01893nas a2200289   4500000000100000000000100001008004100002260001200043653001500055653001400070653003200084653001500116653002700131653001800158100002800176700002900204700002600233700002600259700002900285700002600314245008600340856008100426300000700507490000600514520106900520022001401589       2020                            d  c06/202010ae-learning10aEducation10aLearning Management Systems10aPrediction10aSupport Vector Machine10aData Analysis1 aCarlos Villagrá-Arnedo1 aFrancisco Gallego-Durán1 aFaraón Llorens-Largo1 aRosana Satorre-Cuerda1 aPatricia Compañ-Rosique1 aRafael Molina-Carmona00aTime-Dependent Performance Prediction System for Early Insight in Learning Trends  uhttps://www.ijimai.org/journal/sites/default/files/2020-05/ijimai_6_2_12.pdf  a130 v63 aPerformance prediction systems allow knowing the learning status of students during a term and produce estimations on future status, what is invaluable information for teachers. The majority of current systems statically classify students once in time and show results in simple visual modes. This paper presents an innovative system with progressive, time-dependent and probabilistic performance predictions. The system produces by-weekly probabilistic classifications of students in three groups: high, medium or low performance. The system is empirically tested and data is gathered, analysed and presented. Predictions are shown as point graphs over time, along with calculated learning trends. Summary blocks are with latest predictions and trends are also provided for teacher efficiency. Moreover, some methods for selecting best moments for teacher intervention are derived from predictions. Evidence gathered shows potential to give teachers insights on students' learning trends, early diagnose learning status and selecting best moment for intervention.  a1989-1660