Artificial Intelligence in Education: Adoption and Usage Patterns Among Technical and Non-Technical Students

This paper discusses the adoption and usage patterns of AI tools among technical and non-technical students at Kathmandu Shiksha Campus (KSC). The data were drawn from 13 technical students studying in the Bachelor of Computer Applications (BCA) program and 10 non-technical students from Bachelor of Business Studies (BBS) and Bachelor of Education (B.Ed.) programs. A mixed-methods approach was adopted, combining questionnaires with interviews. This present paper investigates the frequency of AI tool usage, major purposes, the most commonly used tools, perceptions about the integration of AI into the curriculum, challenges in adoption, and perceived benefits. The results point the usage of AI tools among both technical and non-technical students, their opinion regarding frequency of usages, purpose of using, challenges faced or benefits from it. The study has also underlined that technical students usually use AI tools for coding, debugging, and fine-tuning their coding ability, while non-technical students use the tool basically in report writing, analysis, and presentation. This paper suggests curriculum developers and college management to make a policy or conduct frequent seminars regarding AI literacy and accessibility in various educational faculties.

Authors

Institutions

Publication Details

Journal
Shiksha Shastra Saurabh
Published
2024-12-31
DOI
https://doi.org/10.3126/sss.v24i1.75369
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial Intelligence in Education: Adoption and Usage Patterns Among Technical and Non-Technical Students

Yuba Raj Devkota
Shiksha Shastra Saurabh
Online Learning and Analytics
article

Artificial Intelligence in Education: Adoption and Usage Patterns Among Technical and Non-Technical Students

Yuba Raj Devkota
article en

Abstract

This paper discusses the adoption and usage patterns of AI tools among technical and non-technical students at Kathmandu Shiksha Campus (KSC). The data were drawn from 13 technical students studying in the Bachelor of Computer Applications (BCA) program and 10 non-technical students from Bachelor of Business Studies (BBS) and Bachelor of Education (B.Ed.) programs. A mixed-methods approach was adopted, combining questionnaires with interviews. This present paper investigates the frequency of AI tool usage, major purposes, the most commonly used tools, perceptions about the integration of AI into the curriculum, challenges in adoption, and perceived benefits. The results point the usage of AI tools among both technical and non-technical students, their opinion regarding frequency of usages, purpose of using, challenges faced or benefits from it. The study has also underlined that technical students usually use AI tools for coding, debugging, and fine-tuning their coding ability, while non-technical students use the tool basically in report writing, analysis, and presentation. This paper suggests curriculum developers and college management to make a policy or conduct frequent seminars regarding AI literacy and accessibility in various educational faculties.

Shiksha Shastra SaurabhVol. 24
Kathmandu University (NP)
Openalex Percentile: Top 71%
Online Learning and Analytics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Artificial Intelligence in Education: Adoption and Usage Patterns Among Technical and Non-Technical Students — Yuba Raj Devkota · Shiksha Shastra Saurabh (2024) | TGRS Research Map | TGRS