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Privacy and Security in Mixed Reality Learning Environments by Input and User/Bot Interaction Protection

Published: 14 March 2022 Publication History

Abstract

Mixed reality is known as an advanced technology that provides a new approach for learning environments. Such environments allow learners to interact with both virtual and real worlds and bringing in potential enhancements to the learning process at the same time. For example, chatbots can facilitate the learning process. However, security and privacy settings for interacting with chatbots in such mixed reality environments are complex. In this paper, we introduce a mixed reality virtual assistant that is integrated into the collaborative environment of our existing application VIAProMa. This embodied chatbot allows lecturers and students to participate in mixed reality and online classrooms in real-time. The participants can interact with each other via VIAProMa’s avatar representations and can communicate with the chatbot that is represented by the mixed reality bot. The bot is realized by connecting a Slack chatbot with the mixed reality learning environment. It is displayed as an intuitive 3D model and is able to communicate with the users in spoken language. In this environment, privacy and security settings are conducted to protect the user input and user interaction with the bot. The evaluation results show that the system works stably with good performance. All the visualizations and features are well designed and were understood by the users. Users preferred the speech interface with the bot over a textual interface. The research has a strong impact on the design of security and privacy features for mixed reality environments in general.

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Cited By

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  • (2024)TARPS: A Toolbox for Enhancing Privacy and Security for Collaborative ARProceedings of the ACM on Human-Computer Interaction10.1145/36602518:EICS(1-22)Online publication date: 17-Jun-2024
  • (2023)A Modularity Approach in Design Science Research for Mixed Reality Learning Artifacts2023 IEEE International Conference on Advanced Learning Technologies (ICALT)10.1109/ICALT58122.2023.00080(252-254)Online publication date: Jul-2023
  • (2023)A Systematic Literature Review of Mixed Reality Learning ApproachesExtended Reality10.1007/978-3-031-43404-4_2(15-34)Online publication date: 6-Sep-2023

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cover image ACM Other conferences
APIT '22: Proceedings of the 2022 4th Asia Pacific Information Technology Conference
January 2022
239 pages
ISBN:9781450395571
DOI:10.1145/3512353
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 14 March 2022

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Author Tags

  1. collaboration
  2. learning environment
  3. mixed reality
  4. social bots

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APIT 2022
APIT 2022: 2022 4th Asia Pacific Information Technology Conference
January 14 - 16, 2022
Virtual Event, Thailand

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Cited By

View all
  • (2024)TARPS: A Toolbox for Enhancing Privacy and Security for Collaborative ARProceedings of the ACM on Human-Computer Interaction10.1145/36602518:EICS(1-22)Online publication date: 17-Jun-2024
  • (2023)A Modularity Approach in Design Science Research for Mixed Reality Learning Artifacts2023 IEEE International Conference on Advanced Learning Technologies (ICALT)10.1109/ICALT58122.2023.00080(252-254)Online publication date: Jul-2023
  • (2023)A Systematic Literature Review of Mixed Reality Learning ApproachesExtended Reality10.1007/978-3-031-43404-4_2(15-34)Online publication date: 6-Sep-2023

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