DSR Buddy

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Michi Gau

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Alex Maedche

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Jan vom Brocke

Description

In this project, we aim to create a new and lightweight user interface for the MyDesignProcess platform in order to create new research activity descriptions. The interface is based on a conversational agent and supports different user stories. The agent should act as a research "buddy" and will support novice researchers and experienced researchers in conducting their design science research process documentation.

Design Canvas

Problem

Creating documentation needs a lot of effort and is often time-consuming (Mohammad, 2005).

Lack of integration of knowledge management into individuals daily work activities (Akhavan, 2015)

Research Process

Design Science Research
Develop a prototype and study the impact of the documentation behavior of design science researchers.

Solution

Designing and implementing a contextual AI assistant with design features to support novice researchers in their DSR activity documentation process.

Input Knowledge

Human AI Interaction (Human-Computer Interaction)
Knowledge Management
Smart Personal Assistant
Design Science Research

Concepts

Knowledge Reuse (Markus, 2001)
Knowledge Management Prozess

Output Knowledge

Design features for integrated research activity documentation tool support.

DSR Buddy implementation: A Conversational Agent to support research activity documentation.

Research Pitch

Internal presentation and discussion of the first draft of the research idea in our research group.

We pitched the idea of using conversational agents (CA) to support design science researchers in their research activity documentation tasks to increase productivity and decrease the workload. Based on the feedback we reshaped the idea and designed an initial research design. The reshaped research design is described in the following activity descriptions.

  • Kickoff
  • Pitch Presentation
Problem

We aim to support design science researchers in structuring research activities and transforming them into research activity documentation.

Additionally, we support captureing different research activities, for example, requirements, design decisions, research activity ... that contribute to the design knowledge of a DSR project.

Furthermore, we aim to facilitate the documentation process to reduce the efforts of researchers in their documentation tasks.

We first conduct a literature review to identify related work and the research gap. Based on the results we derive a research question. We then defined an initial set of design requirements.

Relevant Literatur

We collected prior research and relevant literature on how to document knowledge-intense research process activities in DSR and other research fields.

The core references are listed below.

Documentation in the field of healthcare:

https://www.researchgate.net/publication/202342455_Management_of_Knowledge-Intensive_Healthcare_Processes_on_the_Example_of_General_Medical_Documentation

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5297955/

https://www.semanticscholar.org/paper/Quality-of-nursing-documentation%3A-Paper%E2%80%90based-Akhu-Zaheya-Al-Maaitah/45b82afd0501065013a95a09a7437efc0e8b5d99

Half a day is used for documentation in health care: https://www.ama-assn.org/press-center/press-releases/type-click-tasks-drain-half-primary-care-workday and http://telecareaware.com/now-ehr-data-entry-50-of-primary-care-doctors-workday-ama-university-of-wi-report/

Knowledge Management Perspektives

Retrieving knowledge from human minds is an expensive process that is time-consuming and requires skilled personnel (Mohammad, A. H., & Al Saiyd, N. A. M. (2012). Guidelines for tacit knowledge acquisition. Journal of
Theoretical and Applied Information Technology, 38(1), 110-118. Retrieved on October 10th, 2013,
from http://www.jatit.org/volumes/Vol38No1/15Vol38No1.pdf
)

Lack of integration of KM into individuals' daily work activities, creation of repositories without addressing the
need to manage content... (
Akhavan, P., Jafari, M., & Fathian, M. (2005). Exploring failure factors of implementing knowledge management systems in organizations. Journal of Knowledge Management Practice, 6. Available at
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2188273
)

https://www.scielo.br/scielo.php?pid=S0104-530X2017000200248&script=sci_arttext&tlng=en

Mind to paper: https://www.researchgate.net/publication/236040925_Mind-to-paper_is_an_effective_method_for_scientific_writing

Conversational Agents in Education

https://www.sciencedirect.com/science/article/pii/S0360131521000257

Source: Winkler, R., Söllner, M., & Leimeister, J. M. (2021). Enhancing problem-solving skills with smart personal assistant technology. Computers & Education165, 104148. https://doi.org/10.1016/j.compedu.2021.104148


  • Literature Review
  • Problem Definition
Research Question

How to design a conversational agent to support design science researchers in documenting their DSR projects?

Design Requirements

In the following, we describe an initial set of design requirements (DR) derived from the literature to support research activity documentation in DSR.

DR1The DSR Buddy should support structured research activity documentation.

Source: vom Brocke, J., Fettke, P., Gau, M., Houy, C., Maedche, A., Morana, S., & Seidel, S. (2017). Tool-Support for Design Science Research: Design Principles and Instantiation (SSRN Scholarly Paper ID 2972803). Social Science Research Network; https://ssrn.com/abstract=2972803. https://doi.org/10.2139/ssrn.2972803

DR2: The DSR Buddy should support DSR with different levels of skills and experience to document their research activities. 

Source: Herwix, A., & Rosenkranz, C. (2019). A Multi-Perspective Framework for the Investigation of Tool Support for Design Science Research. In Proceedings of the 27th European Conference on Information Systems (ECIS)https://aisel.aisnet.org/ecis2019_rp/164

DR3: The DSR Buddy should be integrated into individuals’ daily work activities.

Source: Winkler, R., Söllner, M., & Leimeister, J. M. (2021). Enhancing problem-solving skills with smart personal assistant technology. Computers & Education165, 104148. https://doi.org/10.1016/j.compedu.2021.104148

DR4The DSR Buddy should support the learning process of DSR novices.

Source: Winkler, R., Söllner, M., & Leimeister, J. M. (2021). Enhancing problem-solving skills with smart personal assistant technology. Computers & Education, 165, 104148. https://doi.org/10.1016/j.compedu.2021.104148

DR5The DSR Buddy should be highly engaging so that researchers document their design decision and knowledge.

Lukyanenko, R., & Parsons, J. (2020). Design Theory Indeterminacy: What is it, how can it be reduced, and why did the polar bear drown? Journal of the Association for Information Systems, 1–59. https://doi.org/10.17705/1jais.00639

  • Design Requirements
Development

In the following, we describe the development and the implementation activities of the DSR buddy.

Design Features

DF1: DSR process documentation guidance (DR2, DR4):

The CA provides knowledge on well-established DSR process and activity descriptions including the original source, examples, and further readings on different DSR approaches used in the field of IS in order to provide guidance on how to execute and document DSR activities. Moreover, the CA provides process descriptions on DSR support processes, such as descriptions of the literature review process proposed by Webster and Watson, focus group research according to Trembly et al., and a description of the case study research process proposed by Benbasat et al.

DF2: Easy capturing of DSR activities (DR1, DR3):

The CA enables the creation of new research activities and aggregates them to selected DSR projects. In contrast to the MDP web form, where a user must navigate to a project and the new activity form first, the CA asks researchers to provide the necessary information to create a new activity description in a DSR project. Activities might, for example, take the form of a meeting, a new idea supporting a research project, or a planned evaluation. Activity descriptions can be provided either by text or by speech input. In the case of speech input, the system transcribes the speech to text and stores the activity description in the form of text. The automatic transcription feature supports only the English language so far. Descriptions created by the CA can be edited and refined using MDP at a later stage.

DF3: Feedback on DSR process descriptions (DR4, DR5):

The CA can provide feedback to researchers based on existing activity descriptions in a DSR project. The system analyzes all activities in a project and based on predefined rules, reports if there are any issues or improvements available for a DSR project. The current implementation contains two rules. The first rule seeks for specific activity types, for example, a research question or constructs, and reports if they are missing in the selected project. The second rule analyses the activity descriptions based on the provided text. Suggested improvements may include recommendations to provide more detail in empty (or very short) activity descriptions, or when essential activities are missing—for example, when no research question is found in a project. The CA reports on the found issues and asks the researcher to fix them if necessary.

  • Design Features
System Architecture

The DSR buddy is integrated into the MyDesignProcess.com (MDP) platform but is running on its own server. This separation is mainly due to the performance requirements of the conversational agent. Almost every change in the CA business logic results in a recreation of the CA model. The underlying TensorFlow framework requires a bunch of resources to retrain the model that the webserver of MDP can not fulfill.

The proposed architectures allow the use of existing MDP features like login, activity management, templates, and many more.

  • Design
  • System Architecture
Conversational Agent Implementation

The CA is implemented on top of the chatbot framework RASA.

Currently, the CA implementation contains 3 stories, 17 rules, 16 intends, 8 custom actions, and 3 forms.

The server is set up to listen to a socket channel. The action server interacts with a REST API with the MDP system.

Integration of the DSR buddy into MDP:


Screenshots of the single design feature implementations: