Skip to content
naulon
Not checkedNot checked for notices yet.

A Current View on Dual-Task Paradigms and Their Limitations to Capture Cognitive Load

Shirin Esmaeili Bijarsari

Frontiers in Psychology · 2021

doi:10.3389/fpsyg.2021.648586 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

Dual-task paradigms encompass a broad range of approaches to measure cognitive load in instructional settings. As a common characteristic, an additional task is implemented alongside a learning task to capture the individual’s unengaged cognitive capacities during the learning process. Measures to determine these capacities are, for instance, reaction times and interval errors on the additional task, while the performance on the learning task is to be maintained. Opposite to retrospectively applied subjective ratings, the continuous assessment within a dual-task paradigm allows to simultaneously monitor changes in the performance related to previously defined tasks. Following the Cognitive Load Theory, these changes in performance correspond to cognitive changes related to the establishment of permanently existing knowledge structures. Yet the current state of research indicates a clear lack of standardization of dual-task paradigms over study settings and task procedures. Typically, dual-task designs are adapted uniquely for each study, albeit with some similarities across different settings and task procedures. These similarities range from the type of modality to the frequency used for the additional task. This results in a lack of validity and comparability between studies due to arbitrarily chosen patterns of frequency without a sound scientific base, potentially confounding variables, or undecided adaptation potentials for future studies. In this paper, the lack of validity and comparability between dual-task settings will be presented, the current taxonomies compared and the future steps for a better standardization and implementation discussed.

Abstract licence: CC BY

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.