GROUP DYNAMIC PORTRAIT
Who-Know Who They Are?
With the perspective of dynamic development and change, using data to dynamically describe the group characteristics of "students" and "teachers", to provide the latest analysis and decision-making basis for "students group teaching" and "teacher group management".
DYNAMIC LEARNING SITUATION TRACKING AND EARLY WARNING
WHEN, WHERE, WHAT-what have you experienced in the teaching process(When, where, what happened)?
Pay attention to the dynamics of academic conditions, track each student's real-time attendance rate, classroom participation, homework completion rate & excellence rate, predict academic trends, early warning of homework plagiarism, and early warning of missed subjects to help the school adjust the teaching process in a targeted manner.
TEACHING QUALITY EVALUATION TRACKING
HOW MUCH-How is the teaching quality of our teachers?
Regular teacher-student evaluation, peer evaluation, quality quantification and trend comparison, positively motivate teachers and warn of abnormal teaching quality.
PERFORMANCE ANALYSIS, EARLY WARNING
HOW MUCH-How are the learning outcomes of our students?
Multi-dimensional insights into teaching problems, roll-face proposition analysis, continuous improvement, and verification of the effectiveness of decision-making measures.
Support single-volume single-question distinction degree & change, difficulty & change, scoring rate and average level, difficulty of wrong questions and knowledge analysis.
Students’ individual scores in each subject are in class, grade position, trend of change, as well as analysis of strengths and weaknesses of knowledge points, analysis of partial subjects, academic predictions and comparison of actual results.
The overall situation of the students in the class (scoring rate, analysis of the answers to various difficult questions, difficulty of wrong questions-analysis of knowledge points), comparison with other classes, etc.
Multi-dimensional data insights (public courses/core courses are cross-analyzed from subjects, average score distribution, subjects, colleges, teachers, and classes to insight into the essence).
Get through the daily teaching, teaching quality evaluation, semester exams, performance analysis and other teaching data cycles and various links.
Provide data application scenarios for members of various roles in university teaching organizations (students, subject teachers, class teachers/counselors, subject leaders, college-level and school-level administrators, etc.).
Analysis and display and data mining, data drill down, abnormal warnings, in-depth layer by layer, deep data insights.
Users can grasp teaching dynamics and abnormal warnings anytime and anywhere, support WeChat business notifications, approval pending, and real-time view of analysis data.
Provide API interface to facilitate data connection with educational administration system and third-party system.