Training, assessing, and matching students in technology-mediated peer learning environments

Dissertation Abstract Article 1: One-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 were developed to test the viability of using online, scalable training to foster students' adoption of learner-centered teaching methods. To test the efficacy of these interventions, 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. Article 2: "Learning loss" and "learning recovery" have become commonplace terms to describe schooling needs in a COVID-impacted world. It is unsurprising that tutoring is emerging as a key stopgap measure to accelerate recovery. Historically, tutoring has been the most powerful learning intervention, but it is costly to administer and challenging to integrate in classrooms. Peer tutoring is a relatively untapped solution, due to barriers around time management, organization, matching, and assessment. Following trials of an interactive training platform called PeerTeach that rapidly improved middle schoolers' peer tutoring ability, our research team established a research practice partnership to design self-sustaining classrooms with peer tutoring as a central focus. This chapter reports on our five-month design-based research study with an Indian middle school where we found convincing evidence for the viability of tech-mediated peer tutoring as an antidote to key challenges of Group Learning. Through this study, we gained valuable insights into the critical roles technology can play in training effective peer helpers, optimally matching tutoring pairs, overcoming pitfalls that often preclude Group Learning, and promoting the motivational elements which students most value. Article 3: In fields like computer science or mechanical engineering, academic findings consistently influence real-world products and activity. Research on the science of learning, on the other hand, has a relatively small influence on classroom practice. This phenomenon exists despite an enormous workforce of potential research consumers—the US has over 3 million teachers and about 100,000 principals—and several large-scale dissemination initiatives, including the What Works Clearinghouse. This article explores the challenges and obstacles precluding the translation of learning science research to practice. It discusses the past few decades of methodological evolution focused on engendering relevant projects by conducting ecologically valid research inside classrooms, centering teacher voice in the research process, and deviating from fixed-intervention study designs in favor of more iterative, increasingly effective models. The chapter culminates with a set of recommendations aimed at supporting learning scientists in executing research that produces solutions that are viable and efficacious in classrooms. The highlighted methods are concretized through illustrative examples drawn from the six-year PeerTeach research project. They include need-finding in the wild to validate prevalent issues, low-fidelity prototyping to quickly reach viable designs, informant recruitment for constant reality checks, and representative sampling to inform dissemination

Keywords: Education.
Advisor: Goldman Shelley V.
Pea Roy D.
Langer-Osuna Jennifer