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Developing an intelligent chatbot that can imitate human-to-human interaction has become important in recent years. For this reason, many studies have been conducted to evaluate the quality of chatbots. Furthermore, various approaches and tools, such as sentiment analysis, have been created to improve the performance of chatbots.
This study examines previous research to identify the quality dimensions used to measure chatbots performance in order to develop a general chatbot assessment model that evaluates and compares chatbots quality. The developed evaluation model measures ten chatbot quality dimensions. This model is based on user experience. It requires human testers to interact with the chatbot to test its functioning and then a quantitative approach is used to collect data from user testing by conducting a survey with these testers. In this survey, they are instructed to evaluate the quality of the chatbot using a questionnaire that contains the items needed to evaluate each dimension.
This study also investigates whether sentiment analysis can improve the quality of chatbots and, if so, to identify the dimensions improved with sentiment analysis. For this reason, two chatbot versions are implemented using the Rasa framework (one that cannot detect sentiment and the other that analyzes sentiment and responds accordingly).
Following that, we used our evaluation model to evaluate and compare the two chatbot versions with two groups of participants by conducting a survey. In this survey, each group tested the functioning of one version. Then, both groups were instructed to use the items of the evaluation model to evaluate the version they tested. The goal of this survey was to evaluate the validity and reliability of the items used in the evaluation model to evaluate chatbots, and also to determine if sentiment analysis improved the chatbot quality by comparing survey results between the two groups. The results show that items used in the assessment model to evaluate chatbots are valid and reliable. The findings also indicate that sentiment analysis improves the chatbot’s quality. However, it improves the quality of some dimensions but not the majority of them.
In the course of this thesis, an overview will be given on which way developers can guide
users into acting environmentally friendly without the users realizing they are being
nudged. In the last couple of years, our private and work-life have been more and more
shifted away from reality into a digital context. Since the start of the Covid – 19 pandemic
in 2019, even more aspects of everyday life have been shifted to an online context, one
of them being groceries shopping. Even though online groceries shopping is not yet
common in Germany, there is a trend toward the online purchase of groceries visible.
This can be seen as a possibility to tackle another challenge the world is facing, the
climate crisis. One reason for the climate crisis is mindless consumption and purchasing
of too much food. This paper aims to combine the need for more aware consumption
with the newly rising trend of online supermarkets. Furthermore, a supermarket will be
provided to show if the implementation of environmentally–friendly nudges is technically
possible. To eventually prove the effectiveness of a nudge, it needs to be tested.
Keywords: Nudging, Environment, Online supermarkets
Digital technology is increasingly becoming a part of life and culture in society, and it must be consciously designed for the long-term benefit of humanity. Today, information systems are designed to do more than fulfill human duties or complete tasks. A widely adopted approach is a system design that focuses on the positive aspects of human-technology interaction. Positive computing is a design paradigm gaining traction because it emphasizes the importance of well-being as a bold goal to be implemented in system design. In this dissertation, technology design is part of an intergenerational environment aiming to facilitate information sharing regarding global startup innovation. Nevertheless, much of the research focuses on how technology can be used to facilitate intergenerational collaboration. On the other hand, very little is known about how technology can be "positively" designed to promote intergenerational innovation. Therefore, this dissertation applied Design Science Research (DSR) to inform and guide the creation of design principles through the lens of positive computing. The study results provide a holistic picture of the numerous barriers, well-being factors, competing concerns, and competencies that have been encountered in the context of intergenerational innovation and their implications. This dissertation is presented as a cumulative dissertation, answering three research questions divided into seven studies, consisting of nine articles.
In this study, we looked at the competencies and changes in the competency spectrum required for global start-ups in the digital age. Specifically, we explored intergenerational collaboration as an intervention in which experienced business-people from senior adult groups support young entrepreneurs. We conducted a Delphi study with 20 experts from different disciplines, considering the study context. The results of this study shed light on understanding the necessary competencies of entrepreneurs for intergenerationally supported start-up innovation by providing 27 competencies categorized as follows: intergenerational safety facilitation, cultural awareness, virtues for growth, effectual creativity, technical expertise, responsive teamwork, values-based organization, and sustainable network development. In addition, the study results also reveal the competency priorities and the minimum requirements for each competency group based on the global innovation process and can be used to develop a readiness assessment for start-up entrepreneurs.
In this document a reliable data streaming mechanism for a TDMA LPWAN application is developed by adapting a link layer solution for power line communication, published at the International Symposium on Power Line Communications and its Applications (ISPLC) 2015. A C++ implementation of the services link layer is provided and demonstrated
working at a packet error rate of 50%.
This work aims to generate synthetic electromyographic (EMG) signals using Generative Adversarial Network (GAN). GANs are considered as one of the most exciting and promising approaches in deep learning [6], offering the possibility to generate artificial data based on real data. GAN consists of two main parts, a discriminator that attempts to differentiate between the generated data and the original data, and a generator that tries to fool the discriminator by generating data which looks like real data, the GAN works by staging a two-player
minimax game between generator and discriminator networks. To achieve the objective of generating realistic artificial electromyographic signals, two different architectures are considered for the generator and the discriminator networks of the GAN model: Long short-term memory (LSTM), which can avoid the long-term dependency problem and remembers information over a long period of time, and convolutional neural network (CNN), which is a powerful tool at automatic feature extraction. Different combinations of CNN and LSTM including hybrid model are experimented within the GAN using the same training data-set. The results and performances of each combination are compared and reviewed. The generated artificial EMG signals can be used to
simulate real muscle activity situations to for example improve muscle signal controlled prostheses using artificial data that may include conditions that does not exist in real data. This method of artificial data generation is not limited to EMG signals, the network can also be used to generate other synthetic biomedical signals such as electroencephalogram (EEG) or electrocardiogram (ECG) that can be practically used for testing algorithms and classifiers.
This study aims to determine the competing concerns of people interested in startup development and entrepreneurship by using topic modeling and sentiment analysis on a social question-and-answer (SQA) website. Understanding the underlying concerns of startup entrepreneurs is critical to society and economic growth. Therefore, greater scientific support for entrepreneurship remains necessary, including data mining from virtual social communities. In this study, an SQA platform was used to identify the sentiment of thirty concerns of people interested in startup entrepreneurship. Based on topic modeling and sentiment analysis of 18819 inquiries in various forums on an SQA, we identified additional questions about founder figures, keys to success, and the location of a startup. In addition, we found that general questions were rated more positively, especially when it came to pitching, finding good sources, disruptive innovation, idea generation, and marketing advice. On average, the identified concerns were considered 48.9 percent positive, 41 percent neutral, and 10.1 percent negative. This research establishes a critical foundation for future research and development of digital startups by outlining a variety of different concerns associated with startup development in the digital age.
This study proposes a framework for the collaborative development of global start-up innovators in a multigenerational digital environment. Intergenerational collaboration has been identified as a strategy to support entrepreneurs during their formative years. However, integrating and fostering intergenerational collaboration remains elusive. Therefore, this study aims to identify competencies for successful global start- ups through intergenerational knowledge transfer. We used a systematic literature review to identify a competency set consisting of growth virtues, effectual creativity, technical domain, responsive teamwork, values-based organization, sustainable networking, cultural awareness, and facilitating intergenerational safety. The competency framework serves as a foundation for knowledge management research on the global innovation readiness of people to collaborate across generations in the digital age.
So far, researchers have used a wellbeing-centered approach to catalyze successful intergenerational collaboration (IGC) in innovative activities. However, due to the subject’s multidisciplinary nature, there is still a dearth of comprehensive research devoted to constructing the IGC system. Thus, the purpose of this study is to fill a research void by providing a conceptual framework for information technology (IT) system designers to use as a jumping-off point for designing an IGC system with a wellbeing-oriented design. A systematic literature study was conducted to identify relevant terms and develop a conceptual framework based on a review of 75 selected scientific papers. The result consists of prominent thematic linkages and a conceptual framework related to design technology for IGC systems. The conceptual framework provides a comprehensive overview of IGC systems in the innovation process by identifying five barrier dimensions and using six wellbeing determinants as IGC catalysts. Moreover, this study discusses future directions for research on IGC systems. This study offers a novel contribution by shifting the technology design process from an age-based design approach to wellbeing-driven IGC systems. Additional avenues for investigation were revealed through the analysis of the study’s findings.
Public transportation will become highly automated in the future, and at some point, human drivers are no longer necessary. Today many people are skeptical about such scenarios of autonomous public transport (abbr.: APT). In this paper, we assess users’ subjective priority of different factors that lead to personal acceptance or rejection of APT using an adapted online version of the Q-Methodology with 44 participants. We found four prototypical attitudes to which subgroups of participants relate: 1) technical enthusiasts, 2) social skeptics, 3) service-oriented non-enthusiasts, and 4) technology-oriented non-enthusiasts. We provide an unconventional perspective on APT acceptance that helps practitioners prioritize design requirements and communicate, targeting users’ specific attitudes.
Rapid digital transformation is taking place due to the COVID-19 pandemic, forcing organisations and higher educational institutions to change their working and learning culture. This study explores the challenges of rapid digital transformation arising during the pandemic in the higher education context. This research used the Q-methodology to understand the nine challenges that higher education encountered, perceived differently as four main patterns: (1) Digital-nomad enterprise; (2) Corporate-collectivism; (3) Well-being-oriented; and (4) Pluralistic. This study broadens the current understanding of digital transformation, especially in higher education. The nine challenges and four patterns of transformation actors serve as a starting point for organisations in supporting technological choice and strategic interventions, based on individual, group, and organisational behavioural levels. Moreover, five propositions, based on the competing concerns of these challenges, establish a framework for comprehending the ecosystem that enables rapid digital transformation. Strategies, prerequisites, and key factors during the (digital) technology development process benefit the cyber-society ecosystem. As a practical contribution, Q-methodology was used to investigate perspectives on digitalisation challenges during the pandemic.
Blended learning offers learning solutions for higher educational institutions facing the industrial revolution 4.0. In this study, we investigated the influence factors student perceptions of blended learning based on gender-specific differences in Indonesia. We applied a research model to systematically assess the effect of design features on the effectiveness of blended learning indicators (intrinsic motivation and student satisfaction). Moreover, we evaluated the research model for both genders separately. Based on the quantitative survey of 223 Indonesian students, our study confirms that the design features significantly influence the effectiveness of blended learning for male and female students.
In this demo paper we present a new visualization technique for dynamic networks. It displays the time slices of the dynamic network using two dimensional graph layouting algorithms and stacks these in the third dimension to show the development over time. The visualization ensures that the same node always has the same position in each time slice so that it is easy to follow its development. It also allows filtering data and influencing node appearance based on properties. Additionally we offer a two dimensional comparison view for two time slices which highlights changes in graph structure and (if available) in measures of nodes. The presented visualization technique is implemented using Web technology and is available in a Web-based analytics workbench. We demonstrate the benefits of these techniques by an analysis of a data set from a learning community.
Starting with the automatic gear change, the operation of a vehicle becomes more and more abstract. In the future, we could control vehicles with single, simple commands. For such a maneuver-based vehicle control system, we investigate a head-up display design in a workshop. The aims are to identify common and distinct features of various display designs through mock-ups. First results show that different sizes of GUI elements are preferred by different states. The preferred position of GUI elements in the head-up display (HUD) is the central bottom area. We found two major interface design styles: static interfaces (all elements visible) with fixed layout and dynamic interfaces (only relevant elements visible) with fixed or adaptive layout.
The uprising levels of autonomous vehicles allow the drivers to shift their attention to non-driving tasks while driving (ie, texting, reading, or watching movies). However, these systems are prone to failure and, thus, depending on human intervention becomes crucial in critical situations. In this work, we propose using human actuation as a new mean of communicating take-over requests (TOR) through proprioception. We conducted a user study via a driving simulation in the presence of a complex working memory span task. We communicated TORs through four different modalities, namely, vibrotactile, audio, visual, and proprioception. Our results show that the vibrotactile condition yielded the fastest reaction time followed by proprioception. Additionally, proprioceptive cues resulted in the second best performance of the non-driving task following auditory cues.
Understanding user needs and behavior in automated vehicles (AVs) while traveling is essential for future in-vehicle interface and service design. Since AVs are not yet market-ready, current knowledge about AV use and perception is based on observations in other transportation modes, interviews, or surveys about the hypothetical situation. In this paper, we close this gap by presenting real-world insights into the attitude towards highly automated driving and non-driving-related activities (NDRAs). Using a Wizard of Oz AV, we conducted a real-world driving study (N= 12) with six rides per participant during multiple days. We provide insights into the users’ perceptions and behavior. We found that (1) the users’ trust a human driver more than a system,(2) safety is the main acceptance factor, and (3) the most popular NDRAs were being idle and the use of the smartphone.
This paper describes a system which allows platform independent access to quizzes of the popular learning platform Moodle. The main focus is on the software architecture which is implemented on the base of platform independent technology like Web Services, HTML5 and JavaScript. Another aspect is the user interface which was developed with the goal to run on a broad range of mobile devices from small mobile phones up to large tablets.
Knowledge of fundamentals of human-computer interaction resp. usability engineering is getting more and more important in technical domains. However this interdisciplinary field of work and corresponding degree programs are not broadly known. Therefore at the Hochschule Ruhr West, University of Applied Sciences, a program was developed to give teen-aged pupils insights into this area in a project-based learning environment with professional tools. Within the last 18 month this project was successfully conducted several times with participants of different age.
Human computer interaction in security and time-critical systems is an interdisciplinary challenge at the seams of human factors, engineering, information systems and computer science. Application fields include control systems, critical infrastructures, vehicle and traffic management, production technology, business continuity management, medical technology, crisis management and civil protection. Nowadays in many areas mobile and ubiquitous computing as well as social media and collaborative technologies also plays an important role. The specific challenges require the discussion and development of new methods and approaches in order to design information systems. These are going to be addressed in this special issue with a particular focus on technologies for citizen and volunteers in emergencies.
Recently, rescue worker resources have not been sufficient to meet the regular response time during large-scale catastrophic events in every case. However, many volunteers supported official forces in different disaster situations, often self-organized through social media. In this paper, a system will be introduced which allows the coordination of trained volunteers by a professional control center with the objective of a more efficient distribution of human resources and technical equipment. Volunteers are contacted via app on their private smartphone. The design of this app is based on user requirements gathered in focus group discussions. The feedback of the potential users includes privacy aspects, low energy consumption, and mechanisms for long-term motivation and training. The authors present the results of the focus group analyses as well as the transfer to their app design concept.