Enhancing Synchronous Collaborative Learning with AI-Supported Audience Response Systems: The EchoQuiz Approach

Benedikt Brünner; Martin Ebner

doi:10.1007/978-3-032-18885-4_2

Enhancing Synchronous Collaborative Learning with AI-Supported Audience Response Systems: The EchoQuiz Approach

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

This paper introduces echoQuiz, an open-source, AI-supported Audience Response System (ARS) designed for synchronous university (online) teaching with open-ended questions. The system follows a two-phase interaction model: In the quiz phase, students/learners submit their responses and then rate their peers’ responses. In the echo phase, the instructor highlights one response for group reflection, with all responses remaining anonymous. To ease the interpretation of open responses, the lecturer can be assisted by an AI system during live sessions. Developed with an Educational Design Research (EDR) approach, echoQuiz was piloted in synchronous university courses with a total of 62 participants. Survey results show high motivation and moderate perceived learning gains. The findings suggest that free-text interaction, supported by AI, can enhance engagement and adaptability in digital classrooms.

Original language	English
Title of host publication	Innovation via Collaborative Learning in Engineering Education
Editors	Michael E. Auer, Peter Toth
Place of Publication	Cham
Publisher	Springer Nature Switzerland AG
Pages	14-26
Number of pages	13
ISBN (Print)	978-3-032-18885-4
DOIs	https://doi.org/10.1007/978-3-032-18885-4_2
Publication status	Published - 1 Apr 2026
Event	Innovation via Collaborative Learning in Engineering Education, ICL 2025 - Budapest, Hungary Duration: 1 Oct 2025 → 3 Oct 2025

Publication series

Name	Lecture Notes in Networks and Systems
Volume	LNNS 1847

Conference

Conference	Innovation via Collaborative Learning in Engineering Education, ICL 2025
Country/Territory	Hungary
City	Budapest
Period	1/10/25 → 3/10/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 4 Quality Education

Fields of Expertise

Information, Communication & Computing

Access to Document

10.1007/978-3-032-18885-4_2

Cite this

Brünner, B., & Ebner, M. (2026). Enhancing Synchronous Collaborative Learning with AI-Supported Audience Response Systems: The EchoQuiz Approach. In M. E. Auer, & P. Toth (Eds.), Innovation via Collaborative Learning in Engineering Education (pp. 14-26). (Lecture Notes in Networks and Systems; Vol. LNNS 1847). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-032-18885-4_2

Enhancing Synchronous Collaborative Learning with AI-Supported Audience Response Systems: The EchoQuiz Approach. / Brünner, Benedikt ; Ebner, Martin.
Innovation via Collaborative Learning in Engineering Education. ed. / Michael E. Auer; Peter Toth. Cham: Springer Nature Switzerland AG, 2026. p. 14-26 (Lecture Notes in Networks and Systems; Vol. LNNS 1847).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Brünner, B & Ebner, M 2026, Enhancing Synchronous Collaborative Learning with AI-Supported Audience Response Systems: The EchoQuiz Approach. in ME Auer & P Toth (eds), Innovation via Collaborative Learning in Engineering Education. Lecture Notes in Networks and Systems, vol. LNNS 1847, Springer Nature Switzerland AG, Cham, pp. 14-26, Innovation via Collaborative Learning in Engineering Education, ICL 2025, Budapest, Hungary, 1/10/25. https://doi.org/10.1007/978-3-032-18885-4_2

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