184 research outputs found
Recommended from our members
Social Addictive Gameful Engineering (SAGE): A Game-based Learning and Assessment System for Computational Thinking
At an unrivaled and enduring pace, computing has transformed the world, resulting in demand for a universal fourth foundation beyond reading, writing, and arithmetic: computational thinking (CT). Despite increasingly widespread acceptance of CT as a crucial competency for all, transforming education systems accordingly has proven complex. The principal hypothesis of this thesis is that we can improve the efficiency and efficacy of teaching and learning CT by building gameful learning and assessment systems on top of block-based programming environments. Additionally, we believe this can be accomplished at scale and cost conducive to accelerating CT dissemination for all.
After introducing the requirements, approach, and architecture, we present a solution named Gameful Direct Instruction. This involves embedding Parsons Programming Puzzles (PPPs) in Scratch, which is a block-based programming environment currently used prevalently in grades 6-8. PPPs encourage students to practice CT by assembling into correct order sets of mixed-up blocks that comprise samples of well-written code which focus on individual concepts. The structure provided by PPPs enable instructors to design games that steer learner attention toward targeted learning goals through puzzle-solving play. Learners receive continuous automated feedback as they attempt to arrange programming constructs in correct order, leading to more efficient comprehension of core CT concepts than they might otherwise attain through less structured Scratch assignments. We measure this efficiency first via a pilot study conducted after the initial integration of PPPs with Scratch, and second after the addition of scaffolding enhancements in a study involving a larger adult general population.
We complement Gameful Direct Instruction with a solution named Gameful Constructionism. This involves integrating with Scratch implicit assessment functionality that facilitates constructionist video game (CVG) design and play. CVGs enable learner to explore CT using construction tools sufficiently expressive for personally meaningful gameplay. Instructors are enabled to guide learning by defining game objectives useful for implicit assessment, while affording learners the opportunity to take ownership of the experience and progress through the sequence of interest and motivation toward sustained engagement. When strategically arranged within a learning progression after PPP gameplay produces evidence of efficient comprehension, CVGs amplify the impact of direct instruction by providing the sculpted context in which learners can apply CT concepts more freely, thereby broadening and deepening understanding, and improving learning efficacy. We measure this efficacy in a study of the general adult population.
Since these approaches leverage low fidelity yet motivating gameful techniques, they facilitate the development of learning content at scale and cost supportive of widespread CT uptake. We conclude this thesis with a glance at future work that anticipates further progress in scalability via a solution named Gameful Intelligent Tutoring. This involves augmenting Scratch with Intelligent Tutoring System (ITS) functionality that offers across-activity next-game recommendations, and within-activity just-in-time and on-demand hints. Since these data-driven methods operate without requiring knowledge engineering for each game designed, the instructor can evolve her role from one focused on knowledge transfer to one centered on supporting learning through the design of educational experiences, and we can accelerate the dissemination of CT at scale and reasonable cost while also advancing toward continuously differentiated instruction for each learner
LISA Data Analysis using MCMC methods
The Laser Interferometer Space Antenna (LISA) is expected to simultaneously
detect many thousands of low frequency gravitational wave signals. This
presents a data analysis challenge that is very different to the one
encountered in ground based gravitational wave astronomy. LISA data analysis
requires the identification of individual signals from a data stream containing
an unknown number of overlapping signals. Because of the signal overlaps, a
global fit to all the signals has to be performed in order to avoid biasing the
solution. However, performing such a global fit requires the exploration of an
enormous parameter space with a dimension upwards of 50,000. Markov Chain Monte
Carlo (MCMC) methods offer a very promising solution to the LISA data analysis
problem. MCMC algorithms are able to efficiently explore large parameter
spaces, simultaneously providing parameter estimates, error analyses and even
model selection. Here we present the first application of MCMC methods to
simulated LISA data and demonstrate the great potential of the MCMC approach.
Our implementation uses a generalized F-statistic to evaluate the likelihoods,
and simulated annealing to speed convergence of the Markov chains. As a final
step we super-cool the chains to extract maximum likelihood estimates, and
estimates of the Bayes factors for competing models. We find that the MCMC
approach is able to correctly identify the number of signals present, extract
the source parameters, and return error estimates consistent with Fisher
information matrix predictions.Comment: 14 pages, 7 figure
Sensitivity and parameter-estimation precision for alternate LISA configurations
We describe a simple framework to assess the LISA scientific performance
(more specifically, its sensitivity and expected parameter-estimation precision
for prescribed gravitational-wave signals) under the assumption of failure of
one or two inter-spacecraft laser measurements (links) and of one to four
intra-spacecraft laser measurements. We apply the framework to the simple case
of measuring the LISA sensitivity to monochromatic circular binaries, and the
LISA parameter-estimation precision for the gravitational-wave polarization
angle of these systems. Compared to the six-link baseline configuration, the
five-link case is characterized by a small loss in signal-to-noise ratio (SNR)
in the high-frequency section of the LISA band; the four-link case shows a
reduction by a factor of sqrt(2) at low frequencies, and by up to ~2 at high
frequencies. The uncertainty in the estimate of polarization, as computed in
the Fisher-matrix formalism, also worsens when moving from six to five, and
then to four links: this can be explained by the reduced SNR available in those
configurations (except for observations shorter than three months, where five
and six links do better than four even with the same SNR). In addition, we
prove (for generic signals) that the SNR and Fisher matrix are invariant with
respect to the choice of a basis of TDI observables; rather, they depend only
on which inter-spacecraft and intra-spacecraft measurements are available.Comment: 17 pages, 4 EPS figures, IOP style, corrected CQG versio
Occurrence of extended-spectrum beta-lactamase producing E. coli in broiler farm workers and the farm environment in Chiang Mai-Lamphun, Thailand
Antimicrobial resistance has become a major global public health threat. Extended-spectrum beta-lactamase (ESBL) producing E. coli appears as an emergence cause of treatment failure and increase mortality due to limited available effective antimicrobial agents. This study was conducted to determine the occurrence and antimicrobial resistance of ESBL producing E. coli in broilers, farm workers and environment in broiler farms in Chiang Mai-Lamphun, Thailand. The prevalence of ESBL producing E. coli in the broiler farms was 60.4% (29/48). The prevalence of ESBL producing E. coli from boot swabs, farm worker’s rectal swabs, feed and water samples were 43.8%, 55.7%, 12.5% and 2.1%, respectively. All isolates showed susceptible to imipenem and, in contrast, resistant to ampicillin. The results demonstrated high antimicrobial resistant rate to streptomycin (94.3%), gentamicin (86.8%), tetracycline (77.4%), chloramphenicol (66.0%), nalidixic acid (58.5%), and sulfamethoxazole/trimethoprim (56.6%). High percentage (96.2%) of isolates was classified as multidrug resistance (MDR). Thirty-five antimicrobial resistance profiles were identified with AMP-GEN-SXT-NAL-TET-CHL-STR, AMP-GEN-SXT-TET-CHL-STR (14.3%) as the 2 most prevalent profiles. The common resistance profiles between farm workers and broilers was demonstrated. These findings are suggestive for possible transmission between poultry and humans in broiler farms, most likely via close contact. Antimicrobial usage should be strictly controlled together with increase awareness on hygiene practices in broiler farms
Evidence for He I 10830 \AA~ absorption during the transit of a warm Neptune around the M-dwarf GJ 3470 with the Habitable-zone Planet Finder
Understanding the dynamics and kinematics of out-flowing atmospheres of hot
and warm exoplanets is crucial to understanding the origins and evolutionary
history of the exoplanets near the evaporation desert. Recently, ground based
measurements of the meta-stable Helium atom's resonant absorption at 10830
\AA~has become a powerful probe of the base environment which is driving the
outflow of exoplanet atmospheres. We report evidence for the He I 10830 \AA~in
absorption (equivalent width \AA) in the exosphere of
a warm Neptune orbiting the M-dwarf GJ 3470, during three transits using the
Habitable Zone Planet Finder (HPF) near infrared spectrograph. This marks the
first reported evidence for He I 10830 \AA\, atmospheric absorption for a
planet orbiting an M-dwarf. Our detected absorption is broad and its
blueshifted wing extends to -36 km/sec, the largest reported in the literature
to date. We modelled the state of Helium atoms in the exosphere of GJ3470b
based on assumptions on the UV and X-ray flux of GJ 3470, and found our
measurement of flux-weighted column density of meta-stable state Helium
, derived from our transit
observations, to be consistent with model, within its uncertainties. The
methodology developed here will be useful to study and constrain the
atmospheric outflow models of other exoplanets like GJ 3470b which are near the
edge of the evaporation desert.Comment: Accepted in Ap
Banner News
https://openspace.dmacc.edu/banner_news/1406/thumbnail.jp
Extracting galactic binary signals from the first round of Mock LISA Data Challenges
We report on the performance of an end-to-end Bayesian analysis pipeline for
detecting and characterizing galactic binary signals in simulated LISA data.
Our principal analysis tool is the Blocked-Annealed Metropolis Hasting (BAM)
algorithm, which has been optimized to search for tens of thousands of
overlapping signals across the LISA band. The BAM algorithm employs Bayesian
model selection to determine the number of resolvable sources, and provides
posterior distribution functions for all the model parameters. The BAM
algorithm performed almost flawlessly on all the Round 1 Mock LISA Data
Challenge data sets, including those with many highly overlapping sources. The
only misses were later traced to a coding error that affected high frequency
sources. In addition to the BAM algorithm we also successfully tested a Genetic
Algorithm (GA), but only on data sets with isolated signals as the GA has yet
to be optimized to handle large numbers of overlapping signals.Comment: 13 pages, 4 figures, submitted to Proceedings of GWDAW-11 (Berlin,
Dec. '06
- …