Difference between revisions of "Education Pathways"

Latest revision as of 22:19, 16 February 2019

Looking at data science products in the educational space.

Get input data
- Dataset of all courses
  - Create components of courses
  - Course tagging, MDM, metadata
- Get Student Data
  - Aptitude
  - Location of residence
  - Socio-Economic profile
  - Age etc..
  - Aspirations
- Get environmental data
  - Access to finance
  - Economic conditions
  - Benefits of Educational Outcome / Sentiment Media
Overlay any dependencies
- Automated identification of dependencies via NLP, topic modelling, downstream word co-relation
- Tokenisation, Topic Modelling
- Correlation of topics -> Correlation of Courses
- Generate Educational Graph Pathways
- Analyse Graph nodes for waypoints, course clusters, Badging
  - Allows us to identify duplication in course content
Overlay value of courses
- Based on demand, Based on market need, Social feedback
- Scoring of courses using sentiment analysis
Recommendation
- Based on user selection/user goals?
- Based on university marketing?
- Based on end goals?
- Based on user aptitude?
- Recommendation using inputs + trained recommendation model

@@ Line 1: / Line 1: @@
+Looking at data science products in the educational space.
+* Get input data
-* Badging
+** Dataset of all courses
-* Create dataset of all courses
+*** Create components of courses
-** Create components of courses
+*** Course tagging, MDM, metadata
-** Course tagging, MDM, metadata
+** Get Student Data
+*** Aptitude
+*** Location of residence
+*** Socio-Economic profile
+*** Age etc..
+*** Aspirations
+** Get environmental data
+*** Access to finance
+*** Economic conditions
+*** Benefits of Educational Outcome / Sentiment Media
 * Overlay any dependencies
-** Automated identification of dependencies via NLP, downstream word co-relation
+** Automated identification of dependencies via NLP, topic modelling, downstream word co-relation
 ** Tokenisation, Topic Modelling
+** Correlation of topics -> Correlation of Courses
+** Generate Educational Graph Pathways
+** Analyse Graph nodes for waypoints, course clusters, [[Badging]]
+*** Allows us to identify duplication in course content
 * Overlay value of courses
 ** Based on demand, Based on market need, Social feedback
 ** Scoring of courses using sentiment analysis
 * [[Recommendation]]
-** Based on user selection?
+** Based on user selection/user goals?
 ** Based on university marketing?
 ** Based on end goals?
@@ Line 18: / Line 32: @@
 ** Recommendation using inputs + trained recommendation model
+==Related==
+* [[Pathing]]
 [[Category: Data Science Applications]]