The appearance-reality distinction refers to the understanding that objects can have misleading appearances that contradict reality. Traditionally, studies investigating children's ability to make this distinction have used a verbal-based task that requires children to answer two questions regarding the appearance and reality of a target object whose appearance has been altered. In general, these studies have found that children are not successful in this task until 4–5 years of age. The purpose of the current study was to investigate three different hypotheses regarding why 3-year-olds fail the traditional verbal-based task in order to determine whether their poor performance truly represents an inability to distinguish appearance from reality. In Experiment 1, the hypothesis that 3-year-olds fail the traditional task simply because they are unfamiliar with the property-distorting devices typically used to alter the appearances of target objects, rather than an inability to distinguish appearance from reality, was examined. Experiments 1 and 2 also examined the hypothesis that 3-year-olds' failure in this task may be due to an inability to assign conflicting, dual representations to a single object. Finally, the role of the language used in making the appearance-reality distinction also was examined in both experiments. In this case, the hypothesis that 3-year-olds may be able to distinguish appearances from reality in an action-based, but not verbal-based task, was evaluated. In Experiment 1, all of this was done using a property-distorting device typically used in traditional appearance-reality studies, whereas a completely new method for altering the appearances of objects was used in Experiment 2. No supporting evidence for the familiarity or dual representation hypotheses was found in either experiment, however, children in both experiments performed better on an action-based task than on two verbal-based tasks. Children went from answering the traditional appearance-reality questions on the basis of misleading perceptual information to overriding this misleading information in an action-based task. Together, these results provide evidence that 3-year-olds have some competence in distinguishing appearances from reality that is masked by the language demands of the traditional verbal-based task.

Four experiments investigated how verb-specific lexical information is used in resolving the noun phrase complement/tensed sentence complement ambiguity, extending prior research (Ferreira & Henderson, 1990; Holmes, Stowe, & Cupples, 1989; Trueswell, Tannenhaus, & Kello, 1993). Predictions from the Constraint Satisfaction Approach (MacDonald, 1994; MacDonald, Pearlmutter, & Seidenberg, 1994a; 1994b; Tannenhaus & Trueswell, 1994; Trueswell, Tannenhaus, & Kello, 1993) and the Lexical Filtering Proposal (Clifton, Speer, & Abney, 1991; Ferreira & Henderson, 1990; 1991; Frazier, 1987; Frazier & Clifton, 1989) were contrasted. The former approach assumes that lexical information is used to guide the analysis of syntactically ambiguous phrases, predicting that comparable effects of verb bias should be observed for ambiguous versus unambiguous tensed sentence complements as for sentences containing temporarily ambiguous noun phrase complements and for sentences containing unambiguous tensed sentence complements. The latter proposal, an extension of the Garden Path Model (Frazier, 1978; Frazier & Fodor, 1978; Frazier, & Rayner, 1982), assumes that lexical information may be used when it becomes available; however, the analysis of syntactically ambiguous phrases is not delayed until lexical information becomes available, but instead is made in accordance with the syntactic parsing principles Minimal Attachment and Late Closure. Therefore, larger effects of verb bias are predicted for ambiguous versus unambiguous tensed sentence complements than for sentences containing temporarily ambiguous noun phrase complements or for sentences containing unambiguous tensed sentence complements. In Experiments 1-3, two self-paced reading methods (phrase by phrase and word by word presentation) and eye tracking were used to compare reading time on sentences containing ambiguous and unambiguous tensed sentence complements, containing either short or long ambiguous noun phrases, preceded by either NP-biased verbs, i.e., verbs generally occurring most frequently with noun phrase complements, or S-biased verbs, i.e., verbs generally occurring most frequently with tensed sentence complements. In Experiment 4, eye tracking was used to compare reading time on sentences containing temporarily ambiguous tensed sentence complements, temporarily ambiguous noun phrase complements, and unambiguous tensed sentence complements, containing either short or long ambiguous noun phrases, preceded by either NP-biased or S-biased verbs. Results from these four experiments are most compatible with the Lexical Filtering Proposal. Implications for models of human sentence processing are discussed.

Located on what today is Gröna Lund's parking lot, you'll find Stockholm Science Center - a building aiming to combine entertainment with education. Taking care of the waterfront promenade Djurgårdsstrand was important from the project start, and thus pathway creation was at the basis for the design strategy. The educational values of the building resides in the scientific experiments that the building is filled with. Three main reference buildings has been used in the design process: Tom Tits and Experimentarium gave inspiration for the building program while Louisiana Museum of Modern Art inspired the pathway creation. From the Louisiana museum, a toolbox of building elements was formed and this has been used in creating the building. Main materials are wood, concrete and glass. The result is a versatile and multifunctional building that give life to the site and its surroundings.

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This dissertation takes an employee-oriented approach to the within-firm OM decisions and investigates the effects of interventions focusing on employees on the process outcomes. Through a series of three essays, we handle three management tools; rank-based performance feedback, knowledge transfer via the adoption of best practices, and algorithmic real-time feedback and coaching; each has potential adverse effects on employees yet could be very rewarding once successfully implemented. We seek to gain a profound understanding of employee behavior and stimulate engagement, thereby fostering more efficient and productive systems. In the first chapter, we conduct a series of experiments to study the impact of three different types of relative performance feedback (RPF) on middle-ranked workers' output on a skill-based task. We find that receiving any type of feedback reduces performance compared to no feedback. We conduct mediation analysis and show that receiving feedback changes employees' feelings associated with general performance, which explains the performance reduction. Aligned with theory, delivering feedback increases the focal employee's social comparison involvement (SCI), which measures the focal individual's tendency to compare themselves to others while performing the task, and their shame. The second chapter concentrates on enhancing performance through fostering internal knowledge transfer and promoting the adoption of best practices. Through a series of experiments, we assess the effects of providing performance feedback in conjunction with best practices on knowledge-seeking behavior, best practice adaptions, and operational performance. Our study poses an exciting finding by showing that RPF's previously documented negative effect on middle-ranked workers could be mitigated, and performance improvement could be attained when combined with best practices. The concluding chapter focuses on the effect of using algorithmic feedback and coaching as management tools in service operations within call center environments. Companies are deploying artificial intelligence applications into service settings in a variety of ways, from automating agent tasks to replacing human servers altogether. This study examines how artificial intelligence-based feedback (AI) impacts customer service agent employee productivity as measured by three key performance indicators: call-handle time, customer satisfaction, and call service quality. Our field partner, a North American outsourced call center deployed the AI software to monitor calls during a bill collection campaign and provide visible cues to remind agents of their service script requirements. In this way, the AI acts as a real-time supervisor, assessing agent performance and offering real-time feedback during and after the call. Using international call center data, we provide evidence that agents with access to the AI feedback are indeed more likely to comply with scripts and in so doing, deliver increased operational efficiency with lower call handle time. Moreover, calls conducted with AI feedback show an increase in two service quality metrics not commonly associated with technology-assisted communication: respect and rapport. In summary, through three studies, we offer theoretical and practical implications about the use and challenges associated with various management tools and provide ways to improve employee behavior to stimulate engagement and foster more efficient and productive systems.

Spontaneous verbal initiations and social interactions are a central deficit of children with autism. This study examined the effects of gradually fading a tactile prompting device, a vibrating pager, as a prompt for children with autism to make verbal initiations during play activities. Three children diagnosed with autism participated in the study. An ABAB withdrawal design was used to evaluate the effect of the prompting device on verbal initiations. During training, the tactile prompt was placed in the children's pockets and they were taught to initiate a verbal interaction (e.g., “Look at this” or “I have [object label]) when the tactile prompt was activated. Once the children responded independently to the tactile prompt in their pocket, they were given access to free-play activities with normally developing peers. The tactile prompting device was then used to prompt children to initiate an interaction with a peer. The results indicated that the tactile prompting device was effective in increasing verbal initiations and decreasing aberrant behavior (e.g., stereotypy) exhibited by the participants. Peers were also more likely to initiate a verbal interaction with the participants during and after the prompting conditions. In addition, for two of the children with autism, verbal initiations remained at high levels once the use of the tactile prompting device was faded.

The purpose of this study was to determine the effectiveness of Rational-Emotive Therapy (RET), Progressive Relaxation (PR), Attention Placebo (AP), and a no-treatment group in reducing levels of trait anxiety in undergraduate students who participated in anxiety reduction workshops. The subjects in this study were fifty-one volunteer male and female undergraduate students from the University of the Pacific, Stockton, California, who chose to participate in a seven session anxiety reduction workshop. The subjects were randomly assigned to one of the four treatment groups. The Attention Placebo procedure consisted of a discussion of learning styles, and the effects that the learning styles have on adjustments in the classroom. The no-control group served as a control with no treatment being administered. Two self-report measures, the State-Trait Anxiety Inventory (STAI) (A-State), and the Multiple Affect Adjective Checklist (MAACL) ("In General"), as well as a behavioral measure, the Anxiety Rating Scale (ARS), were used to assess the effectiveness of each treatment on anxiety. It was hypothesized that the self-report scales would reflect a decrease in anxiety which would be greatest for the RET treatment. The second hypothesis was that the students in the RET treatment would report the greatest amount of anxiety reduction according to the behavioral measure. The third hypothesis stated that there would be no sex differentiation in relation to anxiety reduction within any of the treatments. An analysis of variance (ANOVA) on the difference scores from pre-test to post-test, and an analysis of co-variance (ANCOVA) of the difference scores from pre-test to post-test by group and sex with pre-test scores as the co-variant, were the methods for each measure, with alpha set at .05 for all analyses. Results showed that there was a significant difference, in the effectiveness of anxiety reduction of the RET group, according to the STAI. The MAACL failed to reveal any significant differences between treatments. The RET group was more effective than the other treatments in anxiety reduction, and the PR group was more effective than the NT group, according to the ARS. All instruments revealed no difference between sexes in anxiety reduction within any of the treatments.

Crowdsourcing involves releasing tasks on the internet for people with diverse backgrounds and skills to solve. Its adoption has come a long way, from scaling up problem-solving to becoming an environment for running complex experiments. Designing tasks to obtain reliable results is not straightforward as it requires many design choices that grow with the complexity of crowdsourcing projects, often demanding multiple trial-and-error iterations to properly configure. These inherent characteristics of crowdsourcing, the complexity of the design space, and heterogeneity of the crowd, set quality control as a major concern, making it an integral part of task design. Despite all the progress and guidelines for developing effective tasks, crowdsourcing still is addressed as an ``art'' rather than an exact science, in part due to the challenges related to task design but also because crowdsourcing allows more complex use cases nowadays, where the support available has not yet caught up with this progress. This leaves researchers and practitioners at the forefront to often rely on intuitions instead of informed decisions. Running controlled experiments in crowdsourcing platforms is a prominent example. Despite their importance, experiments in these platforms are not yet first-class citizens, making researchers resort to building custom features to compensate for the lack of support, where pitfalls in this process may be detrimental to the experimental outcome. In this thesis, therefore, our goal is to attend to the need of moving crowdsourcing from art to science from two perspectives that interplay with each other: providing guidance on task design through experimentation, and supporting the experimentation process itself. First, we select classification problems as a use case, given their importance and pervasive nature, and aim to bring awareness, empirical evidence, and guidance to previously unexplored task design choices to address performance concerns. And second, we also aim to make crowdsourcing accessible to researchers and practitioners from all backgrounds, reducing the requirement of in-depth knowledge of known biases in crowdsourcing platforms, experimental methods, as well as programming skills to overcome the limitations of crowdsourcing providers while running experiments. We start by proposing task design strategies to address workers' performance, quality and time, in crowdsourced classification tasks. Then we distill the challenges associated with running controlled crowdsourcing experiments, propose coping strategies to address these challenges, and introduce solutions to help researchers report their crowdsourcing experiments, moving crowdsourcing forward to standardized reporting.

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