Worked Examples in Physics Games: Challenges in Integrating Proven Cognitive Scaffolds into Game Mechanics

The current study is an exploratory study into the potential of integrating research on worked examples and physics games. Students were assigned to either a base version of a physics game, called the Fuzzy Chronicles, or assigned to a version of the Fuzzy Chronicles augmented with worked examples. Students in both conditions demonstrated significant gains on the pre-post-test, but students in the base game version demonstrated significantly greater gains than the students in the worked example version. The results from the current study reinforce results from other studies by our research group demonstrating how important it is that scaffolds based on multimedia research (a) do not over scaffold the student or promote passive, automatic behaviors, (b) do not excessively detract from the student’s gameplay time, and (c) do not disrupt game cognition and flow

Digital Games in the Science Classroom: Leveraging Internal and External Scaffolds during Game Play

We have developed a disciplinarily integrated game (DIG) to support students in interpreting, translating, and manipulating across formal representations in the domain of Newtonian kinematics. In this study, we seek to understand what game play looks like in a classroom context with particular attention given to how students leverage internal and external scaffolds to progress through the game and deepen their conceptual knowledge. We investigate the following questions: (1) In what ways do students interact with the game, with each other, and with their teacher when they play SURGE Symbolic in a classroom environment? (2) How do game scaffolds, both within and outside of the game, support or impede student learning and game play? (3) What are the implications of these observations for teachers and game designers? We found that although most students used internal scaffolds in some way to assist their game play, many found that these scaffolds were insufficient to get through challenges. They quickly sought help from external resources available to them outside the game to help them advance in the game. The source of information they needed to make progress came from various people or resources outside the game, what we are calling “knowers.

Using earth observation data to evaluate a land surface model in three Siberian catchments

In this paper, we analyse the ability of the JULES (Joint UK Land Environment Simulator) model to simulate the physical conditions in the terrestrial Arctic using satellite-based earth observation data products. Catchment-average seasonal surface temperatures and snow cover are constructed over the largest river basins of the Eurasian Arctic (the Ob, Lena and Yenisei) and compared with the modelled values. The results indicate that the modelled snow cover decreases too quickly in spring in all studied areas, and that the modelled surface temperature of snow-free areas is too high. There are several causes of uncertainty in both the model outputs and the earth observation products, and care has to be taken to ensure consistent use and sampling of the data. The results indicate that earth observation products provide important information that can assist in the diagnosis of problems in a land-surface model

Multiplayer Disciplinarily-Integrated Agent-Based Games: SURGE Gameblox

Early work on disciplinary-integrated games (DIGs) focused on Cartesian time-series analyses as the formal representations through which the game communicates challenges and opportunities to the players as well as the formal representations through which the players control the game. In our earlier work, we explored the potential generalizability of the DIG genre in terms of hypothetical examples in physics, biology, chemistry, and the social sciences as well as in terms of multiple model types including constraint-system analyses, system dynamics models, situation-action models, and agent-based models. In particular, Sengupta and Clark and Krinks, Sengupta, and Clark explored the integration of computational modeling, physical models, and Cartesian models. Building on that work, we began outlining theoretical frameworks and arguments highlighting the affordances of moving DIG design more deeply into agent-based modeling. In the current paper, we present the actual design process and rationale through which we developed prototypes of two multiplayer DIG prototypes with agent-based models as the mode of control wherein players create, trade, and elaborate on one another’s code as part of gameplay. We close with a discussion of implications for the design of disciplinary-integrated games leveraging agent-based modeling as the focal formal representation for communication and control

Modeling the Impact of Land Surface Degradation on the Climate of Tropical North Africa

Degradation of the land surface has been suggested as a cause of persistent drought in tropical north Africa. A general circulation model is used to assess the impact of degradation of five regions within tropical north Africa. Idealized degradation scenarios are used since existing observations are inadequate the determine the extent and severity of historical degradation. It is found that the impact of degradation varies between the regions. The greatest effects are found from degradation of the Sahel or West Africa, which result in substantial reduction of precipitation over the degraded area. Both surface evaporation and atmospheric moisture convergence are reduced. In the Sahelian case the precipitation reduction extends well to the south of the area of changed land surface. The occurrence of easterly wave disturbances is not altered by degradation, but the mean rainfall from each event is reduced. Degradation of an area in eastern north Africa results in smaller reductions of precipitation and moisture convergence. Finally, degradation of a southern area next to the Gulf of Guinea has little effect on precipitation because of a compensatory increase of moisture convergence. The simulated rainfall reduction following degradation of the Sahel is comparable to observed changes in recent decades, suggesting that degradation may have contributed to that change

Dedication

This issue of the Nebraska Law Review is dedicated to the Honorable Earl Warren, Chief Justice of the United States, upon his retirement

The future for global water assessment

The global water cycle is a fundamental component of our climate and Earth system. Many, if not the majority, of the impacts of climate change are water related. We have an imperfect description and understanding of components of the water cycle. This arises from an incomplete observation of some of the stores and fluxes in the water cycle (in particular: precipitation, evaporation, soil moisture and groundwater), problems with the simulation of precipitation by global climate models and the wide diversity of global hydrological models currently in use. This paper discusses these sources of errors and, in particular, explores the errors and advantages of bias correcting climate model outputs for hydrological models using a single large catchment as an example (the Rhine). One conclusion from this analysis is that bias correction is necessary and has an impact on the mean flows and their seasonal cycle. However choice of hydrological model has an equal, if not larger effect on the quality of the simulation. The paper highlights the importance of improving hydrological models, which run at a continental and global scale, and the importance of quantifying uncertainties in impact studies

Using Gravity Recovery and Climate Experiment data to derive corrections to precipitation data sets and improve modelled snow mass at high latitudes

The amount of lying snow calculated by a land surface model depends in part on the amount of snowfall in the meteorological data that are used to drive the model. We show that commonly used data sets differ in the amount of snowfall, and more generally precipitation, over four large Arctic basins. An independent estimate of the cold-season precipitation is obtained by combining water balance information from the Gravity Recovery and Climate Experiment (GRACE) with estimates of evaporation and river discharge and is generally higher than that estimated by four commonly used meteorological data sets. We use the Joint UK Land Environment Simulator (JULES) land surface model to calculate the snow water equivalent (SWE) over the four basins. The modelled seasonal maximum SWE is 38 % less than observation-based estimates on average, and the modelled basin discharge is significantly underestimated, consistent with the lack of snowfall. We use the GRACE-derived estimate of precipitation to define per-basin scale factors that are applied to the driving data and increase the amount of cold-season precipitation by 28 % on average. In turn this increases the modelled seasonal maximum SWE by 30 %, although this is still underestimated compared to observations by 19 % on average. A correction for the undercatch of precipitation by gauges is compared with the the GRACE-derived correction. Undercatch correction increases the amount of cold-season precipitation by 23 % on average, which indicates that some, but not all, of the underestimation can be removed by implementing existing undercatch correction algorithms. However, even undercatch-corrected data sets contain less precipitation than the GRACE-derived estimate in some regions, and it is likely that there are other biases that are not currently accounted for in gridded meteorological data sets. This study shows that revised estimates of precipitation can lead to improved modelling of SWE, but much more modest improvements are found in modelled river discharge. By providing methods to better define the precipitation inputs to the system, the current study paves the way for subsequent work on key hydrological processes in high-latitude basins