Analysis of Students’ Role Perceptions and their Tendencies in Classroom Education Based on Visual Inspection

Abstract

This paper presents an in-depth study and analysis of students’ role perceptions and their tendencies in classroom education using a visual inspection approach. A multi example learning student engagement assessment method based on a one-dimensional convolutional neural network is proposed. Based on the conceptual composition of student engagement, head posture, eye gaze, and eye-opening and closing states and the most used facial movement units are used as visual features. For feature extraction, the proposed view of relative change features, based on the video features extracted from the Open Face toolset, the standard deviation of the distance between adjacent multiple frames relative to the center point of the three visual features is used as the relative change features of the video. This results in the phenomenon that students are highly motivated in the early stage and significantly increase the rate of absenteeism in the later stage. With the development of information technology injecting new vitality into educational innovation, many researchers have introduced computer vision and image processing technology into students’ online learning activities, and understand students’ current learning situation by analyzing students’ learning status. There are relatively few studies in this area in classroom teaching. Considering the low relative position correlation of the features in the examples, the examples are analyzed using a one-dimensional convolutional neural network to obtain the example-level student engagement, and a multi-example pooling layer is used to infer the student engagement in the video from the example-level student engagement. Finally, the experimental method is used to apply the student classroom attention evaluation detection system to actual classroom teaching activities, and the effectiveness and accuracy of the design of the student classroom attention evaluation detection system are investigated in depth through specific applications and example analysis, and the accuracy of the method of this paper is further verified by communicating feedback with teachers and students in the form of interviews.

The Attention of Students in Online Education

“…However, other works that were also of interest for this study because they are related to factors that influence the student's attention are an analysis of students' role perceptions and their tendencies in classroom education using a visual inspection approach presented by Jiang [22]. The authors propose a multi-example learning student engagement assessment method based on a one-dimensional convolutional neural network.…”

Retracted: Analysis of Students’ Role Perceptions and their Tendencies in Classroom Education Based on Visual Inspection

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Manipulated or compromised peer review …”

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”

Uso de modelos 3D de proteínas en la docencia de las áreas biológicas

“…La rápida popularización de internet ha dado lugar a un cambio importante en los recursos educativos, así como en el surgimiento de varios recursos didácticos en línea; algunos son de acceso gratuito, lo que ha permitido a los estudiantes eliminar las limitaciones de tiempo y espacio para elegir libremente las materias y los temas que les interese aprender o profundizar (Jiang, 2022). El aprendizaje en línea se puede definir como una instrucción impartida a través de un dispositivo digital cuyo destino es apoyar la enseñanza.…”

“…Para poder superar el desafío durante la emergencia sanitaria, se aceleró el desarrollo en un tiempo récord de la educación en línea, así como la adaptación para las diferentes áreas. Sin embargo, durante este periodo se observaron algunos problemas con la enseñan-za en el aula en línea, tales como una disminución de la motivación de los estudiantes y un aumento en la tasa de ausentismo, para lo cual se propuso el desarrollo y uso de estrategias digitales, las cuales involucraron un mayor dinamismo e interacción de los alumnos durante la enseñanza virtual (Jiang, 2022).…”