TutorUp: What If Your Students Were Simulated? Training Tutors to Address Engagement Challenges in Online Learning
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866913703222312960 |
|---|---|
| author | Pan, Sitong Schmucker, Robin Bueno, Bernardo Garcia Bulle Llanes, Salome Aguilar Alarcón, Fernanda Albo Zhu, Hangxiao Teo, Adam Xia, Meng |
| author_facet | Pan, Sitong Schmucker, Robin Bueno, Bernardo Garcia Bulle Llanes, Salome Aguilar Alarcón, Fernanda Albo Zhu, Hangxiao Teo, Adam Xia, Meng |
| contents | With the rise of online learning, many novice tutors lack experience engaging students remotely. We introduce TutorUp, a Large Language Model (LLM)-based system that enables novice tutors to practice engagement strategies with simulated students through scenario-based training. Based on a formative study involving two surveys (N1=86, N2=102) on student engagement challenges, we summarize scenarios that mimic real teaching situations. To enhance immersion and realism, we employ a prompting strategy that simulates dynamic online learning dialogues. TutorUp provides immediate and asynchronous feedback by referencing tutor-students online session dialogues and evidence-based teaching strategies from learning science literature. In a within-subject evaluation (N=16), participants rated TutorUp significantly higher than a baseline system without simulation capabilities regarding effectiveness and usability. Our findings suggest that TutorUp provides novice tutors with more effective training to learn and apply teaching strategies to address online student engagement challenges. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_16178 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | TutorUp: What If Your Students Were Simulated? Training Tutors to Address Engagement Challenges in Online Learning Pan, Sitong Schmucker, Robin Bueno, Bernardo Garcia Bulle Llanes, Salome Aguilar Alarcón, Fernanda Albo Zhu, Hangxiao Teo, Adam Xia, Meng Human-Computer Interaction With the rise of online learning, many novice tutors lack experience engaging students remotely. We introduce TutorUp, a Large Language Model (LLM)-based system that enables novice tutors to practice engagement strategies with simulated students through scenario-based training. Based on a formative study involving two surveys (N1=86, N2=102) on student engagement challenges, we summarize scenarios that mimic real teaching situations. To enhance immersion and realism, we employ a prompting strategy that simulates dynamic online learning dialogues. TutorUp provides immediate and asynchronous feedback by referencing tutor-students online session dialogues and evidence-based teaching strategies from learning science literature. In a within-subject evaluation (N=16), participants rated TutorUp significantly higher than a baseline system without simulation capabilities regarding effectiveness and usability. Our findings suggest that TutorUp provides novice tutors with more effective training to learn and apply teaching strategies to address online student engagement challenges. |
| title | TutorUp: What If Your Students Were Simulated? Training Tutors to Address Engagement Challenges in Online Learning |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2502.16178 |