Supporting computer science student reading through multimodal engagement interfaces

Pike, Matthew, Shen, Kejia and Towey, Dave (2020) Supporting computer science student reading through multimodal engagement interfaces. In: 2019 IEEE International Conference on Engineering, Technology and Education (TALE), 10-13 Dec. 2019, Yogyakarta, Indonesia, Indonesia.

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While many computer science (CS) curricula are increasingly addressing a demand for more communicative and ethical graduates, reports of CS student difficulties with nontechnical subjects, such as Professional Ethics, persist. These seem compounded for students learning through a second or foreign language. This paper explores the impact that multimodal engagement interfaces can have on content comprehension. 30 participants of varying English language ability were asked to engage with four unrelated articles under four different conditions: baseline reading (C1); guided reading (sentence-by-sentence) (C2); audio/listening only (C3); and concurrent (multi-modal) presentation of C2 & C3 (C4). After each engagement, participants were asked to complete a comprehension test on the material that they had just encountered. A subjective survey evaluating the “comfort” and “engagement quality” of each interface was also completed after each interaction. Our results paint a complex picture with the guided reading interface (C2) producing both the best performance, and the poorest subjective evaluation from participants. This result aligns with existing findings identified in the field of reading education. The results highlight how varying language levels in participants impact subjective and performance metrics, suggesting how future interfaces may better support readers, according to their language ability or intended outcomes of reading.

Item Type: Conference or Workshop Item (Paper)
Keywords: article comprehension; multi-modal interfaces; Simultaneous listening and reading; listening comprehension; L2 readers
Schools/Departments: University of Nottingham Ningbo China > Faculty of Science and Engineering > School of Computer Science
Identification Number:
Depositing User: Wu, Cocoa
Date Deposited: 21 Dec 2020 05:48
Last Modified: 21 Dec 2020 05:48

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