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<strong>TOJET</strong>: The <strong>Turkish</strong> Online Journal <strong>of</strong> Educational Technology – October <strong>2012</strong>, volume 11 Issue 4<br />

4. Dynamic Real-Time based Learning Effort Quantification Technique<br />

Learning effort (Hsu et al, 2009, Hsu & Chang, 2011) is developed based on cognition load <strong>the</strong>ory (Sweller,<br />

1990) and dynamic assessment <strong>the</strong>ory (Allal & Ducrey, 2000). Learning effort with positive value represents<br />

ascending learning effort, and learning effort with negative value represents descending learning effort. Dynamic<br />

real-time based learning effort quantification technique (Hsu et al, 2009, Hsu & Chang, 2011) is developed as a<br />

dynamic real-time based quantification technique based on learning effort, RAT- Rapid Assessment Test (<br />

Kalyuga & Sweller, 2004) and cognition efficiency <strong>the</strong>ory (Kalyuga & Sweller, 2005). It was utilized to convert<br />

learning records into learning effort numerical data in this study.<br />

5. Learning Effort Curve<br />

The learning effort numerical data, which is converted from learning records by <strong>the</strong> dynamic real-time based<br />

learning effort quantification technique, is a two dimensional numerical data that can be transformed to a visual<br />

graphic information called learning effort curve (Hsu et al, 2009, Hsu & Chang, 2011). Refer to Figure 2,<br />

learning effort is increasing from learning unit 1 to 4, which presents a learner tends towards learning effort<br />

growth. Learning effort is decreasing from learning unit 4 to 6, which presents a learner tends towards<br />

descending learning effort.<br />

learning unit<br />

Figure 2. Learning effort curve<br />

Procedure<br />

The research structure is shown in Figure 3. The detail procedure is shown as following:<br />

Learning<br />

performan<br />

ce<br />

learning effort<br />

8<br />

6<br />

4<br />

2<br />

Learning<br />

efficiency<br />

Learning<br />

style<br />

Selfefficacy<br />

Learning<br />

effort<br />

1 2 3 4 5 6<br />

Learning<br />

effort<br />

quantificati<br />

Learning<br />

effort curve<br />

Normalized<br />

Learning<br />

effort curve<br />

Adaptive<br />

learning path<br />

& learning<br />

Learning<br />

effort curve<br />

mode<br />

Learning<br />

progress<br />

diagnosis<br />

database<br />

Future<br />

R h<br />

Figure 3. Research structure<br />

Personalized<br />

adaptive elearning<br />

platform<br />

Copyright © The <strong>Turkish</strong> Online Journal <strong>of</strong> Educational Technology<br />

213

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