%0 Conference Paper %1 weingart2019chatbot %A Weingart, Pablo %A Winkler, Rainer %A Söllner, Matthias %B 14th International Conference on Wirtschaftsinformatik (WI) %D 2019 %K itegpub pub_msö pub_wise-kassel %T A chatbot dialogue model: Understanding human-chatbot collaboration in a complex task environment %X The rise of massive open online courses (MOOC) provides means to economize and scale education in response to higher budget restrictions 1 and raises the number of possible enrolled students by an unprecedented amount, compared to traditional higher education courses 2. However, a disadvantage of MOOCs is the lack of individual support which can’t be addressed economically to a massive audience, often resulting in a less than optimal learning outcome 3. Chatbots have the potential to alleviate this issue as a supporting tool to help the user learn how to solve a complex set of problems 4. In 2017, the use of smart assistants in U.S. households like Amazon Echo or Google Home has increased by 128.9 per cent. Future forecasts indicate that their use will likely rise so that by 2022 the majority of the U.S. households will have at least one smart assistant in their home 5. Chatbots have been around since at least 1966 6, yet their use in more complex settings currently still involves difficulties, as interactions between users and chatbots remain for the most part simple and usually follow a simple question answer approach 7. The application of advanced technologies such as deep learning 8 and the recently unveiled Google Duplex, a more technologically advanced smart assistant, already hints in a direction where in the near future smart assistants can act as collaboration partner in solving more complex tasks 9. However, this remains a research field which is only beginning to unfold, with none or little research taken to how chatbot user interaction can be structurally developed within a problem task scenario. Thus, the aim of this paper is to design a process model on how chatbots and users can collaborate together in order to solve a problem. This model helps chatbot designers to analyze human-chatbot interactions and derive design requirements from it.

@inproceedings{weingart2019chatbot, abstract = {The rise of massive open online courses (MOOC) provides means to economize and scale education in response to higher budget restrictions [1] and raises the number of possible enrolled students by an unprecedented amount, compared to traditional higher education courses [2]. However, a disadvantage of MOOCs is the lack of individual support which can’t be addressed economically to a massive audience, often resulting in a less than optimal learning outcome [3]. Chatbots have the potential to alleviate this issue as a supporting tool to help the user learn how to solve a complex set of problems [4]. In 2017, the use of smart assistants in U.S. households like Amazon Echo or Google Home has increased by 128.9 per cent. Future forecasts indicate that their use will likely rise so that by 2022 the majority of the U.S. households will have at least one smart assistant in their home [5]. Chatbots have been around since at least 1966 [6], yet their use in more complex settings currently still involves difficulties, as interactions between users and chatbots remain for the most part simple and usually follow a simple question answer approach [7]. The application of advanced technologies such as deep learning [8] and the recently unveiled Google Duplex, a more technologically advanced smart assistant, already hints in a direction where in the near future smart assistants can act as collaboration partner in solving more complex tasks [9]. However, this remains a research field which is only beginning to unfold, with none or little research taken to how chatbot user interaction can be structurally developed within a problem task scenario. Thus, the aim of this paper is to design a process model on how chatbots and users can collaborate together in order to solve a problem. This model helps chatbot designers to analyze human-chatbot interactions and derive design requirements from it.}, added-at = {2021-02-10T11:18:42.000+0100}, author = {Weingart, Pablo and Winkler, Rainer and Söllner, Matthias}, biburl = {https://www.bibsonomy.org/bibtex/2103dee9e236fced4332fa9a351dba9fe/wise-kassel}, booktitle = {14th International Conference on Wirtschaftsinformatik (WI)}, interhash = {c9eac89c517cd1771af8e29cdebca350}, intrahash = {103dee9e236fced4332fa9a351dba9fe}, keywords = {itegpub pub_msö pub_wise-kassel}, timestamp = {2021-07-13T12:26:04.000+0200}, title = {A chatbot dialogue model: Understanding human-chatbot collaboration in a complex task environment}, year = 2019 }