Abstract: Examining a fragment of interaction that occurred during a surgery at a teaching hospital, we explore how particular instructed experiences are produced for two trainees, a surgeon in the residency...

Abstract: In many different domains of language acquisition, there exists an apparent learnability problem to which innate knowledge of some aspect of universal grammar (UG) has been proposed as a solution. The present article reviews these proposals in the core domains of (i) identifying syntactic categories, (ii) acquiring basic morphosyntax, (iii) structure dependence, (iv) subjacency, and (v) the binding principles. We conclude that, in each of these domains, the innate UG-specified knowledge posited does not, in fact, simplify the task facing the learner.

Abstract: When designing a distributed network protocol, typically it is infeasible to fully define the target network where the protocol is intended to be used. It is therefore natural to ask: How faithfull...

Abstract: A conceptual framework for measuring the usability characteristics of mobile learning (m-Learning) application has been developed. Furthermore, a software prototype for smartphones to assess usability issues of m-Learning applications has also been designed and implemented. This prototype has been developed, using Java language and the Android Software Development Kit, based on the recommended guidelines of the proposed conceptual framework. The usability of the proposed model was compared to a generally available similar mobile application (based on the Blackboard) by conducting a questionnairebased survey at Western University. The two models were evaluated in terms of ease of use, user satisfaction, attractiveness, and learnability. The results of the questionnaire showed that the participants considered the user interface based on our proposed framework more user-friendly as compared to the Blackboard-based user interface.

Abstract: The noun plural system in Modern Standard Arabic lies at a nexus of critical issues in morphological learnability. The suffixing “sound” plural competes with as many as 31 non-concatenative “broken” plural patterns. Our computational analysis of singular–plural pairs in the Corpus of Contemporary Arabic explores what types of linguistic information are statistically relevant to morphological generalisation for this highly complex system. We show that an analogical approach with the generalised context model is highly successful in predicting the plural form for any given singular form. This model proves to be robust to variation, as evidenced by its stability across 10 rounds of cross-validation. The predictive power is carried almost entirely by the CV template, a representation which specifies a segment's status as a consonant or vowel only, providing further support for the abstraction of prosodic templates in the Arabic morphological system as proposed by McCarthy and Prince.

Abstract: In many different domains of language acquisition, there exists an apparent learnability prob - lem to which innate knowledge of some aspect ofuniversalgrammar (UG) has been proposed as a solution. The present article reviews these proposals in the core domains of (i) identifying syntactic categories, (ii) acquiring basic morphosyntax, (iii) structure dependence, (iv) subja - cency, and (v) the binding principles. We conclude that, in each of these domains, the innate UG- specified knowledge posited does not, in fact, simplify the task facing the learner.

Abstract: Empirical studies of programming language learnability and usability have thus far depended on indirect measures of human cognitive performance, attempting to capture what is at its essence a purely cognitive exercise through various indicators of comprehension, such as the correctness of coding tasks or the time spent working out the meaning of code and producing acceptable solutions. Understanding program comprehension is essential to understanding the inherent complexity of programming languages, and ultimately, having a measure of mental effort based on direct observation of the brain at work will illuminate the nature of the work of programming. We provide evidence of direct observation of the cognitive effort associated with programming tasks, through a carefully constructed empirical study using a cross-section of undergraduate computer science students and an inexpensive, off-the-shelf brain-computer interface device. This study presents a link between expertise and programming language comprehension, draws conclusions about the observed indicators of cognitive effort using recent cognitive theories, and proposes directions for future work that is now possible.

Abstract: Learning and learnability have been long standing topics of interests within the linguistic, computational, and epistemological accounts of inductive inference. Johan van Benthem’s vision of the “dynamic turn” has not only brought renewed life to research agendas in logic as the study of information processing, but likewise helped bring logic and learning in close proximity. This proximity relation is examined with respect to learning and belief revision, updating and efficiency, and with respect to how learnability fits in the greater scheme of dynamic epistemic logic and scientific method.

Abstract: The Argot glove is a one-handed, wearable input device that allows a user to type all English letters, numbers, and symbols without use of a traditional keyboard. The device design considers variables and constraints such as dexterity, feedback, mobility, learnability, speed of input, errors and false inputs, permanence, and comfort, as well as previous user knowledge. The glove design was informed by experimental investigations aimed at balancing tradeoffs between physical variables (reach, dexterity, haptics) and cognitive variables (learnability, text-entry method). It uses weak magnetic interactions during "key" presses to provide passive haptic feedback and reduce the need for precision in proprioceptive hand positioning.

Abstract: We introduce a distinction between disambiguation supporting continuous versus discrete ambiguous text entry. With continuous ambiguous text entry methods, letter selections are treated as ambiguous due to expected imprecision rather than due to discretized letter groupings. We investigate the simple case of a one-dimensional character layout to demonstrate the potential of techniques designed for imprecise entry. Our rotation-based sight-free technique, Rotext, maps device orientation to a layout optimized for disambiguation, motor efficiency, and learnability. We also present an audio feedback system for efficient selection of disambiguated word candidates and explore the role that time spent acknowledging word-level feedback plays in text entry performance. Through a user study, we show that despite missing on average by 2.46--2.92 character positions, with the aid of a maximum a posteriori (MAP) disambiguation algorithm, users can average a sight-free entry speed of 12.6wpm with 98.9p accuracy within 13 sessions (4.3 hours). In a second study, expert users are found to reach 21wpm with 99.6p accuracy after session 20 (6.7 hours) and continue to grow in performance, with individual phrases entered at up to 37wpm. A final study revisits the learnability of the optimized layout. Our modeling of ultimate performance indicates maximum overall sight-free entry speeds of 29.0wpm with audio feedback, or 40.7wpm if an expert user could operate without relying on audio feedback.

Abstract: Markovian models with hidden state are widely-used formalisms for modeling sequential phenomena. Learnability of these models has been well studied when the sample is given in batch mode, and algorithms with PAC-like learning guarantees exist for specific classes of models such as Probabilistic Deterministic Finite Automata (PDFA). Here we focus on PDFA and give an algorithm for inferring models in this class in the restrictive data stream scenario: Unlike existing methods, our algorithm works incrementally and in one pass, uses memory sublinear in the stream length, and processes input items in amortized constant time. We also present extensions of the algorithm that (1) reduce to a minimum the need for guessing parameters of the target distribution and (2) are able to adapt to changes in the input distribution, relearning new models when needed. We provide rigorous PAC-like bounds for all of the above. Our algorithm makes a key usage of stream sketching techniques for reducing memory and processing time, and is modular in that it can use different tests for state equivalence and for change detection in the stream.

Abstract: A vast majority of L1 vocabulary acquisition occurs through incidental learning during reading (Nation, 2001; Schmitt et al., 2001). We propose a probabilistic approach to generating code-mixed text as an L2 technique for increasing retention in adult lexical learning through reading. Our model that takes as input a bilingual dictionary and an English text, and generates a code-switched text that optimizes a defined “learnability” metric by constructing a factor graph over lexical mentions. Using an artificial language vocabulary, we evaluate a set of algorithms for generating code-switched text automatically by presenting it to Mechanical Turk subjects and measuring recall in a sentence completion task.

Abstract: In 2013 Apple introduced a new interface design for their mobile devices. Whereas the previous design language made heavy use of real world metaphors and cited material like wood, paper, and leather, the new interface now has a reduced and immaterial look. Avoiding metaphoric imitations its colourful graphic language is mostly non-representational. The pros and cons of both interface design approaches have been discussed in the interface design community ever since. Apart from aesthetic judgements, especially the question of usability and learnability has been debated heatedly. In this paper the theoretical concepts that are relevant for usability and learnability discussion, and a survey on how the interfaces’ reception changed over time, will be presented.

Abstract: Annotating documents is one of the indispensable interaction between human and documents. The annotation system of electronic documents enables to implement effective functions, such as information retrieval and annotation-based navigation, by using the annotation information; however, traditional systems require users to perform gestures in addition to common gestures for paper-based documents. This can reduce "learnability" of the system. We propose an intelligent ink annotation framework that helps the system to increase the learnability of annotation systems by detecting recognizable intentions from natural annotation behavior on paper-based documents. Our framework recognizes "Targeting Content" and "Commenting," which are related to extraction of annotation information. We have developed a prototype annotation system using our proposed framework and conducted a user study to identify future direction.

Abstract: The exploitation of the underlying semantics of data inherent in the vision of the Semantic Web tackles the limitations of the traditional keywords-based retrieval model and has the ability to change the way search is done. The proliferation of Open Data published on the Web in recent years has driven significant research and development in search. As a result, there is a wide range of approaches with respect to the style of input, the underlying search mechanisms and the manner in which results are presented. Although the performance or effectiveness of these approaches is usually evaluated, understanding their usability and suitability for end users' needs and preferences has been largely overlooked. This is the main motivation behind the work presented in this thesis. The thesis, thus, presents different pieces of work in this area. The �first part focuses on investigating the usability of different query approaches from the perspective of expert and casual users through a user-based study. The �findings of this study show the strengths of graph-based approaches in supporting users during query formulation with a drawback of high query input time and user effort. Therefore, in another user-based study, learnability of a graph-based approach is evaluated to assess the effects of learning and frequency of use on users' proficiency and satisfaction. The results of both studies suggest that the combination of a graph- based approach with a NL input feature could provide high level of support and satisfaction for users during query formulation. This is, hence, the third piece of work presented in the thesis: a hybrid query approach together with a user-based evaluation to assess its usability and users' satisfaction. The thesis also presents thorough analysis of state-of-the-art in semantic search evaluations and describes a set of best practices for running them based on this analysis, lessons learnt from the Information Retrieval community and on my own experience in evaluating semantic search approaches.

Abstract: Many students must learn spatial skills to improve learning achievement in science, mathematics, and engineering. An abundance of literature on the geometric learning theory is available. However, specific guidance on how students can interact with teaching materials through their body is limited. We used a group of undergraduate students as an example and argue that the Kinect sensor-assisted learning interface can provide a “learning-by-doing” framework for learning spatial skills, motivating students, and enhancing students’ effectiveness. The responses to the System Usability Scale (SUS) indicated that our system demonstrated usability and learnability. We conclude that the Kinect sensor-assisted learning system promotes the development of students’ spatial visualization skills and encourages them to become active learners.

Abstract: Empirical evaluations of programming environments have traditionally focused on human performance measures such as task efficiency, error rates, and learnability. In addition to these effectiveness measures, we believe there is good reason to consider the ability of programming environments to promote social interactions and awareness during programming tasks. Indeed, especially in educational contexts, programming success and persistence in the computing discipline have been positively correlated with programmers' sense of community and ability to communicate with others. We introduce social programming environments as a new breed of educational programming environment designed to promote social interaction and awareness, and we propose a way to evaluate such environments relative to social learning theory.

Abstract: This paper replicates and extends experiments by Gruter (2006) and Gruter & Conradie (2006) to explore some of the learnability implications of Full Transfer at the initial state of L2A. L1 English-speaking learners’ comprehension of L2 German questions and relative clauses is tested on the basis of a picture interpretation task. Patterns of (mis)interpretation of the German clauses suggest that lower-intermediate proficiency learners still access the L1 syntax in order to parse L2 input. This is taken to indicate that learners are influenced by L1 word order patterns in assigning thematic roles in L2 clauses. This is discussed in light of approaches to L2 parsing and processing which attribute different roles to L1 influence.

Abstract: Autonomous learning is the ability to learn effectively without much external assistance. An important strength of autonomous learners is that they can shape their own learning and development, in large part by choosing which problems to learn. Such choices include selecting a problem to learn and deciding whether to continue learning on that selected task or abandon it in favor of something else. We extend a constructive neurallearning algorithm, sibling-descendant cascade-correlation, to monitor lack of progress in learning so that unproductive learning can be abandoned. Learning is abandoned when network error fails to change by more than a specified threshold for a specified number of consecutive learning cycles. Here we explore the space defined by these threshold and patience parameters on problems of different degrees of learnability. Our results simulate findings from recent experiments with infants who abandon learning on difficult tasks and focus their attention on tasks of moderate difficulty.

Abstract: Electronic and mobile learning in recent years has been considered as an invaluable tool to support the learning process. Several tools and comprehensive platforms have been developed in the paradigms of e-learning and m-learning. One issue is the usability of these tools. It is essential to define metrics to measure efficiency, learnability, satisfaction and other usability properties. Another equally important issue is the presence of guidelines compiled based on accumulated scientific reasoning behind design decisions. In this paper, we discuss the issue of HCI-based guideline specific to designing e- and m-learning platforms and tools intended for Arabic users. We present our analysis on the availability of such guidelines, their deployment and to whether they adequately address the challenges characteristic to Arabic language.

Abstract: In this paper, we propose a renement of E{stability conditions that select equilibria more robust to specication of the learning algorithm within the RLS/SG/GSG class. We show that the mean{dynamics speed of convergence under RLS learning is an important component of such a renement: E{stable equilib- ria that are characterized by a faster speed of convergence under RLS learning are more likely to be learnable under SG or GSG algorithms. An example of monetary policy under commitment, with a determinate and E-stable REE suggests that such equi- libria may fail to imply learnability when private agents update

Abstract: Based on Harris’s substitutability criterion, the recent denitions of classes of substitutable languages have led to interesting polynomial learnability results for expressive formal languages. These classes are also promising for practical applications: in natural language analysis, because denitions have strong linguisitic support, but also in biology for modeling protein families, as suggested in our previous study introducing the class of local substitutable languages. But turning recent theoretical advances into practice badly needs truly practical algorithms. We present here an ecient

Abstract: Web sites are widely used in daily life no matter for work or for entertainment, and connect with others in their social life. Usability is one of the quality factors that determine the successfulness of a web site. This study reviews existing usability standards and model from previous studies. Most of the previous works only mentioned the attribute of usability in general and no details discussion is included. There are less published works in usability guidelines that comes up with metric for easy measurement especially focusing for web site. This study identifies the major elementsin web site usability from the previous studies and usability standards. It adapted Quality in Use Intergrated Measurement Model or QUIM model that include accessibility in web site usability unlike earlier work which separate between usability and accessibility. The results show effectiveness, efficiency, learnability, satisfaction and accessibility have significant impacts and highly correlated on web site usability. These attributes should needs to be consider when designing web site.

Abstract: This paper aimed to comparatively analyze two methods of Electronic Learning (E-learning), in which avatars were utilized as virtual lecturers, with a particular focus on measuring learnability and Experienced User Performance (EUP). Insight has been provided into E-learning motivations and guidelines within the area of edutainment. Research into the communication of educational materials has also been included to provide explanations into the different edutainment techniques and factors influencing E-leaning performance. An E-learning environment was designed and constructed based on pedagogical principles. Emphasis was placed on the significance of multimodal interaction metaphors, as a means of improving learning skills. An empirical study was conducted to compare two E-learning approaches: avatars as pedagogical agents and E-learning through edutainment. The study was divided into two experiments: learnability and EUP; of which, two groups were instructed to interact with the experimental platforms under two conditions: first-time-use and frequent-use. The results of the experiments showed a statistical significance in favor of EUP in E-learning through edutainment.

Abstract: Gestural interaction leveraging the expressiveness of the human hand, either in touch or in air gestures has been a subject of much research. In this work, a user study focusing mainly on static hand poses has been conducted on a heterogeneous group of participants covering different aspects of this interaction method: role of the participants in the creation of the hand poses, context-free pose-action mapping, learnability and memory issues, and physical comfort. Results of the study are discussed.