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Canadian Initiative for Distance Education Research - CIDER

Canadian Initiative for Distance Education Research - CIDER

Owner: Terry Anderson

Group members: 38


The Canadian Initiative for Distance Education Research (CIDER) is a research initiative of the Centre for Distance Education, Canada's largest graduate and professional distance education programming provider, at Athabasca University, Canada's Open University.

CIDER sponsors a variety of professional development activities designed to increase the quantity and quality of distance education research. CIDER's professional development scope is broad, ranging from learning and teaching application, issues of finance and access, the strategic use of technology in distance education settings, and other factors that influence distance education in Canada.

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Latest session: April 1 2015

Stanford researchers have found that brief web-based interventions with high school students can produce big results in their schoolwork and their appreciation of a positive, purposeful mindset. Stanford University
April 29, 2015 - 3:37pm
IT is simultaneously more challenging, relevant, and exciting than ever; leading IT requires unique characteristics and capabilities. But what qualities make for a successful IT leader in this environment? EDUCAUSE
April 29, 2015 - 3:33pm
YouTube is saying good-bye to its past and many aging tablets, smartphones, and set-top boxes are going to be caught in the cross-fire. If you’ve got a first generation iPad, anything older than an iPhone 4, or a second-generation Apple TV or older, your device’s built-in YouTube app will stop working soon. TechHive  
April 26, 2015 - 9:53pm
These days, logic games aren’t all crosswords and pairs matching, especially not on mobile devices. Dozens of challenging and engaging puzzles, games, and brain teasers are available, and a surprising number are free—either fully or via trial versions. eSchool News
April 26, 2015 - 9:41pm

Next session: May 6 2015

The popularity of online programs that educational institutions offer is continuously increasing at varying degrees, with the major demand coming from adult learners who have no opportunity to access traditional education. These adult learners have to be sufficiently ready and competent for online learning, and have their own varied expectations from the online learning process. Hence, this mixed method study is conducted to explore the participants’ readiness and expectations at the beginning and their satisfaction levels at the end of an online learning experience. An e-readiness scale and an e-satisfaction scale was administered as quantitative measures, with open-ended questions gathering qualitative data. Participants of the research were registered to different e-learning programs at Ankara University Distance Education Center, Turkey, during the 2013-2014 academic year. Analysis of both quantitative and qualitative data revealed facts about online learners, which should prove useful to both e-instructors and e-program administrators.
Wed, 15 Apr 2015
Mobile learning (mLearning) in the open and distance learning landscape, holds promise and provides exciting new opportunities. In order to understand and embrace these opportunities within various contexts and circumstances it is imperative to understand the essence of the phenomenon. In this regard, we first need to understand the core fundamentals of mLearning and gain insight in what mLearning entails.

Using critical reflection, this paper clarifies what mLearning is by invalidating myths and misperceptions related to mLearning. Acknowledging the lessons learnt through past experience, the authors then explore the opportunities that mLearning provides. mLearning challenges and risks are discussed to assist those who are keen to embrace these opportunities, in avoiding unnecessary risks and pitfalls. The paper concludes by sharing a few thoughts on the future of mLearning.

These perspectives on mLearning seek to provide an overview of what mobile learning entails, recognise the achievements of mobile learning to date, and stimulate an appetite to embrace the opportunities in open and distance learning, while minimising the potential negative effects of technological, social and pedagogical change.
Wed, 15 Apr 2015

Mining social web data is a challenging task and finding user interest for personalized and non-personalized recommendation systems is another important task. Knowledge sharing among web users has become crucial in determining usage of web data and personalizing content in various social websites as per the user’s wish. This paper aims to design a framework for extracting knowledge from web sources for the end users to take a right decision at a crucial juncture. The web data is collected from various web sources and structured appropriately and stored as an ontology based data repository. The proposed framework implements an online recommender application for the learners online who pursue their graduation in an open and distance learning environment. This framework possesses three phases: data repository, knowledge engine, and online recommendation system. The data repository possesses common data which is attained by the process of acquiring data from various web sources. The knowledge engine collects the semantic data from the ontology based data repository and maps it to the user through the query processor component. Establishment of an online recommendation system is used to make recommendations to the user for a decision making process. This research work is implemented with the help of an experimental case study which deals with an online recommendation system for the career guidance of a learner. The online recommendation application is implemented with the help of R-tool, NLP parser and clustering algorithm.This research study will help users to attain semantic knowledge from heterogeneous web sources and to make decisions.

Wed, 15 Apr 2015
The aim of this study is to examine validity and reliability of Community of Inquiry Scale commonly used in online learning by the means of Item Response Theory. For this purpose, Community of Inquiry Scale version 14 is applied on 1,499 students of a distance education center’s online learning programs at a Turkish state university via internet. The collected data is analyzed by using a statistical software package. Research data is analyzed in three aspects, which are checking model assumptions, checking model-data fit and item analysis. Item and test features of the scale are examined by the means of Graded Response Theory. In order to use this model of IRT, after testing the assumptions out of the data gathered from 1,499 participants, data model compliance was examined. Following the affirmative results gathered from the examinations, all data is analyzed by using GRM. As a result of the study, the Community of Inquiry Scale adapted to Turkish by Horzum (in press) is found to be reliable and valid by the means of Classical Test Theory and Item Response Theory.
Wed, 15 Apr 2015

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