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Journal Issue
Volume 6 Issue 3 / Oct 2008  pp161‑254

Editor: Shirley Williams, Laura Czerniewicz

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Developing Critically Thoughtful, Media‑Rich Lessons in Science: Process and Product  pp161‑170

Philip Balcaen

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Distinguishing the Field of Educational Technology  pp171‑178

Laura Czerniewicz

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IT Worked for Us: Online Strategies to Facilitate Learning in Large (Undergraduate) Classes  pp179‑188

F. Greyling, M. Kara, A. Makka, S. van Niekerk

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Personal Learning Journal — Course Design for Using Weblogs in Higher Education  pp189‑196

Stefanie Hain, Andrea Back

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The eLIDA CAMEL Nomadic Model of Collaborative Partnership for a Community of Practice in Design for Learning  pp197‑206

Jill Jameson

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Digital Literacies in the Lives of Undergraduate Students: Exploring Personal and Curricular Spheres of Practice  pp207‑216

Sylvia Jones, Mary R. Lea

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Navigating the e‑Learning Terrain: Aligning Technology, Pedagogy and Context  pp217‑226

Mandia Mentis

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Reinventing Papert's Constructionism — Boosting Young Children's Writing Skills with e‑Learning Designed for Dyslexics  pp227‑234

Karin Tweddell Levinsen

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A Data Warehouse Model for Micro‑Level Decision Making in Higher Education  pp235‑244

Liezl van Dyk

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Abstract

An abundance of research, by educational researchers and scholars of teaching and learning alike, can be found on the use of ICT to plan design and deliver learning activities and assessment activities. The first steps of the instructional design process are covered quite thoroughly by this. However, the use of ICT and quantitative methods to close the instructional design cycle by supporting sustainable decision making with respect to the evaluation of the effectiveness of teaching processes hold much unleashed potential. In this paper a business intelligence approach is followed in an attempt to take advantage ICT to enable the evaluation of the effectiveness of the process of facilitating learning. The focus is on micro‑level decision support based on data drawn from the Learning Management System (LMS). Three quantifiable measures of online behaviour and three quantifiable measures of teaching effectiveness are identified from literature to arrive at a 3x3 matrix according to which 9 measures of e‑teaching effectiveness can be derived by means of pair‑wise correlation. The value and significance of information are increased within context of other information. In this paper it is shown how the value of LMS tracking data increases within context of data from other modules or others years and that useful information is created when this tracking data is correlated with measures of teaching effectives such as results, learning styles and student satisfaction. This information context can only be created when a deliberate business intelligence approach if followed. In this paper a data warehouse model is proposed to accomplish exactly this. 

 

Keywords: learning management system, data warehouse, student tracking, decision support, student feedback, learning styles

 

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Technology‑Assisted Reading for Improving Reading Skills for young South African Learners  pp245‑254

Gerda van Wyk, Arno Louw

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