CN110288148B - Student team forming method for open training courses - Google Patents
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Abstract
The invention relates to a student team forming method of an open training course, which consists of a student team forming method of the open training course, a recruitment system, a educational administration system, an alumni system and a course APP, wherein the student team forming method of the open training course is respectively connected with the recruitment system, the educational administration system, the alumni system and the course APP, the open training course evaluation method collects alumni development data and student in-school data, applies the course APP, selects an intention role and intention classmates, takes the number of students in each group and the voluntary team forming intention of the students as constraint conditions, establishes a 'group-student' two-part graph model with constraint, takes the overall team forming income under the maximized constraint condition as an optimization target, and generates student team forming income by using an iterative clustering algorithm.
Description
Technical Field
The invention relates to a course learning team forming method, in particular to a student team forming method of an open training course.
Background
The Washington protocol (Washington Accord) is the international engineering level mutual recognition protocol with the earliest signing time, the most contracting parties and the most authority in the world, and is the official member of the Washington protocol in 2016, 6 months. The industrial and scientific professional layout of China is wide and large in scale, the number and overall quality requirements of the involutory engineers are higher and higher in the effort of changing from the large country of manufacturing industry to the strong country of manufacturing industry, the serious challenges are provided for the higher engineering education of China, and the key problem that the higher engineering education must be solved is how to change the current situation that the engineering education of China is large and not strong in terms of improving engineering practice capability, innovation capability and the like. According to the washington protocol, a peak course (capsule course) is a conventional course in the later stage of education of a family, is an open implementation course, and is centered on projects, each project is composed of a plurality of students, is guided by teachers with project knowledge and experience, requires comprehensive application skills from the fields of engineering, writing, economics, statistics, financial accounting, management, marketing, law, career and the like, simulates activities undertaken by an engineer to the greatest extent within the allowable range of disciplines, stimulates the personal and career skills of a learner, and exercises the professional ability, exploratory ability and other abilities of the students by solving practical problems.
At present, three or five students freely form a team, a plurality of teachers form a guiding team, works are completed within a designated time, and then the knowledge grasping degree of the students is evaluated through modes of demonstration, answering and the like. At present, the student team formation mode is mainly a free and voluntary mode, has stronger randomness, has insufficient excavation of individual characteristics of students such as learning ability, cognition degree, effort degree, learning enthusiasm and the like, and is clearly helpful for improving the learning effect of courses by combining the most distinctive and active teams by how a plurality of students find each other.
The best team forming scheme and model of Han Zhonggeng are published in 4 months 1997, the team forming problem that team members participate in the mathematical modeling competition of college students is selected as the background, and the best team forming scheme and model are provided by using methods such as hierarchical analysis, dynamic planning and the like, so that scientific theoretical basis is provided for selecting excellent team members and reasonably forming teams; wu Dehui and Cao Hui 'a LS-SVM-based method for selecting and teasing electronic design contestants' is published in volume 22, 8-3 of microcomputer information in 2006, and indicates that: the electronic design competition results are closely related to the special combination conditions of the team members (three persons), and the team members can make good use of the long-term and short-term competition after being matched, and the competition results are obtained, so that the point of view of sample collection is adopted, and the ordinary results of each team member who has participated and obtained good results are regarded as one sample X in sample collection i The performance of the team member is seen as a sample set { X ] i X is }, then i,j The jth performance item, which can be expressed as the ith team member, was recently developed using LS-SVM pairsThe ordinary performance of winning players in the electronic design competition is analyzed, 3 key evaluation indexes are found, and a set of quantitative selecting and team forming methods are determined based on the key evaluation indexes; he Haiyan et al, on "3 months in 2009 (total 364 nd) of Cooperation economy and science" university's scientific research team under information asymmetry "indicate: the serious information asymmetry … … of the university family students should establish a dynamic website platform to improve the current situation of the information asymmetry of the university family students; innovation and entrepreneur education, volume 7, journal 4, lin Huihua and other university student innovation training project team implementation mode research, three specific modes of university student innovation training project team and implementation are researched and induced by adopting methods such as questionnaires, interviews and case analysis, the optimal implementation mode mainly comprising team leader responsibility and built together with teacher guidance and team members is summarized, and emphasis is given to: the roles of the members in the group are not suitable for singleization, and the multi-element roles such as 'whippers', 'wisdom' and the like are focused on mining and cultivating; in 2017, the 'mathematical model-based selection and team-forming problems of mathematical modeling contest players' are solved in the 3 rd stage of the 'information and computer', after summer modeling training, the method is examined from the aspects of written test results, machine results, number of winning prizes of mathematical contest, intelligence level (thinking reaction capability, capability of analyzing and solving problems and the like), knowledge surface, team cooperation capability, other relevant conditions and the like, performs fair selection and forming team-forming schemes by using a analytic hierarchy process. In order to reduce the waiting time of users and ensure the fairness and fairness of user team formation, a extremum-based user team formation method is invented in a document CN 106621327B; document CN105701710a discloses a social network team forming method based on graph mining, which solves the team forming problem in the social network, the problem is to give a task which needs some skills to complete, and multiple candidates with different skills, select partial candidates from the candidates to form a subset of candidates, so that the overall skills of the team can not only meet the requirement of completing the task, but also ensure that team members in the team can communicate and work efficiently; application platforms of the types such as games and the like support multiple users to participate in activities online, and are differentUsers can be matched with each other to form teams, because of the difference among the users, if abnormal behaviors exist in the matched users in the teams, the execution efficiency and the execution result of teams are affected, meanwhile, the activity experience of other users in the teams is reduced, and the document CN108066989A discloses a random matching teams method, a device and an application server, and aims to improve the reliability of the matching result of the random matching teams.
The team of peak courses is quite different from the team of competitive activities. The competition activity time is short, the professional requirement is high, the team formation aims at strengthening the score of the tournament, the learning time of the peak course is long, the knowledge coverage is large, the aim is to stimulate the personal ability of the learner, exercise the professional ability and the exploring ability of the students, and the comprehensive quality is improved in the process, so that the competitive team formation mode is in a learning score or voluntary mode and is not suitable for the team formation of the peak course, the strong team formation is not necessarily strong, and the weak team formation is not necessarily weak. Therefore, finding an appropriate peak course team formation method is certainly a significant task for achieving the learning effect of peak courses and achieving the purpose.
Disclosure of Invention
Aiming at the problems, the invention establishes a student team forming method of an open training course, focuses on individual differences and personalized features of learners, reasonably forms groups, promotes team learning effect and achieves the aim of courses.
In order to achieve the above purpose, the design technical scheme of the invention is as follows:
a student team forming method of an open training course comprises a student team forming method of the open training course, a recruitment system, a educational administration system, a alumni system and a course APP, wherein the student team forming method of the open training course is respectively connected with the recruitment system, the educational administration system, the alumni system and the course APP.
According to the student team formation method of the open training course, mySQL database software and Python are used as programming languages, so that various accesses to the database, such as inquiry, modification, deletion, input and update, are realized, and data analysis is realized.
The student team formation method of the open training course comprises student on-school data and alumni development data.
The student on-school data consists of student on-school basic data, student on-school learning data, student on-school scientific and technological activity data and student on-school social activity data. The student on-school basic data come from a recruitment system, and the student on-school basic data table with the structure shown in the table 1-1 is stored; the student learning data in the school comes from a educational administration system, and the student learning data in the structure of the table 1-2 is stored in a school learning data table; the student science and technology activity data in the school comes from a educational administration system, and the student science and technology activity data in the structure of the tables 1-3 is stored in a science and technology activity data table in the school; the student social activity data in the school comes from information systems such as academic departments, group committees and the like, and the student social activity data in the structure shown in tables 1-4 is stored in a school social activity data table.
Table 1-1 student's basic data sheet in school
| Field name | Description of field content |
| Identity card | Identification card number |
| Name of name | Student name |
| Sex (sex) | Male/female |
| Number of school | Unique identification character string for entrance |
| Specialized work | Read-right professional name |
| Biogenic land | Province, city and county where high consideration is given to academic time |
| Middle school of biogenic sources | Middle school with high consideration of academic time |
Table 1-1 student's basic data sheet in school
| Field name | Description of field content |
| Time | The time of registration of this record |
Table 1-2 student study data table in school
| Field name | Description of field content |
| Identity card | Identification card number |
| Name of name | Student name |
| Course code | Course-corresponding digital code |
| Course name | Course name for learning |
| Achievement | Comprehensive learning score |
| Teaching period of course | Typically 1/2/3/4/5/6/7/8/9/10 |
| Dormitory address | Arranged accommodation room address |
| Time | The time of registration of this record |
Table 1-3 student science and technology Activity data sheet in school
Table 1-4 student social Activity data sheet in school
| Field name | Description of field content |
| Identity card | Identification card number |
| Name of name | Student name |
| Activity type | Executive/volunteer/others |
| Activity level | Country level/province level/school level/yard level/train level |
| Year of data | Year of social activity |
| Time | The time of registration of this record |
According to the student team formation method of the open training course, students select intention roles, intention classmates, different intention classmates and the like according to personal wishes by using a mobile phone course APP, complete the team formation intention, complete the Gaalopu high potential energy test, bei Erbin team role test and TKI conflict mode test, upload data, wherein the personal team formation intention data are stored in personal team formation intention data tables with structures of tables 1-5, and the activity types are provided with index selection by an activity dictionary table.
Table 1-5 personal team willingness data sheet
| Field name | Description of field content |
| Identity card | Identification card number |
| Name of name | Student name |
| Activity type | 1=electronic competition, 2=acm, 3=mathematical competition, etc |
| Intent role | Responsible person/technology development/document composition management/etc |
| Intent role ordering | 1/2/3/4/5 |
| Willingness classmates name | Classmates name with willingness to group |
| Will classmates number | College numbers of willingness and team formation |
| Rank ordering of willingness classmates | 1/2/3/4/5 |
| Name of different colleagues | Name of classmates who are obviously unwilling to group with them |
| Study number of different colleges | College numbers that are obviously unwilling to form teams therewith |
| Ordering by different classmates | 1/2/3/…/n |
According to the student team formation method of the open training course, the professional skills A1 of students in a school can be obtained by carrying out cluster analysis on the learning data of the students in the school and the scientific and technological activity data of the students in the school; the individual characteristics A2 of the student in-school social activity data and the student in-school scientific activity data can be obtained through cluster analysis; the psychological characteristic A3 of the personal team will data can be obtained by analyzing the personal team will data by combining the Geigerpu high-potential energy test result, the Bei Erbin team role test result and the TKI conflict mode test result; then, the recommended team role R1 is formed preliminarily by integrating A1, A2 and A3.
The alumni development data consists of student graduation data, alumni basic data sheets and alumni development data. Student graduation data come from a educational administration system and are stored in a student graduation data table with a structure of the table 2-1; the alumni basic data come from alumni system and are stored in alumni basic data table with table 2-2 structure; the alumni development data are from alumni system and stored in alumni development data table with table 2-3 structure.
Table 2-1 student graduation data sheet
| Field name | Description of field content |
| Identity card | Identification card number |
| Name of name | Student name |
| Graduation mode | Acquired/unobscured graduation/32900rib |
| Certificate professional name | Professional name on graduation certificate |
| Year and month of acquisition | Year and month of obtaining certificate |
| Time | The time of registration of this record |
TABLE 2-2 alumni base data sheet
| Field name | Description of field content |
| Identity card | Identification card number |
| Name of name | Student name |
| Job party unit type | Public officer/business type/enterprise |
| Job department location | Office location, city |
TABLE 2-2 alumni base data sheet
| Field name | Description of field content |
| Position of job | Position during data recording |
| Salary condition | Salary for corresponding job position |
| Year of data | Year of data generation |
| Time | The time of registration of this record |
Table 2-3 alumni development data sheet
| Field name | Description of field content |
| Identity card | Identification card number |
| Name of name | Student name |
| Type of achievement | Scientific and technological rewards/papers/patents/honor numbers/social part-time functions and the like |
| Activity level | International/national/province/hall grade |
| Year of data | Year of obtaining scientific and technological achievements |
| Time | The time of registration of this record |
According to the student team formation method of the open training course, the professional skills T1 of students in school during the school are obtained by carrying out cluster analysis on the student learning data and the student science and technology activity data in the school; the individual characteristics T2 are obtained by carrying out cluster analysis on student school social activity data and student school science and technology activity data of the student school data; the personal psychological characteristics T3 of the student in-school data are obtained through analyzing and mining the basic in-school data, T1, T2 and psychological characteristic data of the student in-school data; the characteristic T4 of the alumni development level is obtained by analyzing the student graduation data, alumni basic data and alumni development data of alumni development data and combining MBTI personality test data.
A student team forming method of an open training course comprises the following steps:
s1: collecting alumni development data and student in-school data, and processing and storing the data; constructing a alumni team profit matrix P, and an element P thereof ij Proportional to team formation times of alumni i and j and alumni development levelT4；
S2: and applying course APP to school students, selecting the intention roles and intention classmates according to personal will, completing team intention, and uploading data.
S3: establishing a constrained 'group-student' bipartite graph model by taking the number of students in each group and the voluntary team formation intention of the students as constraint conditions, and initializing student members in each group according to R1; wherein the weight between student k and group g is the team benefit w of each student l in student k and group g kl W of the combination of (a) kl ＝p ij I and j are alumni most similar to students k and l, and the similarity of k and l is calculated based on student characteristics A1, A2 and A3 and alumni characteristics T1, T2 and T3;
s4: generating student team formation by using an iterative clustering algorithm by taking the overall team formation yield under the maximized constraint condition as an optimization target; in each iteration of the algorithm, firstly, using a bipartite graph maximum matching algorithm with constraint to generate bipartite graph maximum matching partition under the condition of not violating the constraint; secondly, constructing a student team generated by the iteration of the round according to the division, and recalculating the weight between each student and the group according to the weight calculation method of S3;
s5: and outputting the student team generated when the iteration of the S4 algorithm is ended.
Compared with the prior art, the method has the beneficial effects that: the method overcomes the limitation of team formation only according to achievements and personal will of students, gives consideration to the individual characteristics of the students, predicts team formation benefits according to the development conditions of similar alumni, aims at maximizing the team formation benefits, performs optimal team formation division by means of an optimization algorithm, realizes comprehensive and diversified consideration indexes, and simultaneously effectively promotes the study and development of team members.
The objects, features and advantages of the present invention will be described in detail by way of example with reference to the accompanying drawings.
Drawings
FIG. 1 is a diagram of a student team organization method of an open training course of the present invention.
FIG. 2 is a diagram of a student data application connection at school according to the present invention.
Fig. 3 is a diagram of a alumni data application connection of the present invention.
FIG. 4 is a flow chart of data analysis of the present invention
Detailed Description
In fig. 1, 101 is a student team forming method of an open training course, 102 is a recruitment system, 103 is a educational administration system, 104 is a alumni system, 105 is a course APP,106 is a student department system, and 107 is a group delegation system, wherein 101 is respectively connected with 102, 103, 104, 105, 106, 107.
The recruitment system mainly refers to a system which is applied to a school in the admission of an college entrance examination by adopting an informatization technology, and saves data information of examinees, such as names, identity cards, examinee admission cards, sexes, source places and the like.
The educational administration system mainly refers to an educational administration management system realized by adopting an informatization technology in schools, and saves the performance of each lesson in each period of school students and alumni to participate in professional technological activities.
The alumni system mainly refers to alumni service systems for graduation and departure school realized by adopting informatization technology, and saves basic data and development data of alumni.
Course APP is mainly used for managing a set of software, and one function is to complete the functions of voluntary team intention selection, involuntary selection and uploading.
The student department system mainly refers to a school which adopts an informatization technology to realize management data of student social activities such as volunteers and the like.
The group delegation system mainly refers to management data such as a challenge cup and the like for realizing the extracurricular scientific and technological activities of students by adopting an informatization technology.
The student team formation method of the open training course adopts MySQL database software and Python as programming languages to realize various accesses to the database such as inquiry, modification, deletion, input and update and analysis of data.
In fig. 2, 201 is a student learning data table, 202 is a student scientific and technological activity table, 203 is a student social activity table, 204 is a student scientific and technological activity table, 205 is a personal team intention data table, 206 is a professional skill A1, 207 is a personality trait A2, 208 is a team character R1, 209 is a guerbent optimal potential energy test table, 210 is a Bei Erbin team character test table, 211 is a TKI conflict pattern test table, and 212 is a psychological trait A3; 206 are respectively connected with 201 and 202, 207 are respectively connected with 203 and 204, 212 are respectively connected with 205, 209, 210 and 211, and 208 are respectively connected with 206, 207 and 212.
In fig. 3, 301 is a student learning data table, 302 is a student science and technology activity table, 303 is a student social activity table, 304 is a student basic data table, 305 is a guestroom potential energy test table, 306 is a Bei Erbin team role test table, 307 is a TKI conflict pattern test table, 308 is a student graduation data table, 309 is a alumni basic data table, 310 is a alumni development data table, 315 is an MBTI personality test data table, 311 is a professional skill T1, 312 is a personality trait T2, 313 is a personality psychological trait T3, and 314 is a alumni development level trait T4; wherein 311 is connected with 301, 302, 313, 312 is connected with 302, 303, 313 is also connected with 304, 305, 306, 307, 314 is connected with 308, 309, 310, 315.
After the data is ready, the algorithm analysis flow of fig. 4 is started, and step 401 is executed first;
step 401: establishing a constrained 'group-student' bipartite graph model, and then executing step 402;
step 402: initializing each group of student members and then performing step 403;
step 403: the biggest match of the bipartite graph under constraint results in team formation, and then step 404 is performed;
step 404: constructing a new student team, executing step 403 to iterate, and executing step 405 if the iteration is completed;
step 405: and (5) ending the iteration and outputting the optimal team.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
While specific embodiments of the invention have been described above, it will be appreciated by those skilled in the art that the specific embodiments described are illustrative only and not intended to limit the scope of the invention, and that any equivalent modifications and variations which are motivated by the present technical route are intended to be included within the scope of the claims.
Claims (1)
1. A student team formation method of an open training course, which is based on student in-school data and alumni development data, comprising the following steps:
s1: collecting alumni development data and student in-school data, and processing and storing the data; constructing a alumni team profit matrix P, and an element P thereof ij The team forming times of the alumni i and j are proportional to the alumni development level characteristic T4;
s2: acquiring personal team formation willingness data on a course APP and uploading the data;
s3: selecting intention data as constraint conditions by using the number of students in each group and personal will, establishing a constrained group-student two-part graph model, and initializing student members in each group according to R1; wherein the weight between student k and group g is the team benefit w of each student l in student k and group g kl W of the combination of (a) kl ＝p ij I and j are alumni most similar to students k and l, and the similarity of k and l is calculated based on student characteristics A1, A2 and A3 and alumni characteristics T1, T2 and T3;
s4: generating student team formation by using an iterative clustering algorithm by taking the overall team formation yield under the maximized constraint condition as an optimization target; in each iteration of the algorithm, firstly, using a bipartite graph maximum matching algorithm with constraint to generate bipartite graph maximum matching partition under the condition of not violating the constraint; secondly, constructing a student team generated by the iteration of the round according to the division, and recalculating the weight between each student and the group according to the weight calculation method of S3;
s5, outputting student team formation generated when the iteration of the S4 algorithm is terminated;
the personal team willingness data sheet has the intentional role, willingness classmates and non-willingness data;
the professional skills A1 of students at school can be obtained by carrying out cluster analysis on the learning data of the students at school and the scientific and technological activity data of the students at school; the individual characteristics A2 of the student in-school social activity data and the student in-school scientific activity data can be obtained through cluster analysis; the psychological characteristic A3 of the personal team will data can be obtained by analyzing the personal team will data by combining the Geigerpu high-potential energy test result, the Bei Erbin team role test result and the TKI conflict mode test result; then integrating A1, A2 and A3 to form a recommended team role R1 preliminarily;
the technical skill T1 of the student is obtained by carrying out cluster analysis on student learning data and student science and technology activity data during school of the alumni; the individual characteristics T2 are obtained by carrying out cluster analysis on student school social activity data and student school science and technology activity data of the student school data; the personal psychological characteristics T3 of the student in-school data are obtained through analyzing and mining the basic in-school data, T1, T2 and psychological characteristic data of the student in-school data; the characteristic T4 of the alumni development level is obtained by analyzing the student graduation data, alumni basic data and alumni development data of alumni development data and combining MBTI personality test data.
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| CN104463399A (en) * | 2013-11-25 | 2015-03-25 | 北京建筑大学 | Student training management method and system |
| CN108492232A (en) * | 2018-05-29 | 2018-09-04 | 黑龙江省经济管理干部学院 | A kind of Higher Vocational College innovative teaching program content development system |
| CN108596807A (en) * | 2018-05-29 | 2018-09-28 | 黑龙江省经济管理干部学院 | A kind of School of High Profession Technology OBE curriculum development tutoring systems |
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| CN104463399A (en) * | 2013-11-25 | 2015-03-25 | 北京建筑大学 | Student training management method and system |
| CN108492232A (en) * | 2018-05-29 | 2018-09-04 | 黑龙江省经济管理干部学院 | A kind of Higher Vocational College innovative teaching program content development system |
| CN108596807A (en) * | 2018-05-29 | 2018-09-28 | 黑龙江省经济管理干部学院 | A kind of School of High Profession Technology OBE curriculum development tutoring systems |
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