Good Luck to all my students GGGE 3143...
wish all of u doing well in ur xm...
regards
tuanmastura
Showing posts with label Teaching Learning TRaining and Evaluation. Show all posts
Showing posts with label Teaching Learning TRaining and Evaluation. Show all posts
Friday, 22 June 2012
Tuesday, 8 May 2012
IERSW 2012
attended IERSW 2012 at USM Penang...5-7 May 2012...
People are illogical, unreasonable and self-centered. LOVE and TRUST them anyway...
The good you do today will be forgotten tomorrow. Do GOOD anyway...
Honesty and frankness make you vulnerable. Be HONEST and FRANK anyway...
The biggest people with the biggest ideas can be shot down by the smallest people with the smallest minds. Think BIG anyway.
What you spend years building maybe destroyed overnight. BUILD anyway.
Give the world the best you have, and you may get kicked in the teeth. Give the WORLD your BEST anyway...
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| registration!!! |
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| the panels... |
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| presenters... |
People are illogical, unreasonable and self-centered. LOVE and TRUST them anyway...
The good you do today will be forgotten tomorrow. Do GOOD anyway...
Honesty and frankness make you vulnerable. Be HONEST and FRANK anyway...
The biggest people with the biggest ideas can be shot down by the smallest people with the smallest minds. Think BIG anyway.
What you spend years building maybe destroyed overnight. BUILD anyway.
Give the world the best you have, and you may get kicked in the teeth. Give the WORLD your BEST anyway...
(Prof Datuk Dr Ibrahim Bajunid, Collumnist...NST, Friday, March 23, 2012...)....
Tuesday, 17 April 2012
Observe practical students
just nak share regarding observe practical students...follow Prof Subahan to observe his students..
Venue: SMK Maahad Hamidiah, Kajang
Time:10.35-12.35
Practical Students: Mohd Arif (Physics), Asnarita (TESL), Aimi (Chemistry)
yang betul2 observe hanya Arif and Asnarita...Aimi Prof Subahan yang observe. masa tue tengah observe Arif.
quiet interesting...coz sebelum nie, hanya follow je Dr or Prof observe...xbrpe nak critic...but for today, also contribute something...comment to them where the teaching method inappropriate...unnecessary thing...unrelated matter...or something that they should stress out while teaching...having discussion with them after the observing process...
hope this also will guide me later on in my teaching...insyaallah...
Tuesday, 10 April 2012
Berita Harian Online | Dasar baru jadikan ICT peneraju pendidikan
Berita Harian Online | Dasar baru jadikan ICT peneraju pendidikan
Dasar baru jadikan ICT peneraju pendidikan
Oleh Magendran Rajagopal
magendran@bharian.com.my
2010/10/13Usaha lahir generasi berilmu bertaraf antarabangsa
PUTRAJAYA: Timbalan Perdana Menteri, Tan Sri Muhyiddin Yassin, berkata Dasar Teknologi Maklumat dan Komunikasi Dalam Pendidikan akan menjadikan teknologi maklumat dan komunikasi (ICT) sebagai pengupaya utama dalam proses pengajaran dan pembelajaran.
Muhyiddin yang juga Menteri Pelajaran, berkata langkah itu meningkatkan kualiti pendidikan dan melahirkan generasi berilmu serta berupaya menyumbang ke arah pembangunan negara.
“Dasar ini kesinambungan daripada inisiatif Sekolah Bestari yang menekankan penggunaan teknologi sebagai wahana menggalakkan perkembangan daya kreativiti, pembelajaran secara bekerjasama, pemikiran kritis dan penyelesaian masalah.
“Dasar ini menggabung dan menyelaraskan semua inisiatif ICT sedia ada seperti SchoolNet, Makmal Komputer, EduWebTV, Pusat Akses dan apa jua inisiatif ICT yang dilaksanakan pada masa depan dengan tujuan meningkatkan pencapaian murid,” katanya ketika melancarkan dasar itu di sini, semalam.
Hadir sama Ketua Pengarah Pelajaran, Tan Sri Alimuddin Mohd Dom; Timbalan Ketua Setiausaha (Pengurusan) Kementerian Pela-jaran, Dr Rosli Mohamad dan Ketua Pegawai Eksekutif Perbadanan Kemajuan Multimedia (MDeC), Datuk Badlisham Ghazali.
Difahamkan, dasar itu dilancar berikutan kajian Unit Perancang Ekonomi (EPU) Jabatan Perdana Menteri yang melaporkan Pelan Induk Pembangunan Pendidikan 2006-2010 tidak menyatakan secara khusus peranan ICT sebagai pengupaya proses pengajaran dan pembelajaran yang berkesan.
EPU turut menyifatkan pelaburan RM6.1 bilion bagi inisiatif ICT untuk tempoh 1999 hingga 2009 sebagai tidak memberikan pulangan setimpal kepada pembangunan modal insan negara.
Muhyiddin berkata, dasar itu akan menjadikan amalan di negara maju sebagai penanda aras untuk memastikan komponen ICT dalam pendidikan mampu mencapai piawaian antarabangsa.
Katanya, dengan menjadikan dasar itu sebagai rujukan, pelaksanaan semua program ICT di kementerian menjurus kepada sasaran yang sama iaitu mempertingkatkan pencapaian murid dan memastikan setiap murid mempunyai akses kepada pendidikan yang berkualiti.
Empat asas menjadi teras dasar iaitu pembangunan modal insan berterusan, penggunaan teknologi yang sesuai bagi mengintegrasikan inisiatif ICT sedia ada dalam pendidikan, proses pengajaran dan pembelajaran dan pengurusan pendidikan menggunakan ICT.
Thursday, 29 March 2012
xcukup tido...
hahaha....
marking paper xsiap...
2 tutorial to mark...
tutorial 2 completed last night, but tutorial 1 will start after this...
this afternoon the class..
huhu...
hopefully will complete it before class...
actually have talk at ANGKASA, FKAB...but cannot make it...
sorry yah...
if not, bleh jumpa DR SMS...
c u next time la...
Wednesday, 28 March 2012
Levels of Measurement
The
level of measurement refers to the relationship among the values that are
assigned to the attributes for a variable. What does that mean? Begin with the
idea of the variable, in this example "party affiliation." That
variable has a number of attributes. Let's assume that in this particular
election context the only relevant attributes are "republican",
"democrat", and "independent". For purposes of
analyzing the results of this variable, we arbitrarily assign the values 1, 2
and 3 to the three attributes.
The level of measurement describes the relationship among these three values. In this case, we simply are using the numbers as shorter placeholders for the lengthier text terms. We don't assume that higher values mean "more" of something and lower numbers signify "less". We don't assume the the value of 2 means that democrats are twice something that republicans are. We don't assume that republicans are in first place or have the highest priority just because they have the value of 1. In this case, we only use the values as a shorter name for the attribute. Here, we would describe the level of measurement as "nominal".
Why is Level of Measurement Important?
First, knowing the level of measurement helps you decide how to interpret the data from that variable. When you know that a measure is nominal (like the one just described), then you know that the numerical values are just short codes for the longer names. Second, knowing the level of measurement helps you decide what statistical analysis is appropriate on the values that were assigned. If a measure is nominal, then you know that you would never average the data values or do a t-test on the data.
There are typically four levels of measurement that are defined:
In nominal measurement the numerical values just "name" the attribute uniquely. No ordering of the cases is implied. For example, jersey numbers in basketball are measures at the nominal level. A player with number 30 is not more of anything than a player with number 15, and is certainly not twice whatever number 15 is.
In ordinal measurement the attributes can be rank-ordered. Here, distances between attributes do not have any meaning. For example, on a survey you might code Educational Attainment as 0=less than H.S.; 1=some H.S.; 2=H.S. degree; 3=some college; 4=college degree; 5=post college. In this measure, higher numbers mean more education. But is distance from 0 to 1 same as 3 to 4? Of course not. The interval between values is not interpretable in an ordinal measure.
In interval measurement the distance between attributes does have meaning. For example, when we measure temperature (in Fahrenheit), the distance from 30-40 is same as distance from 70-80. The interval between values is interpretable. Because of this, it makes sense to compute an average of an interval variable, where it doesn't make sense to do so for ordinal scales. But note that in interval measurement ratios don't make any sense - 80 degrees is not twice as hot as 40 degrees (although the attribute value is twice as large).
Finally, in ratio measurement there is always an absolute zero that is meaningful. This means that you can construct a meaningful fraction (or ratio) with a ratio variable. Weight is a ratio variable. In applied social research most "count" variables are ratio, for example, the number of clients in past six months. Why? Because you can have zero clients and because it is meaningful to say that "...we had twice as many clients in the past six months as we did in the previous six months."
It's important to recognize that there is a hierarchy implied in the level of measurement idea. At lower levels of measurement, assumptions tend to be less restrictive and data analyses tend to be less sensitive. At each level up the hierarchy, the current level includes all of the qualities of the one below it and adds something new. In general, it is desirable to have a higher level of measurement (e.g., interval or ratio) rather than a lower one (nominal or ordinal).
The level of measurement describes the relationship among these three values. In this case, we simply are using the numbers as shorter placeholders for the lengthier text terms. We don't assume that higher values mean "more" of something and lower numbers signify "less". We don't assume the the value of 2 means that democrats are twice something that republicans are. We don't assume that republicans are in first place or have the highest priority just because they have the value of 1. In this case, we only use the values as a shorter name for the attribute. Here, we would describe the level of measurement as "nominal".
Why is Level of Measurement Important?
First, knowing the level of measurement helps you decide how to interpret the data from that variable. When you know that a measure is nominal (like the one just described), then you know that the numerical values are just short codes for the longer names. Second, knowing the level of measurement helps you decide what statistical analysis is appropriate on the values that were assigned. If a measure is nominal, then you know that you would never average the data values or do a t-test on the data.
There are typically four levels of measurement that are defined:
- Nominal
- Ordinal
- Interval
- Ratio
In nominal measurement the numerical values just "name" the attribute uniquely. No ordering of the cases is implied. For example, jersey numbers in basketball are measures at the nominal level. A player with number 30 is not more of anything than a player with number 15, and is certainly not twice whatever number 15 is.
In ordinal measurement the attributes can be rank-ordered. Here, distances between attributes do not have any meaning. For example, on a survey you might code Educational Attainment as 0=less than H.S.; 1=some H.S.; 2=H.S. degree; 3=some college; 4=college degree; 5=post college. In this measure, higher numbers mean more education. But is distance from 0 to 1 same as 3 to 4? Of course not. The interval between values is not interpretable in an ordinal measure.
In interval measurement the distance between attributes does have meaning. For example, when we measure temperature (in Fahrenheit), the distance from 30-40 is same as distance from 70-80. The interval between values is interpretable. Because of this, it makes sense to compute an average of an interval variable, where it doesn't make sense to do so for ordinal scales. But note that in interval measurement ratios don't make any sense - 80 degrees is not twice as hot as 40 degrees (although the attribute value is twice as large).
Finally, in ratio measurement there is always an absolute zero that is meaningful. This means that you can construct a meaningful fraction (or ratio) with a ratio variable. Weight is a ratio variable. In applied social research most "count" variables are ratio, for example, the number of clients in past six months. Why? Because you can have zero clients and because it is meaningful to say that "...we had twice as many clients in the past six months as we did in the previous six months."
It's important to recognize that there is a hierarchy implied in the level of measurement idea. At lower levels of measurement, assumptions tend to be less restrictive and data analyses tend to be less sensitive. At each level up the hierarchy, the current level includes all of the qualities of the one below it and adds something new. In general, it is desirable to have a higher level of measurement (e.g., interval or ratio) rather than a lower one (nominal or ordinal).
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