The Evolution of Cognitive Load Theory and the Measurement of Its Intrinsic, Extraneous and Germane Loads: A Review

Cognitive Load Theory has been conceived for supporting instructional design through the use of the construct of cognitive load. This is believed to be built upon three types of load: intrinsic, extraneous and germane. Although Cognitive Load Theory and its assumptions are clear and well-known, its three types of load have been going through a continuous investigation and re-definition. Additionally, it is still not clear whether these are independent and can be added to each other towards an overall measure of load. The purpose of this research is to inform the reader about the theoretical evolution of Cognitive Load Theory as well as the measurement techniques and measures emerged for its cognitive load types. It also synthesises the main critiques of scholars and the scientific value of the theory from a rationalist and structuralist perspective

Non-matching predictions from different models simulating the effects of elevated atmospheric CO2 on the Amazon forest’s functional diversity

The continuous rising of atmospheric carbon dioxide (CO2) concentration is undoubtedly affecting the resilience of tropical forests worldwide. However, the magnitude of such effects is poorly known, limiting our capacity to assess the vulnerability of tropical forests and to improve their representation by models. Functional diversity (FD) is an important component of biodiversity enhancing ecosystem resilience, as high FD can provide higher response diversity and capacity to buffer against climate change. How FD is represented by different Dynamic Global Vegetation Models (DGVMs) may affect how such models predict the impacts of environmental changes on hyperdiverse ecosystems. We compared simulations of five trait-based DGVMs (i.e., with flexible, variable traits) constrained with data from the Amazon rainforest in the scope of the AmazonFACE project. Simulations were conducted considering initial high or low diversity scenarios under ambient and elevated CO2 (400 ppm and 600 ppm, respectively). We searched for correspondence between the functional identity of simulated plant strategies and their ecophysiological performances under elevated CO2. As models take different approaches to simulating functional trait distributions and they differ in their structure and in the trade-offs implemented, we found important intermodel differences in simulated results. Nevertheless, we took advantage of these differences in order to assess the most likely scenarios in terms of functional composition under elevated CO2, as well as to give feedback for better harmonization of model inputs and outputs and future model improvements. In the face of the pessimistic scenarios that project a continuous increase in CO2 levels, resolving the divergent responses among model predictions is critical, given the global importance of the Amazon rainforest's biodiversity and climate regulation, as well as the approximately 30 million people that directly or indirectly depend on the forest for their well-being

Predicting species dominance shifts across elevation gradients in mountain forests in Greece under a warmer and drier climate

The Mediterranean Basin is expected to face warmer and drier conditions in the future, following projected increases in temperature and declines in precipitation. The aim of this study is to explore how forests dominated by Abies borisii-regis, Abies cephalonica, Fagus sylvatica, Pinus nigra and Quercus frainetto will respond under such conditions. We combined an individual-based model (GREFOS), with a novel tree ring data set in order to constrain tree diameter growth and to account for inter- and intraspecific growth variability. We used wood density data to infer tree longevity, taking into account inter- and intraspecific variability. The model was applied at three 500-m-wide elevation gradients at Taygetos in Peloponnese, at Agrafa on Southern Pindos and at Valia Kalda on Northern Pindos in Greece. Simulations adequately represented species distribution and abundance across the elevation gradients under current climate. We subsequently used the model to estimate species and functional trait shifts under warmer and drier future conditions based on the IPCC A1B scenario. In all three sites, a retreat of less drought-tolerant species and an upward shift of more drought-tolerant species were simulated. These shifts were also associated with changes in two key functional traits, in particular maximum radial growth rate and wood density. Drought-tolerant species presented an increase in their average maximal growth and decrease in their average wood density, in contrast to less drought-tolerant species

Mapping local and global variability in plant trait distributions

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration - specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm), we characterize how traits vary within and among over 50,000 ∼50×50-km cells across the entire vegetated land surface. We do this in several ways - without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means

A model intercomparison project to study the role of plant functional diversity in the response of tropical forests to drought

Uncertainty in how the land carbon (C) sink will change over time contributes to uncertainty in Earth system model (ESM) projections of climate change. Much of the land sink is thought to reside in old-growth tropical forests, but recent analyses suggest a diminishing C sink in these forests due to rising temperatures and drought. Thus, there is an urgent need to better understand tropical forest responses to drought and to incorporate this understanding into ESMs. Previous work with vegetation demographic models (VDMs) – which represent the dynamics of individuals or cohorts, along with hydrology and biogeochemistry − suggest that functional diversity can enhance tropical forest resilience to climate change. However, there is little understanding of how different approaches to representing trait diversity and demography affect model outcomes. To explore the potential for trait diversity to moderate tropical forest responses to drought, we explored the behavior of nine VDMs, ranging from models with detailed site-level parameterizations to more generalized land models designed as ESM components. The behavior of each model was studied using soil and meteorological data collected at each of two tropical forest sites: Paracou Research Station, French Guiana, and Tapajos National Forest, Brazil. Low and high trait-diversity scenarios were simulated for each model using historical meteorology, as well as reduced rainfall scenarios. Few models showed strong effects of trait diversity on drought resistance (short-term response of forest biomass to rainfall reduction), but most models showed positive effects of diversity on resilience (long-term recovery of forest biomass following the initial biomass loss due to rainfall reduction). Long-term recovery was always associated with shifts in community composition towards greater drought-tolerance. However, there were large differences among models in the degree and time-scale of recovery. These differences were unrelated to the goodness-of-fit of model predictions to observations of biomass, productivity, and soil moisture, suggesting that site-level calibration of model parameters is unlikely to strongly affect biodiversity-ecosystem functioning relationships in VDMs. Rather, the degree to which diversity moderated drought responses depended on which axes of trait variation were represented in the model, as well as model assumptions that affect the time-scale over which community composition shifts in response to environmental change. Our study suggests that incorporating trait diversity and demography into ESMs would likely lead to altered climate projections, but additional empirical and modeling work is needed to provide the ESM community with clear guidance on model development

Global variability in leaf respiration in relation to climate, plant functional types and leaf traits

• Leaf dark respiration (Rdark) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of Rdark and associated leaf traits. • Data for 899 species were compiled from 100 sites (from the Arctic to the tropics). Several woody and nonwoody plant functional types (PFTs) were represented. Mixed-effects models were used to disentangle sources of variation in Rdark. • Area-based Rdark at the prevailing average daily growth temperature (T) of each site increased only twofold from the Arctic to the tropics, despite a 20°C increase in growing T (8–28°C). By contrast, Rdark at a standard T (25°C, Rdark25) was threefold higher in the Arctic than in the tropics, and twofold higher at arid than at mesic sites. Species and PFTs at cold sites exhibited higher Rdark25 at a given photosynthetic capacity (Vcmax25) or leaf nitrogen concentration ([N]) than species at warmer sites. Rdark25 values at any given Vcmax25 or [N] were higher in herbs than in woody plants. • The results highlight variation in Rdark among species and across global gradients in T and aridity. In addition to their ecological significance, the results provide a framework for improving representation of Rdark in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs)

Using eye movements to model the sequence of text–picture processing for multimedia comprehension

This study used eye movement modeling examples (EMME) to support students' integrative processing of verbal and graphical information during the reading of an illustrated text. EMME consists of a replay of eye movements of a model superimposed onto the materials that are processed for accomplishing the task. Specifically, the study investigated the effects of modeling the temporal sequence of text and picture processing as shown in various replays of a model's gazes. Eighty-four 7th graders were randomly assigned to one of the four experimental conditions: text-first processing sequence (text-first EMME), picture-first processing sequence (picture-first EMME), picture-last processing sequence (picture-last EMME) and no-EMME (control). Online and offline measures were used. Eye movement indices indicate that only readers in the picture-first EMME condition spent significantly longer processing the picture and showed stronger integrative processing of verbal and graphical information than students in the no-EMME condition. Moreover, readers in all EMME conditions outperformed those in the control condition for recall. However, for learning and transfer, only readers in the picture-first EMME condition were significantly superior to readers of the control condition. Furthermore, both the frequency and duration of integrative processing of verbal and graphical information mediated the effect of condition on learning outcomes

Simultaneous and sequential presentation of realistic and schematic instructional dynamic visualizations

An experiment was conducted to investigate the effects of combining realistic and schematic dynamic visualizations of mitosis. Ninety-two students from four different biology classes were randomly assigned to one of four conditions. Participants in the simultaneous condition studied both a realistic and a schematic visualization of mitosis that were presented simultaneously; participants in the sequential condition studied these two visualizations sequentially; and participants in the schematic-only condition and the realistic-only condition studied only one of the visualizations. Afterwards, participants made a verbal and visual recognition test, and rated the difficulty and comprehensibility of the visualizations. The results showed that the conditions did not differ on verbal and visual recognition. Only on the schematic questions of the visual recognition test, the realistic-only condition scored significantly lower than the other three conditions. Also, no differences were found on the difficulty and comprehensibility ratings. It is concluded that studying multiple representations of a dynamic process is not necessarily better than studying only one representation