We describe the development, pilot-testing, refinement, and four evaluations of Diagnostic Question Generator (DQGen), which automatically generates multiple choice cloze (fill-in-the-blank) questions to test children's comprehension while reading a given text. Unlike previous methods, DQGen tests comprehension not only of an individual sentence but of the context preceding it. To test different aspects of comprehension, DQGen generates three types of distractors: ungrammatical distractors test syntax; nonsensical distractors test semantics; and locally plausible distractors test inter-sentential processing.

1. (1) A pilot study of DQGen 2012 evaluated its overall questions and individual distractors, guiding its refinement into DQGen 2014.

2. (2) Twenty-four elementary students generated 200 responses to multiple choice cloze questions that DQGen 2014 generated from forty-eight stories. In 130 of the responses, the child chose the correct answer. We define the distractiveness of a distractor as the frequency with which students choose it over the correct answer. The incorrect responses were consistent with expected distractiveness: twenty-seven were plausible, twenty-two were nonsensical, fourteen were ungrammatical, and seven were null.

3. (3) To compare DQGen 2014 against DQGen 2012, five human judges categorized candidate choices without knowing their intended type or whether they were the correct answer or a distractor generated by DQGen 2012 or DQGen 2014. The percentage of distractors categorized as their intended type was significantly higher for DQGen 2014.

4. (4) We evaluated DQGen 2014 against human performance based on 1,486 similarly blind categorizations by twenty-seven judges of sixteen correct answers, forty-eight distractors generated by DQGen 2014, and 504 distractors authored by twenty-one humans. Surprisingly, DQGen 2014 did significantly better than humans at generating ungrammatical distractors and marginally better than humans at generating nonsensical distractors, albeit slightly worse at generating plausible distractors. Moreover, vetting DQGen 2014's output and writing distractors only when necessary would halve the time to write them all, and produce higher quality distractors.

Infants with Spina Bifida (SB) were compared to typically developing infants (TD) using a conjugate reinforcement paradigm at 6 months-of-age (n = 98) to evaluate learning, and retention of a sensory-motor contingency. Analyses evaluated infant arm-waving rates at baseline (wrist not tethered to mobile), during acquisition of the sensory-motor contingency (wrist tethered), and immediately after the acquisition phase and then after a delay (wrist not tethered), controlling for arm reaching ability, gestational age, and socioeconomic status. Although both groups responded to the contingency with increased arm-waving from baseline to acquisition, 15% to 29% fewer infants with SB than TD were found to learn the contingency depending on the criterion used to determine contingency learning. In addition, infants with SB who had learned the contingency had more difficulty retaining the contingency over time when sensory feedback was absent. The findings suggest that infants with SB do not learn motor contingencies as easily or at the same rate as TD infants, and are more likely to decrease motor responses when sensory feedback is absent. Results are discussed with reference to research on contingency learning in infants with and without neurodevelopmental disorders, and with reference to motor learning in school-age children with SB. (JINS, 2013, 19, 1–10)

This paper studies the poly-Si crystallization mechanism under the high power (200 W) Nd:YAG solid state pulsed laser annealing system. It is found that the Gaussian-distributed laser beam profile successfully produce large super lateral growth process window. The devices in the SLG process window exhibit field-effect mobility around 250 cm2/V.s and the threshold voltage lower than 1 V. The influence of a-Si film thickness and the laser scan pitch on the process window is also carefully investigated.

SIMS analysis was applied to the characterization of GaN, AlGaN/GaN and InGaN/GaN grown by MOCVD. Such characterization enables the control of purity and doping, and the determination of growth rate and alloy composition. The analysis can be performed on finished optoelectronic and electronic devices and this makes SIMS technique a powerful tool for failure analysis, reverse engineering, and concurrent engineering.

The objective is to derive a variation of constants formula for systems of functional differential equations (or delay differential equations) coupled with functional equations (or difference equations). The difficulties arise because of the constraints imposed by the functional equations.