menu
{ "item_title" : "Assessment Framework for SEL Competencies", "item_author" : [" S. Sharmila", "A. Kanagaraj "], "item_description" : "Social and Emotional Learning (SEL) is vital for students' academic success and overall well-being, yet assessing these competencies remains a challenge due to their subjective and non-cognitive nature. Traditional methods such as surveys and teacher observations often lack accuracy and consistency. To address this, a machine learning-based assessment framework is proposed, integrating diverse data sources such as student behavior, participation, and performance. By identifying patterns and classifying levels of SEL skills, machine learning models reduce human bias and enhance reliability. This data-driven approach not only ensures objective measurement but also provides predictive insights into students' SEL development. Educators can utilize these insights to design targeted interventions and personalized support, ultimately making the assessment of SEL competencies more accurate, scalable, and impactful.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/6/20/847/286/6208472865_b.jpg", "price_data" : { "retail_price" : "52.00", "online_price" : "52.00", "our_price" : "52.00", "club_price" : "52.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Assessment Framework for SEL Competencies|S. Sharmila

Assessment Framework for SEL Competencies

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

Social and Emotional Learning (SEL) is vital for students' academic success and overall well-being, yet assessing these competencies remains a challenge due to their subjective and non-cognitive nature. Traditional methods such as surveys and teacher observations often lack accuracy and consistency. To address this, a machine learning-based assessment framework is proposed, integrating diverse data sources such as student behavior, participation, and performance. By identifying patterns and classifying levels of SEL skills, machine learning models reduce human bias and enhance reliability. This data-driven approach not only ensures objective measurement but also provides predictive insights into students' SEL development. Educators can utilize these insights to design targeted interventions and personalized support, ultimately making the assessment of SEL competencies more accurate, scalable, and impactful.

This item is Non-Returnable

Details

  • ISBN-13: 9786208472863
  • ISBN-10: 6208472865
  • Publisher: LAP Lambert Academic Publishing
  • Publish Date: August 2025
  • Dimensions: 9 x 6 x 0.14 inches
  • Shipping Weight: 0.21 pounds
  • Page Count: 60

Related Categories

You May Also Like...

    1

BAM Customer Reviews