Cognitive resources allocation in computer-mediated dictionary assisted learning: From word meaning to inferential comprehension
Computer-mediated dictionaries have been important and widely used aids in the comprehension of, and learning from online texts. However, despite the convenience of computer-mediated dictionaries in retrieving word meaning, its use may reduce the time that readers spend reading each word and negatively affect word retention. In addition, readers’ vocabulary size is a key factor influencing the lookup process, and its effectiveness. Therefore, in this study, we propose a new ‘checking-meaning’ function to optimize word retention and to explain readers’ cognitive resources allocation in computer-mediated dictionary assisted learning. We conducted a 2 (checking meaning function: with vs. without) × 2 (vocabulary size: large vs. small) between-subjects design to explore the effectiveness of vocabulary acquisition and reading comprehension performance in computer-mediated dictionary-assisted reading. In line with the hypotheses, results revealed that the computer-mediated dictionary with checking-meaning function enhanced small vocabulary size learners’ vocabulary acquisition, but negatively influenced large vocabulary size learners’ reading comprehension performance. Based on these results, we propose the competition-cooperation relationship to explain readers’ cognitive resources allocation in computer-mediated dictionary assisted learning.
|Keywords||Evaluation of CAL systems, Human-computer interface, Media in education|
|Persistent URL||dx.doi.org/10.1016/j.compedu.2018.08.013, hdl.handle.net/1765/109966|
|Journal||Computers & Education|
Chang, Y.-H. (You-Hsuan), Liu, T.-C, & Paas, G.W.C. (2018). Cognitive resources allocation in computer-mediated dictionary assisted learning: From word meaning to inferential comprehension. Computers & Education, 127, 113–129. doi:10.1016/j.compedu.2018.08.013