Using Text Analytics on Reflective Journaling to Identify Cultural Capitals for STEM Students

Nayak, Karuna; Krishna, Shailesh; Tran, Khanh Quoc; Harris, Marissa; Barrera, Ana María Bermejo; Coble, K.; Kulkarni, Anagha

doi:10.1109/icmla51294.2020.00130

Cited by 3 publications

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Traditional methods like bag-of-words and n-grams laid the groundwork, but new advances in deep learning have gotten a lot of attention. Particularly, BERT has become a key milestone because it uses transformer design to make bidirectional context modeling and semantic understanding possible [7]. Using BERT's pre-trained representations, a number of studies have achieved success in tasks like figuring out how people feel about something, classifying text, and recognizing entities.…”

Section: Related Workmentioning

confidence: 99%

Short Text Analytics based on BERT by using Multivariate Filter Methods for Feature Selection

Qais,

2023

Preprint

View full text Add to dashboard Cite

This article present a short text analytics method that uses BERT (Bidirectional Encoder Representations from Transformers) and multivariate filter methods for selecting features. In a world where there is a lot of short written data from many different fields, it is hard to find meaningful insights. This makes it important to come up with new methods that can take into account the context and pick out the most important parts for analysis. This study goes into this area and looks at how BERT's understanding of context and the ability of multiple filters to make distinctions can work together. Through a series of carefully planned experiments, the proposed model shows that a hybrid method improves the accuracy, readability, and speed of short text analysis. The results show that predictive metrics have gotten a lot better, which proves that proposed model way will make a big difference. This work not only helps move the field of natural language processing forward, but it also has real-world uses in areas like sentiment analysis, social media tracking, and understanding customer feedback. As digital communication continues to change, the method is set up to find nuanced insights in the short textual data that is dense with information.

show abstract

Section: Related Workmentioning

confidence: 99%

Short Text Analytics based on BERT by using Multivariate Filter Methods for Feature Selection

Qais,

2023

Preprint

View full text Add to dashboard Cite

show abstract

Emotion Detection from Real-Life Situations Based on Journal Entries Using Machine Learning and Deep Learning Techniques

Oyebode,

Ogubuike,

Daniel

et al. 2024

Lecture Notes in Networks and Systems

View full text Add to dashboard Cite

Artificial Intelligence and New Technologies in Inclusive Education for Minority Students: A Systematic Review

2022

View full text Add to dashboard Cite

Artificial intelligence (AI) and new technologies are having a pervasive impact on modern societies and communities. Given the potential of these new technologies to transform the way things are done, it is important to understand how they can be used to support inclusive education, particularly regarding minority students. This systematic review analyzes the advantages and challenges of using AI and new technologies in different sociocultural contexts, and their impact on minority students. In terms of advantages, this review found that AI and new technologies (a) improved student performance, (b) encouraged student interest in STEM/STEAM, (c) promoted student engagement, and (d) showed other advantages. This review also identifies the main challenges associated with the use of AI and new technologies for inclusive education: (a) technological challenges, (b) pedagogical challenges, (c) dataset limitations, (d) low satisfaction using technology, and (e) cultural differences. This review proposes some solutions to these challenges at the pedagogical, technological, and sociocultural levels, and also explores important aspects of inclusive education that address the students’ sociocultural diversity. The findings and implications will aid teachers, practitioners, and policymakers in making decisions on the effective use of AI and new technologies to support sociocultural inclusiveness in education.

show abstract

Using Text Analytics on Reflective Journaling to Identify Cultural Capitals for STEM Students

Cited by 3 publications

References 11 publications

Short Text Analytics based on BERT by using Multivariate Filter Methods for Feature Selection

Short Text Analytics based on BERT by using Multivariate Filter Methods for Feature Selection

Emotion Detection from Real-Life Situations Based on Journal Entries Using Machine Learning and Deep Learning Techniques

Artificial Intelligence and New Technologies in Inclusive Education for Minority Students: A Systematic Review

Contact Info

Product

Resources

About