How to blend your ifolio course – Video guide.
30 Saturday Sep 2017
30 Saturday Sep 2017
24 Thursday Aug 2017
Posted Allah Selamatkan Kami, How-To, To Know UKM is to Love UKM :p, Web2.0
in07 Wednesday Jun 2017
Click On The Above Image To Download
Courtesy of DR. KAMARUL BARAINI BINTI KELIWON
PENYELARAS E-PEMBELAJARAN 2017
FAKULTI EKONOMI & PENGURUSAN
15 Monday May 2017
How To Use Camtasia Studio
Sample – Zoom-In
Sample – Call Outs – Sketch Box, Blur & Text.
Sample – Blue Screen Removal To Add Own Pics
Original source of the lyrics with blue screen.
Materials for 17/5/17 exercise;
– Blue screen removal
– Track 1
– Track 2
– Screencast-o-matic
– Jing
– SnagIt
17 Monday Apr 2017
31 Friday Mar 2017
Topic 1: Introduction to MOOC. (5/4/2017 am & 3/5/2017 pm)
– Starts with an overview of MOOC and how it is applied in UKM.
– Creating a MOOC account
– downloadable slides
– Creating thumbnail and banner using PowerPoint
– downloadable slides
– Creating a MOOC Course – access, description, various subtopics of your course.
– downloadable slides
– Creating your course certificate.
– downloadable slides
– Getting your MOOC course listed
– downloadable slides
27 Friday Jan 2017
25 Friday Mar 2016
1. First log-in into iFolio using the latest Chrome or Mozilla browser;
2. Choose the course/module that you want to add the assignment to; i.e. FK6163;
4. Click on the “+ New Task” symbol on the top right corner of the screen;
5. Type in the name of the assignment, tick the boxes for “assignment”, “filedrop” and “publish”, then fill in the details about the assignment. Then click the “Save” button on the top right corner of the screen.
23 Wednesday Mar 2016
This exercise was prepared for the year 3 to year 5 module heads of PPUKM, to train them on how to tabulate the marks.
For the Excel exercise, 3 sets of dummy data were prepared before hand. Please download these data sets into your computer before following the exercise below.
EMIÂ 30%
OBAÂ 30%
MEQÂ 40%
16 Thursday Apr 2015
Posted How-To
inPart 4
This article is the fourth in this series of assessing the validity & reliability of examination questions. The first three were published earlier last week in the same blog. Kindly read these before going through this blog article;
This blog post is a continuation of the discussion from the third article. If you have done all the necessary due diligence as stated in that article and yet you have a large number of failure (or too many students with distinctions), maybe the questions were not suitable for the students. Maybe the questions were more appropriate for the postgraduate students rather than for the undergraduate students or vice-versa. How to check for that, whether the questions were appropriate for these students?
For that, we can use Rasch.
Yeah, I know what’s on your mind right now. What is Rasch?
I asked that very same question way back in 2011.
The Rasch model, named after Georg Rasch, is a psychometric model for analyzing categorical/ordinal data, such as respondents’ answers to a set of questions. Based on the answers given, we can measure the every respondent’s level of ability and the difficulty of each questions/items in that set of questions.
Those active in the education research in UKM had been using Rasch Model for quite a while but it has never been heard of in the UKM medical field. I only knew of it because I happened to ride together with two Rasch’s experts, Prof. Trevor Bond and Dr Zali Mohd. Later I endured two courses on Rasch, one by Dr Saidfudin Mas’udi and the other by Prof. Trevor Bond himself, but I have yet to be enlightened.
So please bear with me as I try to demonstrate the basic Rasch Model in this blog post. Basically “it is the blind leading the blind”, but I know that someone in my audience will correct me of any gross error.
Rasch Analysis is conducted using Winsteps and Facets. In this example, I would be using Winsteps.
First we have to import the data from SPSS into Winsteps format. We will use the same dataset that we used in the earlier blog posts.
Upon successfully converting the data into Winsteps format, we open the file in Winsteps application, then press the “Enter” key twice. It will generate the convergence and fit statistics table as illustrated below.
From the fit statistics, the table has separate tables for “Person” and “Item”. You can clearly see that there are 22 respondents (person) and 30 questions (item). However the item-mean-measure (the red circle in the above image) has a value of “-0.11”. So there is a slight item-misfit here. It should be “0”. The usual practice is to omit the misfitting item (question) and run the analysis again. But we are going to ignore that for the time being since the value is quite small, very near to zero.
If we click on the menu “Diagnosis” and “Output Tables”, there are a variety of commands than we can access. For Diagnosis, thet are tagged from A to H. For Output Tables, they are tagged using numbers but they are NOT ARRANGED in chronological order.
I am just going to focus on a few output tables that are pertinent to our aim, which is whether the items (questions) were appropriate for the persons (students).
The first output table of interest is the Guttman Scalogram. That is the output table tagged with the number 22 in the image below.
The Guttman Scalogram output looks like this image below;
It really looks like a mess of numbers and letters. So allow me to put in some labels to explain the scalogram.
At the top are the items (questions). They are arranged from the easiest items on the left side to the most difficult ones on the right side. So question 8 (DI of 100) is the easiest item and question 27 (DI of 31.82) is the most difficult item.
So Rasch automatically arranged the items by their level of difficulty, from left to right in the scalogram. No need to mess around using Excel and SPSS 😉
Remember this diagram from the Excel & SPSS? It helps you to understand on what basis the items are arranged from left to right.
It also arranges the persons (students) from the smartest to the poorest, from top to bottom. You can see that clearly in the earlier Guttman scalogram. So A is the smartest student who scored 30 out of 30, while V is the poorest student who scored only 12 out of 30.
 Sorry for not continuing writing this. Instead I will share my slides.
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