Instructor Interface Research Articles

Systemic shock, cultural differences, and customer satisfaction: lessons from student perceptions in shift to non-classroom education during initial phases of pandemic

ABSTRACT This study captured perceptions of students immediately following the covid pandemic campus lockdowns of March, 2020. It is a cross-cultural sample of 407 students in USA, India, and United Arab Emirates. Met expectations are the theoretical base. Analysis was done using PLS-SEM. Positive main effects in all three markets point to the value of the front-line instructor interface at such a time. Their efforts were directly related to met expectations in the form of positive advocacy and university image to the external stakeholders. Cultural dimensions of Individualism, power distance, and universalism appeared influential in low tolerance for personal inconvenience in the USA. Self-efficacy also moderated in USA. Lower self-efficacy was associated with weaker perceptions of positive university image. Implications for marketing point to the essential qualities of front-line instructors. A varied approach is called for, particularly with the generally less forgiving Western audience that differ East to West.

Neural Network Topology Construction and Classroom Interaction Benchmark Graph Based on Big Data Analysis

With the rapid development of artificial intelligence and deep learning in recent years, many universities have put forward the goal of achieving digitalization, intelligent, and education informatization on campus. Throughout the lecture and learning process, the classroom status is an important reference factor to assess students’ acceptance of the course and the quality of lectures. However, at present, classroom status analysis is mainly conducted manually, which can distract teachers’ attention, so it is of great research significance to find a method that can improve the efficiency of classroom status analysis. In this paper, we choose an offline method to analyze the status of a classroom video recording in terms of students’ behavior and attendance in terms of frames, in which student behavior is identified by an improved target detection algorithm and attendance is analyzed by face recognition. By analyzing the structure of the neural network model, an improved neural network model is proposed for its characteristics of a large number of parameters and poor detection of small targets in the basic network. The backbone network is replaced by the improved neural network, and the depth‐separable convolutional network is used to reduce the network parameters and increase the computation speed. The information in the deeper feature map is fused upward into the shallow layer to improve the accuracy of small target recognition. Finally, the optimization algorithm is incorporated into the network to optimize the network model and accelerate the model convergence speed. In addition, this paper incorporates the improved behavior recognition method and face recognition method into the system to realize the analysis of the offline classroom status. The system is divided into a teacher side and a management side, where the teacher side is responsible for uploading course recordings and the management side is responsible for randomly analyzing students’ status and attendance at any time, and the combination of the two forms a convenient and comprehensive classroom status analysis system platform. Users can upload classroom videos through the instructor interface and can view the classroom status analysis results of a course at any time by searching randomly in the administration. In this paper, the classroom status is mainly judged by the recognition of students’ behaviors.

Seeing into your Teams: An Instructor Interface to Support Team Learning

This paper outlines the design of a new instructor interface that has been added to the on-line Team-effectiveness Learning System (TELS) at the University of Toronto. TELS is a tool that supports team-based project courses by facilitating the development of individual team-effectiveness competencies in students within their teams. Instructors saw the system as beneficial for student growth, but they also saw opportunities for them to get a better understanding of the state of their student teams. As a result, TELS has now developed an instructor interface to let instructors “see” into their teams. The instructor interface has been adopted by four courses since its development

The U.S. Merchant Marine Academy Liquid Cargo Handling Simulator

This paper describes the tanker cargo handling simulator recently installed at the U.S. Merchant Marine Academy. The tanker simulator is modeled on a nominal 80 000-dwt tank vessel with segregated ballast, crude oil wash, and inert gas systems. The loading console is typical in design, construction, and detail to that which is normally found in a shipboard cargo control room. Through the real-time operation of this console, the student receives training in tanker loading, discharging, and ballasting operations. In addition, a unique method of instructor interface and control allows the incorporation of spontaneous malfunctions in an exercise. The simulator is based on a computer model using hydraulic network theory to describe the piping systems and overall performance. This paper describes the development of the simulator and many of the features incorporated in it. Attention is given to the instructor's interface, which is made user friendly through the use of simulation control menus. These menus allow the instructor to completely command and monitor the simulation exercise.

Implementation of an instructional subsystem for a simulator-based training device on Apollo workstation

An instructional subsystem is an important constituent of every simulator-based training system essentially with capabilities that are designed specifically to enhance the training process by assisting the instructor, providing feedback information to the students and supporting training system management activities. Specific instructor support capabilities should be determined through a cost-effective trade-off analysis based on instructor functions, tasks and load. The hardware/software capabilities of currently available low-cost workstations can potentially be exploited to include versatile and highly cost-effective instructional features to improve the instructional process. This paper presents one such effort to implement the instructional subsystem of a sophisticated simulator-based shiphandling training system on a task-oriented multi-window graphics workstation, in association with a large screen graphics display. The instructional subsystem is specifically tailored based on numerous contextual considerations related to this particular training application and the training device. The workstation supports activities such as providing immediate graphical feedback, recording the history for freeze as well as post exercise feedback and control of the simulated training exercise. Different forms of feedback are simultaneously generated by processing a set of messages received periodically either from the host computer running the simulator or from the history file depending on whether it is on-line feedback mode or off-line feedback mode. Gaming area display in the feedback is accomplished by combining the positional information with the exercise area map which is digitized off-line and stored in a graphics metafile. Mouse-driven interactive graphics with hierarchical menus, on-line help facility and built-in knowledge-base provide a highly user-friendly instructor interface, improved feedback presentation and easier simulation control. The large screen graphical display connected to the workstation provides an effective trainee interface for exercise briefings prior to, during a pause in, and following the training exercise.