Productivity Enhancing Interruption-Information Management Chat Interface

Shreejana Prajapati; Koichi Yamada; Muneyuki Unehara; Izumi Suzuki

doi:10.20965/jaciii.2017.p0456

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JACIII Vol.21 No.3 pp. 456-466

doi: 10.20965/jaciii.2017.p0456

(2017)

Paper:

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Productivity Enhancing Interruption-Information Management Chat Interface

Shreejana Prajapati, Koichi Yamada, Muneyuki Unehara, and Izumi Suzuki

Graduate School of Engineering, Nagaoka University of Technology
1603-1 Kamitomioka-machi, Nagaoka, Niigata 940-2188, Japan

Received:

April 11, 2016

Accepted:

December 15, 2016

Online released:

May 19, 2017

Published:

May 20, 2017

Keywords:

interruption-information management, task fragmentation, productivity enhancement, users’ preferences, receiver oriented communication

Abstract

Spontaneous communication is an integral part of any workplace as well as everyday life. In workplaces that use computer or similar devices, most of the spontaneous conversations happen over email or chat. Frequent use of chat application or email disrupts a recipient’s workflow and leads to constant interruptions causing task fragmentation. In this paper, we present a receiver oriented Interruption-Information Management (IIM) chat which incorporates automated agents to prevent receivers from getting a plethora of messages. This framework manages both interruption and forthcoming information in the chat interface. It is a novel approach in the area of interruption management. It not only considers interruption management, but also manages the information based on the users’ behavior and preferences. It is a cooperative approach where both the message sender and the receiver work together to deliver messages during the receiver’s most favorable times. The receiver contributes to manage interruption whereas the sender contributes to manage information, together forming an interruption-information management mechanism to decide the least interruptible time for message delivery.

Cite this article as:

S. Prajapati, K. Yamada, M. Unehara, and I. Suzuki, “Productivity Enhancing Interruption-Information Management Chat Interface,” J. Adv. Comput. Intell. Intell. Inform., Vol.21 No.3, pp. 456-466, 2017.

Data files:

References

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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] R. K. Garrett and J. N. Danziger, “IM = Interruption Management? Instant Messaging and Disruption in the Workplace,” J. of Computer-Mediated Communication, Vol.13, pp. 23-42, 2008.

[2] [2] D. D. Salvucci and P. Bogunovich, “Multitasking and Monotasking: The Effects of Mental Workload on Deferred Task Interruptions,” Proc. of the SIGCHI Conf. on Human Factors in Computing Systems, pp. 85-88, 2010.

[3] [3] T. Shrot, A. Rosenfeld, J. Golbeck, and S. Kraus, “CRISP: An Interruption Management Algorithm based on Collaborative Filtering,” CHI, 2014.

[4] [4] E. Arroyo and T. Selker, “Attention and Intention Goals Can Mediate Disruption in Human-Computer Interaction,” Human-Computer Interaction INTERACT 2011, Vol.6947, pp. 454-470, 2011.

[5] [5] T. Tanaka, K. Aoki, N. A. Taatgen, and K. Fujita, “Resumption Lag at Interruptible Timing might not be short in Actual Environment,” Proc. of CHI 2014, pp. 1801-1806, 2014.

[6] [6] E. M. Altmann and J. G. Trafton, “Task Interruption: Resumption Lag and the Role of Cues,” Proc. 26th Annual Conf. of the Cognitive Science Society, 2004.

[7] [7] C. Parnin and S. Rugaber, “Resumption Strategies for Interrupted Programming Tasks,” Software Quality J., Vol.9, No.1, pp. 5-34, 2011.

[8] [8] E. B. Cutrell, M. Czerwinski, and E. Horvitz, “Effects of Instant Messaging Interruption on Computing Task,” Proc. Human Factors in Computing Systems, 2000.

[9] [9] S. Prajapati, K. Yamada, and M. Unehara, “An Approach to Obtain Proper Time for Interruption with Self Initiated Intermission,” J. Adv. Comput. Intell. Intell. Inform. (JACIII), Vol.19, No.1, pp. 109-117, 2015.

[10] [10] E. Shiu and A. Lenhart, “PEW Internet and American Life Project: How Americans Use Instant Messaging,” http://www.pewinternet.org, 2004.

[11] [11] H. Ajjan, Y. Niu, M. A. Zaffar, and S. J. Winter,“How Does The Use of Instant Messaging Impact Performance?,” Southeast Decision Sciences Institute 38th Annual Conf., 2008.

[12] [12] H. Li, A. Gupta, X. Luo, and M. Warkentin, “Exploring the Impact of Instant Messaging (IM) on Subjective Task Complexity and User Satisfaction,” European J. of Information Systems, Vol.20, pp. 139-155, 2011.

[13] [13] D. C. McFarlane and K. A. Latorella, “The Scope and Importance of Human Interruption in Human-Computer Interaction Design,” Human Computer Interaction, Vol.17, pp. 1-61, 2002.

[14] [14] T. Tanaka and K. Fujita, “Secretary Agent for Mediating Interaction Initiation,” Proc. of Human Agent Interaction, URL: http://hai-conference.net/ihai2013/proceedings/pdf/II-2-p5.pdf, 2013.

[15] [15] T. Tanaka, R. Abe, K. Aoki, and K. Fujita, “Interruptibility Estimation Based on Head Motion and PC Operation,” Int. J. of Human-Computer Interaction, Vol.31, pp. 167-179, 2015.

[16] [16] Y. Hyashi, “On Pedagogical Effects of Learner-Support Agents in Collaborative Interaction,” Intelligent Tutoring Systems, Vol.7315, pp. 22-32, 2012.

[17] [17] T. Bickmore, D. Mauer, F. Crespo, and T. Brown, “Negotiating Task Interruptions with Virtual Agents for Health Behavior Change,” Proc. of the 7th Int. Joint Conf. on Autonomous Agents and Multiagent Systems, pp. 1241-1244, 2008.

[18] [18] A. Rosenfeld, I. Zuckerman, E. Segal-Halevi, O. Drein, and S. Kraus, “Negochat: A Chat-Based Negotiation Agent with Bounded Rationality,” Auton Agent Multi-Agent System, doi:10.1007/s10458-01509281-9, 2015.

[19] [19] C. Smith, N. Crook, J. Boye, D. Charlton, S. Dobnik, D. Pizzi, M. Cavazza, S. Pulman, R. S. Camara, and M. Turunen, “Interaction Strategies for an Affective Conversational Agent,” Proc. of the 10th Int. Conf. on Intelligent Virtual Agents, pp. 301-314, 2010.

[20] [20] R. Sekten, “Aspiration Adaptation Theory,” J. or Mathematical Psychology, Vol.42, pp. 191-214, 1998.

[21] [21] R. Lina, S. Kraus, J. Wilkenfeldb, and J. Barryd, “Negotiating with bounded rational agents in environments with incomplete information using automated agents,” Artificial Intelligence, Vol.172, Iss. 6-7, pp. 823-851, 2008.

[22] [22] A. Rosenfeld, and S. Kraus, “Modeling Agents Based on Aspiration Adaptation Theory,” Autonomous Agents and Multi-agents Systems, Vol.24, Iss. 2, pp. 221-254, 2012.

[23] [23] M. G. Pimentel, H. Fuks, and C. J. P. D. Lucena, “Mediated Chat 2.0 Embedding Coordination into Chat Tools,” Proc. of 6th Int. Conf. on the Design of Cooperative System, pp. 99-103, 2004.

[24] [24] S. A. Grandhi and Q. Jones, “Conceptualizing Interpersonal Interruption Management: A Theoretical Framework and Research Program,” Proc. of 42nd Hawaii Int. Conf. on System Sciences, pp. 1-10, 2009.

[25] [25] J. E. Fischer, N. Yee, V. Bellotti, N. Good, S. Benford, and C. Greenhalgh, “Effects of Content and Time of Delivery on Receptivity to Mobile Interruptions,” Proc. of Human Computer Interaction with Mobile Devices and Services, pp. 103-112, 2010.

[26] [26] P. Saint-Andre, “Extensive Messaging and Presence Protocol (XMPP): Instant Messaging and Presence,” URL:http://xmpp.org/rfcs/rfc3921.html, 2004.

[27] [27] G. Mark, V. M. Gonzalez, and J. Harris, “No Task Left Behind? Examining the Nature of Fragmented Work,” Proc. of ACM CHI 2005, ACM, pp. 321-330, 2005.

[28] [28] URL: https://www.typing.com/

[29] [29] C. K. Foroughi, N. E. Werner, D. Barragn, and D. A. Boehm-Davis, “Interruptions Disrupt Reading Comprehension,” J. of Experimental Psychology: General, Vol.144, No.3, pp. 704-709, 2015.

[30] [30] T. Gillie and D. Broadbent, “What makes interruptions disruptive? A study of length, similarity, and complexity,” Psychological Research, Vol.50, Iss. 4, pp. 243-250, 1989.

[31] [31] H. Sanchez, R. Robbes, and V. M. Gonzalez, “An Empirical Study of Work Fragmentation in Software Evolution Tasks,” Proc. of Software Analysis, Evolution and Reengineering (SANER), pp. 251-260, 2015.