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Mudpoint: Evaluating Instructor Perception on a Continuous and Non-specific Feedback System

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12205))

Abstract

In this paper, we introduce a platform called Mudpoint. It is an educational system that: a) allows students to provide real-time, continuous and anonymous feedback on their comprehension levels using a mobile application and b) enables instructors to visualize an aggregated form of student comprehension feedback on a web dashboard in real-time. A number of studies show that real-time feedback on instructor methodologies has several benefits including improvement in teaching [1] and better communication between instructors and students [2]. Also, student response systems (SRS) in classroom teaching have been explored in several studies previously [3,4,5], including the effects of instantaneous and anonymous feedback. Therefore in this study, we explore the instructor’s perception of receiving student feedback that, in addition to being instantaneous and anonymous, is also continuous and non-specific. Through interviews with instructors, we found that the system resulted in significantly more feedback on student confidence in the material, improved the pace of the class, and encouraged more responsible learning behaviour for students. This work shows that, from the instructor’s perception, continuous and non-specific feedback systems can improve the classroom experience for both instructors and students.

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Correspondence to Jamshidbek Mirzakhalov .

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Mirzakhalov, J., Babu, A., Andujar, M. (2020). Mudpoint: Evaluating Instructor Perception on a Continuous and Non-specific Feedback System. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. Designing, Developing and Deploying Learning Experiences. HCII 2020. Lecture Notes in Computer Science(), vol 12205. Springer, Cham. https://doi.org/10.1007/978-3-030-50513-4_20

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  • DOI: https://doi.org/10.1007/978-3-030-50513-4_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-50512-7

  • Online ISBN: 978-3-030-50513-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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