Provision of a tip regarding student conduct
View Patent ↗The invention relates to the field of computer engineering. The technical result consists in reducing the number of errors in the detection of breaches of remote examination regulations in automated proctoring systems. The technical result is achieved in that, if more than one breach is detected during an examination, a sum total of the weights of the detected breaches is determined and compared with at least one preset threshold value; a tip regarding the conduct of a student is returned, said tip indicating the extent to which said sum total of weights has reached the threshold value, wherein the weight of at least one breach is determined as the sum total of weights for said breach, detected in one or more modes from the following group: automatically detected, automatically detected and manually confirmed, and manually detected; wherein quantitatively differing weights are set for the same breach depending on which of the above-mentioned modes the breach was detected in.
1 . A method for providing tips about a student's behavior during a remote exam, in which a data stream from at least one software or hardware provided with a student's computer is analyzed, at least one student behavior event is detected in said data stream; when the mentioned event is a violation of the regulations of the remote exam, then such an event is assigned a weight depending on the type of violation, when more than one violation is detected during the exam, then the set of weights of the detected violations is determined and compared with at least one pre-set threshold value, return a tip about the student's behavior, indicating the degree of achievement of the said set of weights of at least one threshold value, wherein the weight of at least one violation is determined as the set of weights for this violation, detected in modes from the following group: detected automatically, detected automatically and confirmed in manual mode, and detected in manual mode, and wherein quantitatively different weights are set for one violation, depending on which of the modes the violation was detected.
2 . The method of claim 1 , wherein the software of the student's computer monitors the desktop of the computer.
3 . The method of claim 1 , wherein the student's computer hardware is a webcam and a microphone.
4 . The method of claim 1 , wherein violations, depending on the type of data stream being analyzed, are assigned to one or more of the following categories: video violations, voice violations, violations associated with desktop activity, violations associated with student identification.
5 . The method of claim 1 , wherein the conditions for classifying the event of the student's behavior as a violation of the regulations of the remote exam are pre-loaded on the student's computer.
6 . The method of claim 1 , wherein the type of violation is an indicator of the severity of that violation and is predetermined for each violation.
7 . The method of claim 1 , wherein different types of disturbances are given quantitatively different weights.
8 . The method of claim 1 , wherein the weight of the violation detected automatically is provided with an additional reduction factor that sets the weight value lower in comparison with the weights of violations detected automatically and confirmed in manual mode or detected in manual mode.
9 . The method of claim 1 , wherein the detection of violations in automatic mode is carried out simultaneously with the course of the remote exam.
10 . The method of claim 1 , wherein the detection of violations in automatic mode is carried out after the completion of the remote exam.
11 . The method of claim 1 , wherein the detection of violations in manual mode is carried out simultaneously with the progress of the remote exam.
12 . The method of claim 1 , wherein the detection of violations in manual mode is carried out after the completion of the remote exam.
13 . The method of claim 1 , wherein the confirmation of violations in manual mode is carried out simultaneously with the progress of the remote exam.
14 . The method of claim 1 , wherein the confirmation of violations in manual mode is carried out after the end of the remote exam.
15 . The method of claim 1 , wherein the prompt is textual, graphical, or audio information.
16 . A non-transitory computer-readable storage medium storing one or more programs for execution by one or more processors, the one or more programs including instructions for executing the method of claim 1 .
17 . A system for providing tips about a student's behavior during a remote exam, the system comprising:
at least one processor and memory operably coupled to the at least one processor;
instructions that, when executed on the at least one processor, cause the at least one processor to:
analyze a data stream from at least one software or hardware provided with a student's computer,
detect at least one student behavior event in the data stream,
wherein when the mentioned event is a violation of the regulations of the remote exam, then such an event is assigned a weight depending on the type of violation, when more than one violation is detected during the exam, then the set of weights of the detected violations is determined and compared with at least one pre-set threshold value, return a tip about the student's behavior, indicating the degree of achievement of the set of weights of at least one threshold value, wherein the weight of at least one violation is determined as the set of weights for this violation, detected in modes from the following group: detected automatically, detected automatically and confirmed in manual mode, and detected in manual mode, and wherein quantitatively different weights are set for one violation, depending on which of the modes the violation was detected.
18 . The system of claim 17 , wherein the type of violation is an indicator of the severity of that violation and is predetermined for each violation.
19 . The system of claim 17 , wherein the weight of the violation detected automatically is provided with an additional reduction factor that sets the weight value lower in comparison with the weights of violations detected automatically and confirmed in manual mode or detected in manual mode.
20 . The system of claim 17 , wherein the detection of violations in automatic mode or in manual mode is carried out simultaneously with the course of the remote exam.