ABSTRACT This study examined whether MBTI personality types and CliftonStrengths themes could predict academic major indecision in 177 undergraduates using random forest classification and K‐means clustering. The model achieved strong predictive performance (accuracy = 88.9%, macro F1 = 0.88), with lower ranked strengths (Strengths 4 and 5) emerging as the most influential predictors. Clustering identified three distinct strength profiles; students in the execution‐dominant cluster were significantly more likely to have declared a major, whereas influence‐oriented or diffuse profiles were associated with indecision. These findings support the use of strengths‐informed modeling for the early identification of students who may benefit from targeted academic advising.
Park et al. (Fri,) studied this question.