The effects of segmentation on cognitive load, vocabulary learning and retention, and reading comprehension in a multimedia learning environment

BACKGROUND

Segmentation is a common pedagogical approach in multimedia learning, but its effects on cognitive processes and learning outcomes have yet to be comprehensively explored. Understanding the role of segmentation is crucial, as it has the potential to influence the way instructional materials are designed and delivered in digital learning environments.

OBJECTIVES

This research aims to fill this gap by examining the impact of segmentation on cognitive load, vocabulary acquisition, retention, and reading comprehension in a multimedia learning context.

METHODOLOGY

Participants were selected from two language schools in Zhengzhou through a multi-stage random sampling method. Ninety teenage students were randomly assigned to six experimental groups. The study utilized a 2 × 3 factorial design to examine segmentation and textual augmentation effects. Four assessment instruments were employed: a Reading Comprehension Test, a Vocabulary Assessment Test, a Cognitive Load Assessment Scale, and a Prior Knowledge Test. The experiment comprised four stages: pre-test, Instruction, post-test, and follow-up. Data analysis was performed using SPSS 22 software, involving descriptive statistics, one-way, and multi-way analysis of variance.

RESULTS

Results indicated that high segmentation significantly impacts cognitive load, vocabulary learning, retention, and reading comprehension across various aspects of multimedia learning. In essence, segmentation reduces cognitive load, supports learning efficiency, and facilitates more profound understanding, vocabulary learning, and retention.

CONCLUSIONS AND IMPLICATIONS

High segmentation in multimedia learning significantly impacts cognitive load, vocabulary learning, comprehension, and retention. Educators should prioritize segmentation for more effective and engaging e-learning experiences.

Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review

COVID-19 is deemed as the most critical world health calamity of the 21st century, leading to dramatic life loss. There is a pressing need to understand the multi-stage dynamics, including transmission routes of the virus and environmental conditions due to the possibility of multiple waves of COVID-19 in the future. In this paper, a systematic examination of the literature is conducted associating the virus-laden-aerosol and transmission of these microparticles into the multimedia environment, including built environments. Particularly, this paper provides a critical review of state-of-the-art modelling tools apt for COVID-19 spread and transmission pathways. GIS-based, risk-based, and artificial intelligence-based tools are discussed for their application in the surveillance and forecasting of COVID-19. Primary environmental factors that act as simulators for the spread of the virus include meteorological variation, low air quality, pollen abundance, and spatial-temporal variation. However, the influence of these environmental factors on COVID-19 spread is still equivocal because of other non-pharmaceutical factors. The limitations of different modelling methods suggest the need for a multidisciplinary approach, including the 'One-Health' concept. Extended One-Health-based decision tools would assist policymakers in making informed decisions such as social gatherings, indoor environment improvement, and COVID-19 risk mitigation by adapting the control measurements.