PRE2020 4 Group4

Group Description

Members

Name	Student ID	Department	Email address
Eline Ensinck	1333941	Industrial Engineering & Innovation Sciences	e.n.f.ensinck@student.tue.nl
Julie van der Hijde	1251244	Industrial Engineering & Innovation Sciences	j.v.d.hijde@student.tue.nl
Ezra Gerris	1378910	Industrial Engineering & Innovation Sciences	e.gerris@student.tue.nl
Silke Franken	1330284	Industrial Engineering & Innovation Sciences	s.w.franken@student.tue.nl
Kari Luijt	1327119	Industrial Engineering & Innovation Sciences	k.luijt@student.tue.nl

Logbook

See the following page: Logbook Group 4

Subject

We want to analyze and design an AI robot componanion to improve online learning and working from home problems like diminished motivation, loneliness and physical health problems. In order to address these problems we will introduce you to Coco, the computer companion. Coco will be an artificially intelligent and interactive agent that users can easily install on their laptop or PC.

Problem Statement and Objectives

Ik wilde heel even uitproberen hoe de referencing werkt dus vandaar dat die 1 hier even start

Due to the COVID-19 pandemic that emerged at the beginning of 2020 everyone's lives have been turned upside down. Working from home as much as possible was (and still is) the norm in many places all around the world and it applies to office workers, but also to college-, university-, and high school students. Even though there might be benefits from working in a home office, there are also many disadvantages that are critical to everyone's health. Multiple studies have found such effects, both mental and physical, because of the work from home situation. Mental issues that might arise are emotional exhaustion, but also feelings of loneliness, isolation and depression. Moreover, because people have a high exposure to computer screens, they can experience fatigue, tiredness, headaches and eye-related symptoms (Xiao et al., 2021). Additionally, people exercise less while working from home during the pandemic. This can have effects on metabolic, cardiovascular, and mental health, and all this might result in higher chances of mortality (Werneck et al., 2021).

Approach

Concerning the mental health of users, a main problem is loneliness. It has been researched before what the impact of robotic technologies is on social support. Ta et al. (2020) have found that artificial agents do not only provide social support in laboratory experiments, but also in daily life situations (Ta et al., 2020). Furthermore, Odekerken-Schröder et al. (2020) have also found that companion robots like Vector, can fulfill to reduce feelings of loneliness by building supportive relationships (Odekerken-Schröder et al., 2020).

Regarding the physical well-being of users, the use of technology could be useful to improve physical activity. Concerning Cambo et al. (2017), using a mobile application/wearable that tracks self-interruption and initiates a playful break, could induce physical activity in the daily routine of users. Moreover, Henning et al. (1997) have found that at smaller work sites, users’ well-being improved when exercises were included in the small breaks (Henning et al., 1997).

Finally considering the productivity of users, a paper by Abbasi and Kazi (2014) shows that a learning chatbot systems enhances the performance of students. In an experiment where one group used Google and another group used a chatbot to solve problems, the chatbot had impact on memory retention and learning outcomes of the students (Abbasi & Kazi, 2014). The same research as mentioned before from Henning et al. (1997) also showed that not only the users’ well-being, but also the users’ productivity would increase (Henning et al., 1997). Moreover, as has been researched in an experiment of Lester et al. (1997), the presence of a lifelike character in an online learning environment can have a strong influence on the perceived learning experience of students around the age of 12. Adding such an interactive agent to the learning process can make it more fun and the agent is perceived to be helpful and credible (Lester et al., 1997).

Method

At the end of the project, we will present our complete concept of the AI companion. This will include its design and functionality, which are based on both literature research and statistical analysis of send-out questionnaires. The questionnaires will be completed by the user group to make sure the actual users of the technology have their input in the development and analysis of the companion. Moreover, the user needs and perceptions will be described. The larger societal and entrepreneurial effects will also be taken into account. In this way, all USE-aspects will be addressed. Finally, a risk assessment will be included, as limitations related to the costs and privacy of the product are also important for the realization of the technology. These deliverables will be presented both in a Wiki-page and final presentation. A schematic overview of the deliverables can be found in Table 1.

Table 1: Schematic overview of the deliverables

Topic	Deliverable
Functionality	Literature study
	Results questionnaire 1: user needs
Design	Results questionnaire 2: design
	Example companion
Additional	Risk assessment

Milestones

During the project, several milestones are planned to be reached. These milestones correspond to the deliverables mentioned in the section above and can be found in table 2.

Table 2: Overview of the milestones

Topic	Milestone
Organization	Complete planning
Functionality	Complete literature study
	Responses questionnaire 1: user needs
	Complete analysis questionnaire 1: user needs
Design	Responses questionnaire 2: design
	Complete analysis questionnaire 2: design
	Design of the companion

Planning

Research

Related Literature

A list of related scientific papers, including short summaries stating their relevance, can be found here.