.
As shown in FIG. 7, the interface of the behavior data acquisition module comprises a task area and an exchange area, wherein the task area comprises a problem area and a data center.
In one embodiment, the individual behavior encoding module specifically includes:
reading multi-modal behavior data from a data center, converting the multi-modal behavior data of a tester into individual behavior evidence according to a coding rule, and uploading an analysis result to the data center; the coding rule defines a mapping relation between the multi-mode behavior data and the individual behavior evidence; the individual behavioral evidence is the behavioral evidence related to the collaborative problem solving performance determined from three dimensions of cognitive investment, social investment and meta-cognitive investment.
The creating coding rule of the embodiment of the invention is used for defining the mapping relation between the individual behavior data and the individual behavior evidence, and realizing the structural characterization of the multi-modal behavior data. Defining individual behavioral evidence 36 behavioral evidence related to collaborative problem solving performance are determined from three dimensions of cognitive investment, social investment and meta-cognitive investment: ibi= { AA1 (providing support), AA2 (issuing commands and requirements), AC1 (analyzing and comparing), AMS1 (cognition of own abilities), AMS3 (expressing uncertainty), AT1 (cognition of tasks), AR3-3 (encouraging timely when peers have negative emotions), AR3-4 (reporting progress timely when peers ask progress), AR3-5 (responding peers timely when peers ask for data), EA1 (asking for current results), ECA1 (issuing alternatives), ECA2 (pointing out errors), FP1 (planning future actions), IA1 (assuming and predicting), MM1 (self-affirming), NE1 (responding peers), NE2 (conflict and contradiction), NE4-2 (asking for comments), NE4-3 (asking for questions), NE6 (asking for help to peers), PA2 (describing problem space), PP1 (issuing solutions), PP2 (seeing and publishing methods), PP2-1 (analyzing error answers), RC1 (identifying relationships), RC1 (voting relationships), RI1 (different, RI1 (participation in task-seeking), NE1 (self-affirming), NE1 (response peers) NE2 (conflict) and task-seeking), NE2 (conflict) and NE2 (conflict-seeking task-seeking), NE2 (participation in task-seeking), NE2 (task-seeking) and task-seeking 1 (participation) and task-seeking 1 (participation) UT1 (alert task progress).
The individual behavior evidence coding module reads the behavior data generated by the student individual from the data center in real time, converts the behavior data into structured behavior evidence according to the defined coding rule, and uploads the processed behavior evidence to the data center in xAPI specification, wherein the behavior evidence is provided with student id, group id and time stamp time of the behavior evidence. For example, a tester StuA such as group 1 votes "disagree", this operational behavior is noted as Record1= { StuA, group 1, vote, "disagree", 2020-12-2814:10}; next, the individual's behavioral data is converted into behavioral Evidence with student id, team id, and time of behavioral Evidence generation, e.g., record1 is converted into Evides1= { StuA, team 1, RD1, 2020-12-2814:10}; then, the behavioral evidences of all students in the same group id are arranged according to time sequence to form an individual behavioral evidence table, each row is a behavioral evidence, then the number num of the group is taken as the length of a coding unit, each time, the coding is carried out by a rule of increasing one cell forwards, the coding is carried out to form an interactive behavioral index of the group, for example, in a certain cell, student StuA generates behavioral evidence MM1, partner StuB generates behavioral evidence RI1, and the two evidences are marked as interactive behavioral index P when being shared 1_1 The result of the encoding is denoted Indicator 1= { group 1, p 1_1 StuA, MM1, stuB, RI1, all encoding results are uploaded to the data center.
In one embodiment, the group interaction analysis module specifically includes:
reading individual behavior evidences from a data center, analyzing the individual behavior evidences by taking a group as a unit according to a group cooperation problem solving capability evaluation model to obtain interactive behavior indexes, calculating scores of different sub-dimensions based on the interactive behavior indexes, finally obtaining a group cooperation problem solving capability grade according to a Euclidean distance calculation formula, and uploading an analysis result to the data center;
wherein the group collaboration problem resolution capability assessment model comprisesFive sub-dimensions fd= { population interaction frequency FD 1 Group interaction timing FD 2 Population interaction Property FD 3 Group interaction results FD 4 Group interaction emotion FD 5 }；
Each sub-dimension of the group collaboration problem solving capability assessment model is associated with a plurality of interactive behavior indexes, and FD is removed 1 The method is obtained based on a hysteresis sequence analysis principle, and the scores of the other four sub-dimensionality scores are the average value of the associated interactive behavior index scores; the method comprises the steps of obtaining interactive behavior indexes based on individual behavior evidences, firstly sequencing the individual behavior evidences in the same group according to time sequence, taking the number of the group as a fixed time pane length, coding by advancing a rule of one lattice each time, and coding into interactive behavior indexes when the correlated behavior evidences of different individuals appear in the same time pane, wherein the interactive behavior indexes comprise: gbi= { motivation and confidence establishment P 1_1 Emotion management P 1_2 Frequency of group interaction P 2 Resource sharing P 3_1 Self-thinking P 3_2 Progress monitor P 3_3 Task Regulation P 3_4 Response partner P 4_1 Timely error correction P 4_2 Suggesting and supporting P 4_3 Mental model P of team 5_1 Team interactive memory P 5_2 Group cognitive architecture P 5_3 -a }; based on the sum of the occurrence frequencies of 13 interactive behavior indexes GBI of the coding result summarizing group, carrying out normalization processing, wherein each sub-dimension score is the normalization result of the associated interactive behavior index and is added to obtain a total score, and the specific steps are as follows: and comparing the value of each interaction behavior index with a predefined threshold value, if the value is larger than the threshold value, directly assigning 1, and if the value is smaller than the threshold value, dividing the score by the threshold value and converting the score into a number smaller than 1. The score of each group on the interactive behavior index can be converted into (0, 1) through normalization processing]A certain value within a range. According to the invention, the Threshold values of 13 interactive behavior indexes obtained by experimental calculation are threshold= { P 1_1 :6.17，P 1_2 :5.33，P 2 :64.3，P 3_1 :4，P 3_2 :5.5，P 3_3 :6.67，P 3_4 :5.8，P 4_1 :10.5，P 4_2 :14，P 4_3 :11，P 5_1 :138.33，P 5_2 :11，P 5_3 :8}；
The group collaboration problem resolution capability level is defined as: CPS = { passive collaboration group N, medium collaboration group M, active collaboration group P, best collaboration group B }; determining a Center point value Center of each group collaboration problem resolution capability level on the group collaboration problem resolution capability assessment model Negative electrode ＝{FD_Neg 1 ,FD_Neg 2 ,FD_Neg 3 ,FD_Neg 4 ,FD_Neg 5 }，Center Medium and medium ＝{FD_Neu 1 ,FD_Neu 2 ,FD_Neu 3 ,FD_Neu 4 ,FD_Neu 5 },Center Active role of ＝{FD_Pos 1 ,FD_Pos 2 ,FD_Pos 3 ,FD_Pos 4 ,FD_Pos 5 },Center Optimum for ＝{FD_Bes 1 ,FD_Bes 2 ,FD_Bes 3 ,FD_Bes 4 ,FD_Bes 5 }；
The values of the Center points of the four capability classes on the FD obtained by the invention according to experiments are centers Negative electrode ＝{0.1767157、0.1466089、0.1002193、0.11934383、0.1055059}，Center Medium and medium ＝{0.5107611、0.4653842、0.3504621、0.4345891、0.2841044}，Center Active role of ＝{0.7808116、0.7136608、0.7279061、0.9483362、0.4738843}，Center Optimum for ＝{1.1063030、0.9520279、1.3480950、1.5955698、0.6157560}；
Finally, respectively calculating the Euclidean distance between the value of the group i on the FD and the central point value of the group collaborative problem solving capability level on the FD according to the following formula, and taking the level corresponding to the minimum distance as the capability level of the group i;
wherein Q is i 、X i 、S i 、J i 、L i The five sub-dimensions FD values of the group i in the group collaborative problem-solving capability assessment model are respectively.
For example, the value of group 1 at FD is calculated to be { Q 1 ，X 1 ，S 1 ，J 1 ，L 1 Then calculate the Euclidean distance between group 1 and the values of the center points of the four predefined capability levels on FD, respectively denoted as Dist Negative electrode 、Dist Medium and medium 、Dist Active role of 、Dist Optimum for Comparing the four values, taking the grade corresponding to the minimum value as the capacity grade of the group 1, and finally uploading the calculation result to the data center.
In one embodiment, the evaluation result output module specifically includes:
reading the analysis result from the data center, generating a visual report of the group collaborative problem solving capability level and the group task information of each group, and presenting the visual report to students and teachers.
After the task is finished, the data center calls a processing result of the process behavior data, calculates the participation frequency of all members in each group on all behavior indexes, namely, gathers contribution levels of all members in the group on the behavior indexes according to the coding rule, namely, counts the number of times that each member participates in effective coding, represents the contribution level of individuals in the group cooperation problem solving process, and uploads the calculation result to the data center;
the assessment result output module automatically reads the behavior data processing result and task basic information from the data center, generates a visual report of information such as the group collaboration problem solving capability level and the group task, and presents the visual report to students and teachers; according to different user roles (students and teachers), the system pushes different report contents after the test is finished, the students can check the evaluation report after the test is finished, the teacher can check the evaluation report of all the groups participating in the test, and a group check result can be screened on a report page.
In one embodiment, the data center module is configured to store a data table, and specifically includes:
teacher information, task information, behavior data, an evaluation model, parameters, coding results and evaluation results.
The invention discloses a group interaction-oriented collaborative problem solving capability assessment system, which designs a function for supporting teachers to independently create collaborative tasks, can generate diversified collaborative problem scenes and custom group scales, can trigger individuals to generate a large amount of process behavior data for characterizing collaborative problem solving capability by enabling students to conduct online problem exploration and real-time communication negotiation with groups, and pre-establishes mapping relations between different types of behavior data and behavior evidences, so as to realize automatic processing and coding of the behavior data, realize 'problem-finding-evaluating-reporting' integrated assessment flow, reduce complex work of manual coding, improve assessment efficiency and facilitate the use of teachers in daily teaching activities. The invention provides a universal data interface which can be connected with different types of mobile intelligent equipment, so that multimode behavior data generated by individuals in different scenes can be conveniently collected, synchronization and alignment of the different types of data are realized through a time phase detection and time normalization method, semantic features are further extracted based on a deep learning model, fusion of the multimode behavior data in a feature layer is realized, and sources of evaluation evidences are further enriched. According to the invention, the group capacity level is calculated based on group interaction behavior analysis, the interaction activities among individuals are converted into interaction behavior indexes with evaluation significance by adopting a sliding time pane coding mode, the scores of the groups in different sub-dimensions are calculated, and on the basis, the group collaboration problem solving capacity level is judged by utilizing a Euclidean distance calculation formula, so that the comprehensive evaluation of the group collaboration problem solving capacity facing the group interaction behavior analysis is realized. The problem that an existing collaborative problem solving capability evaluating system only focuses on individual performance and lacks evaluation of a group-oriented collaborative level is solved. The invention provides capability assessment reports for different roles of teachers and students, students can check the capability assessment reports of a group of a certain cooperative task participated in by the students, screening conditions are added to the role of the teachers, the teacher can select the assessment report of a certain group participated in a certain task, and the attention points of users are considered more.
Example two
The embodiment of the invention provides a group interaction-oriented collaborative problem solving capability assessment method, which comprises the following steps:
step S1: the teacher user logs in the collaborative problem solving capability evaluation system facing group interaction, enters a collaborative Task editing module, designs a collaborative Task, determines a student list participating in a test, submits a grouping scheme and uploads the student list to a data center;
step S2: the student user logs in the group interaction-oriented collaborative problem solving capability assessment system, enters a behavior data acquisition module, checks a collaborative Task, performs collaboration with a panelist to complete the Task, and jointly acquires multi-mode behavior data MBD generated by the student during the group interaction-oriented collaborative problem solving capability assessment system and the terminal equipment, and uploads the multi-mode behavior data MBD to a data center; the multi-mode behavior data MBD is uploaded and stored in the data center based on xAPI specifications;
step S3: the multi-modal behavior data MBD is processed and analyzed by utilizing an individual behavior coding module and a group interaction analysis module, so that a group collaboration problem solving capability level is obtained;
step S4: reading the analysis result from the data center, generating a visual report of the group collaborative problem solving capability level and the group task information of each group, and presenting the visual report to students and teachers.
The above examples are provided for the purpose of describing the present invention only and are not intended to limit the scope of the present invention. The scope of the invention is defined by the appended claims. Various equivalents and modifications that do not depart from the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (7)
1. A group interaction-oriented collaborative problem resolution capability assessment system, comprising:
and a user terminal module: the user logs in a teacher role or a student role through terminal equipment, and the terminal equipment comprises: a mobile phone, a tablet, a computer and data acquisition equipment;
implementing a collaborative problem resolution capability assessment module: creating a collaboration task by a teacher, grouping students, collecting and analyzing multi-mode data when the students solve the collaboration task, evaluating the group collaboration problem solving capability of the analysis of the interaction behaviors of the face group, and generating an evaluation report in real time; the method comprises the following steps of: the system comprises a collaborative task editing module, a behavior data acquisition module, an individual behavior coding module, a group interaction analysis module and an evaluation result output module;
and the data center module is used for storing the data table.
2. The group interaction-oriented collaborative problem resolution capability assessment system of claim 1, wherein the collaborative task editing module specifically comprises:
the question setting module: a template for a teacher to create tasks and topics, wherein the template comprises: a general task template, a plurality of types of problem templates and a task data template;
the distribution module: a tester for a teacher's selection task;
and a grouping module: the system is used for teachers to group the testers and determine the panelists of each tester.
3. The group interaction oriented collaborative problem-solving capability assessment system of claim 1, wherein the behavioral data collection module specifically comprises:
the students are used as testers to check tasks and participate in the tasks, the testers and the panelists thereof communicate with the task area in real time and complete the tasks through the communication area, and the multi-mode behavior data of each tester are collected in real time and uploaded to a data center;
the communication area is used for the real-time communication between the tester and the team member and the receiving of the system message;
the task area is used for presenting task information and a response area;
the multi-modal behavioral data includes: interactive behavior data of the testers in the communication area and the task area, and physiological data and physical sign data of the testers recorded by the data acquisition equipment.
4. The group interaction oriented collaborative problem resolution capability assessment system of claim 3, wherein the individual behavior encoding module specifically comprises:
reading the multi-modal behavior data from the data center, converting the multi-modal behavior data of the tester into individual behavior evidence according to a coding rule, and uploading an analysis result to the data center; wherein the encoding rule defines a mapping relationship between the multimodal behavioral data and the individual behavioral evidence; the individual behavior evidence is the behavior evidence related to the solution performance of the cooperative problems, which is determined from three dimensions of cognitive investment, social investment and meta-cognitive investment.
5. The group interaction-oriented collaborative problem-solving-capability assessment system of claim 4, wherein the group interaction analysis module specifically comprises:
reading the individual behavior evidence from the data center, analyzing the individual behavior evidence by taking a group as a unit according to a group cooperation problem solving capability evaluation model to obtain an interactive behavior index, calculating scores of different sub-dimensions based on the interactive behavior index, finally obtaining a group cooperation problem solving capability grade according to a Euclidean distance calculation formula, and uploading an analysis result to the data center;
wherein the group collaborative problem solving capability assessment model comprises five sub-dimensions fd= { population interaction frequency FD 1 Group interaction timing FD 2 Population interaction Property FD 3 Group (a) of groupsVolume interaction results FD 4 Group interaction emotion FD 5 }；
The interactive behavior index is obtained based on the individual behavior evidence, the individual behavior evidence in the same group is firstly ordered according to time sequence, the number of people in the group is taken as the fixed time pane length, each time a rule of advancing forward is coded, when the correlated behavior evidence of different individuals appears in the same time pane, the interactive behavior index is coded, and the interactive behavior index comprises: gbi= { motivation and confidence establishment P 1_1 Emotion management P 1_2 Frequency of group interaction P 2 Resource sharing P 3_1 Self-thinking P 3_2 Progress monitor P 3_3 Task Regulation P 3_4 Response partner P 4_1 Timely error correction P 4_2 Suggesting and supporting P 4_3 Mental model P of team 5_1 Team interactive memory P 5_2 Group cognitive architecture P 5_3 }；
The group collaboration problem resolution capability level is defined as follows: CPS = { passive collaboration group N, medium collaboration group M, active collaboration group P, best collaboration group B }; determining a Center point value Center of each of the subgroup collaborative problem resolution capability levels on the subgroup collaborative problem resolution capability assessment model Negative electrode ＝{FD_Neg 1 ,FD_Neg 2 ,FD_Neg 3 ,FD_Neg 4 ,FD_Neg 5 }，Center Medium and medium ＝{FD_Neu 1 ,FD_Neu 2 ,FD_Neu 3 ,FD_Neu 4 ,FD_Neu 5 },Center Active role of ＝{FD_Pos 1 ,FD_Pos 2 ,FD_Pos 3 ,FD_Pos 4 ,FD_Pos 5 },Center Optimum for ＝{FD_Bes 1 ,FD_Bes 2 ,FD_Bes 3 ,FD_Bes 4 ,FD_Bes 5 -a }; respectively calculating Euclidean distances between the value of the group i on the FD and the central point value of the group collaborative problem solving capability level on the FD according to the following formula, and taking the level corresponding to the minimum distance as the capability level of the group i;
wherein Q is i 、X i 、S i 、J i 、L i Each being five sub-dimensions FD values of the group i in the group collaborative problem-solving-capability assessment model.
6. The system for evaluating collaborative problem-solving capability for group-oriented interaction according to claim 5, wherein the evaluation result output module specifically comprises:
reading the analysis result from the data center, generating a visual report of the group collaborative problem solving capability level and the group task information of each group, and presenting the visual report to students and teachers.
7. The method for evaluating the collaborative problem solving capability facing group interaction is characterized by comprising the following steps of:
step S1: the teacher user logs in the evaluation system of the group interaction-oriented collaboration problem solving capability, enters a collaboration Task editing module, designs a collaboration Task, determines a student list participating in a test, submits a grouping scheme and uploads the student list to a data center;
step S2: the student user logs in the evaluation system of the group interaction-oriented collaboration problem solving capability, enters a behavior data acquisition module, checks the collaboration Task, cooperates with a panelist to complete the Task, and the evaluation system of the group interaction-oriented collaboration problem solving capability and the terminal equipment acquire multi-mode behavior data MBD generated by the student together and upload the multi-mode behavior data MBD to the data center; wherein, the multi-modal behavior data MBD is uploaded and stored in a data center based on xAPI specifications;
step S3: processing and analyzing the multi-modal behavior data MBD by using an individual behavior coding module and a group interaction analysis module to obtain a group collaboration problem solving capability level;
step S4: reading the analysis result from the data center, generating a visual report of the group collaborative problem solving capability level and the group task information of each group, and presenting the visual report to students and teachers.
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