Difference between revisions of "PRE2019 1 Group3"

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Line 12: Line 12:
| Tom Verberk  || Software Science || 1016472
| Tom Verberk  || Software Science || 1016472
| Peter Visser || ||  
| Peter Visser || Applied Physics || 0877628

== Planning ==
== Planning ==

Revision as of 12:09, 9 September 2019

Artificial intelligence in Education

Group Members

Name Study Student ID
Ruben Haakman Electrical Engineering 0993994
Tom Verberk Software Science 1016472
Peter Visser Applied Physics 0877628


Every week we will have 2 meetings, in between the meetings we will work on individual tasks, results of the individual tasks will be examined in the meetings, the tasks dicussed are the time when the tasks has to be done.

Week Monday (morning) Thursday (afternoon)
1 ALL : choose topic ALL :
literary research
problem definition
make the planning
define structure of the report
2 Ruben : introduction/problem statement
All : wiki page
All : state of the art
Peter : users/stakeholders
Tom: Approach, milestones and deliverables, Who’s doing what

Who is doing what

Research about “didactiek” ~ Ruben, Peter
Build application ~ Tom
Build database. ~ Tom
Ask high school teachers stuff ~ Ruben, Peter
Test application. ~ All


There has been a big increase of technology in education; smart boards, laptops, tablets and online learning systems are now commonly used in classrooms. Artificial intelligence (AI) is however still new and little used. AI can generate exercises based on individual student’s particular needs to give each student personalized questions. This can help students learn faster and keep them motivated. It also reduces the workload for teachers.

Problem Statement

Currently a teacher makes a set of exercises which is the same for all students. In this way the level of the student is not taken into account resulting in questions which are too simple or too difficult. Using AI it is possible to give a student a personal learning program and give exercises that match the level of the student.

State of the art

Stake Holders





Our approach will look the following. We will start with some up front research, we will make some sort about “didactiek” and how to apply this in our webpage we want to create. While doing research about these topics we will start working on our webpage. We are planning to build some sort of web page or program. This artifact will have some sort of artificial intelligence which keeps track of the level of skill of the student and gives exercises matching the skill level of the student. After being done with the research about “didactiek”. We will lay the proposal of our artifact in front of several high school teachers. We want to have their input, as the artifact is build for there purpose. We then imply the given advise in our artifact. Lastly we plan to test our improved application for use, we will go to the same (or other) high school teachers and ask if we can test them in their classes. We then come up with a conclusion and finish the research.

Our milestones will be the finish of our research, the alpha version of our application, then the comments of the teachers, then the beta version of our application. The findings of the test subject and finally the final version.

Our deliverables will be a research about the current AI in education, the findings we got from talking to teachers, the test results found when testing on students and finally our artifact.


Rational Agent Models



Peer Evaluations