A Pedagogy of Play: Integrating Computer Games into the Writing Classroom

Traditional distinctions between work/play and classroom/gamespace create barriers to computer games’ integration into academic settings and the writing classroom in particular. For a writing class, the work/play distinction often relegates games to an object of analysis in which students critique the games but have little invested in the gameplay itself. After examining briefly how historical changes in education created these distinctions, we offer an alternative position that places play and gamespace within the realm of the classroom. In so doing, we open up a gap for computer game theory to inform the pedagogy that can be practiced in a writing classroom. We show one such example of game theory informing writing pedagogy—the theory of emergent gaming. We then offer an example of an enacted emergent pedagogy in which students play the massively multiplayer online role-playing game World of Warcraft throughout the term, composing self-determined, rhetorically focused writing projects informed by play and written for other game players.     

Composition, Computer Games, and the Absence of Writing

Computer games fundamentally incorporate composition into their game play. Highly symbolic constructs, whose photo-realistic graphical environments are often produced by combining pre-existing elements, computer games not only require players to read and to make meaning of symbols presented on the screen but to write and ultimately to revise their actions in the game relationship to these symbols. This activity, which is often constructed as “play” rather than writing, is significant in that, although its effects appear to be limited to the conversations taking place on the screen, its focus is ultimately on how players read and write (compose) themselves in relationship to the game and to the larger socio-political structures upon which the game is beholden. Computer games thus have the potential to help students not only understand the fundamentals of the compositional process and the larger socio-political structures within which this process occurs but to recognize how these socio-political structures construct reading and writing and in doing so determine the way that the individuals subject to them construct (read and write) themselves.     

The effect of an information ethics course on the information ethics values of students - A Chinese guanxi culture perspective

The development of information technology has a significant influence on social structure and norms, and also impacts upon human behavior. In order to achieve stability and social harmony, people need to respect various norms, and have their rights protected. Students’ information ethics values are of critical and radical importance in achieving this goal. Using qualitative approach, the present study utilizes Kohlberg’s CMD model to measure improvement in students’ “information ethics values” through “technology mediated learning (TML)” models, and to assess the extent to which it is influenced by gender and Chinese guanxi culture. We find that while e-learning improves female students’ “respect rules,” “privacy,” “accessibility” and “intellectual property” values more than male students, the percentages relating to “intellectual property” for females in the higher stages remain lower than for males. Moreover, these results are interpreted from a Chinese guanxi culture perspective. In light of these results, educators should take account of such improvements when designing effective teaching methods and incentives.     

Effects of constructing versus playing an educational game on student motivation and deep learning strategy use

In this study the effects of two different interactive learning tasks, in which simple games were included were described with respect to student motivation and deep strategy use. The research involved 235 students from four elementary schools in The Netherlands. One group of students (N = 128) constructed their own memory ‘drag and drop’ game, whereas the other group (N = 107) played an existing ‘drag and drop’ memory game. Analyses of covariance demonstrated a significant difference between the two conditions both on intrinsic motivation and deep strategy use. The large effect sizes for both motivation and deep strategy use were in favour of the construction condition. The results suggest that constructing a game might be a better way to enhance student motivation and deep learning than playing an existing game. Despite the promising results, the low level of complexity of the games used is a study limitation.     

Neural network estimation of LAI, fAPAR, fCover and LAI×Cab, from top of canopy MERIS reflectance data: Principles and validation

A neural network is developed to operationally estimate biophysical variables over land surfaces from the observations of the ENVISAT-MERIS instrument: the leaf area index (LAI), the fraction of absorbed photosynthetically active radiation (fAPAR), the fraction of vegetation cover (fCover), and the canopy chlorophyll content (LAI×C_ab). The neural network requires as input the geometry of observation and the top of canopy reflectances, corrected from the atmospheric effects, in eleven spectral bands. It is trained on a reflectance database made of radiative transfer model simulations. The principles underlying the generation of the database and the design of the network are first presented. The estimated variables are then compared to other existing products, LAI- and fAPAR-MODIS and MGVI-MERIS, and validated against ground measurements performed in the framework of the VALERI project. Results show remarkable consistency of the temporal dynamics between the several products with however some differences in the range of variation. When compared to actual VALERI ground measurements, the proposed algorithm shows the best performances for LAI (RMSE = 0.47) and fAPAR (RMSE = 0.09).     

Pricing and inventory management in a system with multiple competing retailers under (r, Q) policies

We consider a multi-retailer system operated on an infinite horizon, in which each retailer faces stochastic demand following a Poisson process and adopts a continuous-review (r, Q) policy for replenishing inventory to satisfy customer demand. The system involves decisions of pricing and inventory management with the goal of maximizing profit, which equals the sales revenue minus the purchase and inventory costs. Taking Cournot competition into account, models are formulated to optimize simultaneously the expected sales volumes and (r, Q) policies of all retailers. An efficient approach is proposed to calculate the approximate inventory cost. Based on this approach, solution methods for centralized and decentralized scenarios are developed. A great number of numerical computations are provided to evaluate the efficiency of the solution methods, and their performance in the two scenarios. Moreover, system performance under sequential decisions (first pricing and then inventory management) is also investigated.     

Why do you play World of Warcraft? An in-depth exploration of self-reported motivations to play online and in-game behaviours in the virtual world of Azeroth

Massively multiplayer online role-playing games (MMORPGs) are video games in which players create an avatar that evolves and interacts with other avatars in a persistent virtual world. Motivations to play MMORPGs are heterogeneous (e.g. achievement, socialisation, immersion in virtual worlds). This study investigates in detail the relationships between self-reported motives and actual in-game behaviours. We recruited a sample of 690 World of Warcraft players (the most popular MMORPG) who agreed to have their avatar monitored for 8 months. Participants completed an initial online survey about their motives to play. Their actual in-game behaviours were measured through the game’s official database (the Armory website). Results showed specific associations between motives and in-game behaviours. Moreover, longitudinal analyses revealed that teamwork- and competition-oriented motives are the most accurate predictors of fast progression in the game. In addition, although specific associations exist between problematic use and certain motives (e.g. advancement, escapism), longitudinal analyses showed that high involvement in the game is not necessarily associated with a negative impact upon daily living.     

Remote sensing chlorophyll a of optically complex waters (rias Baixas, NW Spain): Application of a regionally specific chlorophyll a algorithm for MERIS full resolution data during an upwelling cycle

This study takes advantage of a regionally specific algorithm and the characteristics of Medium Resolution Imaging Spectrometer (MERIS) in order to deliver more accurate, detailed chlorophyll a (chla) maps of optically complex coastal waters during an upwelling cycle. MERIS full resolution chla concentrations and in situ data were obtained on the Galician (NW Spain) shelf and in three adjacent rias (embayments), sites of extensive mussel culture that experience frequent harmful algal events. Regionally focused algorithms (Regional neural network for rias Baixas or NNRB) for the retrieval of chla in the Galician rias optically complex waters were tested in comparison to sea-truth data. The one that showed the best performance was applied to a series of six MERIS (FR) images during a summer upwelling cycle to test its performance. The best performance parameters were given for the NN trained with high-quality data using the most abundant cluster found in the rias after the application of fuzzy c-mean clustering techniques (FCM). July 2008 was characterized by three periods of different meteorological and oceanographic states. The main changes in chla concentration and distribution were clearly captured in the images. After a period of strong upwelling favorable winds a high biomass algal event was recorded in the study area. However, MERIS missed the high chlorophyll upwelled water that was detected below surface in the ria de Vigo by the chla profiles, proving the necessity of in situ observations. Relatively high biomass “patches” were mapped in detail inside the rias. There was a significant variation in the timing and the extent of the maximum chla areas. The maps confirmed that the complex spatial structure of the phytoplankton distribution in the rias Baixas is affected by the surface currents and winds on the adjacent continental shelf. This study showed that a regionally specific algorithm for an ocean color sensor with the characteristics of MERIS in combination with in situ data can be of great help in chla monitoring, detection and study of high biomass algal events in an area affected by coastal upwelling such as the rias Baixas.     

Spectral sensing of foliar water conditions in two co-occurring conifer species: Pinus edulis and Juniperus monosperma

Many fundamental ecosystem properties and dynamics are determined by plant water stress, particularly in dryland ecosystems where water is usually limiting. Indeed, under severe drought, plant water stress and associated insect infestations can produce landscape-scale mortality. Despite the fundamental importance of plant water stress in determining properties and dynamics at ecosystem and landscape scales, approaches for remotely sensing plant water stress are largely lacking, particularly for conifers. We evaluated the remotely sensed detection of foliar drought stress in two conifer species, Pinus edulis and Juniperus monosperma, which are co-dominants of extensive-juniper woodlands in North America, the first of which experienced extensive mortality in association with a recent drought. Needle spectra were made on these species in the field using an integrating sphere and portable spectrometer. Two indices of foliar water condition, plant water content (% of dry mass) and plant water potential, were compared to five spectral analyses: continuum removal of the 970 and 1200 nm water absorption features, the Normalized Difference Water Index (NDWI), the Normalized Difference Vegetation Index (NDVI), and the red edge wavelength position. For P. edulis, plant water content was significantly correlated with four of the five indices: NDVI (R²=0.71) and NDWI (R²=0.68) which exhibited stronger relationships than 970 nm continuum removal (R²=0.57) or red edge position (R²=0.45). All five indices were significantly correlated with P. edulis water content when trees undergoing mortality were included in analyses (R²=0.60-0.93). Although the correlations were weaker than for plant water content, plant water potential was significantly correlated with NDWI (R²=0.49), 970 nm (R²=0.44), NDVI (R²=0.35), and red edge (R²=0.34); again all five indices had significant relationships when trees undergoing mortality were included (R²=0.51-0.86). The relationships were weaker for J. monosperma: water content was significantly related to 970 nm (R²=0.50) and 1200 nm (R²=0.37) continuums and NDVI (R²=0.33), while water potential was related only to 1200 nm (R²=0.40). Our results demonstrate a critical link between plant physiological characteristics tied to water stress and associated spectral signatures for two extensive co-occurring conifer species.     

Neural network estimation of chlorophyll a from MERIS full resolution data for the coastal waters of Galician rias (NW Spain)

In typical Case 2 waters, accurate remote sensing retrieval of chlorophyll a (chla) is still a challenging task. In this study, focusing on the Galician rias (ΝW Spain), algorithms based on neural network (NN) techniques were developed for the retrieval of chla concentration in optically complex waters, using Medium Resolution Imaging Spectrometer (MERIS) data. There is considerable interest in the accurate estimation of chla for the Galician rias, because of the economic and social importance of the extensive culture of mussels, and the high frequency of harmful algal events. Fifteen MERIS full resolution (FR) cloud-free images paired with in situ chla data (for 2002-2004 and 2006-2008) were used for the development and validation of the NN. The scope of NN was established from the clusters obtained using fuzzy c-mean (FCM) clustering techniques applied to the satellite-derived data. Three different NNs were developed: one including the whole data set, and two others using only points belonging to one of the clusters. The input data for these latter two NNs was chosen depending on the quality level, defined on the basis of quality flags given to each data set. The fitting results were fairly good and proved the capability of the tool to predict chla concentrations in the study area. The best prediction was given for the NN trained with high-quality data using the most abundant cluster data set. The performance parameters in the validation set of this NN were R² = 0.86, mean percentage error (MPE) = − 0.14, root mean square error (RMSE) = 0.75 mg m^− 3, and relative RMSE = 66%. The NN developed in this study detected accurately the peaks of chla, in both training and validation sets. The performance of the Case-2-Regional (C2R) algorithm, routinely used for MERIS data, was also tested and compared with our best performing NN and the sea-truthing data. Results showed that this NN outperformed the C2R, giving much higher R² and lower RMSE values.This study showed that the combination of in situ data and NN technology improved the retrieval of chla in Case 2 waters, and could be used to obtain more accurate chla maps. A local-based algorithm for the chla retrieval from an ocean colour sensor with the characteristics of MERIS would be a great support in the quantitative monitoring and study of harmful algal events in the coastal waters of the Rias Baixas. The limitations and possible improvements of the developed chla algorithms are also discussed.     

Lattice structure of e-implications on L

In this paper, we consider the set of all e-implications on L^∗ and define two operations on the set of all representable e-implications on L^∗, thus endowing it with monoid structure which is also a distributive complete lattice.     

Using hyperspectral remote sensing to detect and quantify southeastern pine senescence effects in red-cockaded woodpecker (Picoides borealis) habitat

Conservation of threatened and endangered species requires maintenance of critical habitat. The red-cockaded woodpecker Picoides borealis (RCW) is a threatened bird species, endemic to the mixed conifer forests of the southeastern United States. RCW nests and forages preferentially in mature longleaf pine Pinus palustris, but also uses mature loblolly pine Pinus taeda and shortleaf pine Pinus echinata forests. In the last century, the extent of mature pine forests has been greatly reduced by logging. The RCW, in contrast to other woodpeckers, excavates nest cavities in living trees and senescence symptoms (year round leaf chlorosis and leaf mortality) have been observed in mature pine stands across the southeast. Widespread mortality of the mature pine forests would threaten the long-term survival of the RCW. We used airborne hyperspectral data across a portion of Ft. Benning Military Installation, Georgia, U.S.A., to determine if senescent trees can be identified and mapped and assess the likely persistence of mature pines in the RCW habitat. Univariate analysis of variance showed good separation between asymptomatic, senesced and dead physiological conditions with asymptomatic trees having significantly higher reflectance for all bands in the wavelength range between 0.719 and 1.1676 µm, senescent trees having significantly lower reflectance for bands in the range between 1.1927 and 1.3122 µm, and dead trees having significantly higher reflectance for bands in the range between 1.8151 and 1.9471 µm. Classification and Regression Tree (CART) models achieved correct classification rates and kappa statistics above 70%. CART models selected information from wavelength regions similar to those identified from the ANOVA, which likely explains their performance. Our aggregated CART model of tree senescence estimated that 141.4 ha (3%) of the study area is affected. RCW nests occurred in areas with significantly higher tree cover, and trees within foraging and home ranges did not have significantly more senescence than areas without RCW. These results indicate that although tree senescence is widespread, mortality is yet to significantly affect RCW habitat. Results and analysis of critical habitat similar to those exemplified in this study can extend our knowledge about the stressors of these important and imperiled components of biodiversity.     

Assessing effectiveness of learning units under the teaching unit model in an undergraduate mathematics course

This paper reports on the findings of the evaluation of Learning Units (LU), a special type of Learning Object designed to help overcome the difficulties associated with learning Calculus concepts at undergraduate level. An Interactive Platform for Learning Calculus (PIAC) that serves as a container for the LU was created following a specific instructional design, namely, the Teaching Unit Model (TUM), which in turn, rules the platform's design, development and implementation. A general perspective on the development of the platform and its LU is presented, including the results of usability and functionality evaluations, which indicate that the platform and the LU comply with different functionality and usability criteria which are fundamental for their introduction into formal university courses. The platform was utilized in a higher education Calculus course, and its effects on different aspects of the learning process were studied. Two experimental groups and two control groups for a total of 102 students taking the Calculus course participated in the study. Results indicated an overall acceptance of using PIAC in class. Important evidence was obtained on the positive effects of using PIAC, not only influencing academic performance of students, but also in motivational aspects of the learning process. The grades obtained in all of academic activities by the groups using PIAC, compared with the control groups, provide solid evidence to the positive influence of the intervention of the technology under the TUM.     

(?, T)-fuzzy rough approximation operators and the TL-fuzzy rough ideals on a ring

In this paper, we consider a ring as a universal set and study (?, T)-fuzzy rough approximation operators with respect to a TL-fuzzy ideal of a ring. First, some new properties of generalized (?, T)-fuzzy rough approximation operators are obtained. Then, a new fuzzy algebraic structure - TL-fuzzy rough ideal is defined and its properties investigated. And finally, the homomorphism of (?, T)-fuzzy rough approximation operators is studied.     

Remote detection of Trichodesmium blooms in optically complex coastal waters: Examples with MODIS full-spectral data

Remote detection of the Trichodesmium spp. cyanobacteria blooms on the west Florida shelf (WFS) has been problematic due to optical complexity caused by sediment resuspension, coastal runoff, and bottom interference. By combining MODIS data measured by the ocean bands and land bands, an approach was developed to identify surface mats of Trichodesmium on the WFS. The approach first identifies possible bloom patches in MODIS FAI (floating algae index) 250 m resolution imagery derived from the Rayleigh-corrected reflectance at 667, 859, and 1240 nm. Then, spectral analysis examines the unique reflectance characteristics of Trichodesmium at 469, 488, 531, 551, and 555 nm due to specific optical properties (absorption, backscattering, and fluorescence) of the unusual pigments in Trichodesmium. These spectral characteristics (i.e., high-low-high-low-high reflectance at 469-488-531-551-555 nm, respectively) differentiate Trichodesmium mats unambiguously from other features observed in the FAI imagery, such as Sargassum spp. Tests in other coastal locations show that the approach is robust and applicable to other optically complex waters. Results shown here can help study Trichodesmium bloom dynamics (e.g., initiation and bloom formation) and may also help design future sensors to better detect and quantify Trichodesmium, an important N₂ fixer in the global oceans.     

Second order (F, α, ρ, d)-convexity and duality in multiobjective programming

A class of second order (F, α, ρ, d)-convex functions and their generalizations is introduced. Using the assumptions on the functions involved, weak, strong and strict converse duality theorems are established for a second order Mond-Weir type multiobjective dual.     

Continuous reverse k nearest neighbor monitoring on moving objects in road networks

Continuous reverse k nearest neighbor (CRkNN) monitoring in road networks has recently received increasing attentions. However, there is still a lack of efficient CRkNN algorithms in road networks up to now. In road networks, moving query objects and data objects are restricted by the connectivity of the road network and both the object–query distance and object–object distance updates affect the result of CRkNN queries. In this paper, we present a novel algorithm for continuous and incremental evaluation of CRkNN queries in road networks. Our method is based on a novel data structure called dual layer multiway tree (DLM tree) we proposed to represent the whole monitoring region of a CRkNN query q. We propose several lemmas to reduce the monitoring region of q and the number of candidate objects as much as possible. Moreover, by associating a variable NN_count with each candidate object, we can simplify the monitoring of candidate objects. There are a large number of objects roaming in a road network and many of them are irrelevant to a specific CRkNN query of a query object q. To minimize the processing extension, for a road in the network, we give an IQL list and an IQCL list to specify the set of query objects and data objects whose location updates should be maintained for CRkNN processing of query objects. Our CRkNN method consists of two phase: the initial result generating phase and incremental maintenance phase. In each phase, algorithms with high performance are proposed to make our CRkNN method more efficient. Extensive simulation experiments are conducted and the result shows that our proposed approach is efficient and scalable in processing CRkNN queries in road networks.     

Detecting near-surface moisture stress in Sphagnum spp.

Estimating near-surface moisture conditions from the reflectance spectra (400-2500 nm) of Sphagnum moss offers great opportunities for the use of remote sensing as a tool for large-scale detailed monitoring of near-surface peatland hydrological conditions. This article investigates the effects of changes in near-surface and surface moisture upon the spectral characteristics of Sphagnum moss. Laboratory-based canopy reflectance data were collected from two common species of Sphagnum subjected to drying and subsequent rewetting. Several spectral indices developed from the near infra-red (NIR) and shortwave infra-red (SWIR) liquid water absorption bands and two biophysical indices (REIP and the chlorophyll index) were correlated with measures of near-surface moisture. All spectral indices tested were significantly correlated with near-surface moisture (with r between 0.27 and 0.94). The strongest correlations were observed using indices developed from the NIR liquid water absorption features (fWBI₉₈₀ and fWBI₁₂₀₀). However, a hysteretic response was observed in both NIR indices when the canopies were re-hydrated, a finding which may have implications for the timing of remote sensing image acquisition. The Moisture Stress Index (MSI), developed from the SWIR liquid water absorption feature also showed strong correlations with near-surface wetness although the range of moisture conditions over which the index was able to detect change was highly dependent on Sphagnum species. Of the biophysical spectral indices tested (REIP and the chlorophyll index), the most significant relationships were observed between the chlorophyll index and near-surface wetness. All spectral indices tested were species specific, and this is attributed to differences in canopy morphology between Sphagnum species. The potential for developing estimations of surface and near-surface hydrological conditions across northern peatlands using remote sensing technology is discussed.     

How international is Computers and Composition?

In this article, I examine to what extent Computers and Composition: An International Journal for Teachers of Writing is international. My analysis of several aspects of the journal indicates limited international scope. I also discuss two issues important when considering the potential international scope of computers and writing research and practices: the differing uses of computers for writing by different language users and the differing concepts of identity and self in different cultures in relation to writing. I conclude with concrete suggestions for broadening our perspectives on computers and writing and making this journal truly international.