Elevating Academic Advising: Natural Language Processing of Student Reviews

Abstract

Academic advising is often pivotal in shaping students’ educational experiences and choices. This study leverages natural language processing to quantitatively evaluate reviews of academic advisors, aiming to provide actionable insights on key feedback phrases and demographic factors for enhancing advising services. This analysis encompassed a comprehensive evaluation of 1151 reviews of undergraduate students for academic advisors, which were collected within a European University alliance consisting of five universities, offering a diverse pool of feedback from a wide range of academic interactions. Employing sentiment analysis powered by artificial intelligence, we computed compound sentiment scores for each academic advisor’s reviews. Subsequently, statistical analyses were conducted to provide insights into how demographic factors may or may not influence students’ sentiment and evaluations of academic advisory services. The results indicated that advisor’s gender had no substantial influence on the sentiment of the reviews. On the contrary, the academic advisors’ age showed a notable impact, with younger advisors surprisingly receiving more favorable evaluations. Word frequency analyses, both for positive and negative expressions, were also performed to contextualize the language used in describing academic advisors. The prevalent word combinations in reviews of highly rated academic advisors emphasized attributes like empathy, approachability, and effectiveness in guiding students towards achieving their academic goals. Conversely, advisors with less favorable reviews were often perceived as inadequate in addressing students’ concerns related to their academic journey, revealing persistent challenges in the student–advisor interaction that impacted their evaluation. This analysis of academic advisor reviews contributes to the body of literature by highlighting the significance of managing student expectations and enhancing advisor skills and qualities to foster positive interactions and academic success.

Keywords

• natural language processing
• academic advising
• student satisfaction
• sentiment analysis