Educational intervention in fostering L2 learner autonomy

There is not enough conceptual work done on autonomy relating it to other individual difference variables. Some researchers have investigated the characteristics of L2 English learners in terms of motivation and learning strategy constructs, but they did not include variables associated with learners' perceived L2 learning competence/anxiety. Some other researchers investigated the characteristics of L2 English learners in terms of strategy use and confidence constructs, but did not include motivational constructs. Motivational, affective, and strategy use have been hypothesized to be important in fostering L2 learner autonomy (Benson, 2011), but conceptual work linking these constructs to L2 learner autonomy is needed. The present study aims to identify the links among L2 learner motivation, confidence/anxiety, and strategy use with L2 English learners with varying degrees of L2 learner autonomy, measured with the Self-Determination Theory-based motivational continuum. The results will help to illuminate how autonomy is related to other variables and thereby provide a clearer understanding of L2 English learner autonomy. The second purpose is to investigate which of the above-mentioned constructs can be changed through a specific educational intervention. This is important given that positive changes in such variables are hypothesized to result in more positive educational outcomes. The study also aims to investigate how the participants perceive a set of learner autonomy fostering activities that aims at transferring learning responsibility from teacher to learner

Specifying and Targeting Cognitive-Affective Dysfunctions in Antisocial Individuals

Antisocial behavior includes a wide range of behaviors that violate social norms, from criminal acts to substance misuse. The adverse consequences of antisocial behavior produce a great physical and emotional burden on perpetrators, victims, and family members. This burden is not addressed adequately, with incarceration being the most common intervention for antisocial behavior. When individuals who chronically engage in antisocial behavior are offered therapeutic treatments, the majority neither complete nor benefit from them. One reason existing treatments do not fully address antisocial behavior is because they do not consider or target cognitive-affective dysfunctions driving such behavior, and mechanistic research, to date, does not adequately characterize these cognitive-affective dysfunctions. The present dissertation consists of three studies that refine accounts of cognitive-affective dysfunctions contributing to antisocial behavior and demonstrate how targeting identified dysfunctions can improve cognition and behavior in chronically antisocial individuals. More specifically, Study 1 examines how reward features impact perception, executive functioning, and risk-based decision-making in antisocial individuals. Study 2 examines how reward information is integrated during effort-based decision-making in antisocial individuals, and how negative affect impacts this integration. Finally, Study 3 tests a novel cognitive remediation training package designed to address cognitive-affective dysfunctions in antisocial individuals. Across the three studies in this dissertation, findings highlight that cognitive-affective dysfunctions related to antisocial behavior reflect difficulty integrating information in specific affectively charged circumstances, and call for a less pessimistic view about treatment for antisocial behavior, and the burden it produces, when these dysfunctions are considered

On the Relationship between People, Objects, & Interactive Technologies: Transforming Digital & Physical experiences through the process of Realizing Empathy

La manera com les persones es relacionen amb el seu entorn, ja sigui físic o digital, és cada cop més complexa i fugaç, fent que la relació de l'usuari amb els seus objectes i eines digitals, de vegades, sigui extrema i de curta durada. Tanmateix, la propietat d'objectes i objectes tecnològics interactius no és buida de significat, són mostres de reflexió i representació per als altres i del seu paper a la societat. La clau per mantenir una relació i el significat amb aquests objectes rau en el disseny i la intenció de l'experiència interactiva creada. Inspirats en les disciplines de la psicologia, el procés de disseny, la interacció humà-ordinador i els models de negoci, aquesta tesi explora, analitza, crea i prova els fonaments teòrics sobre l'empatia i el concepte d'entaular una relació de llarga durada entre les persones i les tecnologies interactives.  Amb aquesta finalitat, aquesta tesi es divideix en 4 fases: (1) l’estudi en profunditat de les referències bibliogràfiques dins del sector HCI, amb especial atenció al rol del disseny i la psicologia amb la intenció de respondre preguntes com: “Com podem construir relacions de llarga durada entre persones i objectes intel·ligents?” (2) Recopilar i adoptar definicions, eines i terminologia de treballs relacionats que aportin a la construcció de la contribució principal d'aquesta tesi, (3) Crear i presentar un model d'interacció entre persones i tecnologia que aporti a una interacció de llarga durada, i (4) presentar un cas d’estudi on s’implementi el model proposat.  Després del treball bibliogràfic, al sector de l'HCI, s'ha identificat un buit, fruit de les principals preocupacions expressades: la manca de connexió entre la teoria i la pràctica del disseny, així com una mancança en l’àmbit de l'Empatia. El resultat fa que molts dels models d’interacció amb intenció empàtica i afectiva no se sustentin entre si. Això ens ha portat a la segona fase de la tesi on aprofitem les referències de múltiples disciplines per estudiar què és l'empatia, com s'implementa, com es percep i com evoluciona cap a l'objectiu d'una relació a llarg termini, com a punt focal cap a les principals contribucions de la tesi. .  Després de reunir i analitzar exhaustivament les referències al voltant de l'empatia, entrem a la tercera fase on presentem el model teòric d'interacció amb el potencial d'establir una interacció a llarg termini i l’anomenat Procés de realització de l'empatia (RE). Més que intentar definir què és l'empatia, aquesta proposta intenta oferir una perspectiva diferent de l'empatia i visualitza el seu abast com un procés influenciat per models de diàleg i col·laboració amb el propòsit de crear comprensió mútua i donar significat a aquest intercanvi.  Amb un model clar i una sòlida base teòrica, la fase final de la tesi cerca provar el model proposat amb l'objectiu d'observar si es poden detectar indicadors d'afecció afectiva i confiança entre una persona i el seu objecte tecnològic. En aquest cas, vam tenir l'oportunitat de treballar amb robots socials com el nostre “altre actor” per dissenyar les proves del model. Aquestes proves pretenien capturar els indicadors d'empatia entre un humà i un robot que abraça: l'aferrament afectiu, la confiança, la regulació de les expectatives i la reflexió sobre la perspectiva de l'altre dins un conjunt d'estratègies de col·laboració. Plantegem la hipòtesi que una estratègia de col·laboració activa condueix a un compromís més significatiu de generar empatia entre un humà i un robot en comparació amb una estratègia passiva. Els resultats són encoratjadors i clarament estableixen un camí per a futures investigacions sobre el disseny d'aquest model. La forma en que las personas se relacionan con su entorno, ya sea físico o digital, se vuelve cada vez más compleja y fugaz, haciendo que la relación del usuario con sus objetos y herramientas digitales, en ocasiones, sea extrema y de corta duración. Sin embargo, la propiedad de objetos y objetos tecnológicos interactivos no es vacía de significado, son muestras de reflexión y representación para los demás y de su papel en la sociedad. La clave para mantener una relación y significado con estos objetos radica en el diseño y la intención de la experiencia interactiva creada. Inspirados en las disciplinas de la psicología, el proceso de diseño, la interacción humano-ordenador y los modelos de negocio, esta tesis explora, analiza, crea y prueba los fundamentos teóricos sobre la empatía y el concepto de entablar una relación de larga duración entre las personas y las tecnologías interactivas.  Con este fin, esta tesis se divide en 4 fases: (1) estudio en profundidad de las referencias bibliográficas dentro del sector HCI, con especial atención al rol del diseño y la psicología con la intención de responder a preguntas como: “¿Cómo podemos construir relaciones de larga duración entre personas y objetos inteligentes?”(2) Recopilar y adoptar definiciones, herramientas y terminología de trabajos relacionados que aporten a la construcción de la contribución principal de esta tesis, (3) Crear y presentar un modelo de interacción entre personas y tecnología que aporte a una interacción de larga duración, y (4) presentar un caso de estudio donde se implemente el modelo propuesto.  Tras el trabajo bibliográfico en el sector del HCI se ha identificado un vacío, fruto de las principales preocupaciones expresadas: la falta de conexión entre la teoría y la práctica del diseño, así como una falta en el tema de la Empatía. El resultado hace que muchos de los modelos de interacción con intención empática y afectiva no se sustenten entre sí. Esto nos ha llevado a la segunda fase de la tesis en la que aprovechamos las referencias de múltiples disciplinas para estudiar qué es la empatía, cómo se implementa, cómo se percibe y cómo evoluciona hacia el objetivo de una relación a largo plazo, como punto focal hacia las principales contribuciones de la tesis. .  Después de una reunir y analizar exhaustivamente las referencias en torno a la empatía, entramos en la tercera fase donde presentamos el modelo teórico de interacción con el potencial de entablar una interacción a largo plazo y denominado Proceso de realización de la empatía (RE). Más que intentar definir qué es la empatía, esta propuesta trata de ofrecer una perspectiva diferente a la empatía y visualiza su alcance como un proceso influenciado por modelos de diálogo y colaboración con el propósito de crear comprensión mutua y dar significado a ese intercambio.  Con un modelo claro y una sólida base teórica, la fase final de la tesis busca probar el modelo propuesto con el objetivo de observar si el modelo puede detectar indicadores de Apego Afectivo y Confianza entre una persona y su objeto tecnológico. En el caso de este trabajo, tuvimos la oportunidad de trabajar con robots sociales como nuestro “otro actor” para diseñar las pruebas del modelo. Estas pruebas pretendían capturar los indicadores de de empatía entre un humano y un robot que abarca: el apego afectivo, la confianza, la regulación de las expectativas y la reflexión sobre la perspectiva del otro dentro de un conjunto de estrategias de colaboración. Planteamos la hipótesis de que una estrategia de colaboración activa conduce a un compromiso más significativo de generar empatía entre un humano y un robot en comparación con una estrategia pasiva. Los resultados son alentadores y claramente establecen un camino para futuras investigaciones sobre el diseño de este modelo. How people engage with their surroundings, whether physical or digital, becomes increasingly complex and rapid, making the user’s relationship with their objects and digital tools, at times, extreme and short-lived. Yet, there is still meaning in ownership of objects and interactive technological objects, they are tokens of reflection and representation to others and their role in society. The key to sustaining a relationship and sense of meaning with these objects lies in the design and intention of the interactive experience created. Inspired by disciplines of psychology, design, Human-computer interaction, and business modeling, this thesis explored, analyzed, created, and tested theoretical foundations on Empathy and the concept of initiating a long-term relationship between people and their interactive technologies.  To that end, the thesis book was managed in 4 main stages: (1) presenting a deeper dive into bibliographic references within HCI and the role of both design and psychology in the attempt to tackle questions like: “How can we build long-term relationships between people and their smart objects?” (2) Collect and adopt from related works that helped build the main contributions of the thesis book, (3) Create an interaction model between humans and their technology that lent itself for potential long-term engagement, and (4) a case study that implemented and instantiated the model designed.     After mapping the HCI bibliographical works in the first phase, a gap was revealed indicative of the main concerns expressed: a lack of connection between theory and design practice as well as a lack in the topic of Empathy. The result makes many of the models of interaction with empathetic and affective intention unsupported between each other. This has led us to the second phase of the thesis where we leveraged references across multiple disciplines to survey what empathy is, how it is implemented, perceived and evolved toward the goal of long-term relationship, as a focal point toward the main thesis contributions.   After an exhaustive gathering and analysis of the work around Empathy, we entered the third phase where we present the proposed theoretical model of interaction with the potential for long-term engagement named the Process of Realizing Empathy (RE). Rather than attempting to further define empathy, this proposal is about offering a different perspective to empathy that visualizes its scope as a process influenced by dialogue and collaborative models with the goal to reach meaning between the actors involved.  With a clear model in place and a strong theoretical foundation, the final phase of the thesis looked to test the proposed model with the goal of observing if the model can provoke its indicators of Affective Attachment and Trust between a person and their technological object. In the case of this thesis work, we had the opportunity to work with social robots as our “other actor” to design the tests for the model. This testbed meant to capture the indicators of early empathy realization between a human and a robot encompassing affective attachment, trust, expectation regulation, and reflecting on the other’s perspective within a set of collaborative strategies. We hypothesized that an active collaboration strategy is conducive to a more meaningful and purposeful engagement of realizing empathy between a human and a robot compared to a passive one. The results are encouraging and clearly establish a path for further research on this model’s design.

Logging Stress and Anxiety Using a Gamified Mobile-based EMA Application, and Emotion Recognition Using a Personalized Machine Learning Approach

According to American Psychological Association (APA) more than 9 in 10 (94 percent) adults believe that stress can contribute to the development of major health problems, such as heart disease, depression, and obesity. Due to the subjective nature of stress, and anxiety, it has been demanding to measure these psychological issues accurately by only relying on objective means. In recent years, researchers have increasingly utilized computer vision techniques and machine learning algorithms to develop scalable and accessible solutions for remote mental health monitoring via web and mobile applications. To further enhance accuracy in the field of digital health and precision diagnostics, there is a need for personalized machine-learning approaches that focus on recognizing mental states based on individual characteristics, rather than relying solely on general-purpose solutions. This thesis focuses on conducting experiments aimed at recognizing and assessing levels of stress and anxiety in participants. In the initial phase of the study, a mobile application with broad applicability (compatible with both Android and iPhone platforms) is introduced (we called it STAND). This application serves the purpose of Ecological Momentary Assessment (EMA). Participants receive daily notifications through this smartphone-based app, which redirects them to a screen consisting of three components. These components include a question that prompts participants to indicate their current levels of stress and anxiety, a rating scale ranging from 1 to 10 for quantifying their response, and the ability to capture a selfie. The responses to the stress and anxiety questions, along with the corresponding selfie photographs, are then analyzed on an individual basis. This analysis focuses on exploring the relationships between self-reported stress and anxiety levels and potential facial expressions indicative of stress and anxiety, eye features such as pupil size variation and eye closure, and specific action units (AUs) observed in the frames over time. In addition to its primary functions, the mobile app also gathers sensor data, including accelerometer and gyroscope readings, on a daily basis. This data holds potential for further analysis related to stress and anxiety. Furthermore, apart from capturing selfie photographs, participants have the option to upload video recordings of themselves while engaging in two neuropsychological games. These recorded videos are then subjected to analysis in order to extract pertinent features that can be utilized for binary classification of stress and anxiety (i.e., stress and anxiety recognition). The participants that will be selected for this phase are students aged between 18 and 38, who have received recent clinical diagnoses indicating specific stress and anxiety levels. In order to enhance user engagement in the intervention, gamified elements - an emerging trend to influence user behavior and lifestyle - has been utilized. Incorporating gamified elements into non-game contexts (e.g., health-related) has gained overwhelming popularity during the last few years which has made the interventions more delightful, engaging, and motivating. In the subsequent phase of this research, we conducted an AI experiment employing a personalized machine learning approach to perform emotion recognition on an established dataset called Emognition. This experiment served as a simulation of the future analysis that will be conducted as part of a more comprehensive study focusing on stress and anxiety recognition. The outcomes of the emotion recognition experiment in this study highlight the effectiveness of personalized machine learning techniques and bear significance for the development of future diagnostic endeavors. For training purposes, we selected three models, namely KNN, Random Forest, and MLP. The preliminary performance accuracy results for the experiment were 93%, 95%, and 87% respectively for these models

When, how and for whom changes in engagement happen:A transition analysis of instructional variables

The pace of our knowledge on online engagement has not been at par with our need to understand the temporal dynamics of online engagement, the transitions between engagement states, and the factors that influence a student being persistently engaged, transitioning to disengagement, or catching up and transitioning to an engaged state. Our study addresses such a gap and investigates how engagement evolves or changes over time, using a person-centered approach to identify for whom the changes happen and when. We take advantage of a novel and innovative multistate Markov model to identify what variables influence such transitions and with what magnitude, i.e., to answer the why. We use a large data set of 1428 enrollments in six courses (238 students). The findings show that online engagement changes differently —across students— and at different magnitudes —according to different instructional variables and previous engagement states. Cognitively engaging instructions helped cognitively engaged students stay engaged while negatively affecting disengaged students. Lectures —a resource that requires less mental energy— helped improve disengaged students. Such differential effects point to the different ways interventions can be applied to different groups, and how different groups may be supported. A balanced, carefully tailored approach is needed to design, intervene, or support students' engagement that takes into account the diversity of engagement states as well as the varied response magnitudes that intervention may incur across diverse students’ profiles

Eye quietness and quiet eye in expert and novice golf performance: an electrooculographic analysis

Quiet eye (QE) is the final ocular fixation on the target of an action (e.g., the ball in golf putting). Camerabased eye-tracking studies have consistently found longer QE durations in experts than novices; however, mechanisms underlying QE are not known. To offer a new perspective we examined the feasibility of measuring the QE using electrooculography (EOG) and developed an index to assess ocular activity across time: eye quietness (EQ). Ten expert and ten novice golfers putted 60 balls to a 2.4 m distant hole. Horizontal EOG (2ms resolution) was recorded from two electrodes placed on the outer sides of the eyes. QE duration was measured using a EOG voltage threshold and comprised the sum of the pre-movement and post-movement initiation components. EQ was computed as the standard deviation of the EOG in 0.5 s bins from –4 to +2 s, relative to backswing initiation: lower values indicate less movement of the eyes, hence greater quietness. Finally, we measured club-ball address and swing durations. T-tests showed that total QE did not differ between groups (p = .31); however, experts had marginally shorter pre-movement QE (p = .08) and longer post-movement QE (p < .001) than novices. A group × time ANOVA revealed that experts had less EQ before backswing initiation and greater EQ after backswing initiation (p = .002). QE durations were inversely correlated with EQ from –1.5 to 1 s (rs = –.48 - –.90, ps = .03 - .001). Experts had longer swing durations than novices (p = .01) and, importantly, swing durations correlated positively with post-movement QE (r = .52, p = .02) and negatively with EQ from 0.5 to 1s (r = –.63, p = .003). This study demonstrates the feasibility of measuring ocular activity using EOG and validates EQ as an index of ocular activity. Its findings challenge the dominant perspective on QE and provide new evidence that expert-novice differences in ocular activity may reflect differences in the kinematics of how experts and novices execute skills

Temperamental Influences on Risk-taking during Middle Childhood

This thesis concerns temperamental qualities and their influence on risk-taking behavior during middle childhood (7–11 years of age). Contemporary research generally agrees upon the notion that temperament constitutes two motivational systems, sensitive to punishment and reward respectively, together with a third system that is responsible for regulating the motivational systems. Risk-taking is generally regarded as the tendency to engage in potentially harmful or dangerous behaviors that at the same time provide opportunities for positive outcomes (Leigh, 1999). Study 1 of this thesis provides a psychometric evaluation of the Temperament in Middle Childhood Questionnaire (TMCQ; Simonds & Rothbart, 2004), one of the temperament questionnaires used in the other two studies. We also tested the ability of the punishment and reward sensitivity factors from the r-RST, as measured by the Sensitivity to Punishment, Sensitivity to Reward Questionnaire for Children (SPSRQ-C; Colder et al., 2011), to validate the corresponding factors from the TMCQ. Our second study examines the interaction effects between temperamental traits fear, drive, and activation control on risk-taking. Fear and drive represent the punishment sensitivity system and the reward system respectively, and activation control is the ability to control the reactions in these two systems. Results from this study suggest that the joint influence of the temperamental systems is of great importance in risk-taking, and also that activation control abilities provide a good protection for children prone to risk-taking behavior. Lastly, our third study examines how children’s temperamental qualities interact with incentive contexts in risky decision-making. Results suggest that incentive-related contextual factors have a strong influence on risky decision-making and that temperament modifies this influence, thereby reducing or increasing children’s proneness to take risks. The findings supported predictions based on the revised Reinforcement Sensitivity Theory (r-RST; Gray & McNaughton, 2000), regarding how temperament and incentive context jointly determine behavior in risk-taking situations. The results from our studies provide a better understanding of how temperamental qualities interact in children’s risk-taking, and of how the effects of temperament on risky decision-making can be moderated. This is highly relevant information, since research suggests that effortful control abilities are possible to improve through training

EMOTICOM: A Neuropsychological Test Battery to Evaluate Emotion, Motivation, Impulsivity, and Social Cognition.

In mental health practice, both pharmacological and non-pharmacological treatments are aimed at improving neuropsychological symptoms, including cognitive and emotional impairments. However, at present there is no established neuropsychological test battery that comprehensively covers multiple affective domains relevant in a range of disorders. Our objective was to generate a standardized test battery, comprised of existing, adapted and novel tasks, to assess four core domains of affective cognition (emotion processing, motivation, impulsivity and social cognition) in order to facilitate and enhance treatment development and evaluation in a broad range of neuropsychiatric disorders. The battery was administered to 200 participants aged 18-50 years (50% female), 42 of whom were retested in order to assess reliability. An exploratory factor analysis identified 11 factors with eigenvalues greater than 1, which accounted for over 70% of the variance. Tasks showed moderate to excellent test-retest reliability and were not strongly correlated with demographic factors such as age or IQ. The EMOTICOM test battery is therefore a promising tool for the assessment of affective cognitive function in a range of contexts.This is the final version of the article. It first appeared from Frontiers via http://dx.doi.org/10.3389/fnbeh.2016.0002