Dirk Tempelaar|Bart Rienties|Bas Giesbers
In search for the most informative data for feedback generation: Learning analytics in a data-rich context
Maastricht University|The Open University|Erasmus University Rotterdam
learning analytics seek enhance learning processes systematic measurements learning related data provide informative feedback learners teachers track data learning management systems lms constitute main data source learning analytics empirical contribution provides application buckingham shum deakin cricks theoretical framework dispositional learning analytics infrastructure combines learning dispositions data data extracted computerassisted formative assessments lmss large introductory quantitative methods module 922 students enrolled module based principles blended learning combining facetoface problembased learning sessions etutorials investigated predictive power learning dispositions outcomes continuous formative assessments system generated data modelling student performance potential generate informative feedback using dynamic longitudinal perspective computerassisted formative assessments seem best predictor detecting underperforming students academic performance basic lms data substantially predict learning timely feedback crucial useintensity related track data etutorial systems learning dispositions valuable sources feedback generation