# Elevating Academic Advising: Natural Language Processing of Student Reviews
## 5 Discussion  
The primary objective of this study was to pinpoint the academic advisor demographics and critical feedback expressions that exhibit the strongest connection with favorable or unfavorable responses from students. An existing similar analysis of 396 undergraduate student reviews revealed that advisor characteristics, including accessibility, availability, encouragement, motivation, and care, significantly influenced the intensity of student ratings [13]. Yet, as far as our research indicates, this is the first study to employ natural language processing to acquire insights into the representation of academic advisors in student reviews, granting us a deeper understanding of the nuanced perceptions expressed in these evaluations. This approach not only facilitated a comprehensive analysis but also unveiled intricate patterns and sentiments that might have remained obscured without the utilization of this AI processing, enhancing the precision and depth of our findings. Furthermore, to our knowledge, no prior study has examined the correlation between the age of academic advisors and student ratings of their performance. In a related study, [PERSON] et al. conducted a demographic analysis of 3629 university professors and discovered that those with fewer cumulative years of academic experience obtained significantly higher ratings in comparison to their more senior counterparts [14]. In a similar vein, [PERSON] et al., who examined 18,946 records, reported that older tenure-track faculty members tended to receive lower overall ratings [15]. [PERSON] et al. also noted that professors with fewer years of experience garnered more positive reviews [16]. Our analysis, which is distinct from existing studies focused on professors, discovered a similar trend within academic advising, indicating that younger advisors tended to garner higher ratings and receive more positively framed student reviews. This parallel trend echoes findings observed in the broader landscape of professorial evaluations, highlighting a consistent correlation between advisor age and favorable student perceptions. Moreover, [PERSON] et al. observed that the gender of academic advisors had no substantial effect on the ratings of academic advisors [17]. Similarly, in a study based on data from a survey of U.S. graduate students in five distinct disciplines within the natural and social sciences, gender was not consistently identified as a significant factor influencing the positivity of reviews [18]. Our research is consistent with prior studies, as we found that the gender of academic advisors had no noticeable influence on their Likert scores or the \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Word** & **Odds Ratio (OR)** & **95\% Confidence Interval (CI)** & _p-Value_ \\ \hline Academic goals & 3.11 & 1.89–5.20 & \textless{}0.01 \\ Accessible & 2.51 & 1.28–4.20 & \textless{}0.01 \\ Availability & 0.47 & 0.21–0.97 & 0.04 \\ Confident & 1.41 & 0.81–3.42 & 0.02 \\ Digital resources & 0.71 & 0.42–2.17 & 0.64 \\ Empathy & 6.21 & 2.81–12.42 & \textless{}0.01 \\ Friendly & 4.36 & 1.25–11.06 & 0.02 \\ Graduation & 3.02 & 1.56–5.12 & \textless{}0.01 \\ Postgraduate & 3.25 & 2.10–5.41 & \textless{}0.01 \\ Clear instructions & 0.31 & 0.24–0.44 & \textless{}0.01 \\ Virtual meetings & 0.42 & 0.08–3.15 & 0.53 \\ Well-informed & 1.54 & 1.06–2.33 & 0.04 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Multiple logistic regression analysis on academically relevant keywords. textual reviews. This implies that both male and female academic advisors are evaluated similarly by students. In our examination, we discovered that there were no notable statistical variations observed in Likert ratings and sentiment analysis scores among the five universities of the INVEST alliance. It is essential to highlight that the INVEST European University provides a set of digital resources and tools including a comprehensive academic advising system powered by AI, aiming to support both academic advisors and students in their decision-making processes [19].