Unpacking Freshmen Aspirations and Expectations in Their Enrolled College Degree Programs: A Sentiment Analysis Approach

The decision to select a college degree program plays a fundamental role in shaping students' academic and professional futures. While much research has examined the factors affecting students' choices prior to enrollment, fewer studies have explored their perceptions and expectations after they have entered their chosen programs. This study seeks to bridge this research gap by investigating the visions and aspirations of freshmen using natural language processing techniques. The textual analysis involves text tokenization, word frequency counts, visual representation of data through word clouds, and sentiment classification. The findings suggest the demand for tailored academic support and curriculum development that align with the specific aspirations of students in different disciplines. Overall, this study contributes to the growing literature on student decision-making and expectations of degree programs, while demonstrating the value of sentiment analysis as a tool for understanding students' academic trajectories.

Authors

Institutions

Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/hnicem64917.2024.11258847
Primary Topic
Higher Education Research Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Unpacking Freshmen Aspirations and Expectations in Their Enrolled College Degree Programs: A Sentiment Analysis Approach

Ronel F. Ramos, Manuel B. Garcia, Alberto Ortíz, Arlene Mae C. Valderama et al.
Higher Education Research Studies
article

Unpacking Freshmen Aspirations and Expectations in Their Enrolled College Degree Programs: A Sentiment Analysis Approach

Ronel F. Ramos, Manuel B. Garcia, Alberto Ortíz, Arlene Mae C. Valderama, Ari Happonen, Rhoda D. Fabe
article en

Abstract

The decision to select a college degree program plays a fundamental role in shaping students' academic and professional futures. While much research has examined the factors affecting students' choices prior to enrollment, fewer studies have explored their perceptions and expectations after they have entered their chosen programs. This study seeks to bridge this research gap by investigating the visions and aspirations of freshmen using natural language processing techniques. The textual analysis involves text tokenization, word frequency counts, visual representation of data through word clouds, and sentiment classification. The findings suggest the demand for tailored academic support and curriculum development that align with the specific aspirations of students in different disciplines. Overall, this study contributes to the growing literature on student decision-making and expectations of degree programs, while demonstrating the value of sentiment analysis as a tool for understanding students' academic trajectories.

José Rizal University (PH), Far Eastern University (PH), Lappeenranta-Lahti University of Technology (FI)
Openalex Percentile: Top 54%
Higher Education Research Studies
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.