Course Analysis, 2D1380 Artificial intelligence, 4p

Course given 2005/2006 in study period 1

  • Course responsible:
    Patric Jensfelt, Danica Kragic
  • Lecturers:
    Henrik I Christensen, Patric Jensfelt, Danica Kragic
  • Lectures:
    total 12 lectures (24 hours) and 10 hours meetings
  • Registered students:
    67 undergraduate and 13 PhD students
  • In total, 59 undergraduate and 13 PhD followed the course
  • Course material:
    Artificial Intelligence: A Modern Approach (Second Edition) by Stuart J. Russell and Peter Norvig, Prentice Hall (2003), ISBN 0-13790-395-2
    All lectures were accessible for download.
    5 project descriptions and two homwork were posted on the web.
  • Examination:
    Assesment consisted of 2 homeworks (1p) and one project (3p). There was a deadline for both the homeworks and the projects announced at the beginning of the course. Homework assignments were graded (U, 3,4,5) and each of them accounted for 25% of the final course grade. The homeworks had to be completed individually and handed in on time. Homework received too late were be graded at all and received grade U.
  • Course results:
    55 undergraduate and 13 PhD completed all the neccessary parts by the end of the course.
    1 undegraduate student was examined during the first 2 weeks after the course and received a passing grade.
    In total, 3 undergraduate students failed to complete the course.
  • "Prestationsgrad":
    (68*1+69*3)/(72*4) = 95%
  • "Examinationsgrad":
  • Relation to the previous years:
    The course was given for the first time and all material was newly prepared. The aim of the course was to give a broad overview of the problems and methods studied in the field of artificial intelligence to enable students to develop systems that utilize artificial intelligence.
  • Summary:
    12 lectures were held and most of them were followed by more than 60% of students. During the lectures, students were posing questions but more interaction has to be encouraged next year. Students were supposed to read the book on their own in parallel with lectures.

    During the course, students were given a number of project proposals that embody some of the concepts presented in the course. They were supposed to choose and complete one of them. Course instructors provided help and discussion once a week according to the timetable posted on the course web. Students were given feedback regarding their ideas toward solutions. The main goal was not to necessarily come up with completely new solutions to problems: students had to show that they learned course related material and had the opportunity to gain relevant AI experience in the process. The deliverables included a written report, describing the approach and results and an oral presentation during the final week of the term. Projects were graded (U, 3,4,5) and they accounted for 50% of the final course grade. It was required that they were performed in groups of 3 or 4 students.

    Results of students evaluation:

    11 students filled in the evaluation.
  • Course level:
    Most students think that the course level was medium. Since it is an introductory course, they felt that their prior knowledge was suitable to follow the course.
  • Planned changes:
    Homeworks will be described more clearly. The text in the study handbook will be changed so that an oral examination will be performed in connection to the project presentations. One more homework related to the statistical methods will be added to the course and project proposals announced at the beginning of the course.
  • How difficult was this course?

    1. 17% (3 st) Easy.
    2. 44% (8 st) Medium.
    3. 0% (0 st) Diffucult.

  • Was the aim of the course clear from the beginning?

    1. 39% (7 st) Yes.
    2. 6% (1 st) Not sure.
    3. 17% (3 st) No.

  • Was the course interesting and meaningful?

    1. 11% (2 st) Very much.
    2. 39% (7 st) Yes.
    3. 6% (1 st) Neutral.
    4. 0% (0 st) Not particularly.
    5. 6% (1 st) No.

  • Prerequisites for the course were courses in numerics and statistics. Do you think that your prior knowledge on this topics was enough to follow the course?

    1. 56% (10 st) Yes.
    2. 6% (1 st) Not sure.
    3. 0% (0 st) No.

  • Do you find course book by Russell and Norvig suitable?

    1. 33% (6 st) Yes.
    2. 6% (1 st) Not sure.
    3. 6% (1 st) No.
    4. 17% (3 st) Did not buy the book.

  • How many lectures did you attend?

    1. 0% (0 st) Less than 30%.
    2. 0% (0 st) 30-60%.
    3. 11% (2 st) 60-80%.
    4. 50% (9 st) More than 80%.

  • What do you think about the quality of teaching? Were the topics clearly presented?

    1. 6% (1 st) Very good
    2. 33% (6 st) Good.
    3. 11% (2 st) Acceptable.
    4. 6% (1 st) Not so good.
    5. 6% (1 st) Bad.
    6. 0% (0 st) Did not attend.

  • Did you read the relevant book chapters before they were presented at the lectures?

    1. 0% (0 st) Yes, always.
    2. 0% (0 st) Sometimes.
    3. 22% (4 st) Rearly.
    4. 39% (7 st) Never.

  • How much time did you spend on homework 1?

    1. 11% (2 st) Less than 2 hours.
    2. 33% (6 st) 2-5 hours.
    3. 17% (3 st) More than 5 hours.

  • How much time did you spend on homework 2?

    1. 6% (1 st) Less than 2 hours.
    2. 39% (7 st) 2-5 hours.
    3. 17% (3 st) More than 5 hours.

  • How much time did you spend on the project?

    1. 0% (0 st) Less than 10 hours.
    2. 11% (2 st) 10-20 hours.
    3. 44% (8 st) More than 20 hours.

  • How many other courses did you attend in parallel to this course?

    1. 28% (5 st) One.
    2. 17% (3 st) Two .
    3. 17% (3 st) Three.
    4. 0% (0 st) More than three.

  • This is a 4p course. Compared to other similar courses, is 4p suitable?

    1. 39% (7 st) 4p is OK.
    2. 6% (1 st) Should be less than 4p.
    3. 17% (3 st) Should be more than 4p.

    5 things you liked/appreciated about the course:

    organisation of the course
    1. real examples in the Robotic part
    2. concrete homeworks and project
    3. three different teachers

    1.- no exam: i thing homework and project is enough, and more considered the lack of time.
    2. english

    interesting course.
    very easy to pass. hours/credit was very low.
    fun homeworks and project.

    vissa intressanta saker videorna på projektorn övningarna med hela klassen (lekar) som visar upp intressanta fenomen, men dom är inte heller så sammanhängande med kursen..
    - content in general
    - patric's lectures
    - examples
    - relations to the practice
    - project instead of written exam

    It was great to finally get a fundamental ai-course to the main campus!
    I think the course would profit from being split up into two more detailed courses.
    I would have greatly appreciated some guest-lecturers from the industry coming to speak on topics like: expert systems, computer game ai and so on, but in a course with this much information there is no possibility of this.

    Still a very interesting course!

    5 things you would like to see changed next year:

    actualy when i sign me for the course i thought will be much more interesting and practical,we need to have basic knowledge , but anyway could be more modern:)) i mean the problem with vacuum clean agent for example is maybe main, but already everything is said almost 10 years ago.
    1. the teachers should talk more about their backgrounds in the field of A.I.
    2. more concrete examples
    3. what should we remember from this course ? Is it just a global overview ?

    * Gå igenom färre kapitel ur boken, men mer i detalj.
    * Fler exempel på tillämpningar av olika delar (inte bara de i boken)
    * Inget överlappande av inlämningsuppgifter/projekt. Jobbigt när uppg. 2 kommer ut innan 1an ska vara inne

    1.- i would do this course from september to december.
    improving the lecturing technique (see above).
    more material that is not just copied right from the book.
    how does sl trafikupplysning work?
    what AI is used in robotics?
    in danis stuff?
    how does the NASA spacecraft use AI?

    more detailed instructions on the homeworks.

    för lite av sååå mycket, allt är så osammanhängande och mycket är av lite intresse, vad har familjerelationer att göra med robotars sett att se omgivningen ?? inget av ämnena koncentrerade vi oss på kontkret.. att lära oss det vi har lärt oss om robotar kan förklaras på 10 minuter och det jag inte redan kunde skulle ta 1 minut, introduktionen har inte varit så informationsrik man skulle då ha sett att det är mycket som inte hör ihop och mycket saker borde inte ha varit med ens. ni kanske borde ha specifierat också att kursen inte har något att göra med själva intelligensen för det första. lite historia, spel, introduktion till csp, lite om csp regler, lite om robotar osv och slut... jag skulle ha gärna lärt mig mer om robotar och machine vision.. projektet var bra men man får inte flexa vingarna, för det skulle ha tagit längre tid, och att arbeta i grupp är inte så givande, speciellt om man inte känner nån tidigare till exempel på grund av att dom man råkar hamna i inte är... på samma frekvens som du.
    tack för att ni är kunniga.

    referens kod: 4511932

    - leave some chapters and present the others deeper
    - better slides in the lectures

    As noted above.