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Fred D’Agostino Neil Taylor John G. Hedberg Jennie Lynch John M. Malouff 《高等教育研究与发展》2008,27(3):297-304
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In this article, themost relevant literature on cognitive aging and instructional design is merged to formulate recommendations for designing computer-based training material aimed at elderly learners. The core message is that researchers and instructional designers do not need to develop special computerized instruction for older adults. Rather, existing principles of general instructional and multimedia design can be evaluated and used to accommodate the needs of elderly learners. Particular attention is given to John Sweller’s Cognitive Load Theory (CLT) and Richard Mayer’s Cognitive Theory of Multimedia Learning (CTML). It is argued that these instructional theories bear important benefits for older learners because they support an efficient use of available cognitive resources. New research directions are suggested to test the implications of these theories for learning in old age.
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Pascal W. M. Van GervenEmail: |
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John W. Young Jonathan Steinberg Fred Cline Elizabeth Stone Maria Martiniello Guangming Ling 《Educational Assessment》2013,18(2):87-106
To date, assessment validity research on non-native English speaking students in the United States has focused exclusively on those who are presently English language learners (ELLs). However, little, if any, research has been conducted on two other sizable groups of language minority students: (a) bilingual or multilingual students who were already English proficient when they entered the school system (IFEPs), and (b) former English language learners, those students who were once classified as ELLs but are now reclassified as being English proficient (RFEPs). This study investigated the validity of several standards-based assessments in mathematics and science for these two student groups and found a very high degree of score comparability, when compared with native English speakers, for the IFEPs, whereas a moderate to high degree of score comparability was observed for the RFEPs. Thus, test scores for these two groups on the assessments we studied appear to be valid indicators of their content knowledge, to a degree similar to that of native English speakers. 相似文献
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We highlight critical conceptual and statistical issues and how to resolve them in conducting Satorra–Bentler (SB) scaled difference chi-square tests. Concerning the original (Satorra & Bentler, 2001) and new (Satorra & Bentler, 2010) scaled difference tests, a fundamental difference exists in how to compute properly a model's scaling correction factor (c), depending on the particular structural equation modeling software used. Because of how LISREL 8 defines the SB scaled chi-square, LISREL users should compute c for each model by dividing the model's normal theory weighted least-squares (NTWLS) chi-square by its SB chi-square, to recover c accurately with both tests. EQS and Mplus users, in contrast, should divide the model's maximum likelihood (ML) chi-square by its SB chi-square to recover c. Because ML estimation does not minimize the NTWLS chi-square, however, it can produce a negative difference in nested NTWLS chi-square values. Thus, we recommend the standard practice of testing the scaled difference in ML chi-square values for models M 1 and M 0 (after properly recovering c for each model), to avoid an inadmissible test numerator. We illustrate the difference in computations across software programs for the original and new scaled tests and provide LISREL, EQS, and Mplus syntax in both single- and multiple-group form for specifying the model M 10 that is involved in the new test. 相似文献
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