Distributional effects and individual differences in L2 morphology learning

Second language (L2) learning outcomes may depend on the structure of the input and learners’ cognitive abilities. This study tested whether less predictable input might facilitate learning and generalization of L2 morphology while evaluating contributions of statistical learning ability, nonverbal intelligence, phonological short-term memory, and verbal working memory. Over three sessions, 54 adults were exposed to a Russian case-marking paradigm with a balanced or skewed item distribution in the input. Whereas statistical learning ability and nonverbal intelligence predicted learning of trained items, only nonverbal intelligence also predicted generalization of case-marking inflections to new vocabulary. Neither measure of temporary storage capacity predicted learning. Balanced, less predictable input was associated with higher accuracy in generalization but only in the initial test session. These results suggest that individual differences in pattern extraction play a more sustained role in L2 acquisition than instructional manipulations that vary the predictability of lexical items in the input

An Introduction to 3D User Interface Design

3D user interface design is a critical component of any virtual environment (VE) application. In this paper, we present a broad overview of three-dimensional (3D) interaction and user interfaces. We discuss the effect of common VE hardware devices on user interaction, as well as interaction techniques for generic 3D tasks and the use of traditional two-dimensional interaction styles in 3D environments. We divide most user interaction tasks into three categories: navigation, selection/manipulation, and system control. Throughout the paper, our focus is on presenting not only the available techniques, but also practical guidelines for 3D interaction design and widely held myths. Finally, we briefly discuss two approaches to 3D interaction design, and some example applications with complex 3D interaction requirements. We also present an annotated online bibliography as a reference companion to this article

Toward a second-person neuroscience

LS & BT : equal contributions (shared first-authorship)Peer reviewedPreprin

A Meta-Analysis of Procedures to Change Implicit Measures

Using a novel technique known as network meta-analysis, we synthesized evidence from 492 studies (87,418 participants) to investigate the effectiveness of procedures in changing implicit measures, which we define as response biases on implicit tasks. We also evaluated these procedures’ effects on explicit and behavioral measures. We found that implicit measures can be changed, but effects are often relatively weak (|ds| \u3c .30). Most studies focused on producing short-term changes with brief, single-session manipulations. Procedures that associate sets of concepts, invoke goals or motivations, or tax mental resources changed implicit measures the most, whereas procedures that induced threat, affirmation, or specific moods/emotions changed implicit measures the least. Bias tests suggested that implicit effects could be inflated relative to their true population values. Procedures changed explicit measures less consistently and to a smaller degree than implicit measures and generally produced trivial changes in behavior. Finally, changes in implicit measures did not mediate changes in explicit measures or behavior. Our findings suggest that changes in implicit measures are possible, but those changes do not necessarily translate into changes in explicit measures or behavior

The impact of persuasive messages on IAT performance is moderated by source attractiveness and likeability

In two studies, participants read persuasive messages introduced by an attractive (Study 1) or likeable (Study 2) source before completing measures of implicit and explicit evaluations. The persuasive messages were in favor of an unfamiliar brand of facial soap (Study 1) and the implementation of comprehensive examinations at the participants' university (Study 2). Results showed that persuasive messages had a stronger impact on an Implicit Association Test when the source was high in attractiveness or likeability (Study 1 and Study 2); responses on an Affect Misattribution Procedure, though in the predicted direction, were not significantly impacted by a source high in likeability (Study 2). These findings parallel those of numerous studies that, however, have looked almost exclusively at persuasion of explicit evaluations. They confirm that implicit evaluations can be changed through direct persuasive appeals and provide new information about the conditions under which persuasion of implicit evaluations can be found

Freeform User Interfaces for Graphical Computing

報告番号: 甲15222 ; 学位授与年月日: 2000-03-29 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第4717号 ; 研究科・専攻: 工学系研究科情報工学専

Input manipulation, enhancement and processing: Theoretical views and empirical research

Researchers in the field of instructed second language acquisition have been examining the issue of how learners interact with input by conducting research measuring particular kinds of instructional interventions (input-oriented and meaning-based). These interventions include such things as input flood, textual enhancement and processing instruction. Although the findings are not completely conclusive on whether these instructional interventions have an impact on acquisition, it is clear that we have witnessed a shift in the field from the original question “Does instruction make a difference?” to the more specific question “Does manipulating input make a difference?” In this article, the key classroom-based research conducted to measure the relative effects of different types of enhancement and manipulation is reviewed. Three main research foci are considered: (a) research measuring the effects of saturating the input with the target form (input flood), (b) research measuring the effects of different types of textual enhancements to draw learners’ attention to the target form, and (c) research measuring input restructuring to improve interpretation and processing of target forms or structures (processing instruction).