Identification and characterization of high-achieving student subgroups using two methodological approaches: The role of different achievement indicators and motivational-affective characteristics

How high-achieving student subgroups are identified is widely discussed. Studies use different domain-general and domain-specific achievement indicators and methodological approaches. Traditional research included cut-off scores, which have been criticized as arbitrary. Recently, latent profile analyses have been used more often. The present study compared these approaches regarding their overlap to investigate their interchangeability. Afterwards, high-achieving student subgroups were characterized by their motivational-affective characteristics. Data from N = 1563 high-achieving students were investigated. We used three achievement indicators (two mathematical competences and figural reasoning) for identification and four motivational-affective characteristics for characterization. The four largest high-achieving student subgroups were found through both approaches. However, the two methodological approaches could not be used interchangeably. Large heterogeneity in achievement indicators and motivational-affective characteristics existed across the subgroups. Top Performers have been identified as the target state for education, as they showed high scores on all achievement indicators and the most positive motivational-affective characteristics.