PRE2020 3 Group7

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Time-Machine


Introduction

When you are studying you sometimes forget an important meeting, because you are deeply focused on your materials. Also, sometimes you need a little motivation to start studying. To solve that problem we are going to develop a clock that displays your agenda. This allows for users to get a clearer overview of their daily planning. The clock will also take your study/work time into its planning, and, of course, your spare time. It also gives you a push notification when you need to start studying in the form of a motivational message. So far, we have brainstormed about multiple extra fucntions that could be added in the future. Firstly, there is evidence that environmental lighting conditions influence concentration[1][2][3]. Secondly, there is evidence that student concentration spikes and lowers during their activities[4].
Ideally, it could check the activity of the user's phone during work hours and shut down certain distractors if it is used too much. It is also possible to use a webcam to check whether the user is working with the necessary focus and send a notification if this is not sufficient (should be looked at with privacy regulations).

Group Members

Name Study Student ID
Wouter de Vries Computer Science 1463748 w.p.h.d.vries@student.tue.nl
Ilana van den Akkerveken Psychology & Technology 1224158 i.a.f.v.d.akkerveken@student.tue.nl
Joep Obers Mechanical Engineering 1455117 j.g.p.m.obers@student.tue.nl
Jens Reijnen Psychology & Technology 1378074 j.m.t.reijnen@student.tue.nl
Erick Hoogstrate Mechanical Engineering 1455176 e.hoogstrate@student.tue.nl

Planning

Week Activity Name
1 Choose a subject All
Literature research for the problem statement and SotA All
2 What should the robot look like All
What should the robot be able to do All
3 Order Parts Wouter
Make a survey Jens & Ilana
Make a first sketch of the idea Joep
4 Gather survey responses All
Analyse survey responses Jens & Ilana
Put the raspberry together and install the basics Wouter & Joep
Look at how to plot a clock in python Erick
Look at how to extract an agenda in python Joep
5 Transfer data from agenda to clock Erick & Joep & Wouter
Make small slices from the clock Erick & Joep & Wouter
Implement code on raspbery pi Erick & Joep & Wouter
Implement research from the survey Jens & Ilana
6 Make a code that combines the clock and agenda Erick & Joep & Wouter
Complete the literature on the wiki Jens & Ilana
Make code that can make appointments for studying Erick & Joep & Wouter
Look on how to connect philips hue to rpi Erick & Joep
Research into Philips hue colour temperatures Ilana
7 Add digital clock option All
Finish the program Erick & Joep & Wouter
Finish the interface All
Do a user test All
Make video of prototype + editing All
8 Finishing touch to the interface All
Work on the report All
Do a user test All
9 Finish the report All

Problem statement

As students, we have been working from home due to Covid-19 for over a year, which has been causing drastic changes in our freedom for months. The consequences are noticeable in many areas but primarily in the psychological well-being of the public[5][6]. Since working and studying from home has become the norm, students report feelings of loneliness, less (study) motivation and less concentration. When no fun distractions can take place anymore and everyday seems a repetition of the day before, it is hard to stay productive, or happy in general. Therefore, it is important that we come up with a device that will keep people motivated to study and work from home, but due to time limitations we will focus on students. It has been said that sticking to a set schedule is helpful when working from home, but in practice this is not that easy. It could be beneficial for students to have some help with this. Help in making an executable and achievable week schedule with clear distinctions between work/study and relaxation. Additionally, the students should be made aware of their social media/phone use in order to keep them focused and not distracted.

Project plan

Approach

The approach to this project is as follows. Firstly, a literature study will be conducted to find multiple points that can influence or enhance concentration while studying. This might also help increase the understanding of which distractions are most common while studying. Secondly, a survey will be held. This survey is used to confirm the findings from the literature. Furthermore, if the data is gathered from actual students, it will contain practical problems that might not emerge from literature alone. In the meantime, the first bit of code and a very early prototype could be created. After all the data has been evaluated, the prototype can be finished (until further notice). A user-study/usability test will now be conducted to investigate how helpful the product truly is. As a finishing touch, the prototype or code may need to be adapted, dependent on the user tests.

Requirements

Students want to achieve their degree. In order to achieve it they need to study a lot, which can be very hard in the wrong environment. Therefore they require a stimulating study environment, but also after studying a place to relax and let go of all the stress.


  1. The product displays an analog clock on the screen.
    Without this function our product would simply not work, so this has a very high priority.
  2. The clock reads the agenda items of the user.
    This is a basic funtion of the product, it has very high priority.
  3. The agenda items of the user are displayed on the clock in colors on the time when they are set.
    Many people responded in the survey stating that they would like the clock to display their daily planning in the background, similar to a pie-chart. This has been given a high priority.
    Some participants prefered to see only the current item and some indication about the next item. This will be added as an option, but with medium priority.
  4. The user can connect their agenda to the clock by entering their agenda URL.
    This function is essential in getting our design working and making it user-friendly. It has very high priority.
  5. The clock will automatically show the correct time and agenda items after being turned off and on again.
    If the user has to import their agenda manually every time they boot up, e.g. after unplugging, that would be quite a hassle. User-friendliness is a key point, so we give this high priority.
  6. The product has a digital clock below the analog clock.
    According to our survey, most people want the ability to be able to switch between a digital and an analog clock. Our priority is to make a functional prototype in this course, so we will only add this if we have spare time (priority is low).
    The respondents in our survey seem to slightly prefer a digital clock over an analog clock, but most people prefered to see a pie-chart-like design regarding the colours. We therefore decided to make an analog clock, but put a digital clock on the interface as well (see: current status of the prototype). This seems relatively important, so we gave it medium priority.
  7. The screen displays the agenda items next to clock
    Very few respondents to the survey stated that they did not need for the clock to display the name of the agenda item. This question originally considered the name to be in the area of the 'slice' in the clock. Due to screen size it is also possible to display a list with all the items on the side. We give this medium priority, because it is not essential in our design despite being a nice quality-of-life improvement.
  8. The user can give their desired color to agenda items in which they will be displayed on the clock.
    Inside the agenda app, agenda items already have a colour, this should suffice to discriminate agenda items. The user also has the option to change this on their phone. This function is therefore not a necessity. We give it low priority.
  9. The clock changes the room's lighting according to preset keywords.
    Warmer or colder light can enhance concentration of a student.[1] In the survey, participants answered that changing lighting on the warm-cold spectrum to match the activity at hand might be a good idea.
    There were, however, also quite some respondents who stated that they did not deem that necessary or they could always do that manually. This leads to believe that this is not a vital function and should be given low priority.
  10. The speakers of the clock can set off an alarm sound for certain agenda items.
    In the survey, more than 90% of the participants seemed to like an alarm function for this device. Furthermore, many participants liked to get an alert when they needed to start preparing for their next agenda item, this can be done through an alarm function. The alarm clock does not seem very important in our design, but due to the demand for alerts we will give it medium priority.
  11. The clock plans breaks in study/work time.
    Taking in breaks regularly is very important to be able to keep working efficiently.[7][8][9] Ideally, this device would be able to learn how long the user can work before needing a break. Creating code for this is very difficult and likely beyond the scope of this project. This will get very low priority.
    However, if the user were to tell the clock how long they want to work and how long they want their breaks to be, it seems possible. This is, however, not essential so it is give low priority.

Milestones

  1. Literature study (week 1&2)
  2. Survey creations and analysis of results (week 3)
  3. Sketch of the idea (week3)
  4. Picking up all the parts for the project (week 4)
  5. Setting up the Raspberry Pi so that it can be operated through wifi (week 4)
  6. Creating code for a simple clock (week 4)
  7. Creating code to extract an agenda and import it to our clock (week 5)
  8. A functional prototype (week 6)
  9. Creating a presentation of our prototype (week 7)
  10. Creating the actual presentation (week 7)
  11. Do some user tests (week 7&8)
  12. Finishing the wiki (week 8)

Deliverables

  • survey-study
  • prototype
  • user analysis
  • complete wiki page
  • (optional) user tests

Objectives

  • Create a product that will reduce problems students are facing in times of studying from home. According to our survey, the problems that have to be overcome are lack of motivation, easily distracted and struggles to stick to a planning.
  • Conduct research about what functions and looks such a device should have according to students and find out whether there would be interest in a device that we will prototype.
  • Create a prototype of the idea and test this with users to get feedback on the design, after which small alterations can be made to improve.

USE analysis

User

The main users of this device will be students. In times of the Covid-19 pandemic lots of students are forced to study from home. For some, this has caused motivation and concentration problems and struggles with maintaining/creating a good planning. The goal of our project is to make a device that helps students in maintaining a clear overview of their tasks and help them in study planning. To gather information about the problems students are facing while working/studying from home, a survey study has been done among 85 students in the age of 17-27 years.

Society

A device such as our study clock will benefit society in terms of education. The more and the better students stick to their study tasks the less guidance has to be given by professors and teachers and the less study delay will have to be covered.

Enterprise

Enterprise could benefit from this product by distributing it among their employees. The employees could then have the time-machine on their (home-)office desk to use as their interactive agenda. Also, it would be beneficial if the employers could control the devices as well, so it would make it possible to plan group meetings within the company by maintaining all plannings.

USE case, How our product would work in the future

Robin is a student at Eindhoven university of technology. Since the Covid-19 pandemic, Robin has been having trouble concentrating at sticking to a planning with his uni tasks and work. He often forgets his plans or is procrastination. A week ago he has bought the 'Time-machine'. Ever since Robin gets up easily and performs well on his tasks. This is how a normal day of Robin would look like using the Time-machine.


Robin has set his alarm at 7 'o clock in the morning. At a quarter to 7 Robin's Philips hue light slowly start to brighten, creating a natural wake up light (like the sunrise). At 7:00 Robin wakes up from the alarm of the time-machine in a relaxing environment, ready to start his day. The Time-machine reads out his schedule so he knows what is ahead of him. After a coffee and a good breakfast, Robin takes place behind his desk. He looks at the screen of the time-machine and sees that his first task will start in 2 minutes, lecture preparation, so he grabs his office essentials to get started. The light in his room changes to a cool blueish white colour, creating a concentrating environment. After some time the time-machine notices that Robin is distracted, he is looking at his phone instead of working on his task. The machine sets of an alarm to notify that Robin has to return to his work. Robin puts his phone away and continues his work. After each 25 minutes of work the light changes to a bit warmer colour, making it possible to relax for 5 minutes, after which 25 minutes of concentration will follow again(pomodoro method). This creates an optimal study rhythm for Robin. If, after some time, the device detects that another rhythm would work better, it will change to a more personal break-scheduling setting. After a couple of study hours, Robin scheduled some time for reading. The light changes from a cool blueish white colour to a bit more warm light, perfect for reading. Next, it is time for some relaxation for the rest of the evening and the light gradually changes to the relaxing warm white colour. As the evening progresses the lights get gradually more dimmed until they go out at the time Robin indicated he wanted to go to sleep. Before sleeping Robin checks his planning for the next day and sets his alarm for the morning.

Effects of lighting

There has been done a lot of research on the influence of lighting on humans.

Medical and biological research has shown that light entering the human eye has both visual as non-visual biological effects on the human body. Good lighting can have a positive effect on health, well-being, alertness and sleep quality. For many years, scientists considered cones and rods to be the only photoreceptors in the eye, until Berson et al. (2002) discovered a third type of photoreceptor in the retina of mammals[10]. This photoreceptor regulates non-visual biological effects, such as body temperature, circadian rhythm (sleep-wake cycle), heart rate, cortisol production (stress), melatonin production and alertness. The sensitivity of this specific photoreceptor also varies for different wavelengths of light. The curve of both the cones and the biological action curve can be seen in the figure below. When comparing these two curves it is clear that the biological sensitivity is different from the visual sensitivity.

Spectral eye sensitivity curve for the cone system (dotted line) and biological action curve (full drawn line)

Now, what are the non-visual biological effects that are regulated by the third photoreceptor?

First of all, it sends signals to our biological clock. When the light comes up in the morning, cortisol levels increase and the body gets ready for the day. Gradually the cortisol levels decrease during the day, getting to a minimum at midnight. The sleep hormone melatonin decreases in the morning and increases the moment it gets dark, causing sleepiness. It is important that these rhythms are not disrupted. Therefore, it is important to maintain the right light levels during the day. Additionally, it has been found that high light levels (1700 lux) have and alerting influence on the central nervous system which causes a better concentration and increases productivity. This is something that would be beneficial to implement in an interactive clock design to increase work/study productivity.

Another research paper by Hoffmann et al. (2008)Cite error: Invalid <ref> tag; invalid names, e.g. too many. It will then identify if this direction is sensible, e.g. during study hours the user should be looking at their screen. If it decides that the user has not been doing their work for quite a while it can then alert the user. This alert could be a push notification on their laptop/smartphone, or just a simple noise coming from the machine itself.

Update planning

This device should know at which moments the user should be studying/working. It can check when the user is occupied using their agenda. It will automatically calculate preparation/traveling time based on your location and destination and will sound an alarm when you should leave the house. It will take into account whether it is a weekend or not. Based on this data it should be able to plan in study/work time. It should also take into account that the user has a certain sleep cycle, which it should be able to derive from long-time usage.

Break scheduling

As an addition to the facial recognition function and the planning update, the device can track for how long the user can focus on their work without taking a break. It will then learn from this and at some point start scheduling breaks when and for how long it sees fit. The device will start with implementing the Pomodoro study method. Breaks of 5 minutes and concentrated working for 25 minutes. This will be iterated 4 times after which a longer break of 15-30 minutes will be planned and the routine will start over. If the device notices another schedule timing would work better for the user according the tracking system, it will provide another, more suiting, planning rhythm.

Heart rate monitor

It should be possible to connect the information gathered from a heart rate monitor, like one found on a smartwatch, to the device. The device can then offer a better planning based on your heart rate. For example, by recommending a break when you get tired or very active, so that you can relax on the couch or go for a walk outside. Based on your heart rate, the device can also plan your sleep time more accurately.

Natural wake-up

This device can check through the agenda at what time the user has to get up. A short while before, it can start turning on the lights slowly so that the user will wake up in a more natural way compared to an alarm clock. This could increase productivity during the day by reducing sleep inertia[11]

Settings

Give the user even more possibilities to change settings. For instance, change the sound of the alarm, change the colors for different tasks, dark mode, etc.

State of the Art

  1. Bahsi et al
    This article reports a survey study that was held at the medical faculty of the Gaziantep University school of Medics. The survey considered 11 open-ended demographical questions and 29 Likert-scaled questions about the study environment, attention spans and motivation levels during study and study methods. The researchers used this data to find out how to increase the Grade Point Average (GPA). They concluded that is good to inform students about factors that can influence attention spans and motivation, identifying good learning strategies is beneficial for students and a good place to study is essential.[12]
  2. Bunce et al
    In this study, the researchers investigated how much attention students of chemistry classes could maintain during their lectures. They noted at the start that there were two types of interactivity in a lecture. The first type were quizzes that involved the use of a clicker. This allowed students to answer multiple choice questions on the smartboard and the teacher could show how the students did on these questions immediately. A second way was by doing demonstrations of the phenomena they explained. The study, however, only focused on the first part.
    This study asked students to report lapses of attention through their clickers. Before this study, the researchers expected that students would be able to stay focused for 10 – 20 minutes at a time, disregarding the first and last 5 minutes of lecture, where no student would be active. However, they found that students continuously alternate between being engaged or disengaged during a lecture for periods as short as 1-2 minutes. The suspicion that students are more engaged during interactive parts of the lecture was still confirmed.
    The researchers advise teachers to use interactive ways of teaching and include multiple student-centered pedagogies in their lessons.[4]
  3. Saalmann et al
    In this article, attention is defined as a mechanism that is used to select relevant information from the environment. The authors state that this is a top-down process. There is evidence that the posterior parietal cortex (PPC) is a brain area that is heavily involved in attention. This area is part of a dorsal stream and thus mainly considers spatial information. These two statements are backed by studies with monkeys. In an experiment where monkeys had to respond to certain stimuli, the response times of the monkeys who had to respond to ‘spatial’ or ‘spatial and featural’ stimuli responded significantly faster compared to monkeys in a ‘neutral’ condition. These experiments tested the response of the medial temporal (MT response) lobes, but found that the MT response got feedback from the lateral intraparietal area (LIP). This was evidence for the top-down feedback.
    From these experiments, they concluded that attention is gained quicker if stimuli were within the visual field and if a preceding stimulus was presented within the visual field as well.[13]
  4. Buckley et al
    The gamification of the learning process shows to have a positive effect on the learning experience. While playing people will be more engaged with the material and be more productive. This helps the student to be more motivated to study. However, this effect is mainly visible in students that are naturally keen on learning / are willing to learn. Students who do not like to learn will have different results. However, the method looks promising.[14]
  5. Seifert et al
    A student's motivation can be based on multiple variables, for instance: religion, parents, self-efficacy, self-worth and willingness to achieve certain goals among other things. A student’s motivation will have an influence on the way he or she will learn. It will have an effect on the behavior of things like the pursuit of mastery, failure avoidance, learned helplessness, and passive aggression. Students prefer their work to be meaningful and they like to have control and autonomy during their study. However in the end it all comes down to the personal emotions and beliefs of each student to really get a feel for their individual motivation.[15]
  6. Ames et al
    This article shows the importance of a good working environment and what kind of effects this can have on the learning behavior and motivation of the students.[3]
  7. Zheng et al
    Summary[16]
  8. Iriarte et al
    This paper shows the benefit of using a VR “game” to perform tests on students with a disorder, like ADHD. Since it helps them to focus better on the different tasks than if they would have done them with paper and pencil. While the test in the paper is focused on a younger audience, 6 to 16 years, it could give an indication for (young) adults as well. There also seems to be a difference in performance when looking at the different genders. The main takeaway message is that VR can be used to help students with a (learning) disorder to focus better by removing distractors for instance.[17]
  9. van Gog et al
    Eye tracking can be used as an input but also to measure the effect of various learning processes which make use of visual attention cues. Eye-tracking can provide more information on the split-attention effect, modality effect, redundancy effect, goal-specificity effect. The information gathered can be used to optimize learning strategies or layouts.[18]
  10. Vandewalle et al
    According to this article wavelength, duration, and intensity of light exposure modulates brain responses. Immediately after light exposure, you can observe physiology, for example, heart rate, sleep propensity, alertness, and body temperature. The non-visual responses are maximally for blue light (480nm) while the spectral sensitivity of classical photoreceptors is maximal for green light (550nm).
    Also, cognition is affected by light in which we are interested the most. Because this includes attention, executive functions, and memory. These cognitive performances decline during the biological night and progressively improve during the biological day. The light could affect cognitive performance through its synchronizing/phase-shifting effects on the circadian clock. Also with light exposure, cognitive performance can be increased acutely.
    From the article, we can conclude that exposure to blue light gives the highest brain-responses ranging from a few seconds to about 20 minutes.[19]
  11. Selvaraj et al
    According to this article students are very fond of using social media such as Facebook, Twitter, YouTube (based on the social media form 2013). The colleges are now pushing the classroom through social networks. Also, most of the information on social networks is fake or half-truth which could be a problem for students. Also, the students become addicted to social networks, which also means that their real-life friends become less in numbers while the digital friends become more and more. Too much of anything is good for nothing.[20]
  12. Perrin et al
    From this article, we can conclude that social media usage has increased very much between 2005 and 2015. From which we can only imagine that the trend continued to 2021. So the usage of social media is enormous. Young adults between 18 and 29 years are most likely to use social media 90% of this group uses social media.[21]
  13. Küller et al
    Humans have a circadian rhythm from approximately 24 hours, including being awake and asleep. This process is regulated by neural and hormonal processes. This process is being synchronized by the solar night and day. When far from the equator this internal clock can be disrupted by the short days and long nights (for half a year) which results in fatigue, sadness, and sleep problems. When you are indoors for a long time indoors during the day, windows are very important. Dark environments can have a negative effect on well-being and work capacity.
    All types of light within the visual range can have an influence on the biological clock. Bright is more effective than dim light and white or daylight more effective than colored light(possible with some exceptions).[22]
  14. Ogbodo et al
    In this paper, good study habits are discussed. The most important conclusion from this paper is that to form effective study habits you should have good counseling. They help you with a proper study schedule. They also note that a study should be divided into three periods where the subjects should be divided into relative importance. Also, a good schedule is very important in maintaining a good study schedule. And one point they note is: Do you have enough light in your study place?[23]
  15. Ezemenaka et al
    The author states that students have been more and more distracted since the introduction of the smartphone and that academic performance has become lower. They state, however, that there is no evidence linking the one to the other yet. The goal of their research is to find this link, if it exists. A survey-study was used to find out how many students used smartphones, what they used them for and whether they thought that it had an influence on their academic performance. The outcome of this study was that there was no significant relation detected between the use of a smartphone and academic performance.[24]
  16. Raviv et al
    It has been speculated a lot of times that students’ concentration decreases by a lot after physical exercise. They should be highly aroused, which leads a decrease in their concentration. This study found three things. Firstly, there does not seem to be a difference in concentration between physical or science classes. Secondly, concentration levels are very low at the beginning of a (science) class and higher near the end, but not so much to say that there is a significant effect. Thirdly, the concentration levels of all students are generally higher in the morning than they are in the afternoon. This means that the study found that concentration levels depend more on time than on the nature of the class.[25]
  17. Brophy
    This paper discusses the need for more attention in the cognitive aspects of motivation and the value students place on their academic activity. It mainly focuses on the classroom the students are in. Stating choice of activities is not a useful measure of motivation, since it is not provided. Development of motivation to learn needs attention to the more qualitative and cognitive aspects of academic engagement.
    A conclusion made in this paper are among others is, that performance is likely to be optimal on tasks when the student motivation is positive, a positive motivation in this case means the student is oriented toward the tasks and is free from distractions, anxiety and fear of failure.[26]
  18. Husman & Lens
    In this paper two divisions of student motivation are discussed: intrinsic-extrinsic motivation and future-present orientation. The possibility that intrinsic motivation and future time perspective can be integrated in a meaningful way is considered, to see whether an interaction will contribute to a multidimensional picture of student motivation.
    From this research was concluded that the relation between instrumentality and motivation is complex. Saying ‘do this because it is important’ is simply not enough to facilitate motivation. There are different aspects that have to be taken into account to achieve the right motivation. First, the student’s thoughts about the future (when negative, this can hurt or decrease motivation). Secondly, the student’s values, since instrumentality is most powerful when linked with values. In conclusion, students should discover the values of an activity themselves rather than being told the values. [27]
  19. Dörnyei
    This paper focuses on the temporal dimension of student motivation. The emphasis is placed on portraying motivation processes as they happen in time. In this paper there is focused on the challenge of time and its particular relevance to the understanding of motivation in educational contexts is discussed. It is found that the time dimension is relevant to motivation in two areas: Motivation evolves gradually through a complex mental state that involves planning, goal setting, intention formation and task generation. After which we have action implementation and control. In long term activities, such as mastering a school subject, motivation does not remain constant, but balances various internal and external influences that the student is exposed to, creating a fluctuating pattern of effort and/or commitment. [28]
  20. Küller et al.
    The main aim of the study in this paper is to determine whether indoor lighting and colour would have any systematic impact on the mood of people working indoors.
    The paper concluded that human emotions are influenced by a number of factors and only part of them might be related to the conditions at work. In this perspective the impact of light and colour found in this study certainly seems large enough to warrant increased attention. For the practitioner it will be important to consider both the seasonal impact and the access and distance to windows. [29]
  21. McCloughan et al.
    This study investigates whether artificial interior lighting influences mood and behaviour. The experimental work reported in this paper has demonstrated that there are systematic influences of lighting on mood from lighting parameters within the range of those encountered in everyday interior conditions. The nature of the lighting effect is complex and is best summarised under two separate headings, initial effects and longer-term effects.
    Initial effects: The main effect of illuminance is on the mood variable sensation seeking. Sensation seeking was reported higher on lower illuminance than under higher illuminance. Additionally, the main effects of CCT (correlated colour temperature) relate to a negative mood of hostility, which was higher under warmer CCT. Furthermore, females were significantly higher in positive aspects than males.
    Longer-term effects: The overall characteristics of the change of time in the room was confined to negative aspects of mood only. [30]
  22. Williams & Williams
    Motivation is probably the most important factor to improve learning. This paper discusses five key ingredients for improving student motivation. The five key ingredients impacting student motivation are: student, teacher, content, method/process, and environment. It then tries to use these ingredients to get the best way to motivate students and decides that all can be used as often as possible.
    This paper can give us insight into how we can motivate other students during this project. We will try to create an environment in which a student is reminded to do things but not distracted by for instance his or her phone. [31]
  23. Andrist et al.
    In this research a socially assistive robot has been made that motivates people with its face. This robot matches the personality of the user by changing his gaze, as in an extroverted or introverted personality. The study shows that matching the personality to that of the user increases the motivation to engage in a repetitive task.In our project we could be inspired by this to either give the robot a face or match it to the user to increase their motivation. [32]
  24. Han et al.
    This paper discusses the use of home robots to be used to learn. Robot technology has and will become more interactive and user friendly, communicating gestures, motions and facial expressions. Home robot assisted learning showed improvements in concentration, interest and academic achievement. Even though this study has different users, there might be similarities in the results. [33]
  25. Shin & Kim
    This study is concentrated on three scenarios in which robots relate to student learning. Learning about, from and with robots. In learning with robots which mainly concerns our project, students were expecting the robots to perform tasks like tuition or act as a teacher rather instead of being companions or collaborators. Students found that situations with robots in daily life are more fun and that robots can be helpful. Some however found themselves uncomfortable with the robots as they had the feeling they are being watched. This could also be a problem for our robot as it will not help motivate students if it makes them uncomfortable.[34]
  26. Yot-Domínguez & Marcelo
    This paper analyses the process by which students manage and facilitate their own learning. A survey was taken of 711 students which showed that university students tend to not use technologies to regulate their own learning process. Two distinctive groups of students were identified, which make use of different self-regulation strategies when learning with technologies.
    This study could be seen as that students do not want a technology to regulate their learning strategies. However it could also show that there is still room for improvement in current learning technologies to make them more user-friendly and helpful.[35]

References

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  3. 3.0 3.1 Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84(3), 261–271. https://doi.org/10.1037/0022-0663.84.3.261
  4. 4.0 4.1 Bunce, D. M., Flens, E. A., & Neiles, K. Y. (2010). How Long Can Students Pay Attention in Class? A Study of Student Attention Decline Using Clickers. Journal of Chemical Education, 1438-1443.
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LOGBOOK

Week 1

Name Total [h] Specification
Ilana van den Akkerveken 11 group meetings 4h, literature study 6h, problem statement 1h
Erick Hoogstrate 10 group meetings 4h, literature study 4.5h, updating wiki 1.5h
Joep Obers 11 group meetings 4h, literature study 7.5h
Jens Reijnen 10.5 group meetings 4h, literature study 6h, approach milestones deliverables 0.5h
Wouter de Vries 9.5 group meetings 4h, programming research 2h, literature study 3.5h

Week 2

Name Total [h] Specification
Ilana van den Akkerveken 7 group meetings 3h, brainstorming for project ideas 2.5h, research in student well-being 1.5h
Erick Hoogstrate 6 group meetings 3h, brainstorming for project ideas 3h
Joep Obers 6 group meetings 3h, brainstorming for project ideas 3h
Jens Reijnen 6.5 group meetings 3h, brainstorming for project ideas 3.5h
Wouter de Vries 5.5 group meetings 3h, brainstorming for project ideas 2.5h

Week 3

Name Total [h] Specification
Ilana van den Akkerveken 6.5 group meetings 3h, creating online survey 3.5h
Erick Hoogstrate 7.5 group meetings 3h, list of materials 2.5h, meeting Joep & Wouter 2h
Joep Obers 6.5 group meetings 3h. sketching 1.5h, meeting Erick & Wouter 2h
Jens Reijnen 6.5 group meetings 3h, creating online survey 3.5h
Wouter de Vries 7.5 group meetings 3h, meeting Joep & Erick 2h, mailing to check availability of parts 1h, research on materials 1.5h

Week 4

Name Total [h] Specification
Ilana van den Akkerveken 11 group meetings 3h, finishing survey 2.5h, converting and analyzing survey data 4h, wiki updating and inserting pie-charts 1.5h
Erick Hoogstrate 9 group meetings 3h, research into plotting different clocks with python 2.5h, adapting clock and implementation 2.5h, bug fixes 1h
Joep Obers 13.5 group meetings 3h, updating wiki and write first sketch 2.5h, setting up raspberry pi 4h, setting up virtual keyboard 2h, making holder for screen of rpi 1h, writing status of prototype 1h
Jens Reijnen 10.5 group meetings 3h, finishing survey 2.5h, overlooking results and and responses 1h, converting and analyzing survey data 4h
Wouter de Vries 9.5 group meetings 3h, setting up raspberry pi 4h, working on google calendar API 2.5h

Week 5

Name Total [h] Specification
Ilana van den Akkerveken 9 group meetings 2.5h, research on similar projects 3h, Use analysis, effects of lighting and deliverables 3.5h
Erick Hoogstrate 9 group meetings 2.5h, setting up up-dated version of python and changing settings on raspberry pi 2h, updated the clock to look good on the raspberry pi and functional 2.5h, moving clock and adding legenda 2h
Joep Obers 10 group meetings 2.5h, setting up up-dated version of python and changing settings on raspberry pi 1.5h, work on retrieval code 4.5h, finish agenda retrieval code 1.5h
Jens Reijnen 10.5 group meetings 2.5h, milestones updating 1h, update references section 1h, research into similar projects 3h, research on references and citations on wiki 1h, rewrite wiki, update figure captions references etc 2h
Wouter de Vries 13 group meetings 2.5h, working on google calendar API 2h, begin of redoing technical requirements 1h, working on retrieval code 2h, research agenda retrieval code 1h, finish agenda retrieval code 1.5h, redone technical requirements 1.5h, start programming dateTime 1.5h

Week 6

Name Total [h] Specification
Ilana van den Akkerveken 11.5 Group meetings 5.5h, redoing logbook splitting up the weeks for better overview 2h, research into hue colour temperatures 2.5h, editing effects of lighting 1.5h
Erick Hoogstrate 12 Group meetings 5.5h, getting philips hue connected to rpi 4.5h, adding alarm function & fixing bugs 2h
Joep Obers 13.5 Group meetings 5.5h, getting philips hue connected to rpi 4.5h, Combining codes 3.5h
Jens Reijnen 14.5 Group meetings 5.5h, update requirements 2.5h, further research on the implications of studying/working from home during pandemic 2h, write section about future development 2h,update wiki and include references in text 2.5h
Wouter de Vries 13.5 Group meetings 5.5h, reformatting and finishing agenda-parsing code 3h, Combining codes 3.5h, updating wiki 1.5h

Week 7

Name Total [h] Specification
Ilana van den Akkerveken 8 Group meetings 3h, making presentation + preparing for presentation 4h, shooting video footage 1h
Erick Hoogstrate 12.5 Group meetings 3h (including overall code implementation), Fixing code 1h, digital clock face 6h, preparation presentation 2.5 hours
Joep Obers 17.5 Group meetings 3h (including overall code implementation), Fixing code 6h, shooting video 3h, editing video 2.5 hours, preparing presentation 3 hours
Jens Reijnen 4 Group meetings 1h, update 'other projects' section 0.5h, prepare for presentation 2.5h
Wouter de Vries 16 Group meetings 3h (including overall code implementation, Finishing code 13h: Fixing at meet-up, researching timers and threading, Connecting all code, rewriting hue code to update live, reformatting slices code, fixing bugs

Week 8

Name Total [h] Specification
Ilana van den Akkerveken 6 Presentation 2h, group meeting 1h, writing about break scheduling 1h, creating a USE story 2h
Erick Hoogstrate 7.5 Presentation 2h, group meeting 1h, commenting and cleaning up code 1.5h, writing 'alarm, future developments, prototype' 3h
Joep Obers 8 Presentation 2h, group meeting 1h, setting up the user test 3.5h, writing 'Setting up the test' 0.5h, writing 'philips hue' 1h
Jens Reijnen 9.5 Presentation 2h, group meeting 1h, writing survey results/conclusion 3h, setting up the test 3.5h
Wouter de Vries 5.5 Presentation 2h, group meeting 1h, writing and practising for presentation 1.5h, Pictures for presentation 1h

Week 9

Name Total [h] Specification
Ilana van den Akkerveken group meeting 3h, collecting data from user test 3h
Erick Hoogstrate 6 group meeting 3h, run through wiki page 3h
Joep Obers 8 group meeting 3h, collecting data from the user test and retrieve prototype 3h, writing 'results' 1h, commenting code and writing about it 1h
Jens Reijnen 10.5 group meeting 3h, updating SotA/references 2.5h, collecting data from user test 3h, checking wiki 2h
Wouter de Vries 6.5 group meeting 3h, Commenting and cleaning up code 1.5h, Downloading code and putting on wiki 0.5h, updating time sheets 0.5h, writing about the code on the wiki 1h

Total hours

Name Total [h]
Ilana van den Akkerveken 70
Erick Hoogstrate 79.5
Joep Obers 94
Jens Reijnen 83
Wouter de Vries 81