Implementing a Machine Learning Approach to Predicting Students' Academic Outcomes.
Svyatoslav OreshinAndrey FilchenkovPolina PetrushaEgor KrasheninnikovAlexander PanfilovIgor GlukhovYulia E. KaliberdaDaniil MasalskiyAlexey SerdyukovVladimir KazakovtsevMaksim KhlopotovTimofey PodolenchukIvan SmetannikovDaria KozlovaPublished in: CCRIS (2020)
Keyphrases
- learning experience
- computer engineering
- information literacy
- student learning
- college students
- learning environment
- higher education
- faculty members
- national science foundation
- undergraduate engineering
- special education
- high school
- online environment
- semester long
- undergraduate students
- high school students
- collaborative learning
- students learning
- distance education
- intelligent tutoring systems
- distance learning
- learning outcomes
- design studio
- tutoring system
- learning activities
- computer programming
- conceptual understanding
- educational environment
- electrical engineering
- computer science students
- computer supported collaborative learning
- learning process
- university students
- programming course
- computer science education
- project based learning
- teaching materials
- university level
- control group
- digital government
- online course
- mobile learning
- graduate students
- learning styles
- learning strategies
- grade students
- elementary school
- secondary school