An analysis of the application of AI to the development of intelligent aids for flight crew tasks

This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research

Nonword Item Generation: Predicting Item Difficulty in Nonword Repetition

abstract: The current study employs item difficulty modeling procedures to evaluate the feasibility of potential generative item features for nonword repetition. Specifically, the extent to which the manipulated item features affect the theoretical mechanisms that underlie nonword repetition accuracy was estimated. Generative item features were based on the phonological loop component of Baddelely's model of working memory which addresses phonological short-term memory (Baddeley, 2000, 2003; Baddeley & Hitch, 1974). Using researcher developed software, nonwords were generated to adhere to the phonological constraints of Spanish. Thirty-six nonwords were chosen based on the set item features identified by the proposed cognitive processing model. Using a planned missing data design, two-hundred fifteen Spanish-English bilingual children were administered 24 of the 36 generated nonwords. Multiple regression and explanatory item response modeling techniques (e.g., linear logistic test model, LLTM; Fischer, 1973) were used to estimate the impact of item features on item difficulty. The final LLTM included three item radicals and two item incidentals. Results indicated that the LLTM predicted item difficulties were highly correlated with the Rasch item difficulties (r = .89) and accounted for a substantial amount of the variance in item difficulty (R2 = .79). The findings are discussed in terms of validity evidence in support of using the phonological loop component of Baddeley's model (2000) as a cognitive processing model for nonword repetition items and the feasibility of using the proposed radical structure as an item blueprint for the future generation of nonword repetition items.Dissertation/ThesisM.A. Educational Psychology 201

Development and Validation of a Modified Multiple Errands Test for Adults with Intellectual Disabilities

Background: The aims of the current study were to adapt a version of the MET for people with intellectual disabilities (IDs) and assess its ecological and construct validity. Material and Methods: Using a correlational design, 40 participants with IDs were invited to complete a battery of neuropsychological assessments and the modified Multiple Errands Test for Intellectual Disabilities (mMET-IDs). Results: The ability to successfully complete tasks on the mMET-IDs correlated significantly with measures of the Supervisory Attentional System, namely, the Tower of London Test and the Six Parts Test. However, performance on the mMET-IDs and the Six Parts Test could be accounted for by Verbal IQ and receptive vocabulary. The mMET-IDs failed to correlate with the DEX-IR. Conclusions: The mMET-IDs can be successfully used to assess some aspects of the Supervisory Attentional System in people with IDs. Further development is needed, however, to improve the ecological validity of the mMET-IDs

A comparison of traditional test blueprinting to assessment engineering in a large scale assessment context

This dissertation investigates the plausibility of computing Assessment Engineering cognitive task model derived difficulty parameters through careful engineering design, and to compare the task model derived difficulty with empirical Rasch model ‘b’ parameter estimates. In addition, this research seeks to examine whether cognitive task model derived difficulty can replace the Rasch Model ‘b’ parameter estimates for scoring examinees. The study uses real data constituting four assessments from a large-scale testing company. The results of the analysis indicated strong correlations between the task model and the empirical difficulty parameter estimates. While most of the empirical items satisfied the standard requirements of fit, there were several misfitting task model items, however, the task model was able to provide adequate fit for most of the items. Furthermore the proficiency scores for the empirical and the task model matched each other quite well for all of the assessments, showing no differences among the empirical and task model scores. An examination of the standard error statistics showed no differences between the empirical Rasch model and the cognitive task models. Assessment engineering is a new field, therefore very little research exists on comparing assessment engineering cognitive task model derived difficulties to empirical Rasch model parameter estimates. Moreover, the effects of cognitive task model estimate on proficiency scores has not been investigated. This study showed that through assessment engineering cognitive task modelling design process, it is possible to generate the item difficulty parameters a priori, without the use of any complex data hungry statistical models. For large scale testing companies, this will significantly reduce cost for pilot testing and make available hundreds of items that operate in a psychometrically similar manner. This design process produces difficulty parameters that operate in a similar manner to the statistical difficulty parameters computed in traditional ways using the Rasch model

Component processes of early reading, spelling, and narrative writing skills in Turkish: a longitudinal study

The study examined: (a) the role of phonological, grammatical, and rapid automatized naming (RAN) skills in reading and spelling development; and (b) the component processes of early narrative writing skills. Fifty-seven Turkish-speaking children were followed from Grade 1 to Grade 2. RAN was the most powerful longitudinal predictor of reading speed and its effect was evident even when previous reading skills were taken into account. Broadly, the phonological and grammatical skills made reliable contributions to spelling performance but their effects were completely mediated by previous spelling skills. Different aspects of the narrative writing skills were related to different processing skills. While handwriting speed predicted writing fluency, spelling accuracy predicted spelling error rate. Vocabulary and working memory were the only reliable longitudinal predictors of the quality of composition content. The overall model, however, failed to explain any reliable variance in the structural quality of the composition

Joint morphological-lexical language modeling for processing morphologically rich languages with application to dialectal Arabic

Language modeling for an inflected language such as Arabic poses new challenges for speech recognition and machine translation due to its rich morphology. Rich morphology results in large increases in out-of-vocabulary (OOV) rate and poor language model parameter estimation in the absence of large quantities of data. In this study, we present a joint morphological-lexical language model (JMLLM) that takes advantage of Arabic morphology. JMLLM combines morphological segments with the underlying lexical items and additional available information sources with regards to morphological segments and lexical items in a single joint model. Joint representation and modeling of morphological and lexical items reduces the OOV rate and provides smooth probability estimates while keeping the predictive power of whole words. Speech recognition and machine translation experiments in dialectal-Arabic show improvements over word and morpheme based trigram language models. We also show that as the tightness of integration between different information sources increases, both speech recognition and machine translation performances improve

Development and application of computer software techniques to human factors task data handling problems Final report, 21 Jun. 1965 - 21 Jun. 1966

Computer software techniques applied to human factors task data handling problem