Background: The guidance of prospective therapists focused on Cognitive Behavioral Therapy (CBT) is most often made by groups of four students. However, learning therapist skills is a sensitive process that will be af...Background: The guidance of prospective therapists focused on Cognitive Behavioral Therapy (CBT) is most often made by groups of four students. However, learning therapist skills is a sensitive process that will be affected by the processes which occur within the group. Objective: The aim was to examine prospective psychotherapists’ attitudes to group assessments based on the revised version of the Cognitive Therapy Scale (CTS-R). Method: Participants were 56 students with an average age of 45.65 years (range = 31 - 64). They were recruited from psychotherapy training at the Gothenburg University and the Evidens University College in Sweden. A questionnaire was constructed in which the questions were answered by check on visual analogue scales (VAS). Results: A majority of students consisting of 38 participants (68%) had a very positive approach to group assessments, while a minority of 18 participants (32%) was more negative. Most crucial for how to answer the question of group assessments was whether they considered themselves as fairly evaluated by their student colleagues within the group and whether or not only the supervisor should make the assessments. The view of group assessments (negative or positive) was not related to age, gender, and level of education in CBT or profession. In addition, both groups had a very positive view of both the CTS-R and the supervisors. Conclusion: It was concluded that more studies with the same focus are needed to determine the extent to which the results are generalizable.展开更多
In smart classrooms, conducting multi-face expression recognition based on existing hardware devices to assessstudents’ group emotions can provide educators with more comprehensive and intuitive classroom effect anal...In smart classrooms, conducting multi-face expression recognition based on existing hardware devices to assessstudents’ group emotions can provide educators with more comprehensive and intuitive classroom effect analysis,thereby continuouslypromotingthe improvementof teaching quality.However,most existingmulti-face expressionrecognition methods adopt a multi-stage approach, with an overall complex process, poor real-time performance,and insufficient generalization ability. In addition, the existing facial expression datasets are mostly single faceimages, which are of low quality and lack specificity, also restricting the development of this research. This paperaims to propose an end-to-end high-performance multi-face expression recognition algorithm model suitable forsmart classrooms, construct a high-quality multi-face expression dataset to support algorithm research, and applythe model to group emotion assessment to expand its application value. To this end, we propose an end-to-endmulti-face expression recognition algorithm model for smart classrooms (E2E-MFERC). In order to provide highqualityand highly targeted data support for model research, we constructed a multi-face expression dataset inreal classrooms (MFED), containing 2,385 images and a total of 18,712 expression labels, collected from smartclassrooms. In constructing E2E-MFERC, by introducing Re-parameterization visual geometry group (RepVGG)block and symmetric positive definite convolution (SPD-Conv) modules to enhance representational capability;combined with the cross stage partial network fusion module optimized by attention mechanism (C2f_Attention),it strengthens the ability to extract key information;adopts asymptotic feature pyramid network (AFPN) featurefusion tailored to classroomscenes and optimizes the head prediction output size;achieves high-performance endto-end multi-face expression detection. Finally, we apply the model to smart classroom group emotion assessmentand provide design references for classroom effect analysis evaluation metrics. Experiments based on MFED showthat the mAP and F1-score of E2E-MFERC on classroom evaluation data reach 83.6% and 0.77, respectively,improving the mAP of same-scale You Only Look Once version 5 (YOLOv5) and You Only Look Once version8 (YOLOv8) by 6.8% and 2.5%, respectively, and the F1-score by 0.06 and 0.04, respectively. E2E-MFERC modelhas obvious advantages in both detection speed and accuracy, which can meet the practical needs of real-timemulti-face expression analysis in classrooms, and serve the application of teaching effect assessment very well.展开更多
This paper examines dependencies of voice and video contents on human perception of group (or inter-destination) synchronization error in remote learning by Quality of Experience (QoE) assessment. In our assessment, w...This paper examines dependencies of voice and video contents on human perception of group (or inter-destination) synchronization error in remote learning by Quality of Experience (QoE) assessment. In our assessment, we use two videos and three voices (two voices for one video and one voice for the other video). We also investigate influences of silence periods in the voices and temporal relations between the voices and videos (called the tightly-coupled and loosely-coupled contents here). The voices are spoken by a teacher according to the videos. Each subject as a student assesses the group synchronization quality by watching each lecture video and the corresponding explanation voice, and then the subject answers whether he/she perceives the group synchronization error or not. As a result, assessment results illustrate that silence periods mitigate the perception rate of the error, and we can also find that we can more easily perceive the error for tightly-coupled contents than loosely-coupled ones.展开更多
On the basis of practical teaching and leading innovation theory,this paper explores the necessity and importance of self-and peer assessment in the teaching to non-English majored college students. It is characterize...On the basis of practical teaching and leading innovation theory,this paper explores the necessity and importance of self-and peer assessment in the teaching to non-English majored college students. It is characterized with learner-centre and group work,the subject evaluation which takes formative assessment as a main method in order to promote the enthusiasm and initiatives of students' learning as well as improve the teaching effect. The research shows that Self-assessment improves Ss' independent learning skills,peer assessment group work help students in active learning,self-and peer assessment motivate students' English learning. In a comparison of other classes which aren't involved in this innovation,the group of freshmen know better about their learning outcome in an objective manner and can improve their method of English learning. Over all,the project can train students' ability to solve problems independently,and raise their language communicative competence gradually.展开更多
文摘Background: The guidance of prospective therapists focused on Cognitive Behavioral Therapy (CBT) is most often made by groups of four students. However, learning therapist skills is a sensitive process that will be affected by the processes which occur within the group. Objective: The aim was to examine prospective psychotherapists’ attitudes to group assessments based on the revised version of the Cognitive Therapy Scale (CTS-R). Method: Participants were 56 students with an average age of 45.65 years (range = 31 - 64). They were recruited from psychotherapy training at the Gothenburg University and the Evidens University College in Sweden. A questionnaire was constructed in which the questions were answered by check on visual analogue scales (VAS). Results: A majority of students consisting of 38 participants (68%) had a very positive approach to group assessments, while a minority of 18 participants (32%) was more negative. Most crucial for how to answer the question of group assessments was whether they considered themselves as fairly evaluated by their student colleagues within the group and whether or not only the supervisor should make the assessments. The view of group assessments (negative or positive) was not related to age, gender, and level of education in CBT or profession. In addition, both groups had a very positive view of both the CTS-R and the supervisors. Conclusion: It was concluded that more studies with the same focus are needed to determine the extent to which the results are generalizable.
基金the Science and Technology Project of State Grid Corporation of China under Grant No.5700-202318292A-1-1-ZN.
文摘In smart classrooms, conducting multi-face expression recognition based on existing hardware devices to assessstudents’ group emotions can provide educators with more comprehensive and intuitive classroom effect analysis,thereby continuouslypromotingthe improvementof teaching quality.However,most existingmulti-face expressionrecognition methods adopt a multi-stage approach, with an overall complex process, poor real-time performance,and insufficient generalization ability. In addition, the existing facial expression datasets are mostly single faceimages, which are of low quality and lack specificity, also restricting the development of this research. This paperaims to propose an end-to-end high-performance multi-face expression recognition algorithm model suitable forsmart classrooms, construct a high-quality multi-face expression dataset to support algorithm research, and applythe model to group emotion assessment to expand its application value. To this end, we propose an end-to-endmulti-face expression recognition algorithm model for smart classrooms (E2E-MFERC). In order to provide highqualityand highly targeted data support for model research, we constructed a multi-face expression dataset inreal classrooms (MFED), containing 2,385 images and a total of 18,712 expression labels, collected from smartclassrooms. In constructing E2E-MFERC, by introducing Re-parameterization visual geometry group (RepVGG)block and symmetric positive definite convolution (SPD-Conv) modules to enhance representational capability;combined with the cross stage partial network fusion module optimized by attention mechanism (C2f_Attention),it strengthens the ability to extract key information;adopts asymptotic feature pyramid network (AFPN) featurefusion tailored to classroomscenes and optimizes the head prediction output size;achieves high-performance endto-end multi-face expression detection. Finally, we apply the model to smart classroom group emotion assessmentand provide design references for classroom effect analysis evaluation metrics. Experiments based on MFED showthat the mAP and F1-score of E2E-MFERC on classroom evaluation data reach 83.6% and 0.77, respectively,improving the mAP of same-scale You Only Look Once version 5 (YOLOv5) and You Only Look Once version8 (YOLOv8) by 6.8% and 2.5%, respectively, and the F1-score by 0.06 and 0.04, respectively. E2E-MFERC modelhas obvious advantages in both detection speed and accuracy, which can meet the practical needs of real-timemulti-face expression analysis in classrooms, and serve the application of teaching effect assessment very well.
文摘This paper examines dependencies of voice and video contents on human perception of group (or inter-destination) synchronization error in remote learning by Quality of Experience (QoE) assessment. In our assessment, we use two videos and three voices (two voices for one video and one voice for the other video). We also investigate influences of silence periods in the voices and temporal relations between the voices and videos (called the tightly-coupled and loosely-coupled contents here). The voices are spoken by a teacher according to the videos. Each subject as a student assesses the group synchronization quality by watching each lecture video and the corresponding explanation voice, and then the subject answers whether he/she perceives the group synchronization error or not. As a result, assessment results illustrate that silence periods mitigate the perception rate of the error, and we can also find that we can more easily perceive the error for tightly-coupled contents than loosely-coupled ones.
文摘On the basis of practical teaching and leading innovation theory,this paper explores the necessity and importance of self-and peer assessment in the teaching to non-English majored college students. It is characterized with learner-centre and group work,the subject evaluation which takes formative assessment as a main method in order to promote the enthusiasm and initiatives of students' learning as well as improve the teaching effect. The research shows that Self-assessment improves Ss' independent learning skills,peer assessment group work help students in active learning,self-and peer assessment motivate students' English learning. In a comparison of other classes which aren't involved in this innovation,the group of freshmen know better about their learning outcome in an objective manner and can improve their method of English learning. Over all,the project can train students' ability to solve problems independently,and raise their language communicative competence gradually.
