| Faculty Member: | KAN MIN-YEN | ||
| Department: | COMPUTER SCIENCE | Academic Year: | 2010/2011 |
| Faculty: | SCHOOL OF COMPUTING | Semester: | 1 |
| Module: | INTRODUCTION TO ARTIFICIAL INTELLIGENCE - CS3243 | ||
| Activity Type: | LECTURE | ||
| Class Size/Response Size/Response Rate/Contact Session/Teaching Hour : | 103 / 55 / 53.4% / 13 / 26 |
| 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. | 3.891 | 0.089 | 3.995 ( 3.829) | 3.976 ( 3.945) |
| 2 | The teacher provides timely and useful feedback. | 3.945 | 0.075 | 3.961 ( 3.819) | 3.976 ( 3.984) |
| 3 | The teacher is approachable for consultation. | 3.963 | 0.091 | 4.044 ( 3.937) | 4.050 ( 4.109) |
| 4 | The teacher has helped me develop relevant research skills.* | NA | NA | NA | NA |
| 5 | The teacher has increased my interest in the subject. | 3.727 | 0.120 | 3.839 ( 3.728) | 3.845 ( 3.847) |
| 6 | The teacher has helped me acquire valuable/relevant knowledge in the field. | 3.964 | 0.086 | 4.019 ( 3.838) | 4.014 ( 3.963) |
| 7 | The teacher has helped me understand complex ideas. | 3.745 | 0.120 | 3.916 ( 3.740) | 3.909 ( 3.865) |
| Average of Qn 1-7** | 3.872 | 0.079 | 3.959 ( 3.815) | 3.960 ( 3.952) | |
| 8 | Overall the teacher is effective. | 3.909 | 0.079 | 4.021 ( 3.815) | 4.018 ( 3.971) |
* This includes skills in research methodology, research problems/questions, literature search/evaluation, oral presentation and manuscript preparation.
** If Qn 4 is NA, it will not be included in the computation of average score (Average of Qn 1-7).
Frequency Distribution of responses for Qn 8
| Nos. of Respondents(% of Respondents) |
| | | ||||||
ITEM\SCORE | | | 5 | 4 | 3 | 2 | 1 |
| | | ||||||
Self | | | 6 (10.91%) | 39 (70.91%) | 9 (16.36%) | 1 (1.82%) | 0 (.00%) |
Teachers teaching all Modules of the Same Activity Type (Lecture), at the same level within Department | | | 78 (17.81%) | 244 (55.71%) | 86 (19.63%) | 17 (3.88%) | 13 (2.97%) |
Teachers teaching all Modules of the Same Activity Type (Lecture), at the same level within Faculty | | | 207 (24.91%) | 443 (53.31%) | 146 (17.57%) | 20 (2.41%) | 15 (1.81%) |
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: | 2010/2011 |
| Faculty: | SCHOOL OF COMPUTING | Semester: | 1 |
| Module: | INTRODUCTION TO ARTIFICIAL INTELLIGENCE - CS3243 | ||
| Activity Type: | LECTURE | ||
| Q9 | What are the teacher's strengths? |
| 1. | Clear in delivering content. |
| 2. | Really approachable, and gives really nice and quick replies to our queries on the IVLE forums, just like ALL the other SOC lecturers that I've met : ) |
| 3. | Friendly and care about students' problems and concerns |
| 4. | Very good in making student understand concepts |
| 5. | very helpful and interacts with students very much in order to help them to think critically |
| 6. | Good at explaining complex problems, communicates well with students, very open to students not understanding concepts and helping them to understand it. |
| 7. | Clear and simple explanations. Very approachable during consultations. |
| 8. | Friendly, I supposed. I think he is a very strict lecturer with high expectation from his students |
| 9. | Does well to teach concepts, but really gets vague at times. |
| 10. | Clearly explains the concepts, and answers questions well. |
| 11. | Prof. Kan gave interesting lectures. |
| 12. | Interaction with student, well knowledge |
| 13. | N/A |
| 14. | - |
| 15. | American style |
| 16. | Easy-going, respond very fast to student e-mails. |
| 17. | Tries to engage students during lectures. Generally explains concepts quite well. |
| 18. | clear |
| 19. | Good use of illustrations and examples. |
| 20. | As a lecturer, lectures are quite clear with good illustrations. |
| 21. | - |
| 22. | very willing to help weak student like me by re-iterating concepts as a starting point(for assignments) but still gives students opportunity to go on and learn and find out for themselves. |
| 23. | Clear slides to illustrate ideas to be put across. |
| 24. | Well prepared with all the answers to your questions |
| 25. | Friendly. Shows mastery of the subject. Able to explain the subject very clearly and well. |
| Q10 | What improvements would you suggest to the teacher? |
| 1. | More interesting ideas, videos etc. |
| 2. | Maybe its my fault but sometimes I find the pace of coverage too quick and it gets difficult to understand the explanation of the algorithms. That may just be my own problem though. |
| 3. | Give stimulation for Homework with robots since the sensors are not acurate |
| 4. | nil |
| 5. | Lecture pace can be faster at times (esp when the class doesnt participate). |
| 6. | -No comments- |
| 7. | We need clearer explanations! |
| 8. | NA |
| 9. | N/A |
| 10. | None |
| 11. | N/A |
| 12. | - |
| 13. | Too american style. |
| 14. | Improve on the lecture notes. Make it more content, such that it can be used as a revision. |
| 15. | Maybe other methods of engaging students would be more effective? Playing relevant videos and such will be easier to get our attention. |
| 16. | Uploading the tutorial answers decreases the motivation to do the tutorial on your own. Tutorial answers can be uploaded at the end of the semester or after the week's tutorial is over. |
| 17. | As a lecturer, make the lesson more interesting and perhaps do not set tests and exams too difficult as concepts are already hard to understand by themselves. |
| 18. | - |
| 19. | -no comments- |
| 20. | nil. |
| 21. | Speak more laymen terms. |
| 22. | Keep up the good work. |
| Faculty Member: | KAN MIN-YEN | ||
| Department: | COMPUTER SCIENCE | Academic Year: | 2010/2011 |
| Faculty: | SCHOOL OF COMPUTING | Semester: | 1 |
| Module: | INTRODUCTION TO ARTIFICIAL INTELLIGENCE - CS3243 | ||
| Activity Type: | TUTORIAL | ||
| Class Size/Response Size/Response Rate/Contact Session/Teaching Hour : | 56 / 29 / 51.79% / 30 / 30 |
| 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. | 3.966 | 0.116 | 3.927 ( 3.851) | 3.942 ( 3.927) |
| 2 | The teacher provides timely and useful feedback. | 4.034 | 0.105 | 3.972 ( 3.896) | 4.003 ( 4.001) |
| 3 | The teacher is approachable for consultation. | 4.107 | 0.130 | 4.063 ( 3.995) | 4.087 ( 4.080) |
| 4 | The teacher has helped me develop relevant research skills.* | NA | NA | NA | NA |
| 5 | The teacher has increased my interest in the subject. | 3.759 | 0.154 | 3.791 ( 3.790) | 3.813 ( 3.838) |
| 6 | The teacher has helped me acquire valuable/relevant knowledge in the field. | 3.931 | 0.110 | 3.916 ( 3.835) | 3.946 ( 3.914) |
| 7 | The teacher has helped me understand complex ideas. | 3.897 | 0.135 | 3.908 ( 3.823) | 3.923 ( 3.894) |
| Average of Qn 1-7** | 3.948 | 0.105 | 3.928 ( 3.865) | 3.951 ( 3.942) | |
| 8 | Overall the teacher is effective. | 3.966 | 0.105 | 3.975 ( 3.889) | 4.003 ( 3.982) |
* This includes skills in research methodology, research problems/questions, literature search/evaluation, oral presentation and manuscript preparation.
** If Qn 4 is NA, it will not be included in the computation of average score (Average of Qn 1-7).
Frequency Distribution of responses for Qn 8
| Nos. of Respondents(% of Respondents) |
| | | ||||||
ITEM\SCORE | | | 5 | 4 | 3 | 2 | 1 |
| | | ||||||
Self | | | 4 (13.79%) | 20 (68.97%) | 5 (17.24%) | 0 (.00%) | 0 (.00%) |
Teachers teaching all Modules of the Same Activity Type (Tutorial), at the same level within Department | | | 79 (19.95%) | 225 (56.82%) | 71 (17.93%) | 11 (2.78%) | 10 (2.53%) |
Teachers teaching all Modules of the Same Activity Type (Tutorial), at the same level within Faculty | | | 176 (22.80%) | 441 (57.12%) | 131 (16.97%) | 13 (1.68%) | 11 (1.42%) |
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: | 2010/2011 |
| Faculty: | SCHOOL OF COMPUTING | Semester: | 1 |
| Module: | INTRODUCTION TO ARTIFICIAL INTELLIGENCE - CS3243 | ||
| Activity Type: | TUTORIAL | ||
| Q9 | What are the teacher's strengths? |
| 1. | Helps students understand deeper concepts, other than rote questions |
| 2. | Explain the tutorial clearly and give very good brieft summary of lecture |
| 3. | Tutorials are generally excellent. Takes the time and effort to go through the main concepts, and having the students to participate aids learning and recap of the study material. |
| 4. | he makes concepts very easy to understand and apply. a great tutor :) |
| 5. | as above. |
| 6. | NA |
| 7. | N/A |
| 8. | - |
| 9. | clear |
| 10. | As a tutor, conscious effort was made to interact personally with students. Good job. |
| Q10 | What improvements would you suggest to the teacher? |
| 1. | More interactive tutorials |
| 2. | n/a |
| 3. | as above. |
| 4. | NA |
| 5. | N/A |
| 6. | - |
| 7. | As a tutor, can provide clearer solution guides. |
| Faculty Member: | KAN MIN-YEN | ||
| Department: | COMPUTER SCIENCE | Academic Year: | 2010/2011 |
| Faculty: | SCHOOL OF COMPUTING | Semester: | 1 |
| Module Code: | CS3243 | No of Nominations: | 6 |
| 1. | Clear delivery, and dedication to students is evident through the manner in which Prof Kan responds to his students. |
| 2. | A caring and great professor |
| 3. | - Great lecturer, takes the time to go through important concepts during tutorial. - Very approachable. Doors are always open to students with questions. - Responds to queries via email quickly. - Provides excellent teaching materials that helps in revision. |
| 4. | He's a really good lecturer and TA who can make his students understand whatever he had covered for the week. Awesome |
| 5. | Partial and knowledgeable. |
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