Tagged: ML

AI/ML in Next Generation E-learning Solutions

As the Next Gen E-learning solutions will cover some or all objectives to bring effective utilization of e-learning solutions using AI/ML, some of them are already present in some solutions.


Moodle is shipped with the following core models,

  • Students at risk of dropping out
  • Upcoming activities due
  • No teaching

The following table contains, AI/ ML, Data-mining Techniques in E-learning solutions for different objectives with prediction accuracy.

E-learning FeatureML Models and TechniquePrediction AccuracyCriteria Evaluated using ML
User OpinionHMM [Hidden Markov Model],SVM [Support Vector Machine]
Data Mining Technique :
MI [Mutual Information],IG[Infor-
mation Gain],CHI
F-Measure 0.803The accuracy rate of user opinion predicted
Course Recommendation to StudentsADTree classification Algorithm, Apriori Association Rule algorithm, Simple K-Means AlgorithmApriori Association gives the best cluster of coursesCourse mapping is obtained
Timely system response to studentsGenetic Algorithm, ML techniqueAutomated web bot gives timely reply
Student performance knowledgeSVM F-Measures-0.986Predicts the rate of student’s knowledge
Student Emotionsk-NN, SVMSVM accuracy ration- 97.15%Accurately predicts students emotions
Online session assessmentEnsemble Classifier Baggins embedded with ML78.04% accuracyPredict the beneficial session
Student ranking creditsECOC [Error Correcting Output Code] combines ClassifierF statistics is 3.05Predicts college opportunity
Learning style and learning objectsBayesian EstimationBayesian infer the increase in the visual categoryEstimate learning style
Learner behaviors sequenceFuzzy cluster technique78% matched with real-world dataPredicts learner behavior
Learner sequence, Learning patternFCM [Fuzzy Clustering Methodd], K-means clusteringFCM shows 96.89% accuracy
K-Means shows 80.12 % accuracy
Classified learner Sequence
Student graduation resultsperception ANN [Artificial Neural Network]Predicts successful 77% unsuccessful 68%Predicts graduation successfulness
AUI features coursesFelder Silverman modelClassifies learning ModelsLearning Models predicted
Course informationANN, LMA algorithmR-value 9.08%Evaluate future GPA
learning processing dataConv-GRU-avgP in P-xNNaccuracy 80.04%Predicted Learning Performance
Student assessmentDeep learning TensorFlow Engine80%-91% of accuracyPredicts student pathway
Student test resultsRadom Forest26.7% error ratepredicts student performance
Student engagement in the courseK-means clusteringSilhouette coefficient for two-level cluster is .7003Classify student groups

Aws AI and ML (Machine Learning Stack)

Everyday AWS is improving their set of services in all aspect. As this decade in IT focusing on AI and ML, so

Here is a list of services provided by AWS .

AWS AI ML sservices
AI ML services provided by aws

AI Services : –

  • Vision
  • Speech
    • POLLY
  • Language
  • Chatbots
    • LEX
  • Forecasting
  • Recommendation

Fore more –https://aws.amazon.com/machine-learning/ai-services/

MLServices : –


Fore more https://aws.amazon.com/machine-learning/

ML Framework and Infrastructure : –

  • Supported Frameworks
    • Tensor Flow
    • Mxnet
  • Interface
    • GLUON
    • KERAS
  • Infrastructure
    • EC3 P3 & P3N
    • EC2 CS
    • FPGA

In re-invent 2019, AWS launched many new services and tools in that domain,

As Enterprise Search, Fraud Detection, and Codeguru in AI are launched in this event,

Check all the latest information here,