With the rise of the gig economy, online language tutoring platforms are becoming increasingly popular. These platforms provide temporary and flexible jobs for native speakers as tutors and allow language learners to have one-on-one speaking practices on demand, on which learners occasionally practice the language with different tutors. With such distributed tutorship, learners can hold flexible schedules and receive diverse feedback. However, learners face challenges in consistently tracking their learning progress because different tutors provide feedback from diverse standards and perspectives, and hardly refer to learners' previous experiences with other tutors. We present RLens, a visualization system for facilitating learners' learning progress reflection by grouping different tutors' feedback, tracking how each feedback type has been addressed across learning sessions, and visualizing the learning progress. We validate our design through a between-subjects study with 40 real-world learners. Results show that learners can successfully analyze their progress and common language issues under distributed tutorship with RLens, while most learners using the baseline interface had difficulty achieving reflection tasks. We further discuss design considerations of computer-aided systems for supporting learning under distributed tutorship.
翻译:随着就业经济的兴起,在线语言辅导平台越来越受欢迎。这些平台为本地语言使用者提供临时和灵活的工作,作为辅导员,使语言学习者能够按需求采用一对一的讲法,学生偶尔会与不同的辅导员一起使用这种语言。通过这种分散式辅导,学生可以保持灵活的时间安排,并获得不同的反馈。然而,由于不同的辅导员提供不同标准和观点的反馈,而且几乎不与其他辅导员一起参考学习经验,学习者在不断跟踪学习进展方面面临挑战。我们介绍了一个可视化系统RLens,通过将不同辅导员的反馈组合,跟踪每个反馈类型是如何解决的,以及将学习进展视觉化。我们通过与40名现实世界学习者进行的主题间研究来验证我们的设计。结果显示,学习者可以在与RLens一起分发的辅导课程中成功分析他们的进展和共同的语言问题,而大多数使用基线界面的学生则难以完成反思任务。我们进一步讨论了计算机辅助系统的设计考虑。