Affective experience modeling based on interactive synergetic dependence in big data

Affective computing is important in human–computer interaction. Especially in interactive cloud computing within big data, affective modeling and analysis have extremely high complexity and uncertainty for emotional status as well as decreased computational accuracy. In this paper, an approach for affective experience evaluation in an interactive environment is presented to help enhance the significance of those findings. Based on a person-independent approach and the cooperative interaction as core factors, facial expression features and states as affective indicators are applied to do synergetic dependence evaluation and to construct a participant’s affective experience distribution map in interactive Big Data space. The resultant model from this methodology is potentially capable of analyzing the consistency between a participant’s inner emotional status and external facial expressions regardless of hidden emotions within interactive computing. Experiments are conducted to evaluate the rationality of the affective experience modeling approach outlined in this paper. The satisfactory results on real-time camera demonstrate an availability and validity comparable to the best results achieved through the facial expressions only from reality big data. It is suggested that the person-independent model with cooperative interaction and synergetic dependence evaluation has the characteristics to construct a participant’s affective experience distribution, and can accurately perform real-time analysis of affective experience consistency according to interactive big data. The affective experience distribution is considered as the most individual intelligent method for both an analysis model and affective computing, based on which we can further comprehend affective facial expression recognition and synthesis in interactive cloud computing.     

Exploring the role of e-learning readiness on student satisfaction and motivation in flipped classroom

Decrease in student satisfaction and motivation in flipped classroom (FC) model of instruction is among frequently observed problems. And these problems could reduce the efficiency of FC model. It is believed that the problems related to student satisfaction and motivation in FC model of instruction are related to the e-learning readiness of the students. The purpose of the current study was to explore the impact of the e-learning readiness of the students on student satisfaction and motivation in FC model of instruction. The study was carried out with 236 undergraduate students taking Computing I class taught using FC model of instruction. Data were collected from three self-report instruments: E-learning Readiness Scale (subscales: ‘computer self-efficacy’, ‘internet self-efficacy’, ‘online communication self-efficacy’, ‘self-directed learning’, ‘learner control’ and ‘motivation towards e-learning’), Satisfaction Scale and Motivated Strategies for Learning Questionnaire. The path analyses with structural equation modelling (SEM) further verified that students' e-learning readiness were related to their satisfaction and motivation while undertaking academic tasks in FC model of instruction. The results of the study indicated that students' e-learning readiness was a significant predictor of their satisfaction and motivation in FC model of instruction. Findings were presented and discussed for future studies and applications.     

A novel database of children's spontaneous facial expressions (LIRIS-CSE)

Computing environment is moving towards human-centered designs instead of computer centered designs and human's tend to communicate wealth of information through affective states or expressions. Traditional Human Computer Interaction (HCI) based systems ignores bulk of information communicated through those affective states and just caters for user's intentional input. Generally, for evaluating and benchmarking different facial expression analysis algorithms, standardized databases are needed to enable a meaningful comparison. In the absence of comparative tests on such standardized databases it is difficult to find relative strengths and weaknesses of different facial expression recognition algorithms. In this article we present a novel video database for Children's Spontaneous facial Expressions (LIRIS-CSE). Proposed video database contains six basic spontaneous facial expressions shown by 12 ethnically diverse children between the ages of 6 and 12 years with mean age of 7.3 years. To the best of our knowledge, this database is first of its kind as it records and shows spontaneous facial expressions of children. Previously there were few database of children expressions and all of them show posed or exaggerated expressions which are different from spontaneous or natural expressions. Thus, this database will be a milestone for human behavior researchers. This database will be a excellent resource for vision community for benchmarking and comparing results. In this article, we have also proposed framework for automatic expression recognition based on Convolutional Neural Network (CNN) architecture with transfer learning approach. Proposed architecture achieved average classification accuracy of 75% on our proposed database i.e. LIRIS-CSE.     

Quantifying influence from form manipulation of artificial facial expression to viewers

Abstract

Creating facial expressions manually needs to be enhanced through a set of easy operating rules, which involves adjectives and the manipulating combinations of facial design elements. This article tries to analyse viewers' cognition of artificial facial expressions in an objective and scientific way. We chose four adjectives – ‘satisfied’, ‘sarcastic’, ‘disdainful’, and ‘nervous’ – as the experimental subjects. The manipulative key factors of facial expressions (eyebrows, eyes, pupils, mouth and head rotation) were used to create permutations and combinations and to make 81 stimuli of different facial expressions with a 3-D face model in order to conduct a survey. Next, we used Quantification Theory Type I to find the best combinations that participants agreed on as representing these adjectives. The conclusions of this research are that: (1) there are differences in adopting facial features between creating artificial characters' expressions and recognising real humans' expressions; (2) using survey and statistics can scientifically analyse viewers' cognition of facial expressions with form changing; and (3) the results of this research can promote designers' efficiency in working with subtler facial expressions.     

Gaze tutor: A gaze-reactive intelligent tutoring system

We developed an intelligent tutoring system (ITS) that aims to promote engagement and learning by dynamically detecting and responding to students' boredom and disengagement. The tutor uses a commercial eye tracker to monitor a student's gaze patterns and identify when the student is bored, disengaged, or is zoning out. The tutor then attempts to reengage the student with dialog moves that direct the student to reorient his or her attentional patterns towards the animated pedagogical agent embodying the tutor. We evaluated the efficacy of the gaze-reactive tutor in promoting learning, motivation, and engagement in a controlled experiment where 48 students were tutored on four biology topics with both gaze-reactive and non-gaze-reactive (control condition) versions of the tutor. The results indicated that: (a) gaze-sensitive dialogs were successful in dynamically reorienting students’ attentional patterns to the important areas of the interface, (b) gaze-reactivity was effective in promoting learning gains for questions that required deep reasoning, (c) gaze-reactivity had minimal impact on students’ state motivation and on self-reported engagement, and (d) individual differences in scholastic aptitude moderated the impact of gaze-reactivity on overall learning gains. We discuss the implications of our findings, limitations, future work, and consider the possibility of using gaze-reactive ITSs in classrooms.     

Cyber-slacking in the classroom: Potential for digital distraction in the new age

In the modern world of constant connectivity, it is difficult to detach students from technology. Today, we walk into classrooms that are filled with computers and Ethernet plugs. Students are carrying laptops, smartphones, and other devices into classrooms for their learning needs. Although technology in classroom has its benefits, many students constantly succumb to its use during class for non-class related purposes, thereby impacting their learning. This study draws upon the augmented version of the theory of planned behavior, social learning theory and the pedagogical literature to investigate the factors influencing students' attitudes and intentions to use technology during class for non-class related purposes. The hypothesized model was validated by conducting a survey to collect the data and using partial least squares for analysis. The results demonstrate that students' attitudes are influenced by student consumerism, escapism, lack of attention, cyber-slacking anxiety, and distraction by others' cyber-slacking behavior. Further, lack of attention is shaped by intrinsic and extrinsic motivation, class engagement, and apathy towards course material. Theoretical and practical implications of the findings are discussed.     

Teacher-created video instruction in the elementary classroom—Its impact on students and teachers

Despite the proliferation of multimedia devices in elementary classrooms, there is limited research examining teacher-created video instruction, particularly regarding its effect on academic growth and engagement. This study investigated the effect of teacher-created computer-based video instruction (CBVI) using iPads on students' academic, behavioural and affective learning in elementary classrooms. The study used a repeated-measures design with counterbalancing to measure the effects of CBVI during mathematics lessons on student achievement scores, time on-task and attitudes towards learning. Three year three classes (n = 49) completed three lessons, each using a different mode of instruction: CBVI created by the class teacher, CBVI created by a stranger, and a traditional live lesson delivered by the class teacher. Results were analysed using a Linear Mixed Model. No significant growth in performance was detected during video instruction, however a significant growth result was achieved for the traditional live teaching mode (p < 0.001), possibly attributable to the longer duration of experimental session. Behavioural engagement was considerably higher during CBVI lessons than live lessons and students preferred their teacher's voice during CBVI. Three teachers were interviewed to examine how CBVI affected teaching and learning, with two main themes emerging: (1) positive impacts of CBVI upon students; and (2) positive impacts on teacher wellbeing. This research indicates benefits for students and teachers when using teacher-created CBVI. Further research is needed to better understand the factors that influence cognitive development of students using CBVI and to also further explore the effect of CBVI on teacher wellbeing.     

A two-dimensional facial-affect estimation system for human–robot interaction using facial expression parameters

A social robot should be able to autonomously interpret human affect and adapt its behavior accordingly in order for successful social human–robot interaction to take place. This paper presents a modular non-contact automated affect-estimation system that employs support vector regression over a set of novel facial expression parameters to estimate a person’s affective states using a valence-arousal two-dimensional model of affect. The proposed system captures complex and ambiguous emotions that are prevalent in real-world scenarios by utilizing a continuous two-dimensional model, rather than a traditional discrete categorical model for affect. As the goal is to incorporate this recognition system in robots, real-time estimation of spontaneous natural facial expressions in response to environmental and interactive stimuli is an objective. The proposed system can be combined with affect detection techniques using other modes, such as speech, body language and/or physiological signals, etc., in order to develop an accurate multi-modal affect estimation system for social HRI applications. Experiments presented herein demonstrate the system’s ability to successfully estimate the affect of a diverse group of unknown individuals exhibiting spontaneous natural facial expressions.     

Reconsidering off‐task: a comparative study of PDA‐mediated activities in four classrooms

Mobile technology is ubiquitous and diverse and permeates many aspects of daily life at home, during leisure activities, and in public spaces. The study presented here is of two sixth grade classes in Michigan, USA and two seventh grade classes in Norway. The students and the teachers in these four classrooms were equipped with mobile technologies (PDAs). We found that the students' PDA‐mediated actions in the classroom were not exclusively used for the tasks and activities set by the teacher, but that the students also used the PDAs on their own initiative – so‐called ‘off‐task’ activities. We analyze the findings by reconsidering off‐task activities from a sociocultural perspective.     

基于深度注意力网络的课堂教学视频中学生表情识别与智能教学评估

为了解决复杂课堂场景下学生表情识别的遮挡的问题,同时发挥深度学习在智能教学评估应用上的优势,提出了一种基于深度注意力网络的课堂教学视频中学生表情识别模型与智能教学评估算法.构建了课堂教学视频库、表情库和行为库,利用裁剪和遮挡策略生成多路人脸图像,在此基础上构建了多路深度注意力网络,并通过自注意力机制为多路网络分配不同权...     

Changing teachers,changing students? The impact of a teacher-focused intervention on students' computer usage,attitudes, and anxiety

An important purpose of integrating computer use into everyday classroom instruction is to help students approach technology as a learning tool. Effective classroom integration is dependent not only on access to computers but also teachers' implementation of computing into learning. Successful implementation, in turn, depends largely on teachers' beliefs about classroom computing. The purpose of this study is to examine the effects of a teacher-focused technology intervention on students' attitudes toward and use of computers as learning tools. Teachers' attitudes, anxiety, and classroom computer use are explored as mediators of this relationship. Data were collected during a technology intervention in fourth and fifth grade classrooms in an urban public school district. Results suggest that the technology intervention itself had a positive effect on students' attitudes toward and use of computers for educational purposes. There was no evidence, however, that teachers' use or attitudes had any mediating effect on this relationship. These results suggest that it is possible to increase students' attitudes toward computer use through intense interventions aimed at their teachers. Future research should further investigate the mechanisms through which this relationship exits.     

人机交互中的智能体情感计算研究

机器的情感是通过融入具有情感能力的智能体实现的,虽然目前在人机交互领域已经有大量研究成果,但有关智能体情感计算方面的研究尚处起步阶段,深入开展这项研究对推动人机交互领域的发展具有重要的科学和应用价值。本文通过检索Scopus数据库选择有代表性的文献,重点关注情感在智能体和用户之间的双向流动,分别从智能体对用户的情绪感知和对用户情绪调节的角度开展分析总结。首先梳理了用户情绪的识别方法,即通过用户的表情、语音、姿态、生理信号和文本信息等多通道信息分析用户的情绪状态,归纳了情绪识别中的一些机器学习方法。其次从用户体验角度分析具有情绪表现力的智能体对用户的影响,总结了智能体的情绪生成和表现技术,指出智能体除了通过表情之外,还可以通过注视、姿态、头部运动和手势等非言语动作来表现情绪。并且梳理了典型的智能体情绪架构,举例说明了强化学习在智能体情绪设计中的作用。同时为了验证模型的准确性,比较了已有的情感评估手段和评价指标。最后指出智能体情感计算急需解决的问题。通过对现有研究的总结,智能体情感计算研究是一个很有前景的研究方向,希望本文能够为深入开展相关研究提供借鉴。     

Factors influencing students' beliefs about the future in the context of tablet-based interactive classrooms

With the distribution of easy-to-use tablet computers, tablet-based interactive classrooms have become popular environments for innovative learning activities in recent years. However, little research has investigated the relationship between technologically enhanced learning environments and students' beliefs about the future and self-efficacy for learning. In this study, young students' perceptions of tablet-based interactive classrooms, beliefs about the future, and self-efficacy for learning in rural areas of Korea were examined after the students engaged in tablet-based interactive classrooms. To develop the theoretical framework, we created a structural research model of ease of use, usefulness, satisfaction, deepened experiences through tablet use, beliefs about the future, and self-efficacy in tablet-based interactive classrooms based on a partial least squares (PLS) method. The results indicate that (1) students in tablet-based interactive classrooms perceive frequent experiences with tablet-based instructions as easy and useful and (2) student satisfaction is significantly influenced by their perceptions of deeper learning experiences through tablet use, which are significantly influenced by their future expectations and self-efficacy for learning. This study provides relevant implications for educators who design learning activities for students in rural schools in tablet-based interactive classroom environments.     

Patterns of students' collaborations by variations in their learning orientations in blended course designs: How is it associated with academic achievement?

Background

While a number of learner factors have been identified to impact students' collaborative learning, there has been little systematic research into how patterns of students' collaborative learning may differ by their learning orientations.

Objectives

This study aimed to investigate: (1) variations in students' learning orientations by their conceptions, approaches, and perceptions; (2) the patterns of students' collaborations by variations in their learning orientations and (3) the contribution of patterns of collaborations to academic achievement.

Methods

A cohort of 174 Chinese undergraduates in a blended engineering course were surveyed for their conceptions of learning, approaches to learning and to using online learning technologies, and perceptions of e-learning, to identify variations in their learning orientations. Students' collaborations and mode of collaborations were collected through an open-ended social network analysis (SNA) questionnaire.

Results and Conclusions

A hierarchical cluster analysis identified an ‘understanding’ and ‘reproducing’ learning orientations. Based on students' learning orientations and their choices to collaborate, students were categorized into three mutually exclusive collaborative group, namely Understanding Collaborative group, Reproducing Collaborative group and Mixed Collaborative group. SNA centrality measures demonstrated that students in the Understanding Collaborative group had more collaborations and stayed in a better position in terms of capacity to gather information. Both students' approaches to learning and students' average collaborations significantly contributed to their academic achievement, explaining 3% and 4% of variance in their academic achievement respectively. The results suggest that fostering a desirable learning orientation may help improve students' collaborative learning.     

Technology and its impact in the classroom

Recent findings have shown that at-risk students in grades k-12 are being deprived of challenges and of the chance to use complex thinking skills. The purpose of this study is to determine the effect that the level of computer technology use in the classroom has on at-risk students' grades and attendance. A teacher technology survey is used to measure teacher use, student use and overall use of technology in the classrooms. The sample for this study consists of teachers from a Northwest Ohio high school. Results of the study indicate that teachers' technology use, students' technology use, and overall technology use have no significant positive effect on the grades and attendance of at-risk students. In addition the study finds that technology use is low among the teachers in the sample. These results suggest that for technology to be effective and make changes in at-risk students' grades and attendance, schools must be prepared for technology use in the classroom. Leaders need to develop a model that would include a shared vision, entire school community involvement, specific training for staff and time for the training, a full time technology director and time for the staff to communicate and share among peers for technology to be an effective tool in the classroom curriculum.     

Pedagogy embedded in educational software design: report of a case study

Most educational software is designed to foster students' learning outcomes but with little consideration of the teaching framework in which it will be used. This paper presents a significantly different model of educational software that was derived from a case study of two teachers participating in a software design process. It shows the relationship between particular elements of the teachers' pedagogy and the characteristics of the software design. In this model, the ‘classroom atmosphere’ is embedded in the human–computer interface scenarios and elements, the ‘teaching strategy’ in the design of the browsing strategies of the software, and the ‘learning strategy’ in the particular forms of interaction with the software. The model demonstrates significant links between the study of Pedagogy and the study of Information Technology in Education and has implications for the relationship between these two areas of research and consequently for teacher training. The model proposes a perspective on educational software design that takes into consideration not only learning theories, but also teaching theories and practice.     

Designing a technology‐enhanced flipped learning system to facilitate students' self‐regulation and performance

In recent years, the flipped classroom has become prevalent in many educational settings. Flipped classroom adopts a pedagogical model in which short video lectures are viewed by students at home before class so that the teacher can lead students to participate in activities, problem‐solving, and discussions. Yet the design or use of technology that employs planned instructional strategies with sustainable support of self‐regulation is scant. We propose a technology‐enhanced flipped language learning system (Flip2Learn) that provides facilitation and guidance for learning performance and self‐regulation. A quasi‐experimental study was carried out to examine whether Flip2Learn could enhance college students' self‐regulatory skills and later contribute to the learning performance in the flipped classrooms. The results showed that Flip2Learn not only better prepared students for flipped classrooms but also better promoted learning performance compared to the conventional flipped classrooms. The results of this research advanced our understanding of the dynamics of flipped classrooms and represented a revolutionary new approach to the technology‐enhanced learning for flipped classrooms.