PRE2020 4 Group4: Difference between revisions
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Although these learning agents or platforms focus specifically on education, there also exist personal computer assistants that are developed to help children more generally with their daily activities. The study by Kessens et al investigated such a computer assistant, namely the Philips iCat. This animated virtual robot can show varying emotional expressions and fulfilled the roles of both companion, educator and motivator <ref name='kessens'>Kessens, J. M., Neerincx, M. A., Looije, R., Kroes, M., & Bloothooft, G. (2009). Facial and vocal emotion expression of a personal computer assistant to engage, educate and motivate children. Proceedings - 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009. https://doi.org/10.1109/ACII.2009.5349582 </ref>. | Although these learning agents or platforms focus specifically on education, there also exist personal computer assistants that are developed to help children more generally with their daily activities. The study by Kessens et al investigated such a computer assistant, namely the Philips iCat. This animated virtual robot can show varying emotional expressions and fulfilled the roles of both companion, educator and motivator <ref name='kessens'>Kessens, J. M., Neerincx, M. A., Looije, R., Kroes, M., & Bloothooft, G. (2009). Facial and vocal emotion expression of a personal computer assistant to engage, educate and motivate children. Proceedings - 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009. https://doi.org/10.1109/ACII.2009.5349582 </ref>. | ||
Experiments with these state of the art technologies can also provide useful insights in this area. Cambo, Avrahami, & Lee (2017) investigated the application “BreakSense” and concluded that the technology should let the user decide for themselves when to take a break. In this way, | Experiments with these state of the art technologies can also provide useful insights in this area. Cambo, Avrahami, & Lee (2017) investigated the application “BreakSense” and concluded that the technology should let the user decide for themselves when to take a break. In this way, physical activity became namely part of their daily routine <ref name = 'cambo'>Cambo, S. A., Avrahami, D., & Lee, M. L. (2017). BreakSense: Combining physiological and location sensing to promote mobility during work-breaks. Conference on Human Factors in Computing Systems - Proceedings, 2017-May, 3595–3607. https://doi.org/10.1145/3025453.3026021 </ref>. | ||
===Related Literature=== | ===Related Literature=== | ||
Revision as of 09:27, 25 April 2021
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
Problem Statement
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 [1] [2]. 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[1]. 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[2].
Objectives
Our objectives are the following:
- Help with concentration and motivation (study-buddy)
- Improve physical health
- Provide social support for the user
Target user group
The user groups for this project will be office workers, college-, university-, and high school students, since these groups experience the most negative effects of the restrictions to work from home. There are several requirements for each group, most of them are related to COVID-19. First of all, there are some requirements relating to mental health. It is important for people to have social interactions from time to time. Individuals living alone could get mental health issues such as depression and loneliness due to the lack of these social interactions, caused by the restrictions [1]. It is also important for people to be able to concentrate well when they are working and that they can maintain their motivation and focus. Studies show that due to COVID-19 students experience a heavier workload, fatigue and a loss of motivation [3]. Considering the physical health, it is important that students and office workers are physically active and healthy. Some problems for the physical health of students and employees can arise from working from home. People that have an office job often do not get a lot of physical exercise during their workhours, but quarantine measures have reduced this even more [1]. This can affect cardiovascular and metabolic health, but even mental health [2]. In addition to this, the increased exposure to computer screens since the outbreak of COVID-19, especially applicable to high school students, can result in tiredness, headache and eye-related symptoms [1]. Hence, students and employees should become more physically active to improve their physical (and mental) health.
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
.PNG)
Research
State of the Art
At the moment there exist various online or AI-based systems that help both students and teachers with their educational tasks. The platform “X5Learn”, for instance, can be used by both students and teachers and provides personal recommendations to the students and enables collaboration between teachers [4]. However, the complexity of educational agents makes development expensive and difficult, as mentioned by [5].
Although these learning agents or platforms focus specifically on education, there also exist personal computer assistants that are developed to help children more generally with their daily activities. The study by Kessens et al investigated such a computer assistant, namely the Philips iCat. This animated virtual robot can show varying emotional expressions and fulfilled the roles of both companion, educator and motivator [6].
Experiments with these state of the art technologies can also provide useful insights in this area. Cambo, Avrahami, & Lee (2017) investigated the application “BreakSense” and concluded that the technology should let the user decide for themselves when to take a break. In this way, physical activity became namely part of their daily routine [7].
Related Literature
A list of related scientific papers, including short summaries stating their relevance, can be found here.
References
- ↑ 1.0 1.1 1.2 1.3 1.4 Xiao, Y., Becerik-Gerber, B., Lucas, G., & Roll, S. C. (2021). Impacts of Working From Home During COVID-19 Pandemic on Physical and Mental Well-Being of Office Workstation Users. Journal of Occupational and Environmental Medicine, 63(3), 181–190. https://doi.org/10.1097/JOM.0000000000002097 Cite error: Invalid
<ref>tag; name "Xiao" defined multiple times with different content Cite error: Invalid<ref>tag; name "Xiao" defined multiple times with different content Cite error: Invalid<ref>tag; name "Xiao" defined multiple times with different content - ↑ 2.0 2.1 2.2 Werneck, A. O., Silva, D. R., Malta, D. C., Souza-Júnior, P. R. B., Azevedo, L. O., Barros, M. B. A., & Szwarcwald, C. L. (2021). Changes in the clustering of unhealthy movement behaviors during the COVID-19 quarantine and the association with mental health indicators among Brazilian adults. Translational Behavioral Medicine, 11(2), 323–331. https://doi.org/10.1093/tbm/ibaa095 Cite error: Invalid
<ref>tag; name "Werneck" defined multiple times with different content - ↑ Niemi, H. M., & Kousa, P. (2020). A Case Study of Students’ and Teachers’ Perceptions in a Finnish High School during the COVID Pandemic. International Journal of Technology in Education and Science, 4(4), 352–369. https://doi.org/10.46328/ijtes.v4i4.167
- ↑ Perez-Ortiz, M., Dormann, C., Rogers, Y., Bulathwela, S., Kreitmayer, S., Yilmaz, E., Noss, R., & Shawe-Taylor, J. (2021). X5Learn: A Personalised Learning Companion at the Intersection of AI and HCI. 26th International Conference on Intelligent User Interfaces, 70–74. https://doi.org/10.1145/3397482.3450721
- ↑ Chou, C. Y., Chan, T. W., & Lin, C. J. (2003). Redefining the learning companion: The past, present, and future of educational agents. Computers and Education, 40(3), 255–269. https://doi.org/10.1016/S0360-1315(02)00130-6
- ↑ Kessens, J. M., Neerincx, M. A., Looije, R., Kroes, M., & Bloothooft, G. (2009). Facial and vocal emotion expression of a personal computer assistant to engage, educate and motivate children. Proceedings - 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009. https://doi.org/10.1109/ACII.2009.5349582
- ↑ Cambo, S. A., Avrahami, D., & Lee, M. L. (2017). BreakSense: Combining physiological and location sensing to promote mobility during work-breaks. Conference on Human Factors in Computing Systems - Proceedings, 2017-May, 3595–3607. https://doi.org/10.1145/3025453.3026021