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How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology?
How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology?
Cognitive load theory (CLT) has driven numerous empirical studies for over 30 years and is a major theme in many of the most cited articles published between 1988 and 2023. However, CLT articles have not been compared to other educational psychology research in terms of the research designs used and the extent to which recommendations for practice are justified. As Brady and colleagues found, a large percentage of the educational psychology articles reviewed were not experimental and yet frequently made specific recommendations from observational/correlational data. Therefore, in this review, CLT articles were examined with regard to the types of research methodology employed and whether recommendations for practice were justified. Across several educational psychology journals in 2020 and 2023, 16 articles were determined to directly test CLT. In contrast to other articles, which employed mostly observational methods, all but two of the CLT articles employed experimental or intervention designs. For the two CLT articles that were observational, recommendations for practice were not made. Reasons for the importance of experimental work are discussed.
·mdpi.com·
How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology?
1994 cupm maa quantitative reasoning for college graduates
1994 cupm maa quantitative reasoning for college graduates

Quantitative Reasoning for College Graduates: A Complement to the Standards

Mathematical Association of America

pp 9 of 36

In short, every college graduate should be able to apply simple mathematical methods to the solution of real-world problems. A quantitatively literate college graduate should be able to:

  1. Interpret mathematical models such as formulas, graphs, tables, and schematics, and draw inferences from them.
  2. Represent mathematical information symbolically, visually, numerically, and verbally.
  3. Use arithmetical, algebraic, geometric and statistical methods to solve problems.
  4. Estimate and check answers to mathematical problems in order to determine reasonableness, identify alternatives, and select optimal results.
  5. Recognize that mathematical and statistical methods have limits.
·statlit.org·
1994 cupm maa quantitative reasoning for college graduates