| Faculty Member: | KAN MIN-YEN | ||
| Department: | COMPUTER SCIENCE | Academic Year: | 2007/2008 |
| Faculty: | SCHOOL OF COMPUTING | Semester: | 1 |
| Module: | FOUNDATIONS OF ARTIFICIAL INTELLIGENCE - CS3243 |
| Activity Type: | LECTURE |
| Class Size / Response Size / Response Rate : | 56 / 30 / 53.57% |
| Qn | Items Evaluated | Fac. Member Avg Score | Fac. Member Avg Score Std. Dev | Dept Avg Score | Fac. Avg Score |
|---|---|---|---|---|---|
| (a) (b) | (c) (d) | ||||
| 1 | The teacher has enhanced my thinking ability. | 4.067 | 0.691 | 3.923 ( 3.850) | 3.902 ( 3.903) |
| 2 | The teacher provides timely and useful feedback. | 4.200 | 0.805 | 3.895 ( 3.848) | 3.899 ( 3.919) |
| 3 | The teacher is approachable for consultation. | 4.133 | 0.681 | 3.912 ( 3.940) | 3.921 ( 3.999) |
| 4 | The teacher has helped me develop relevant research skills.* | NA | NA | NA | NA |
| 5 | The teacher has increased my interest in the subject. | 4.167 | 0.791 | 3.783 ( 3.754) | 3.780 ( 3.815) |
| 6 | The teacher has helped me acquire valuable/relevant knowledge in the field. | 4.167 | 0.834 | 3.946 ( 3.903) | 3.957 ( 3.957) |
| 7 | The teacher has helped me understand complex ideas. | 4.067 | 0.740 | 3.854 ( 3.805) | 3.842 ( 3.845) |
| Average of Qn 1-7** | 4.133 | 0.750 | 3.886 ( 3.850) | 3.884 ( 3.906) | |
| 8 | Overall the teacher is effective. | 4.167 | 0.699 | 3.987 ( 3.884) | 3.981 ( 3.952) |
| Nos. of Respondents(% of Respondents) |
| | | ||||||
ITEM\SCORE | | | 5 | 4 | 3 | 2 | 1 |
| | | ||||||
Self | | | 10 (33.33%) | 15 (50.00%) | 5 (16.67%) | 0 (.00%) | 0 (.00%) |
Teachers teaching all Modules of the Same Activity Type (Lecture), at the same level within Department | | | 141 (20.11%) | 374 (53.35%) | 157 (22.40%) | 22 (3.14%) | 7 (1.00%) |
Teachers teaching all Modules of the Same Activity Type (Lecture), at the same level within Faculty | | | 259 (22.52%) | 627 (54.52%) | 225 (19.57%) | 28 (2.43%) | 11 (.96%) |
Note:
1. A 5-point scale is used for the scores. The higher the score, the better the rating.
2. Fac. Member Avg Score: The mean of all the scores for each question for the faculty member.
3. Fac. Member Avg Score Std. Dev: A measure of the range of variability. It measures the extent to which a faculty member's Average Score differs from all the scores in the faculty member's evaluation. The smaller the standard deviation, the greater the robustness of the number given as average.
4. Dept Avg Score :
(a) the mean score of same activity type (Lecture) within the department.
(b) the mean score of same activity type (Lecture), at the same module level ( level 3000 ) within the department.
5. Fac. Avg Score :
(c) the mean score of same activity type (Lecture) within the faculty.
(d) the mean score of same activity type (Lecture), at the same module level ( level 3000 ) within the faculty.
| Faculty Member: | KAN MIN-YEN | ||
| Department: | COMPUTER SCIENCE | Academic Year: | 2007/2008 |
| Faculty: | SCHOOL OF COMPUTING | Semester: | 1 |
| Module: | FOUNDATIONS OF ARTIFICIAL INTELLIGENCE - CS3243 |
| Activity Type: | LECTURE |
| Q9 | What are the teacher's strengths? |
| 1. | He is very approachable and takes time to explain concepts to students. |
| 2. | Good presentation ability and knowledge of topics. |
| 3. | NA |
| 4. | dedicated lecturer, approachable and friendly |
| 5. | Organize the course well, provide as much as possible learning resources for students. Efficient in lecturing rich knowledge within a short time. |
| 6. | Prof Kan's lecture contains a lot of knowledge, and the way that he explained it is very appealing. I can't imagine that so many difficult content can be taught so clearly in such a short 2hr lecture. |
| 7. | able to answer students' queries clearly to make sure students understand |
| 8. | give clear delivery in lecture. |
| 9. | Explains concepts very clearly Willingness to offer help to students Very approachable, thus making it conducive for students to learn |
| 10. | He has deep understanding of AI. The lecture notes provided are good. |
| Q10 | What improvements would you suggest to the teacher? |
| 1. | Perhaps cut down on material but explain each topic in more depth. |
| 2. | NA |
| 3. | none |
| 4. | lectures are actually hard from a student's perspective, so may be it's better to slow down in lecture, especially when it comes to algorithms. |
| 5. | do not just follow the textbook, pls dun put messy and unsorted lecture notes to ivle! |
| 6. | should amend your notes.. esp the dates... not nice to go with your good teaching abilities. |
| 7. | nil |
| 8. | upload the video version of lecture instead of just the audio version. |
| 9. | - |
| Faculty Member: | KAN MIN-YEN | ||
| Department: | COMPUTER SCIENCE | Academic Year: | 2007/2008 |
| Faculty: | SCHOOL OF COMPUTING | Semester: | 1 |
| Module: | FOUNDATIONS OF ARTIFICIAL INTELLIGENCE - CS3243 |
| Activity Type: | TUTORIAL |
| Class Size / Response Size / Response Rate : | 56 / 29 / 51.79% |
| Qn | Items Evaluated | Fac. Member Avg Score | Fac. Member Avg Score Std. Dev | Dept Avg Score | Fac. Avg Score |
|---|---|---|---|---|---|
| (a) (b) | (c) (d) | ||||
| 1 | The teacher has enhanced my thinking ability. | 4.069 | 0.704 | 3.879 ( 3.945) | 3.864 ( 3.857) |
| 2 | The teacher provides timely and useful feedback. | 4.241 | 0.739 | 3.955 ( 3.978) | 3.952 ( 3.904) |
| 3 | The teacher is approachable for consultation. | 4.207 | 0.774 | 4.073 ( 4.031) | 4.048 ( 3.969) |
| 4 | The teacher has helped me develop relevant research skills.* | NA | NA | NA | NA |
| 5 | The teacher has increased my interest in the subject. | 4.103 | 0.817 | 3.733 ( 3.869) | 3.734 ( 3.790) |
| 6 | The teacher has helped me acquire valuable/relevant knowledge in the field. | 4.103 | 0.772 | 3.902 ( 3.946) | 3.895 ( 3.862) |
| 7 | The teacher has helped me understand complex ideas. | 4.103 | 0.673 | 3.898 ( 3.943) | 3.862 ( 3.843) |
| Average of Qn 1-7** | 4.138 | 0.740 | 3.906 ( 3.952) | 3.892 ( 3.870) | |
| 8 | Overall the teacher is effective. | 4.207 | 0.675 | 3.967 ( 3.997) | 3.959 ( 3.922) |
| Nos. of Respondents(% of Respondents) |
| | | ||||||
ITEM\SCORE | | | 5 | 4 | 3 | 2 | 1 |
| | | ||||||
Self | | | 10 (34.48%) | 15 (51.72%) | 4 (13.79%) | 0 (.00%) | 0 (.00%) |
Teachers teaching all Modules of the Same Activity Type (Tutorial), at the same level within Department | | | 150 (22.35%) | 388 (57.82%) | 118 (17.59%) | 11 (1.64%) | 4 (.60%) |
Teachers teaching all Modules of the Same Activity Type (Tutorial), at the same level within Faculty | | | 215 (19.32%) | 635 (57.05%) | 230 (20.66%) | 27 (2.43%) | 6 (.54%) |
Note:
1. A 5-point scale is used for the scores. The higher the score, the better the rating.
2. Fac. Member Avg Score: The mean of all the scores for each question for the faculty member.
3. Fac. Member Avg Score Std. Dev: A measure of the range of variability. It measures the extent to which a faculty member's Average Score differs from all the scores in the faculty member's evaluation. The smaller the standard deviation, the greater the robustness of the number given as average.
4. Dept Avg Score :
(a) the mean score of same activity type (Tutorial) within the department.
(b) the mean score of same activity type (Tutorial), at the same module level ( level 3000 ) within the department.
5. Fac. Avg Score :
(c) the mean score of same activity type (Tutorial) within the faculty.
(d) the mean score of same activity type (Tutorial), at the same module level ( level 3000 ) within the faculty.
| Faculty Member: | KAN MIN-YEN | ||
| Department: | COMPUTER SCIENCE | Academic Year: | 2007/2008 |
| Faculty: | SCHOOL OF COMPUTING | Semester: | 1 |
| Module: | FOUNDATIONS OF ARTIFICIAL INTELLIGENCE - CS3243 |
| Activity Type: | TUTORIAL |
| Q9 | What are the teacher's strengths? |
| 1. | I think the assignments were really good. Also, the feedback on our submissions was very thorough and helpful. |
| 2. | NA |
| 3. | he's just perfect |
| 4. | Organize the course well, provide as much as possible learning resources for students. Efficient in lecturing rich knowledge within a short time. |
| 5. | his way of conducting tutorial is good. he has his way to memorise the tut question and just iterate thru them during classes. randomly picking students up and having a set of ans solutions to tut qns greatly enhances learning. |
| 6. | ask students questions that are not inside the tutorial, which triggers students to think further. |
| 7. | no |
| 8. | During tutorials, always encouraging students to speak up, and encourage students even though wrong answers are provided. This facilitates students to learn, and not feel bad at providing a wrong answer. |
| 9. | He has deep understanding of AI. The tutorial notes provided are good. |
| 10. | Very thorough. |
| Q10 | What improvements would you suggest to the teacher? |
| 1. | NA |
| 2. | none |
| 3. | - |
| 4. | nil |
| 5. | no |
| 6. | He may want to make the tutorials more interactive and effective. |
| Faculty Member: | KAN MIN-YEN | ||
| Department: | COMPUTER SCIENCE | Academic Year: | 2007/2008 |
| Faculty: | SCHOOL OF COMPUTING | Semester: | 1 |
| Module Code: | CS3243 | No of Nominations: | 7 |
| 1. | he's just perfect. |
| 2. | Prof Kan makes AI 3 times easier than it is. |
| 3. | I like the syllabus which he has set for the semester. Timely feedback from him and he never fail to post some interesting posts on the forum for us to read further indepth into topics which he has covered. |
| 4. | He is able to lecture well, gives examples and walk through them to make sure all the students understands the concepts. He is able to answer the queries given by the students and provides sufficient explanations for them. An approachable and caring lecturer and tutor. |
| 5. | Lecturer is very much approachable. Facilitates students in learning. Lego Assignment given to students allows them room for creativity, and always providing students with encouragement, stimulating student's interest in the subject. A very responsible lecturer. |
| 6. | He has deep understanding of the field he is teaching. He is also closed to students and provide timely help. |