Task analysis

Marksmanship proficiency remains one of the most fundamental competencies required by military personnel, lawenforcement officers, and security operators. Effective weapons training directly influences mission success, force
protection, combat effectiveness, and operational readiness. Traditionally, marksmanship training has relied on
live-fire exercises conducted on outdoor and indoor firing ranges. While live-fire training provides realistic ballistic
effects and authentic weapon handling experience, it is associated with significant challenges, including
ammunition expenditure, safety risks, environmental concerns, range availability constraints, and limited
opportunities for objective performance analytics. Advances in simulation technologies have led to the emergence
of indoor marksmanship simulation systems capable of providing realistic, repeatable, cost-effective, and datadriven training environments. This paper presents a comprehensive review of indoor marksmanship simulation
ranges and associated technologies employed in military and law-enforcement training. The review examines laserbased weapon simulators, infrared and optical tracking systems, high-speed camera-based hit detection
architectures, pneumatic and electromechanical recoil simulators, computer vision-based scoring systems, Virtual
Reality (VR), Augmented Reality (AR), mixed reality (MR), Artificial Intelligence (AI)-assisted coaching platforms,
machine learning-based performance assessment systems, and digital twin technologies. Comparative analysis of
commercial and military simulation systems is conducted, while current technological limitations, implementation
challenges, and future research opportunities are critically evaluated. Particular emphasis is placed on the
integration of computer vision, deep learning, Explainable AI (XAI), reinforcement learning, and adaptive training
technologies for intelligent shooter performance optimisation. The review further identifies research gaps and
proposes a technology roadmap for next-generation AI-enabled indoor marksmanship training ecosystems. The
findings indicate that future military training systems will increasingly transition from score-based simulators
toward autonomous, adaptive, and intelligent training platforms capable of continuously enhancing individual and
collective combat readiness.

This study examines the occupational health challenges faced by artisans in Ghana's Ashanti Region. The study employed a purposive sampling technique to select 425 masons through questionnaires. The data collected included workers' mass, block weights, and health problems. The analysis identified fourteen health problems, with headaches, muscle pain, lower back pain, chronic pain, and bruises being most prevalent. Artisan weight negatively correlated with weights of 125 mm blocks (r =-0.202, p < 0.01) and 150 mm blocks (r =-0.248, p < 0.01). Additionally, artisan weight showed a negative correlation with working hours (coefficient =-0.133, p < 0.05), as did body weight with resting hours (coefficient =-0.217, p < 0.05). Higher educational qualifications correlated positively with lifting-related health issues (coefficient = 0.259, p = 0.000) and negatively with weatherrelated issues (coefficient =-0.154, p = 0.002). Moreover, the number of working days per week was positively correlated with lifting problems (coefficient = 0.270, p < 0.05). The study recommends redesigning block sizes to reduce physical strain. Additionally, policy measures such as reducing machinery import taxes are suggested to encourage mechanisation. The study further emphasises the need for training institutions to incorporate occupational health education into artisan training programs.

Puji syukur ke hadirat Tuhan Yang Maha Esa karena atas rahmat dan karunia-Nya penulis dapat menyelesaikan laporan yang berjudul "Manajemen Risiko dan Audit Keamanan Aplikasi Web Ko-eclipse Berdasarkan Metode OWASP dan Pendekatan ISO/IEC 27001:2022" dengan baik. Laporan ini disusun untuk memenuhi tugas akhir Mata Kuliah Manajemen Risiko dan Keamanan Informasi. Penulis menyadari bahwa penyusunan laporan ini tidak terlepas dari bantuan, bimbingan, dan dukungan dari berbagai pihak. Oleh karena itu, penulis menyampaikan terima kasih kepada Bapak Zulhair Jidan Dj. Tamu, S.Kom., M.Kom., selaku dosen pengampu Mata Kuliah Manajemen Risiko dan Keamanan Informasi yang telah memberikan arahan dan bimbingan selama proses pembelajaran, serta seluruh pihak yang telah memberikan dukungan, masukan, dan referensi yang membantu dalam penyusunan laporan ini. Penulis menyadari bahwa laporan ini masih memiliki berbagai keterbatasan dan kekurangan. Oleh karena itu, kritik dan saran yang membangun sangat diharapkan demi perbaikan dan penyempurnaan karya ilmiah di masa mendatang. Akhir kata, penulis berharap laporan ini dapat memberikan manfaat serta menambah wawasan mengenai penerapan manajemen risiko dan audit keamanan informasi pada pengembangan aplikasi berbasis web.

In the present study, we investigated possible influences on the unitization of responses. In Experiments 1, 2, 3, and 6, we found that when the same small fragment (i.e., a few consecutive responses in a sequence) was presented as part of two larger sequences, participants responded to it faster when it was part of the sequence that was presented more often. This indicates that chunking can be driven by task-relevant considerations, as opposed to co-occurrence. The results are discussed in the context of chunking theories and the relevant motor learning literature.

Small companies can find it difficult to preserve their knowledge, and also to structure a design process. A design methodology is proposed, based on design knowledge reuse and suitable for developing new manufacturing processes in an SME context. This paper describes a knowledge structuring and capitalization method, where a functional description is applied. The purpose is to capitalize technical solutions and the components used to carry out a given function, and to build a knowledge base that could be reused when designing new manufacturing processes. In this way, the time spent on research into design concepts can be reduced. Components are identified using the Converter-Transmitter-Operator-Control classification, based on describing the functional flow path in terms of energy. Produced and induced effects associated with the components are highlighted, by identifying the relevant conjugate variables for the functional flows. The choice of solutions in the reuse phase is thus ...

This paper focuses on second language (L2) learning through task-based interaction as well as the compatibility of the theories of taskbased learning and Vygotsky's sociocultural theory. Language tasks encourage L2 learning by using language as a tool to accomplish a goal. This study analyzes the interaction of first-semester French students while performing a group task created according to criteria in recent research by . The task focused on a particular grammatical point of French. Students' group discussions and activities were recorded. Overall, task interpretation varied among groups (e.g., type of interaction, division of labor, use of English as a mediator, scaffolding, meta-task talk, and off-task talk). However, components of an effective task were apparent (interaction between form and meaning, real communication, interactive learning, later success, and positive classroom morale). The results indicate that Lee's suggestions for task-based classroom interaction are compatible with a Vygotskian framework for learning. Together they provide the theoretical and practical basis for the potential of tasks in the classroom. Two appendixes present the French and English versions of the class activity. (Author/SM) Reproductions supplied by EDRS are the best that can be made from the original document.

Adapting the educational process for students with Autism Spectrum Disorder (ASD) involves a personalized approach to both educational content and the teaching strategies implemented by educators in instructional practice. Personalization requires the creation of a learning environment that encourages the development of academic, social, and emotional skills while considering both the students' needs, for which compensatory elements must be identified, and their strengths, which may serve as anchor resources for the further development of abilities. This article addresses the adaptation of teaching strategies for students with ASD through prompting techniques, reward systems, and visual supports.

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BACKGROUND: Neurosurgical task shifting and task sharing (TS/S), delegating clinical care to non-neurosurgeons, is ongoing in many hospital systems in which neurosurgeons are scarce. Although TS/S can increase access to treatment, it remains highly controversial. This survey investigated perceptions of neurosurgical TS/S to elucidate whether it is a permissible temporary solution to the global workforce deficit. -METHODS: The survey was distributed to a convenience sample of individuals providing neurosurgical care. A digital survey link was distributed through electronic mailing lists of continental neurosurgical societies and various collectives, conference announcements, and social media platforms (July 2018eJanuary 2019). Data were analyzed by descriptive statistics and univariate regression of Likert Scale scores. -RESULTS: Survey respondents represented 105 of 194 World Health Organization member countries (54.1%; 391 respondents, 162 from high-income countries and 229 from low-and middle-income countries [LMICs]). The most agreed on statement was that task sharing is preferred to task shifting. There was broad consensus that both task shifting and task sharing should require competency-based evaluation, standardized training endorsed by governing organizations, and maintenance of certification. When perspectives were stratified by income class, LMICs were significantly more likely to agree that task shifting is professionally disruptive to traditional training, task sharing should be a priority where human resources are scarce, and to call for additional TS/S regulation, such as certification and formal consultation with a neurosurgeon (in person or electronic/telemedicine). -CONCLUSIONS: Both LMIC and high-income countries agreed that task sharing should be prioritized over task shifting and that additional recommendations and regulations could enhance care. These data invite future discussions on policy and training programs.

From equivalence checking to functional verification to design-space exploration, industrial verification tasks entail checking a large number of properties on the same design. Stateof-the-art tools typically solve all properties concurrently, or one-at-a-time. They do not optimally exploit subproblem sharing between properties, leaving an opportunity to save considerable verification resource via concurrent verification of properties with nearly identical cone of influence (COI). These high-affinity properties can be concurrently solved; the verification effort expended for one can be directly reused to accelerate the verification of the others, without hurting per-property verification resources through bloating COI size. We present a near-linear runtime algorithm for partitioning properties into provably highaffinity groups for concurrent solution. We also present an effective method to partition high-structural-affinity groups using semantic feedback, to yield an optimal multi-property localization abstraction solution. Experiments demonstrate substantial endto-end verification speedups through these techniques, leveraging parallel solution of individual groups.

From equivalence checking to functional verification to design-space exploration, industrial verification tasks entail checking a large number of properties on the same design. Stateof-the-art tools typically solve all properties concurrently, or one-at-a-time. They do not optimally exploit subproblem sharing between properties, leaving an opportunity to save considerable verification resource via concurrent verification of properties with nearly identical cone of influence (COI). These high-affinity properties can be concurrently solved; the verification effort expended for one can be directly reused to accelerate the verification of the others, without hurting per-property verification resources through bloating COI size. We present a near-linear runtime algorithm for partitioning properties into provably highaffinity groups for concurrent solution. We also present an effective method to partition high-structural-affinity groups using semantic feedback, to yield an optimal multi-property localization abstraction solution. Experiments demonstrate substantial endto-end verification speedups through these techniques, leveraging parallel solution of individual groups.

This study aimed to investigate the impact of SportsMetrics programs on knee and ankle kinematics, as well as knee-ankle coupling responses during double leg landings among female athletes with dynamic knee valgus (ligament dominance). Methods: Eighty-four female athletes, including 30 volleyball players, 30 basketball players, and 24 soccer players, were randomly divided into two equal training (TG) and a control groups (CG). The TG underwent 18 sessions of SportsMetrics exercises, while the CG maintained their regular exercise routine. Dynamic knee valgus, lower limb kinematics, and coordination were assessed using the double leg squat and landing error scoring system tests. Main outcome measures: The main outcome measures encompassed knee sagittal and frontal kinematics, ankle sagittal kinematics, as well as knee-ankle coordination and its variability. Results: Significant reduction in knee range of motion in the frontal plane was observed across all three sports during landing. The SportsMetrics program tailored for basketball players led to a specific increase in knee flexion. Conclusion: The implementation of SportsMetrics effectively modifies ACL injury risk factors, addressing dynamic knee valgus and landing techniques in female athletes. Female athletes displaying dynamic knee valgus are advised to incorporate sport-specific SportsMetrics programs into their training regimens for optimal results.

Modern automated penetration testing tools effectively identify application-layer vulnerabilities such as SQL Injection, Insecure Direct Object Reference (IDOR), Cross-Site Scripting (XSS), and authentication weaknesses. However, traditional vulnerability scoring systems emphasize technical severity and often overlook the business impact of exposed Personally Identifiable Information (PII), leading to suboptimal prioritization in enterprise environments. This paper presents an AI-Driven Contextual Risk Prioritization Framework for PII-aware penetration testing. The framework integrates AWS Security Agent outputs, API schema metadata, and a PII sensitivity taxonomy to construct enriched vulnerability context. An AI-based reasoning layer generates a Contextual Adjustment Factor (ACF), which is combined with PII sensitivity, exploitability, and exposure to produce a normalized risk score. Experimental results show improved prioritization of high-impact, data-sensitive vulnerabilities compared to CVSS-based approaches, while reducing the priority of lower-impact findings.

This paper presents an approach to layout static components of user interfaces as hand-drawn compositions of simple geometric shapes, using sketch recognition and visual languages. The system uses a visual grammar built from drawings collected from users. We tried to understand how people sketch interfaces and what combinations of shapes they are more likely to used when sketching widgets. From there we implemented a prototype system, for creating user interfaces through hand-drawn geometric shapes, identified by a ...

Cognitive task and work analyses are approaches to the analysis and support of cognitive work (rather than primarily physical or perceptual activities). Although a variety of methods exist for performing cognitive task and work analyses, they share a common goal of providing information about two mutually reinforcing perspectives. One perspective focuses on the fundamental characteristics of the work domain and the cognitive demands they impose. The other focuses on how current practitioners respond to the demands of the domain. This includes a description of the knowledge and skills practitioners have developed to operate effectively as well as any limitations in knowledge and strategies that contribute to performance problems. This chapter provides a broad survey of cognitive task analysis and cognitive work analysis methods. Some of the methods highlight techniques for knowledge gathering, whereas others focus on aspects of analysis and representation. Still other techniques emphasize process outputs, such as formal (computational) models of cognitive activities or design artifacts and associated rationales. In this chapter we review specific cognitive task and work analysis methods and describe through illustration how these methods can be adapted to meet specific project objectives and pragmatic constraints. Cogni tive task and work analyses are approaches to the analysis and support of cognitive work (rather than primarily physical or perceptual activities). Although types of cognitive task and work analysis span a variety of perspectives and methodologies, they share the goal of providing information about two mutually reinforcing perspectives, which will be emphasized throughout this chapter. One perspective focuses on the fundamental characteristics of the work domain and the cognitive demands they impose. The other focuses on how current practitioners respond to the demands of the domain. This includes a characterization of the knowledge and strategies that domain practitioners have developed that allow them to function at an expert level as well as limitations in knowledge and strategies that contribute to performance problems. In this chapter we summarize and highlight aspects of numerous cognitive engineering methods that share the goals of cognitive task and work analyses. The chapter provides a broad survey of alternative, often complementary, methods and, using illustrative cases, demonstrates how these methods can be adapted and combined to meet the goals and pragmatic constraints of real-world projects. In the last quarter of the 20th century, high-profile system failures (e.g., Three Mile Island, numerous aviation accidents, and military incidents such as the July 1988 accidental Key d ocum ents Key d ocum ents that are high p rofit High profit d ocuments ©1999 Patterson

This study introduces a framework for cyber threat intelligence aimed at enhancing Türkiye's proactive cybersecurity capabilities, specifically addressing security vulnerabilities. A geographic analysis involving 11,911 malicious IP addresses and 6,927 malicious URLs from the National Cyber Incident Response Center (TR-CERT) facilitated the formation of intelligence-driven geographic blocking firewall policies, thus reinforcing proactive network defense strategies. The research correlated threat indicators from TR-CERT with exploit intelligence from the open-source Exploit-DB platform, establishing connections between Indicators of Compromise (IoCs) and security vulnerabilities. Risk calibration maps were developed to match these vulnerabilities with the Open Web Application Security Project (OWASP) Top 10 risk categories and validated against the National Vulnerability Database (NVD). This prioritization took into account vulnerability prevalence, Common Vulnerability Scoring System (CVSS) scores, exploitability levels, and potential impact. In addition, a dynamic risk scoring model based on Monte Carlo simulation was also used to estimate vulnerability risks, with exploitability serving as the probability parameter and CVSS scores as the impact parameter. The findings underscore that integrating exploit-focused vulnerability intelligence into national cyber threat intelligence processes can significantly enhance the development of more effective and intelligence-driven cyber defense architectures in rapidly evolving threat environments.

This systematic review examines studies on how adult second language (L2) speakers derive scalar implicaturesinferences such as interpreting 'some' as 'some but not all'and how methodological, linguistic, and individual factors modulate their pragmatic performance. Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a systematic search was conducted across Scopus, Web of Science, and Google Scholar, covering studies published between 2000 and 2025. After screening and applying the inclusion criteria, a total of 19 experimental studies were retained for analysis. These studies collectively test over 2500 participants from diverse linguistic backgrounds and L2 proficiency using a wide range of tasks (truth-value judgment, covered box, self-paced reading, sentence evaluation). Results from the 19 reviewed studies reveal substantial methodological heterogeneity but highlight robust qualitative patterns. L2 learners generally succeed in deriving SIs, yet outcomes vary with (i) exposure type (classroom vs. immersion), (ii) proficiency assessment, (iii) task demands, and (iv) lexical diversity of the tested scales. Evidence from recent studies suggests that differences often reflect processing constraints and lexical-semantic transfer rather than a genuine pragmatic difficulty. Moreover, factors such as response format (binary vs. graded) and stimulus informativeness significantly affect judgments, challenging long-standing assumptions about L2 pragmatic insensitivity. We conclude that L2 pragmatic competence in scalar inference is modulated by input experience, individual factors, cognitive resources, and task design. The review calls for methodological standardization and for expanding beyond the canonical < some, all > scale to encompass scalar diversity, cross-linguistic transfer, and online processing measures.

we can learn extensions and modifications to it, getting better and better with experience. In contrast, if we want to get a computer to do a completely new task, the only practical approach has been through programming. This has served us well so far, but with advances in artificial intelligence, cognitive science, and robotics, we're approaching a future populated with intelligent systems that have the cognitive and physical capabilities to perform many different tasks. Unfortunately, it will be impossible to preprogram all the tasks that creative, generative human users will want their agents and robots to perform. It will be similarly unlikely that billions of users in the general public will have the specialized skills necessary to customize and extend the capabilities of their agents using programming languages. So how will future intelligent systems learn the tasks we want them to perform? A n enabling characteristic of humans and other intelligent entities is that we aren't limited to a fixed set of innate or preprogrammed tasks. We quickly learn new tasks through language, gestures, observation, and other forms of natural communication. After we learn the essence of a task,

Passive transmission-based robotic devices are capable of providing motion guidance while ensuring user safety and engagement. To circumvent some of the drawbacks associated with steering continuously variable transmissions based on rolling contacts, we are exploring a class of discretely variable devices, based on brakes and hydrostatic transmissions. Previously available control methods for discretely variable devices were built on velocity fields and only developed to stabilize a 1D target manifold. For n-DOF devices, methods to stabilize target manifolds of dimension 1 to n-1 are of interest. In this paper we contribute constraint field methods that stabilize n-1 dimensional target manifolds while leaving the orthogonal subspace free to the control of the operator. We also contribute force-modulated SDOF velocity fields, which add between 1 and n-2 virtual DOF to the motion of devices whose physical constraints leave one DOF. Control performance is demonstrated in simulation for 3DOF devices capable of imposing 1D or 2D constraints and in experiment for 2DOF devices imposing 1D constraints. Our experimental apparatus features digital hydraulic transmissions that are easily configured for n-dimensional space and capable of imposing constraints of any dimension, thus motivating the contributed methods.

Adaptive Hypermedia systems have sought to support users by anticipating the usersí information requirements for a particular context, and rendering the appropriate version of the content and hypermedia links. Adaptable Hypermedia, on the other hand, takes the approach that there are times when adaptive approaches may not be feasible or available and that it would still be appropriate to facilitate user-determined access to information. For instance, users may come to a hypermedia and not have a well-defined goal in mind. Similarly their goals may change throughout exploration, or their expertise change from one section to another. To support these shifting conditions, we may need affordances on the content that a solely adaptive approach cannot best support. In this paper we present an interaction design to support user-determined adaptable content and describe three techniques which support the interaction: preview cues, dimensional sorting and spatial context. We call the combined approach mSpace. We present the preliminary task analysis that lead us to our interaction design, we describe the three techniques, overview the architecture for our prototype and consider next steps for generalizing deployment.

Currently, most systems for human-robot teaching allow only one mode of teacher-student interaction (e.g., teaching by demonstration or feedback), and teaching episodes have to be carefully set-up by an expert. To understand how we might integrate multiple, interleaved forms of human instruction into a robot learner, we performed a behavioral study in which 44 untrained humans were allowed to freely mix interaction modes to teach a simulated robot (secretly controlled by a human) a complex task. Analysis of transcripts showed that human teachers often give instructions that are nontrivial to interpret and not easily translated into a form useable by machine learning algorithms. In particular, humans often use implicit instructions, fail to clearly indicate the boundaries of procedures, and tightly interleave testing, feedback, and new instruction. In this paper, we detail these teaching patterns and discuss the challenges they pose to automatic teaching interpretation as well as the machine-learning algorithms that must ultimately process these instructions. We highlight the challenges by demonstrating the difficulties of an initial automatic teacher interpretation system.

Since 1983, discussions focused increasingly on the contribution to economic performance associated with the skills of the work force. Government policy went further by specifying skills important to economic performance and advocating their introduction into schools and training programs. Surprisingly little empirical research examined the importance of specific skills and their relationship with performance. A study examined self-reported skill needs across a range of job settings. Eight public utilities agreed to cooperate in the study, which examined workers across 15 jobs in each company. The companies identified benchmark jobs, common to all the companies and easily identifiable in the outside labor market. Skill issues were assessed by plant managers, workers, and their supervisors. Managers and supervisors were choLen at random. Each superv;sor reported a series of performance measures for each employee. Employees were surveyed and rated about skill issues, work organization, and job attitudes. The response rate was 100 percent from supervisors and 85 percent from employees. Results suggested that basic skills associated with academic learning were especially important to performance in the workplace. These skills were perceived as more important for improving performance by both employees and supervisors, whereas the perceived need to improve these skills was associated with more positive attitudes and behaviors. (Contains 9 endnotes, 34 references, and 8 tables.) (YLB)

Since 1983, discussions focused increasingly on the contribution to economic performance associated with the skills of the work force. Government policy went further by specifying skills important to economic performance and advocating their introduction into schools and training programs. Surprisingly little empirical research examined the importance of specific skills and their relationship with performance. A study examined self-reported skill needs across a range of job settings. Eight public utilities agreed to cooperate in the study, which examined workers across 15 jobs in each company. The companies identified benchmark jobs, common to all the companies and easily identifiable in the outside labor market. Skill issues were assessed by plant managers, workers, and their supervisors. Managers and supervisors were choLen at random. Each superv;sor reported a series of performance measures for each employee. Employees were surveyed and rated about skill issues, work organization, and job attitudes. The response rate was 100 percent from supervisors and 85 percent from employees. Results suggested that basic skills associated with academic learning were especially important to performance in the workplace. These skills were perceived as more important for improving performance by both employees and supervisors, whereas the perceived need to improve these skills was associated with more positive attitudes and behaviors. (Contains 9 endnotes, 34 references, and 8 tables.) (YLB)

ITEAM is proposed as a way to assess integrated human in the loop (HITL) simulation training environment effectiveness (i.e. to determine how well the simulation tools support the deliberate practice of specific skills) at the human ability level. A work in progress, ITEAM has been used to reassess two previously evaluated military simulation environments --the game Full Spectrum Command ( ) and the Engagement Skills Trainer Heavy Weapons Variant (2008). ITEAM results from both studies closely resemble and often match those concluded in the original empirical training effectiveness analysis (TEA) studies. A third study is currently underway to solidify ITEAM validity.

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington DC 20503. June 2014 principles, affordance theory, and human abilities, to measure the potential of integrated training environments (ITEs) to effectively support training. Empirical investigation of ITEs is costly, lacks formal guidance, and is therefore often unreliable. Ad hoc studies, commissioned by individual organizations, constitute the current state of Army ITE evaluation. These assessments are often entirely based on subject matter expert judgment through surveys, which produce results that are linked indirectly and loosely to the ITEs. What is required is a repeatable, inexpensive, analytical approach to ITE assessment that bounds the potential of a given system to the support it provides to the deliberate practice of specific tasks. The results of this research include the development and use of the integrated training environment assessment methodology (ITEAM). ITEAM was used to evaluate the ability of several ITEs to support the deliberate practice of specific tasks during training. The dissertation shows that ITEAM consistently predicted where training was supported by an ITE and generally how well. ITEAM is offered as a tool to be used early in the acquisition process to affordably define and verify the requirements of candidate ITE solutions for Department of Defense needs. Integrated training environment, training assessment, human abilities, fidelity, affordance theory, task analysis, verification, requirements analysis, simulations, TADSS 15. NUMBER OF PAGES 355 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington DC 20503. June 2014 principles, affordance theory, and human abilities, to measure the potential of integrated training environments (ITEs) to effectively support training. Empirical investigation of ITEs is costly, lacks formal guidance, and is therefore often unreliable. Ad hoc studies, commissioned by individual organizations, constitute the current state of Army ITE evaluation. These assessments are often entirely based on subject matter expert judgment through surveys, which produce results that are linked indirectly and loosely to the ITEs. What is required is a repeatable, inexpensive, analytical approach to ITE assessment that bounds the potential of a given system to the support it provides to the deliberate practice of specific tasks. The results of this research include the development and use of the integrated training environment assessment methodology (ITEAM). ITEAM was used to evaluate the ability of several ITEs to support the deliberate practice of specific tasks during training. The dissertation shows that ITEAM consistently predicted where training was supported by an ITE and generally how well. ITEAM is offered as a tool to be used early in the acquisition process to affordably define and verify the requirements of candidate ITE solutions for Department of Defense needs. Integrated training environment, training assessment, human abilities, fidelity, affordance theory, task analysis, verification, requirements analysis, simulations, TADSS 15. NUMBER OF PAGES 355 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified

: This research investigated the development and use of an analytical assessment methodology anchored in systems engineering principles, affordance theory, and human abilities, to measure the potential of integrated training environments (ITEs) to effectively support training. Empirical investigation of ITEs is costly, lacks formal guidance, and is therefore often unreliable. Ad hoc studies, commissioned by individual organizations, constitute the current state of Army ITE evaluation. These assessments are often entirely based on subject matter expert judgment through surveys, which produce results that are linked indirectly and loosely to the ITEs. What is required is a repeatable, inexpensive, analytical approach to ITE assessment that bounds the potential of a given system to the support it provides to the deliberate practice of specific tasks. The results of this research include the development and use of the integrated training environment assessment methodology (ITEAM). ITEAM...

This paper discusses the development of the Integrated Training Environment Assessment Methodology (ITEAM). ITEAM is proposed as a way to assess integrated human in the loop (HITL) simulation training environment effectiveness (i.e. to determine how well the simulation tools support the deliberate practice of specific skills) at the human ability level. A work in progress, ITEAM has been used to reassess two previously evaluated military simulation environments -- the game Full Spectrum Command (2004) and the Engagement Skills Trainer Heavy Weapons Variant (2008). ITEAM results from both studies closely resemble and often match those concluded in the original empirical training effectiveness analysis (TEA) studies. A third study is currently underway to solidify ITEAM validity.

The measurement of adult literacy has usually relied on either self-reports or educational attainment as proxies for proficiency over a broad range of skills. While useful in heightening awareness of the nature and extent of the literacy "problem" in each country, such indirect measures suffer from a number of important methodological deficiencies that ultimately limit their usefulness for informing public policy. In the late 1980s and early 1990s, a number of countries fielded direct assessments of adult basic skills, and these have played a central role in defining a coherent public policy response to the literacy issue. This report describes the development and application of a related suite of "proxy" measures that both extend the usefulness of these assessment-based measures and offer interesting insights into the stability of the phenomenon in a cross-national perspective.

Dozens of studies published on processing instruction (PI) make it one of the highly investigated areas within the field of second language acquisition (SLA). This review article provides an overview of 30 years of research in this area. The article first provides a brief account of the theoretical underpinnings of PI, its features, and the guidelines for devising structured input (SI) activities, which are the main causative factor accounting for the effects of PI. It then proceeds with a review of empirical studies carried out across six strands of research on PI and offers a detailed synthesis of the key findings emerging from each strand. The article ends with a general conclusion based on the findings of research to date and outlines directions for future research.

In this work we tackle the problem of child engagement estimation while children freely interact with a robot in a friendly, room-like environment. We propose a deep-based multi-view solution that takes advantage of recent developments in human pose detection. We extract the child's pose from different RGB-D cameras placed regularly in the room, fuse the results and feed them to a deep neural network trained for classifying engagement levels. The deep network contains a recurrent layer, in order to exploit the rich temporal information contained in the pose data. The resulting method outperforms a number of baseline classifiers, and provides a promising tool for better automatic understanding of a child's attitude, interest and attention while cooperating with a robot. The goal is to integrate this model in next generation social robots as an attention monitoring tool during various Child Robot Interaction (CRI) tasks both for Typically Developed (TD) children and children affected by autism (ASD).

The BRiMS Society and Conference (Behavioral Representation in Modeling and Simulation (BRiMS, brimsconference.org) promote cross-disciplinary communication for basic and applied scientific research in the realm of modeling and simulation of human behavior, with a particular emphasis on defense government-related tasks and behavior. Thus, the BRiMS conference brings together scientists, engineers, practitioners, and application users to discuss modeling behavior ranging from that of individuals to the behavior of whole societies, their interactions, and their implications. For a few days each year, we get to meet to share ideas and experiences, identify gaps in current capabilities, discuss new directions, highlight promising technologies, and showcase applications. This special issue is similar to our previous special issue ( ) in that it includes four papers based on the award winning conference papers of the 2010 annual conference, reviewed and extended to journal article length. The papers include a new model integrating top-down and bottom-up factors affecting visual target acquisition (Jungkunz and Darken 2011), the application of a statistical methodology W.G. Kennedy ( )

The BRiMS Society and Conference (Behavioral Representation in Modeling and Simulation (BRiMS, brimsconference.org) promote cross-disciplinary communication for basic and applied scientific research in the realm of modeling and simulation of human behavior, with a particular emphasis on defense government-related tasks and behavior. Thus, the BRiMS conference brings together scientists, engineers, practitioners, and application users to discuss modeling behavior ranging from that of individuals to the behavior of whole societies, their interactions, and their implications. For a few days each year, we get to meet to share ideas and experiences, identify gaps in current capabilities, discuss new directions, highlight promising technologies, and showcase applications. This special issue is similar to our previous special issue ( ) in that it includes four papers based on the award winning conference papers of the 2010 annual conference, reviewed and extended to journal article length. The papers include a new model integrating top-down and bottom-up factors affecting visual target acquisition (Jungkunz and Darken 2011), the application of a statistical methodology W.G. Kennedy ( )

The BRiMS Society and Conference (Behavioral Representation in Modeling and Simulation (BRiMS, brimsconference.org) promote cross-disciplinary communication for basic and applied scientific research in the realm of modeling and simulation of human behavior, with a particular emphasis on defense government-related tasks and behavior. Thus, the BRiMS conference brings together scientists, engineers, practitioners, and application users to discuss modeling behavior ranging from that of individuals to the behavior of whole societies, their interactions, and their implications. For a few days each year, we get to meet to share ideas and experiences, identify gaps in current capabilities, discuss new directions, highlight promising technologies, and showcase applications. This special issue is similar to our previous special issue ( ) in that it includes four papers based on the award winning conference papers of the 2010 annual conference, reviewed and extended to journal article length. The papers include a new model integrating top-down and bottom-up factors affecting visual target acquisition (Jungkunz and Darken 2011), the application of a statistical methodology W.G. Kennedy ( )

1 June 2011 The BRiMS Society and Conference (Behavioral Representation in Modeling and Simulation (BRiMS, brimsconference.org) promote cross-disciplinary communication for basic and applied scientific research in the realm of modeling and simulation of human behavior, with a particular emphasis on defense government-related tasks and behavior. Thus, the BRiMS conference brings together scientists, engineers, practitioners, and application users to discuss modeling behavior ranging from that of individuals to the behavior of whole societies, their interactions, and their implications. For a few days each year, we get to meet to share ideas and experiences, identify gaps in current capabilities, discuss new directions, highlight promising technologies, and showcase applications. This special issue is similar to our previous special issue (Kennedy, Ritter, & Best, 2010) in that it includes four papers based on the award winning conference papers of the 2010 annual conference, reviewed...

The BRiMS Society and Conference (Behavioral Representation in Modeling and Simulation (BRiMS, brimsconference.org) promote cross-disciplinary communication for basic and applied scientific research in the realm of modeling and simulation of human behavior, with a particular emphasis on defense government-related tasks and behavior. Thus, the BRiMS conference brings together scientists, engineers, practitioners, and application users to discuss modeling behavior ranging from that of individuals to the behavior of whole societies, their interactions, and their implications. For a few days each year, we get to meet to share ideas and experiences, identify gaps in current capabilities, discuss new directions, highlight promising technologies, and showcase applications. This special issue is similar to our previous special issue ( ) in that it includes four papers based on the award winning conference papers of the 2010 annual conference, reviewed and extended to journal article length. The papers include a new model integrating top-down and bottom-up factors affecting visual target acquisition (Jungkunz and Darken 2011), the application of a statistical methodology W.G. Kennedy ( )

The BRiMS Society and Conference (Behavioral Representation in Modeling and Simulation (BRiMS, brimsconference.org) promote cross-disciplinary communication for basic and applied scientific research in the realm of modeling and simulation of human behavior, with a particular emphasis on defense government-related tasks and behavior. Thus, the BRiMS conference brings together scientists, engineers, practitioners, and application users to discuss modeling behavior ranging from that of individuals to the behavior of whole societies, their interactions, and their implications. For a few days each year, we get to meet to share ideas and experiences, identify gaps in current capabilities, discuss new directions, highlight promising technologies, and showcase applications. This special issue is similar to our previous special issue ( ) in that it includes four papers based on the award winning conference papers of the 2010 annual conference, reviewed and extended to journal article length. The papers include a new model integrating top-down and bottom-up factors affecting visual target acquisition (Jungkunz and Darken 2011), the application of a statistical methodology W.G. Kennedy ( )

This chapter presents a study which involved ninety
Ukrainian English language teachers. Intriguing find-
ings surfaced regarding the methodologies employed in
language instruction. Among the participants, a diverse
range of teaching methods was used, but what emerged
as particularly noteworthy was the tendency for educa-
tors to chart their individual pedagogical trajectories.
It was revealed by qualitative and quantitative data
analysis that it typically took between five to ten years
of teaching experience for teachers to realize the signifi-
cance of constructing their unique teaching paths.

This paper summarises the final report on a study first described to MERGA conference delegates in 1998. Following an extensive review of research on integration spanning the past 30 years, a number of middle school settings of integrated teaching and learning from across a range of demographic and socio-economic areas were studied over three years in order to provide data upon which a number of assertions related to curriculum integration were formulated. Using a number of approaches to data collection, the facts about curriculum integration were documented and six assertions were complied concerning what we believe we know about the process. Another five assertions about what we believe we still need to understand about this process were also compiled. Arguments for and against integration are discussed from the viewpoints ofthe students, teachers and administrators.

This study compares the effects of Processing Instruction (PI), an input-based instructional intervention, and Traditional Instruction (TI), an output-oriented instructional intervention targeting the German dative definite articles. Participants included 56 adult learners enrolled in a beginning level German language course. Learners completed a pretest, treatment, immediate posttest, and a delayed posttest (3 weeks after treatment) measuring both interpretation and production of the German dative definite articles. The results revealed significant immediate and long-term gains for PI on interpretation. Both PI and TI revealed immediate gains on production and PI maintained those gains, whereas TI did not. As such, we discuss the theoretical and methodological implications of these findings.

It is becoming increasingly important to understand how drivers strategically manage tasks and thread attention across time, as they drive through varying situations and conditions --and as they have the opportunity to delegate tasks to vehicle automation while taking up other tasks themselves. To develop an understanding of these higher-level driver behaviors requires a research focus on longer periods of driving --even on "whole trip" driving. It may also require new tools and methods. Therefore, to explore insights and implications of a "whole trip" focus, data from 10 drivers were analyzed using methods tailored for identifying patterns within larger sequences of driving data than single-task epochs. The results are reported, discussed, and contrasted with more conventional approaches based on single-task epochs.

The goals of this study were to evaluate (1) how specific aspects of executive control, briefly assessed, predict social competence and classroom adjustment during preschool; and (2) differences between two aspects of executive control, according to child's age, socioeconomic risk status, and gender. The facets of executive control were defined as cool executive control (CEC; affectively neutral, slow acting, and late developing) and hot executive control (HEC; more emotional, fast acting, and early developing). Two hundred eighty-seven 3-to 5-year-old children from private child care and Head Start centers were directly assessed during executive control tasks, and preschool teachers provided information on their school success. Aspects of executive control varied with age, socioeconomic risk, and gender. Specifically, older children performed better on CEC tasks across three age levels; for HEC tasks, change was seen only between 3-yearolds and 4-year-olds. Children of mothers with less formal education performed less well on CEC than those whose mothers had more education; girls performed better than boys on HEC tasks. Further, facets of executive control were differentially related to later social competence and classroom adjustment. HEC predicted social competence, whereas CEC uniquely predicted classroom adjustment. Implications for everyday practice and specific curricula formulation are discussed.

The research reported in this thesis has been carried out under the auspices of SIKS, the Dutch Graduate School for Information and Knowledge Systems. Promotiecommissie: prof.dr. J.C. van Vliet (promotor) dr. G.C. van der Veer (co-promotor) dr. A. Eliëns (co-promotor) dr. F. Paternò (CNUCE Italy, referent) prof.dr. M. Rauterberg (IPO & Technische Universiteit Eindhoven) prof.dr. J.M. Akkermans (Vrije Universiteit Amsterdam) prof.dr. B. Wielinga (University of Amsterdam) Copyright c 2001 by Martijn van Welie. VRIJE UNIVERSITEIT TASK-BASED USER INTERFACE DESIGN ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Vrije Universiteit Amsterdam, op gezag van de rector magnificus prof.dr. T. Sminia, in het openbaar te verdedigen ten overstaan van de promotiecommissie van de faculteit der Exacte Wetenschappen \ Wiskunde en Informatica op dinsdag 17 april 2001 om 13.45 uur in het hoofdgebouw van de universiteit, De Boelelaan 1105 door Martijn van Welie geboren te Lisse Promotor: prof.dr. J.C. van Vliet Copromotoren: dr. G.C. van der Veer dr. A. Eliëns In addition, thanks to my direct colleagues Nico Lassing, Jacco van Ossenbruggen, Frank Niessink and Jaap Gordijn. During a working day, it is also important to relax and have pointless discussions, for example during lunch when Arno Bakker and Gerco Ballintijn used to join us. Thanks to Hallvard Traetteberg for his work on the patterns. During the development of the patterns he was my best reviewer and contributor. Without his help I would not have developed them so fast. Joerka Deen also proved to be a good discussion partner, always emphasizing the more "philosophical" side of patterns. And of course, many thanks to my parents, my sister and Merche for all their support and love during these years. Many methods rely solely on usability testing to guard the usability of the system. Usability testing is very valuable but "trying to get it right the first time" should not be thought of as an illusion. Although incremental development can be very effective, iteration is often done because there is a lack of effective techniques. The more traditional engineering disciplines use proven techniques and knowledge to get it right more Example This snapshot is from the date and time control panel in MS Windows. Entering the date is spit up in three input areas. Each of the input fields allows only valid entries. Entering an invalid date becomes impossible. Known Uses MS Windows Date/Time control panel, Windows 9x serial box Related Patterns Use the GRID LAYOUT pattern to layout the data units.

The study aims to characterise, assess and develop the organisational cultures of participating nuclear power companies&#x27; maintenance units. The assessment is made by the means of maintenance core task modelling that has already been started in previous studies. The theoretical ...

This study investigates the effectiveness of Task-Based Language Teaching (TBLT) in enhancing English speaking skills among first-year undergraduate students at Sambhram University, Jizzax, Uzbekistan. Thirty-six learners participated, divided into control and experimental groups, with the latter engaged in picture description tasks. The findings reveal that visual prompts, fillers, and group discussions significantly improved fluency, idea expansion, and confidence, while grammar accuracy was given less emphasis. The experimental group achieved higher scores in fluency and idea expansion compared to the control group, which relied on a pre-written text. Results confirm that picture description tasks reduce cognitive barriers, encourage spontaneous speech, and foster collaborative learning. Overall, the study supports TBLT as an effective pedagogical approach that prioritizes meaning over form, enabling learners to develop communicative competence and practical speaking skills essential for academic and social contexts.

Multi-Agent Systems (MAS) offer an architecture for distributed problem solving. Distributed Data Mining (DDM) algorithms focus on one class of such distributed problem solving tasks-analysis and modeling of distributed data. This paper offers a perspective on DDM algorithms in the context of multiagents systems. It discusses broadly the connection between DDM and MAS. It provides a high-level survey of DDM, then focuses on distributed clustering algorithms and some potential applications in multi-agent-based problem solving scenarios. It reviews algorithms for distributed clustering, including privacypreserving ones. It describes challenges for clustering in sensor-network environments, potential shortcomings of the current algorithms, and future work accordingly. It also discusses confidentiality (privacy preservation) and presents a new algorithm for privacy-preserving density-based clustering.

Previous research has focused on evaluating the nouns and verbs in parents&#39; input through type/token ratios. This research offers an additional means of evaluating parent speech by first examining the frequencies of individual nouns, verbs and descriptors and second examining the learning task presented to children. Study 1 examines 25 transcripts from the CHILDES database of English-speaking parents&#39; speech to children at five developmental levels ranging from 0;11 to 2;11 in age. Study 2 examines 50 transcripts from the CHILDES database of Mandarin-speaking caregivers&#39; speech to children ranging from 1;9 to 2;3 in age. The results suggest that the patterns of frequency for individual nouns and individual verbs are different, but that the frequency patterns for nouns and the frequency patterns for verbs are similar in English and Mandarin. Further, this research suggests that in both languages the nouns in parents&#39; input are similarly organized: the most frequent no...