More　and　more　higher　education　institutions　are　adopting　computer　based　learning　management　system　to　boost　learning　of　the　students.　Networking　and　collaboration　through　social　media　platforms　are　vital　realities.　Learning　is　not　merely　limited　to　class　rooms,　which　is　now　independent　of　location　and　time.　Understanding　how　students　learn　in　this　realm　is　a　mighty　challenge　for　teaching　professionals.　Fortunately,　data　is　abundantly　available　through　learning　management　systems　and　social　media　platforms.　Analyzing　this　vast　data　could　give　an　insight　into　how　learning　is　happening　in　these　days.　Data　mining　techniques　are　vastly　being　used　for　this　purpose.　In　this　paper,　we　present　a　statistical　analysis　of　e-leaning　data　obtained　from　SCHOLAT,　a　scholar　oriented　social　networking　system.　The　analysis　aims　at　getting　data　oriented　perspectives　of　learning,　e.g.,　which　factor　to　what　extent　impacts　learning.　The　analysis　revealed　factors　which　positively　or　negatively　affect　learning　achievement　of　the　students,　i.e.,　course　final　scores.　©　Springer　International　Publishing　AG　2018.