PRE2017 3 Groep14

Student	Student Number
Abby Berkers	0951825
Dennis van den Berg	0949036
Sophie van den Eerenbeemt	0954445
Christine Ingwersen	0952530
Ellen Mans	0956433

Learning with Smart Home for Kids

Smart Home Entertaining Educational Program

Subject

Enhance knowledge levels of young children through an interactive smart home environment. Teachers and parents will be able to tell the system the desired final knowledge level and the system has to be able to interact with the children and assess his knowledge level to create fitting personal questions. In our project we will focus on the quiz and try to create this.

Users

• Children from class 3 - 4 in the Netherlands. The system could be changed to fit other age groups that have other knowledge levels, but for this project we focus on this group.
• Parents or guardians of these children.
• Teachers that can tell the systems what level of knowledge needs to be reached.

User Requirements

children:

• learning though playing
• competitive, want the highest reward (number of sheep)

parents:

• want their children to study properly
• want their children to be happy
• want their children to be motivated/interested
• want to have more free time as they do not have to tutor anymore
• want to check their children's levels

teachers:

• let the children learn effectively
• the system has to match the curriculum
• easier to check all students' progress

Objective

Develop a smart quiz inside a smart home that can learn himself and ask children fitting questions to let him gain knowledge.

Approach

Creating a simulation in Unity and C#. Creating the smart quiz in C#.

Intelligent Quiz Master

Idea. Use a set of arithmic questions (addition, subtraction, fractions) since then it is easy for us to check if it makes sense. Also, since most children have difficulties with arithmic this is actually useful.

Given a set of questions, the quiz master will test the knowledge of a child, and help the child improve by asking the right questions at the right time. We will build an application that selects the next question to ask the child, based on the previous answers the child gave to previous questions.

The quiz master has to:

• Find out the level of knowledge the child has, and ask questions that are on the 'edge' of a childs knowledge in order to improve their knowledge.
• Optionally invent new questions, similar to the already existing questions.

In order to do so, we must:

• Define distance (or question similarity) between questions, which questions are of similar difficulty. So cluster questions based on their difficulty. Note that this will vary per child.
• Simulate the (increasing/decreasing) knowledge of different children. (To be able to train our app.)
• Construct a (large enough) data set to use parts of it for training and validation.
• Find out what the next right question would be. Our app should do this, based on the question similarity for a certain child. Educational/psychological: what are the best questions to ask?

Milestones

• Finishing planning
• Summarizing SotA
• Quiz
  • Teacher can enter category and boundary (knowledge goal that has to be reached)
  • Smart home/quiz can generate questions inside category
  • Smart home/quiz can understand the person's input
  • Smart home/quiz uses input to generate personal level questions
  • Smart home/quiz gives results to parents/teachers
• Simulation
  • Create environment
  • Create moving people
  • System can react to people and environment
  • Use quiz
  • Reward system (SHEEP)
  • Feedback system

Deliverables

Smart quiz program and a simulation/game that shows how it would be implemented in a smart home with actual people.

Who will do what? Planning

Dennis -> quiz programming //Sophie -> simulation Ellen -> wiki Abby -> quiz programming Christine -> quiz design

week 1:

• literature search, SotA summary
• make plan
• setup Git
• Unity tutorial
• update wiki

week 2:

• interaction plan
• script simulation
• quiz plan:
  • how to make AI
  • categories
  • creating questions
• update wiki

week 3:

• UML of quiz
• teacher program finished
• smart quiz has to generate questions inside the categories
• creating simulation environment and people
• update wiki

week 4:

• quiz has to read input (parsen?)
• start with letting quiz learn from input
• simulation has to react to environment and people
• update wiki

week 5:

• quiz has to learn from input
• simulation has to use quiz
• update wiki

week 6:

• quiz has to learn from input
• feedback system in quiz
• reward system in simulation
• feedback system in simulation
• update wiki

week 7:

• BUFFER
• start with presentation

week 8:

• final presentation

State of the Art Literature Study

These two articles propose methods to find similar questions among a database of questions. The similarity of questions in this article is based on how useful the question to one answer could be to answer a different given question. The methods used here might be useful when we will try to define the distance between questions.

On how we can add probabilities to someones response to an answer representing their knowledge. This can be useful when training and testing our intelligent quiz, as we can use this to simulate the responses of a child. For example, a child who thinks they know the answer might give the wrong answer because they are too quick, but in fact they do know the answer. Or a child who does not know the answer might take a correct guess.

This chapter continues on the previous. It describes how to model a learning path of a human being. This can also be useful when simulating the responses of the children, as children in real life progress while answering questions.

Shows that nowadays the educational aspects in interactive systems is often too separate ("chocolate-covered broccoli") and extrinsic. To create learning systems that work it is important to make them intrinsically motivating. You have to keep in mind that people have to actually use the system, so make it in such a way that they want to. Remember, the primary users will be children.

"Based on the gathered information the next scene presented to the player should be determined in a way such that the learner is neither unchallenged nor overwhelmed by the complexity of the contained tasks. It should rather be ensured that the learner’s knowledge is steadily increased up to full knowledge mastery." This line perfectly captures what we want to achieve. This paper is about how we can make systems adaptive in such a way that they can adapt to the needs and level of its user.

80Days is a game that is comparable to what we want to achieve. However this is a full on computer game while we want an interactive home system. The adaptation principle is relatable which is why it could be nice to base our system on this game.

In the ELEKTRA game they use unobtrusive knowledge assessment to see the user's level of knowledge. They do this by observing the user's behaviour in the game. If we can do something similar but in real life, as a smart home will be able to notice the residents behaviour, we can use this technology to assess the childs level and what he needs from the educational system such that he will get personalized assignments.

Paper about using smart homes to learn about human behaviour. This could be used for multiple things in our project like the knowledge assessment mentioned above, or checking whether or not the user (child) has some free time that he can use interacting with the system and thus learning. There is a need for pattern recognition in this behaviour.

We propose some papers related to the way our smart home system should be designed and implemented. First, a paper that: "proposes a model to improve Activity Recognition in smart homes. The proposed technique is based on defining a profile ofr each activity from training datasets. The profile will be used to induce extra features and will help in distinguishing residents' activities." This technique can be used in our project to develop the way our smart home recognizes activities of the users of the system.

Related to this, a paper that proposes a way to implement an "Adaptable Infant Monitoring System (...) with minimal cost, knowledge and time to set up". This technique can be used in the implementation of our smart home, in order to monitor infants using the system, and so prevent accidents, and keep track of the location of the infant. This could (possibly) be combined with the proposed technique above, to also monitor whát the infant is doing.

Lastly, a paper that "focuses on feedback of interface agents on student perception. (...) This study focuses on three types of feedback from interface agents to clarify student perception of single feedback and multiple feedback types." The results of this study should be taken into account when modeling the way in which our system interacts with users, in order to make it's feedback as effective as possible.

Now, we propose some papers related to the way the educational aspectof our smart home is designed and implemented. First, a paper that does not seem completely relevant to the project at first. However, it discusses "the application of gamification within the environment of education, and more specifically with an emphasis on assessment." This paper "opens the way for the implementationof gamification as a transformative online assessment tool ...", which can be used in our project to determine the way in which our smart home educates and assesses children in a playful manner.

Next, a paper that analyses "the role of digital games in early childhood, especially from the perspectives of learning, literacy and play. (...) The analysis of young children's learning while they are engaged in digital games in informal contexts furthers our understanding of the potential of game-based learning in formal early childhood education settings." The results presented in this chapter can be used in our project to properly design the way in which infants interact with the system, what digital games the system should present, and how.

Lastly, a book that could possibly be helpful. It proposes design principles of educational virtual worlds of preschool children. Especially the principles described in chapter 4 could be applied to the designing of our smart home system.

We reference a paper that conducted a study amongst students in a "Smart Home Lab". It describes their findings and argues that, in order to successfully use a Smart Home as a Pedagogical Tool, one must shift from virtual reality simulations to the physical environment, which they call "real virtuality". These results can be used to guide the development of a Smart Home as a learning (i.e. pedagogical) tool. Note that, even though the study is focussed on individuals that are outside of our research scope in terms of age, some results might still apply.

We reference a paper that "describes an exploratory investigation into the potential effects of a robot exhibiting an adaptive behaviour in reaction to a child’s interaction". The conclusions in this article can be useful in describing the effects of using a Smart Home system for learning purposes.

An interesting paper described a study which "investigated teachers’ perceptions of barriers to using - integrating computers in early childhood settings." Unlike other papers, the viewpoint of this article shifts the view from the developer of the system or the child user to the teachers involved in the process. The findings in this study can be used to descibe the effects on teachers when applying a smart home system to enhance child learning.

A paper released in 2010 presents a "device to systematically assess children's orienting behavior in social situations." An set of relevant tests was carried out with "12-36 months old typically developing infants [which] prove usability of the proposed technology." This study can be used to aid the social learning aspect of childhood in the proposed smart home system.

The following paper describes the trend of using robotics technology to support childhood education. It goes into the ethics involved, as well as social acceptance for such technologies. This chapter from the book "Cybernics" can be used to assess the social acceptance and ethics evolved in creating and deploying the proposed smart home system.

The tutoring system

• This paper shows that by using a different take on machine learning, it is possible to train children as we are training computers. This is called machine teaching. The goal is to find the optimal training set, the smallest training set, to achieve the desired effect, which is a group of children whom all know the course material given by the teacher.

• Combining Artificial intelligence with tutoring has already been used and researched for several years and is called an intelligent tutoring system. Therefore designing such a program requires you to keep in mind all of the things that have already been done, which can be found in the article. For instance the article gives 8 designing principles such as: provide immediate feedback on errors, and it shows a possible architecture.

Smart home

• Current smart homes have already integrated a lot of features, for instance sensors in the floor to accurate locate persons or cameras with image analysis. However these systems are far from perfect. They have to improve their computing infrastructure more.

• It is possible for a smart home to detect speech and react upon it in crowdy and noisy environments

• Smart homes can use their social features to interact with persons.

References

Coaching Questions Group 14