Expertise reversal effect in a pen-tablet-based learning environment: The role of learningcentered emotions in the interplay between learner expertise and task complexity

The study investigated interactions between learner expertise and task complexity evaluated from both cognitive and affective perspectives. One hundred and seventy-three students, both novices and advanced learners, were asked to learn Japanese writing in a pen-tablet-based digital learning environment with varying task complexity levels. Cognitive load and learning-centred emotions were measured at intervals during learning, while writing performance was monitored by runtime tracking. Results indicated that while advanced learners performed better than novices across the range of task complexity, the moderate task complexity was shown to be superior in enhancing performance for both levels of expertise. Results for learning-centred emotions showed that advanced learners reported lower enjoyment and higher frustration when completing the low complexity task, whereas the moderately complex task was reported to be the most enjoyable and less frustrating for these learners. No significant difference in emotions was found across levels of task complexity for novices. Finally, a constructed composite indicator of cognitive-affective efficiency of instructional conditions showed a significant interaction between levels of learner expertise and task complexity primarily caused by affective factors.     

Altering element interactivity and variability in example-practice sequences to enhance learning to write Chinese characters

The isolated elements and variability effects of cognitive load theory were used to alter the element interactivity of Chinese characters when instructing novice learners (72 overseas students at a Chinese university) in writing characters using worked examples-practice procedures. A group of characters with more than eight strokes was disassembled into three individual components. Students were required to trace examples and practice writing of either similar sequences of isolated components followed by integrated components of full characters (Isolated–Integrated sequences); variable sequences of isolated followed by integrated components (Variability–Integrated sequences); or conventional Integrated–Integrated sequences of full characters. It was hypothesized that the fully integrated stroke-movements form of example-practice sequences would result in less learning due to a greater cognitive load. The results demonstrated that the participants in both the Isolated–Integrated and Variable–Integrated groups performed significantly better than the Integrated–Integrated group with the Variable–Integrated group outperforming the Isolated–Integrated group.     

A note on "Optical motions as information for unsigned depth"

Farber and McConkie have questioned whether optical (or retinal) flows provide a basis for the accurate perception of relative distance (or filled depth, in Gibson, Gibson, Smith, & Flock's terms). Some of the analysis Farber and McConkie present is incorrect. In this article I identity some of the fallacies and discuss issues relevant to these fallacies. The critique does not concern the experiments presented by Farber and McConkie but rather the underlying analysis that culminated in the experiments.     

Configured-groups hypothesis: fast comparison of exact large quantities without counting

Our innate number sense cannot distinguish between two large exact numbers of objects (e.g., 45 dots vs 46). Configured groups (e.g., 10 blocks, 20 frames) are traditionally used in schools to represent large numbers. Previous studies suggest that these external representations make it easier to use symbolic strategies such as counting ten by ten, enabling humans to differentiate exactly two large numbers. The main hypothesis of this work is that configured groups also allow for a differentiation of large exact numbers, even when symbolic strategies become ineffective. In experiment 1, the children from grade 3 were asked to compare two large collections of objects for 5 s. When the objects were organized in configured groups, the success rate was over .90. Without this configured grouping, the children were unable to make a successful comparison. Experiments 2 and 3 controlled for a strategy based on non-numerical parameters (areas delimited by dots or the sum areas of dots, etc.) or use symbolic strategies. These results suggest that configured grouping enables humans to distinguish between two large exact numbers of objects, even when innate number sense and symbolic strategies are ineffective. These results are consistent with what we call “the configured group hypothesis”: configured groups play a fundamental role in the acquisition of exact numerical abilities.