The thesis deals with the topic of happiness and happiness increasing intervention strategies. The theoretical chapters discuss different approaches to defining the term and they are inclined to the view that the term reflects the subjective satisfaction with life of an individual. The thesis further deals with a number of major theories of happiness, analyzes its relationship to other variables, such as heredity, health, money or work and it gives an overview of the best known intervention strategies affecting experiencing happiness in the end of the theoretical part of it. Empirical research is aimed at testing the effectiveness of the chosen strategy - attentivenes - on the changes in experiencing happiness. Although the statistical analysis does not confirm the validity of the hypothesis of an increase in subjective levels of happiness after applying the intervention, the results tend to indicate the effectiveness of the method. Keywords: positive psychology, happiness, satisfaction, attentiveness.

Student engagement is a critical component of effective classroom instruction. Many socio-constructive pedagogies, including active learning and peer instruction, depend upon students not only paying attention to, but actively shaping, the learning environment. Student response devices, such as clickers, are thought to increase student engagement by providing students with regular opportunities to check their comprehension or express their opinions. Claims of increased student engagement due to clicker use are often based upon student self-reports and have only a small correlation with observed learning gains or other measures of attentiveness. This paper compared self-report data, pre- and post-test scores, and a direct test of attentiveness to investigate what effect clicker use has on student engagement. Analyses showed that subjects using clickers were significantly slower to respond to tests of attentiveness than subjects in other conditions. This suggests that using clickers affects what students are able or willing to attend to during a lecture. / text

Distraction from personal technology is a widely recognized problem in the modern classroom. Further, instructors have limited abilities to determine when students are waxing or waning in attentiveness. This evaluative experiment leverages the Apple Watch’s heart rate sensors to capture signs of attentiveness in participants simulating remote university lectures of differing interest levels as determined by YouTube commenters. Once captured, the heart rate data separated and analyzed to determine the effect of the lecture treatment on the participants’ heart rates. Twenty-seven students from Mississippi State University’s Electrical and Computer Engineering and Computer Science and Engineering departments elected to participate in the experiment, which shows a statistically relevant finding that the participants’ heart rates generally accelerated when presented interesting content and decelerated when treated with the uninteresting content, expressing with confidence the finding that the Apple Watch is capable of measuring attentiveness through heart rate.

The present study sought to alleviate the response cost inefficiency of the behavioral approach to controlling classroom hyperactivity by increasing the observer-student ratio via behavioral-electronic technology. A portable, integrated-circuit, counting and timing device was developed to enable immediate time-sequenced data recording and reinforcing of eight target behaviors by a single observer. A multiple-baseline design, across matched individuals was utilized to demonstrate the reinforcing effects. The results indicated a significant increase over mean baseline frequency in attention-to-task behavior for the group of eight students. It was concluded that by utilizing the behavioral-technological intervention strategy applied in this study, one observer could accurately monitor and reinforce eight students simultaneously and subsequently increase task attentiveness.

OBJECTIVES: To identify the types of patients who talk with their physicians as a result of Direct-to-Consumer (DTC) advertising. METHODS: Data were taken from a national survey, "Public Health Impact of Direct-to-Consumer Advertising of Prescription Drugs, July 2001- January 2002", conducted by researchers from Harvard Medical School. Participants (n = 3000) were interviewed by telephone. We constructed a conceptual framework consisting of outcomes (3 types of physician visits), intervention (DTC experience) and five groups of explanatory factors (health beliefs, demographics, health status, socioeconomic status and market factors). Data were analyzed with three multivariate stepwise logistic regressions. The three dependent variables were whether an advertisement for a prescription drug had ever prompted the patient to: 1) visit to discuss prescription drug, 2) visit to discuss new condition, and 3) visit to discuss treatment change. RESULTS: Out of all independent variables, only six variables consistently showed significant effects on the three dependent variables after adjusting for other variables. They were: 1) taking medication on regular basis, 2) having anxiety, 3) having high advertisement attentiveness, 4) viewing media as the most important source prompting one to talk with physician, 5) believing that DTC advertisements increased awareness of new treatment, and 6) believing that DTC advertisements improved discussion with health professionals. The six variables were the strongest predictors for DTC-prompted physician visits.CONCLUSIONS: Our nationally representative study found multiple factors were associated with different types of physician visits prompted by DTC advertisements. This information could be used to target those patients most likely to talk to their physicians as a result of DTC advertisements.

This research has developed a novel method which uses an easy to deploy single dry electrode wireless electroencephalogram (EEG) collection device as an input to an automated system that measures indicators of a participant’s attentiveness while they are watching a short training video. The results are promising, including 85% or better accuracy in identifying whether a participant is watching a segment of video from a boring scene or lecture, versus a segment of video from an attentiveness inducing active lesson or memory quiz. In addition, the final system produces an ensemble average of attentiveness across many participants, pinpointing areas in the training videos that induce peak attentiveness. Qualitative analysis of the results of this research is also very promising. The system produces attentiveness graphs for individual participants and these triangulate well with the thoughts and feelings those participants had during different parts of the videos, as described in their own words. As distance learning and computer based training become more popular, it is of great interest to measure if students are attentive to recorded lessons and short training videos. This research was motivated by this interest, as well as recent advances in electronic and computer engineering’s use of biometric signal analysis for the detection of affective (emotional) response. Signal processing of EEG has proven useful in measuring alertness, emotional state, and even towards very specific applications such as whether or not participants will recall television commercials days after they have seen them. This research extended these advances by creating an automated system which measures attentiveness towards short training videos. The bulk of the research was focused on electrical and computer engineering, specifically the optimization of signal processing algorithms for this particular application. A review of existing methods of EEG signal processing and feature extraction methods shows that there is a common subdivision of the steps that are used in different EEG applications. These steps include hardware sensing filtering and digitizing, noise removal, chopping the continuous EEG data into windows for processing, normalization, transformation to extract frequency or scale information, treatment of phase or shift information, and additional post-transformation noise reduction techniques. A large degree of variation exists in most of these steps within the currently documented state of the art. This research connected these varied methods into a single holistic model that allows for comparison and selection of optimal algorithms for this application. The research described herein provided for such a structured and orderly comparison of individual signal analysis and feature extraction methods. This study created a concise algorithmic approach in examining all the aforementioned steps. In doing so, the study provided the framework for a systematic approach which followed a rigorous participant cross validation so that options could be tested, compared and optimized. Novel signal analysis methods were also developed, using new techniques to choose parameters, which greatly improved performance. The research also utilizes machine learning to automatically categorize extracted features into measures of attentiveness. The research improved existing machine learning with novel methods, including a method of using per-participant baselines with kNN machine learning. This provided an optimal solution to extend current EEG signal analysis methods that were used in other applications, and refined them for use in the measurement of attentiveness towards short training videos. These algorithms are proven to be best via selection of optimal signal analysis and optimal machine learning steps identified through both n-fold and participant cross validation. The creation of this new system which uses signal processing of EEG for the detection of attentiveness towards short training videos has created a significant advance in the field of attentiveness measuring towards short training videos.

Even though food-based artworks are no longer a new occurrence within art practice, the particular practice of food that uses taste, smell and touch as artistic medium is still relatively new. This practice poses new challenges at both the creative and receptive ends: for the audience the challenge is linked to understanding and relating with the artwork while for the artist it involves directing the audience’s engagement. Under the theoretical lens of Somaesthetics and Langer’s Mindfulness discourse, this thesis has examined what it means to appreciate food-based artworks through taste, smell and touch. It has also investigated ways in which this form of practice can be developed further. Practice within the research has been used as a means of thinking through the creative choices taken by artists with the purpose of understanding how perceptibility and engagement with food-based works through taste, smell and touch can be enhanced. Some of the key references include Miwa Koizumi’s NY flavors, Burkhard Bacher & Herbert Hinter’s Landscape, Maki Ueda’s Aromascape, and several works by Sam Bompas and Harry Parr amongst others. The outcome of the research include: the development of an attentive discourse of appreciation which outlines the conditions necessary for the appreciation of food-based artwork through its taste, smell and touch; and the articulation of creative strategies that can be used by artists to enhance the perceptibility of taste, smell and touch and encourage engagement. The contributions to knowledge made by this thesis include: The introduction of a new genre of food-based practice; the use of Somaesthetics and Mindfulness as a lens to examine the appreciation of food-based art; the identification of new concerns within practice facing artists using food’s taste, smell and touch as medium; and the new form of encounter with art that requires a mindful-somatic attentiveness.

Domesticated species possess certain cognitive abilities that allow them to thrive in an environment with regular human interaction, and these interactions contribute to the overall human-animal relationship. Studying the human-animal relationship allows us to better understand how domesticated animals perceive and navigate their environment, which can then be used to improve their welfare. In chickens, this relationship is poorly understood, and further research would provide insight into the welfare needs of this animal. Here we show breed differences in the interspecific sociocognitive abilities of Gallus gallus, where the domesticated White Leghorn interacted more with a familiar human than the red junglefowl, and both the domesticated White Leghorn and the red junglefowl breed that had been selected for low fear of humans were habituated to human presence. This study sheds light on the effect of domestication on social cognition in chickens and begins to describe the human-chicken relationship.

The purpose of this study was to contribute with knowledge about the tension between preschool teachers' mission to teach and support children's learning on the one hand and the mission to assess children's learning processes on the other hand, in relation to equality in education. In Swedish preschools, children with different experiences meet, all of whom should have the opportunity to develop and learn based on their varied circumstances and needs. According to the Education Act (SFS, 2010:800), preschool education must be equal, and all children must have the opportunity to learn and develop as far as possible based on their potential. However, previous research (Alasuutari, Vallberg Roth & Markström, 2014) indicates that assessment involves risks for children’s identity creation.  This study examines how seven preschool teachers tackle the challenge of assessing and paying attention to individual children in their ongoing learning processes. A sociocultural perspective (Vygotskij, 1978) has been used to study preschool teachers' reasoning about assessment in relation to each child's possibilities for being supported in their proximal development zone. The sociocultural perspective stresses the importance of cultural tools for communication. Stimulated-recall interviews were conducted with seven preschool teachers in Sweden. Content analysis was used to reveal the views that emerged in preschool teachers’ descriptions. In the preschool teachers' reasoning, different strategies for assessment and methods for making the child's learning processes visible as well as approaches for following the progression in children's learning processes have emerged, which can create both opportunities and limitations for children to learn based on their potential. Findings indicate three areas significant for assessment in relation to an equivalent education in this study. Firstly, there is clarity regarding the approach to assessment, what is to be given attention and assessed and how the assessment should be carried out. Secondly, the preschool teachers in the study have knowledge about various methods to make children's learning processes visible and thus possible to follow over time. Thirdly, the preschool teachers in the study know how to draw attention to and make visible the child's learning from a holistic perspective.  The Licentiate thesis highlights different strategies for assessment, methods for making the child's learning processes visible and approaches for following the progression in children's learning processes that emerged during the preschool teachers' reasoning. The study has shown that attentiveness (Elbaz, 1992) can be used as a concept to bridge the tension surrounding assessment. / Deltagare i forskarskolan ReCEC

<p> Body Posture provides enough information regarding the current state of mind of a person. This idea is used to implement a system that provides feedback to lecturers on how engaging the class has been by identifying the attentive levels of students. This is carried out using the posture information extracted with the help of Mediapipe. A novel method of extracting features are from the key points returned by Mediapipe is proposed. Geometric moments aided features classification performs better than the general distances and angles features classification. In order to extend the single person pose classification to multi person pose classification object detection is implemented. Feedback is generated regarding the entire lecture and provided as the output of the system. </p>