ABSTRACT
Tree-thinking ability is essential in the learning of biological evolution. Spatial ability as a potential factor which might impact students’ tree-thinking ability remains unknown. To explore the influence of spatial ability and spatial-related interventions on students’ tree-thinking ability, 312 undergraduate students participated in this study. Students’ spatial ability was evaluated using the Mental Rotation Test (MRT). A pre-test-post-test design was adopted to assess students’ tree-thinking ability by using the Model of the Use of Evolutionary Trees (MUET) survey. Multiple linear regression analyses were conducted to explore the factors that influenced students’ tree-thinking ability. Pearson product-moment correlation coefficients were calculated when positive or negative predictors of student’ tree-thinking ability were identified. Results shown that students’ MRT scores and previous tree-learning experience were the sole factors that positively predicted students’ pre-MUET survey scores, explaining 2.5% and 4.1% of the observed variance, respectively. Pre-MUET survey scores and the type of tree-thinking-related instructional intervention were found to be the only unique predictors of students’ post-MUET survey scores, explaining 22.2% and 6.5% of the observed variance, respectively. Results suggest that the tree-thinking-related instructional intervention has the potential to modulate the relationship between individuals’ spatial ability and tree-thinking ability.
Acknowledgments
This work was supported by the National Plan of Educational Sciences in China: [Grant Number BHA220123]. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Plan of Educational Sciences in China.
Author contributions
All authors contributed to the study conception and design as well as the data analysis. Material preparation and data collection were performed by Yi Kong. The first draft of the manuscript was written by Yi Kong. Jeffrey T. Olimpo commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Disclosure statement
No potential conflict of interest was reported by the author(s).