AI Education Based on Evaluating Concentration of Students in Class: Using Machine Vision to Recognize Students' Classroom Behavior.
Yuan ZhangChangzhen QiuNingze ZhongXieyang SuXuanrui ZhangFuquan HuangLuping WangLiang WangPublished in: ICVIP (2021)
Keyphrases
- machine vision
- student learning
- deaf students
- learning environment
- learning activities
- secondary school
- elementary school
- classroom environment
- distance learning
- classroom setting
- e learning
- higher education
- classroom teaching
- teaching methods
- information literacy
- collaborative learning
- university level
- project based learning
- post secondary
- science education
- technology enhanced
- high school students
- distance education
- learning community
- learning experience
- educational settings
- mobile learning
- learning process
- teacher education
- problem based learning
- intelligent tutoring systems
- teaching learning
- high school
- learning outcomes
- student centered
- elementary school students
- blended learning
- virtual classroom
- educational process
- computer science education
- classroom activities
- primary school
- middle school
- quality control
- mobile technologies
- game based learning
- mathematics education
- learning opportunities
- science learning
- image processing
- grade level
- online course
- science teachers
- learning sciences
- classroom instruction
- teacher training
- computer vision
- student engagement
- grade students
- online learning
- professional development
- vision system
- lesson plans
- digital literacy
- student participation
- education programs
- communication skills
- tablet pc
- digital games
- character recognition
- learning styles