Abstract
AbstractOne-on-one tutoring is the most effective teaching arrangement. Most schools and families, however, cannot afford to provide each child with a tutor. Peer tutoring in classrooms, a more feasible and scalable learning arrangement, increases learning for both tutors and tutees, but peer tutors’ efficacy is often limited by their didactic and disempowering approaches. Two interventions with distinctly different designs were developed to test the viability of online, scalable training to foster students’ adoption of learner-centered teaching methods. To compare the efficacy of these intervention approaches, two randomized control experiments were conducted with 198 middle school math students. Both trainings increased the frequency that tutors employed learner-centered strategies, evident in clickstream data from virtual scenarios and in tutee reflections following real-life tutoring. Shifts in tutoring behaviors significantly boosted tutee learning at every level of tutor content mastery. This suggests that training students to use learner-centered tutoring strategies can greatly improve the efficacy for peer tutoring in classrooms, and that technological solutions can scale this type of training.
Publisher
Springer International Publishing
Reference38 articles.
1. Allor, J., & McCathren, R. (2004). The efficacy of an early literacy tutoring program implemented by college students. Learning Disabilities Research & Practice, 19(2), 116–129.
2. Ander, R., Guryan, J., & Ludwig, J. (2016). Improving academic outcomes for disadvantaged students: Scaling up individualized tutorials. The Hamilton Project–Brookings.
3. Aronson, J., Fried, C. B., & Good, C. (2002). Reducing the effects of stereotype threat on African American college students by shaping theories of intelligence. Journal of Experimental Social Psychology, 38(2), 113–125.
4. Bamiro, A. O. (2015). Effects of guided discovery and think-pair-share strategies on secondary school students’ achievement in chemistry. SAGE Open, 5(1), 1–7.
5. Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48.