ADIDAS: An Examined Approach for Enhancing Cognitive Load and Attitudes towards Synchronous Digital Learning Amid and Post COVID-19 Pandemic

Int J Environ Res Public Health. 2022 Dec 17;19(24):16972. doi: 10.3390/ijerph192416972.

Abstract

SARS-CoV-2 (COVID-19) has disrupted university education and turned it into distance learning for at least one semester in many countries, including the Kingdom of Saudi Arabia (KSA). However, there was an issue with university students' cognitive load at this critical time, because education totally stopped for about a month and then resumed remotely. This research draws on the cognitive load theory, particularly the extraneous load, to develop an instructional design model called ADIDAS. The model includes six stages, namely: analyse (A), design (D), improve (I), do (D), Assess (A), and Share (S). Thirty-four experts in instructional technology models have reviewed the ADIDAS model in Arab university contexts, producing a consensus about its suitability for use in distance learning amid the COVID-19 pandemic. Following the consensus of the experts, the model was applied to a sample of 527 students at King Faisal University, KSA. The results confirmed significant statistical differences with a very large effect size in relation to the attitude towards synchronous digital learning (SDL) and cognitive load pre and post ADIDAS. Students had a positive attitude towards SDL and a low cognitive load during the educational process pre adoption of the ADIDAS model, compared to post ADIDAS. The current research results have numerous implications for post the COVID-19 pandemic, especially in Arab countries and similar contexts.

Keywords: ADIDAS model; COVID-19; SARS-CoV-2; cognitive load; cognitive load theory; distance learning; instructional design; synchronous digital learning.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Attitude
  • COVID-19* / epidemiology
  • Cognition
  • Education, Distance*
  • Humans
  • Pandemics
  • SARS-CoV-2

Grants and funding

This work was supported through the Annual Funding track by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia (project number: GRANT13).