## 5 Conclusions and Future Work  
To conclude, this study provided meaningful insight into domain concepts' familiarity ratings. Understanding these ratings is valuable in three regards. First, we have underlined the importance of focusing on domain concepts' familiarity ratings to pinpoint helpful linguistic predictors for assessing students' cognitive engagement during language learning or online discussions. For instance, a positive relationship has manifested between concept familiarity and high-quality argumentation, especially in students' epistemic and social interactions [62]. Second, our work opens doors to applying tree-based regression models to expand psycholinguistic resources. Administering and scoring experimental tasks in linguistics are often prohibitively expensive in cognitive and educational studies unless substantial psycholinguistic resources are available [8; 63]. If regression models can reliably approximate human raters, then psycholinguistic properties can be modulated under various educational settings. Word familiarity has been widely acknowledged as a significant predictor of word difficulty in word learning [64]: simpler and more common words promote online discussion and participation [65]. Finally, our SHAP analysis fortified the explanatory power when predicting familiarity with domain concepts. It is essential to identify factors that determine these concepts' familiarity ratings in order to holistically grasp lexical features' importance. Such recognition can facilitate assessments of students' learning engagement in educational settings, such as during language instruction and online discussions.  
Two limitations of this research stand to be addressed. First, a pair of undergraduate science majors constructed our data set. Our findings' generalizability is therefore tempered. It is important to take caution when generalizing the findings of this study to a larger population. Students studying other disciplines, such as art, should be recruited to obtain domain concepts' familiarity ratings in the future. We posited that optimizing data collection would enhance extrapolation methods' performance. Second, our study was carried out in a monolingual context. A language-independent approach to estimating domain concepts' psycholinguistic property values is still important [18]: this method can foster the productive use of psycholinguistics data in multilingual environments [13]. Our subsequent work will seek to further refine familiarity extrapolation methods, namely by expanding our data set with more diverse familiarity ratings for domain concepts. Additional research should also be conducted on the relationship between students' engagement in online discussions and their familiarity with domain concepts. Finally, scholars should investigate which lexical features of domain concepts shape students' engagement.  
Conceptualization, J.H. and Y.Z.; Data curation, X.W. and L.L.; Formal analysis, L.L. and Y.Z.; Funding acquisition, J.H.; Investigation, J.W., C.H. and M.L.; Methodology, J.H.; Project administration, Y.Z.; Resources, J.W., C.H. and M.L.; Software, J.H.; Supervision, J.H.; Validation, X.W. and Y.Z.; Visualization, J.H.; Writing--original draft, J.H. and X.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China: 62207015, and the Humanities and Social Sciences Youth Foundation of the Chinese Ministry of Education: 22 YJC880021.  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
The authors declare no conflict of interest.