Machine Learning based Learning Disability Detection using LMS

Modak, Masooda; Warade, Omkar; Saiprasad, G.; Shekhar, Shweta

doi:10.1109/iccca49541.2020.9250761

Cited by 10 publications

(4 citation statements)

References 3 publications

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“…Learning based Learning Disability Detection using LMS: [2] This research focuses on an E-learning system built with Moodle, an open-source Learning Management System (LMS) that enables tutors and students to work together more e ciently. This method recognizes couple of student pro les: students with and without Learning Disability (LD) by using keen courses constructed base on the topic of numerous features of an LD student (non-LD).…”

Section: Machinementioning

confidence: 99%

“…Learning di culties can be caused by a variety of factors. [1,2] A learning handicap affects one's capacity to grasp knowledge. It's tough to comprehend the nature of these disabilities.…”

Section: Introductionmentioning

confidence: 99%

“…[3] 1.1 Electroencephalography (EEG) is one of the newer approaches being investigated for identifying speci c brain activation patterns in learning disabilities. [1][2][3][4][5], Electroencephalography detects electrical activity present in our brain with the help of metal caps (electrodes) that are placed on our scalp by using 10-20 system as shown in Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

“…[1] It has nothing to do with the IQ of a child. [2] The children, however, can be aided in discovering their potential and determining future career decisions with the correct identi cation and assistance. Machine learning is now used in a variety of businesses to anticipate future events.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Development of EEG based Identification of Learning Disability using Machine Learning Algorithms

Ahire¹,

Awale²,

Wagh³

2022

Preprint

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A learning disability (LDs) is a comprehensive word used for various learning problems. Children with learning disabilities are not sluggish nor intelligently retarded. Learning disability is a neurological condition that is characterized by a vague understanding of words and poor reading skills. It affects many school-aged children, with fellows being more likely to be involved, placing them at risk for deprived academic concerts and low self-esteem for the rest of their lives. Our research entails developing a machine learning model to analyze EEG signals from people with learning difficulties and provide results in minutes with the highest level of accuracy. In this research, we have used Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Linear Discriminant Analysis (LDA) methods were used for component analyze of the dataset. For classification purposes we have used Support Vector Machines (SVM), Random Forest (RF), Logistic Regression (LR), K-nearest neighbours (K-NN), Decision Trees and XGBoost, etc different types of algorithms. The goal is to determine which data pre-processing approaches and machine learning algorithms are the most effective in detecting learning disabilities.

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Section: Machinementioning

confidence: 99%

“…Learning di culties can be caused by a variety of factors. [1,2] A learning handicap affects one's capacity to grasp knowledge. It's tough to comprehend the nature of these disabilities.…”

Section: Introductionmentioning

confidence: 99%