Understanding emotions in technology-based learning environments (TBLEs) has become a paramount goal across different research communities, but to date, these have operated in relative isolation. ...Based on control-value theory (Pekrun, 2006), we reviewed 186 studies examining emotions in TBLEs that were published between 1965 and 2018. We extracted effect sizes quantifying relations between emotions (enjoyment, curiosity/interest, anxiety, anger/frustration, confusion, boredom) and their antecedents (control-value appraisals, prior knowledge, gender, TBLE characteristics) and outcomes (engagement, learning strategies, achievement). Mean effects largely supported hypotheses (e.g., positive relations between enjoyment and appraisals, achievement, and cognitive support) and remained relatively stable across moderators. These findings imply that levels of emotions differ across TBLEs, but that their functional relations with appraisals and learning are equivalent across environments. Implications for research and designing emotionally sound TBLEs are discussed.
•We reviewed 186 studies on emotions in technology-based learning.•Correlations were consistent with hypotheses derived from control-value theory.•Enjoyment correlated positively with control, cognitive support, and achievement.•Anxiety correlated negatively with these variables as well as learning strategies.•Effects were largely unaffected by moderators such as type of learning environment.
Our understanding of how increasing atmospheric CO2 and climate change influences the marine CO2 system and in turn ecosystems has increasingly focused on perturbations to carbonate chemistry ...variability. This variability can affect ocean‐climate feedbacks and has been shown to influence marine ecosystems. The seasonal variability of the ocean CO2 system has already changed, with enhanced seasonal variations in the surface ocean pCO2 over recent decades and further amplification projected by models over the 21st century. Mesocosm studies and CO2 vent sites indicate that diurnal variability of the CO2 system, the amplitude of which in extreme events can exceed that of mean seasonal variability, is also likely to be altered by climate change. Here, we modified a global ocean biogeochemical model to resolve physically and biologically driven diurnal variability of the ocean CO2 system. Forcing the model with 3‐h atmospheric outputs derived from an Earth system model, we explore how surface ocean diurnal variability responds to historical changes and project how it changes under two contrasting 21st‐century emission scenarios. Compared to preindustrial values, the global mean diurnal amplitude of pCO2 increases by 4.8 μatm (+226%) in the high‐emission scenario but only 1.2 μatm (+55%) in the high‐mitigation scenario. The probability of extreme diurnal amplitudes of pCO2 and H+ is also affected, with 30‐ to 60‐fold increases relative to the preindustrial under high 21st‐century emissions. The main driver of heightened pCO2 diurnal variability is the enhanced sensitivity of pCO2 to changes in temperature as the ocean absorbs atmospheric CO2. Our projections suggest that organisms in the future ocean will be exposed to enhanced diurnal variability in pCO2 and H+, with likely increases in the associated metabolic cost that such variability imposes.
Using a global ocean biogeochemical model, we project how diurnal variability of the surface ocean CO2 system responds to historical and future projections of climate change. In a high 21st‐century emission scenario, the global mean diurnal amplitude of pCO2 increases threefold compared to preindustrial values, with a dramatic increase in the probability of extreme diurnal events. The main driver of heightened pCO2 diurnal variability in the surface open ocean is the enhanced sensitivity of pCO2 to changes in temperature as the ocean absorbs anthropogenic carbon.
Johnson et al. (
International Journal of Artificial Intelligence in Education
,
11
, 47–78,
2000
) introduced and surveyed a new paradigm for interactive learning environments: animated pedagogical ...agents. The article argued for combining animated interface agent technologies with intelligent learning environments, yielding intelligent systems that can interact with learners in natural, human-like ways to achieve better learning outcomes. We outlined a variety of possible uses for pedagogical agents. But we offered only preliminary evidence that they improve learning, leaving that to future research and development. Twenty years have elapsed since work began on animated pedagogical agents. This article re-examines the concepts and predictions in the 2000 article in the context of the current state of the field. Some of the ideas in the paper have become well established and widely adopted, especially in game-based learning environments. Others are only now being realized, thanks to advances in immersive interfaces and robotics that enable rich face-to-face interaction between learners and agents. Research has confirmed that pedagogical agents can be beneficial, but not equally for all learning problems, applications, and learner populations. Although there is a growing body of research findings about pedagogical agents, many questions remain and much work remains to be done.
Long-term stress on marine organisms from ocean acidification will differ between seasons. As atmospheric carbon dioxide (CO2) increases, so do seasonal variations of ocean CO2 partial pressure ...(pCO^, causing summer and winter long-term trends to diverge1-5. Trends may be further influenced by an unexplored factor-changes in the seasonal timing of pCO. In Arctic Ocean surface waters, the observed timing is typified by a winter high and summer low6 because biological effects dominate thermal effects. Here we show that 27 Earth system models simulate similar timing under historical forcing but generally project that the summer low, relative to the annual mean, eventually becomes a high across much of the Arctic Ocean under mid-tohigh-level CO2 emissions scenarios. Often the greater increase in summer pCO , although gradual, abruptly inverses the chronological order of the annual high and low, a phenomenon not previously seen in climate-related variables. The main cause is the large summer sea surface warming7 from earlier retreat of seasonal sea ice8. Warming and changes in other drivers enhance this century's increase in extreme summer pCO by 29±9per cent compared with no change in driver seasonalities. Thus the timing change worsens summer ocean acidification, which in turn may lower the tolerance of endemic marine organisms to increasing summer temperatures.
Diurnal variability of ocean CO2 system variables is poorly constrained. Here, this variability and its drivers are assessed using 3‐h observations collected over 8–140 months at 37 stations located ...in diverse marine environments. Extreme diurnal variability, that is, when the daily amplitude exceeds the 99th percentile of diurnal variability, is comparable in magnitude to the seasonal amplitude and can surpass projected changes in mean states of pCO2 and H+ over the twenty‐first century. At coastal sites and near coral reefs, extremes in diurnal amplitudes reach 187 ± 85 and 149 ± 106 μatm for pCO2, 0.21 ± 0.08 and 0.11 ± 0.07 for pH, and 1.2 ± 0.5 and 0.8 ± 0.4 for Ωarag, respectively. Extreme diurnal variability is weaker in the open ocean, but still reaches 47 ± 18 μatm for pCO2, 0.04 ± 0.01 for pH, and 0.25 ± 0.11 for Ωarag. Diurnal variability of the ocean CO2 system is considerable and likely to respond to increasing CO2. Therefore, it should be represented in Earth system models.
Plain Language Summary
Our understanding of how ocean pH and related chemical variables vary during the day (known as diurnal variability) is not well established. Here, we use a recent data set of such observations collected every 3 h during 8–140 months from 37 buoys located across the oceans to assess these diurnal variations and what drives them. In extreme cases, observed changes over 24 h were found to be greater than those observed between seasons. Diurnal variations in these chemical variables are particularly large in coastal waters and near coral reefs and are not negligible further offshore. Along with the more gradual, long‐term acidification of the ocean from atmospheric CO2 increases year after year, diurnal and seasonal variability of ocean chemistry is also expected to change dramatically. Understanding how this diurnal variability will change in the future is important because it modulates the levels of acidification experienced by marine organisms from long‐term yearly changes.
Key Points
Multi‐year 3‐h observations of CO2 system variables are used to assess diurnal and seasonal variability across marine environments
Amplitudes of extreme diurnal variations in pCO2, pH, and Ωarag are often comparable to those of seasonal cycles
The balance between different drivers of diurnal and seasonal CO2 system variability differs across timescales and environments
Our understanding of how increasing atmospheric CO
and climate change influences the marine CO
system and in turn ecosystems has increasingly focused on perturbations to carbonate chemistry ...variability. This variability can affect ocean-climate feedbacks and has been shown to influence marine ecosystems. The seasonal variability of the ocean CO
system has already changed, with enhanced seasonal variations in the surface ocean pCO
over recent decades and further amplification projected by models over the 21st century. Mesocosm studies and CO
vent sites indicate that diurnal variability of the CO
system, the amplitude of which in extreme events can exceed that of mean seasonal variability, is also likely to be altered by climate change. Here, we modified a global ocean biogeochemical model to resolve physically and biologically driven diurnal variability of the ocean CO
system. Forcing the model with 3-h atmospheric outputs derived from an Earth system model, we explore how surface ocean diurnal variability responds to historical changes and project how it changes under two contrasting 21st-century emission scenarios. Compared to preindustrial values, the global mean diurnal amplitude of pCO
increases by 4.8 μatm (+226%) in the high-emission scenario but only 1.2 μatm (+55%) in the high-mitigation scenario. The probability of extreme diurnal amplitudes of pCO
and H
is also affected, with 30- to 60-fold increases relative to the preindustrial under high 21st-century emissions. The main driver of heightened pCO
diurnal variability is the enhanced sensitivity of pCO
to changes in temperature as the ocean absorbs atmospheric CO
. Our projections suggest that organisms in the future ocean will be exposed to enhanced diurnal variability in pCO
and H
, with likely increases in the associated metabolic cost that such variability imposes.
Abstract
Long-term stress on marine organisms from ocean acidification will differ between seasons. As atmospheric carbon dioxide (CO
2
) increases, so do seasonal variations of ocean CO
2
partial ...pressure (
$${p}_{{{\rm{CO}}}_{2}}$$
p
CO
2
), causing summer and winter long-term trends to diverge
1–5
. Trends may be further influenced by an unexplored factor—changes in the seasonal timing of
$${p}_{{{\rm{CO}}}_{2}}$$
p
CO
2
. In Arctic Ocean surface waters, the observed timing is typified by a winter high and summer low
6
because biological effects dominate thermal effects. Here we show that 27 Earth system models simulate similar timing under historical forcing but generally project that the summer low, relative to the annual mean, eventually becomes a high across much of the Arctic Ocean under mid-to-high-level CO
2
emissions scenarios. Often the greater increase in summer
$${p}_{{{\rm{CO}}}_{2}}$$
p
CO
2
, although gradual, abruptly inverses the chronological order of the annual high and low, a phenomenon not previously seen in climate-related variables. The main cause is the large summer sea surface warming
7
from earlier retreat of seasonal sea ice
8
. Warming and changes in other drivers enhance this century’s increase in extreme summer
$${p}_{{{\rm{CO}}}_{2}}$$
p
CO
2
by 29 ± 9 per cent compared with no change in driver seasonalities. Thus the timing change worsens summer ocean acidification, which in turn may lower the tolerance of endemic marine organisms to increasing summer temperatures.
Back in the 1990s, we started work on pedagogical agents — a novel paradigm for interactive learning. Pedagogical agents are autonomous characters that inhabit learning environments to engage with ...learners in rich, face‐to‐face interactions. Building on this work, in 2000, together with our colleague Jeff Rickel, we published an article on pedagogical agents (Johnson, Rickel, and Lester 2000) that surveyed and discussed the potential of this new paradigm. We made the case that pedagogical agents that interact with learners in natural, lifelike ways can help learning environments achieve improved learning outcomes. This article has been widely cited, and was a winner of the 2017 IFAAMAS Award for Influential Papers in Autonomous Agents and Multiagent Systems.1
On the occasion of receiving the IFAAMAS award, and after 20 years of work on pedagogical agents, we take another look at the future of the field. We start by revisiting the predictions we made in 2000 for pedagogical agents, and examine which predictions panned out. Then, informed by what we have learned since then, we take another look at emerging trends and reexamine the future of pedagogical agents. Advances in natural language dialogue, affective computing, machine learning, virtual environments, and robotics are making possible even more lifelike and effective pedagogical agents, with potentially profound effects on the way people learn.
The lives of adolescents and young adults (AYAs) have become increasingly intertwined with technology. Multidisciplinary perspectives and collaboration are needed to capitalize on the strategic use ...of technology during key developmental windows. Technology-rich models of behavior change, with opportunities for personalizing health interventions, offer significant transformative potential to improve adolescent and young adult health. There is considerable momentum behind advancing integration of digital health technology to enhance the efficiency and effectiveness of the clinical encounter, and rapid advances in technology provide mechanisms for enabling AYAs to take agentic roles in promoting health practice and policy.
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