scholarly journals AI-Based Attendance Monitoring System

2019 ◽  
Vol 9 (2S) ◽  
pp. 592-597
Keyword(s):  
Artificial Intelligence ◽  
Student Performance ◽  
Monitoring System ◽  
Motion Pictures ◽  
Individual Student ◽  
Department Heads ◽  
Student Attendance ◽  
Face Detection And Recognition ◽  
The Individual ◽  
Detection And Recognition

Attendance Monitoring System is essential in all organizations for checking the performance of students and it is not easy task to check each and every student is present or not. In all organization attendance are taken manually by calling their register numbers or names and noted in attendance registers issued by the department heads as a proof and in some organizations the students wants to sign in these sheets which are stored for future references. This technique is repetitive, complex work and leads to errors as few students regularly sign for their absent students or telling proxy attendance of the absent students. This method additionally makes it more complex to track all the students attendance and difficult to monitoring the individual student attendance in a big classroom atmosphere. In this article, we use are using the technique of utilization face detection and recognition framework to contunisuly recognize students going to class or not and marking their attendance by comparing their faces with database to match and marking attendance. This facial biometric framework takes a picture of a person using camera and contrast that image and compare the image with the image with is stored at the time of enrolment and if it matches marks the attendance and monitor the student performance contunisuly. We may use the concept of artificial intelligence concept to monitor student attendance like capturing the motion pictures of the student when present in class to analyze the student data how much time the student presents in class.

scholarly journals Peran Kepemimpinan Transformasional dalam Meningkatkan Kinerja Individu Santri pada Unit Usaha Pondok Pesantren

2019 ◽  
Vol 2 (1) ◽  
pp. 50
Author(s):  
Fuad Dhiya Ul Husaen ◽  
Reni Rosari
Keyword(s):  
Transformational Leadership ◽  
Student Performance ◽  
Sample Selection ◽  
Sampling Technique ◽  
Boarding School ◽  
Individual Performance ◽  
Individual Student ◽  
Business Unit ◽  
Innovative Behavior ◽  
The Individual

This study aims to determine how much influence transformational leadership on the individual performances of santri, mediated by the innovative behavior of santri. This research is confirmatory research that aims to examine theories that have been there before. The number of samples in this study was 102 students who worked in the business unit of the Sidogiri Islamic boarding school. The sample selection uses a purposive sampling technique. Data was collected using a questionnaire instrument with a Likert scale. Testing the hypothesis refers to Baron Kenny's mediation theory and processing data using Smart PLS 3 applications, by analyzing the results of evaluating the outer and inner models. The results of this study indicate that; (1) transformational leadership of the head of a business unit has a significant positive effect on the individual performance of students with a coefficient of 0.546. (2) innovative behavior proved not to mediate the influence of transformational leadership head of the unit on individual student performance.

Factors Affecting Students’ Performance in Distributed Pair Programming

2017 ◽  
Vol 57 (2) ◽  
pp. 513-544 ◽  
Author(s):  
Stelios Xinogalos ◽  
Maya Satratzemi ◽  
Alexander Chatzigeorgiou ◽  
Despina Tsompanoudi
Keyword(s):  
Student Performance ◽  
Object Oriented ◽  
Object Oriented Programming ◽  
Pair Programming ◽  
Individual Student ◽  
Broadband Internet ◽  
Factors Affecting ◽  
Final Exams ◽  
The Individual ◽  
Pair Compatibility

Pair Programming has been shown to increase productivity and code quality not only in professional software development but also in the context of programming education. The provision of broadband Internet access gave rise to Distributed Pair Programming (DPP) enabling two programmers to collaborate remotely. To gain insight into the benefits of DPP, we performed an empirical study on an object-oriented programming course where 62 students carried out assignments through a DPP platform. The goal of the study is to investigate, in the context of DPP, whether prior programming skills (assessed at the level of student, his or her partner and pair) and pair compatibility are related to student performance. To further examine the effect of DPP on learning outcomes, we have studied whether a pair’s performance on DPP assignments is related to the students’ grade. The findings indicate that the student’s actual skill and the pair’s actual skill affect his or her performance in an object-oriented programming course. The results also suggested that there is no association between pair compatibility and his or her own performance. Finally, pair performance on DPP assignments is related to the individual student performance in the final exams. Such evidence can be used to guide instructors when planning DPP assignments and especially when forming student pairs.

scholarly journals Academic Assessment

Psychology ◽  
2019 ◽  
Author(s):  
Karen L. Gischlar
Keyword(s):  
School Choice ◽  
Student Performance ◽  
Intervention Program ◽  
Individual Student ◽  
Assessment Data ◽  
Policy And Practice ◽  
Special Education Eligibility ◽  
Academic Assessment ◽  
Statewide Assessment ◽  
The Individual

In the field of education, assessment is used to evaluate and document the learning progress and educational needs of students. Assessment takes many forms, including direct and indirect methods and summative and formative measures, and occurs across levels from the individual student to the district and state levels. At the individual student, classroom, and school levels, academic assessment data are used to make instructional decisions regarding differentiation, intervention, program placement, and special education eligibility. Specifically, academic skills assessment enables the educator to determine student performance on tasks in the basics of reading, writing, and math against a criterion or standard (e.g., grade-level expectations) and in relation to same age or grade peers. At the district level, high-stakes statewide assessment data are used for accountability purposes, such as documenting adequate student progress. Additionally, statewide assessment results often are used to “grade” and rank schools and may influence decisions regarding allocation of resources and school choice vouchers. The purpose of this annotated bibliography is to provide an overview of general resources for academic assessment as well as more-specific resources for differing modalities and methods of assessment, applications, and implications for policy and practice. The bibliography includes seminal and contemporary references from educational publishers and peer-reviewed sources.

scholarly journals Building a Descriptive Exam Model for Student Performance using Process Mining Techniques in Examaize System

2020 ◽  
Vol 9 (3) ◽  
pp. 1043-1050
Keyword(s):  
Student Performance ◽  
High Frequency ◽  
Process Mining ◽  
Performance Outcomes ◽  
Assessment System ◽  
Individual Student ◽  
Multiple Choice Questions ◽  
Improve Student Performance ◽  
The Individual ◽  
Mining Algorithms

Paper The objective of this research paper is to determine the understanding of students’ course contents and evaluate student performance according to expectations. There are predefined navigation models available to answer Multiple Choice Questions (MCQs). The individual student responds to these questions in their navigation pattern that results in various Student Performance Outcomes. The research presents the process mining techniques to evaluate students’ answers in the MCQs predefined navigation model in the exaMAIZE Assessment System. This research shows that students navigate all the twenty-five questions according to their way of answering the exam, where seven questions are under high frequency and later analyze to revise the answer on suspicion or difficult. The experiment compared Student Exam Outcomes with the Student Performance Outcomes of each outcome, and the frequency of navigating a question to find out individual student Strengths and Weaknesses. This work can be extended future development of efficient process mining algorithms by applying the next academic session to improve student performance

scholarly journals Automatic Student Attendance System using Face Recognition

2020 ◽  
Vol 9 (3) ◽  
pp. 93-99
Keyword(s):  
Face Recognition ◽  
Recognition System ◽  
Automated Systems ◽  
Student Attendance ◽  
Face Recognition System ◽  
The Face ◽  
Face Detection And Recognition ◽  
Class Room ◽  
Current Systems ◽  
Detection And Recognition

The most common difficulty that every teacher faces in class room is to take the attendance of the students one by one in each and every class. For the time being many automated systems has been proposed for taking student attendance. In this paper, I introduced an automated student attendance system based on the use of unique techniques for face detection and recognition. This system automatically detects the student when he or she enters the classroom and recognizes that specific student and marks the student's attendance. This method also focuses on the specific features of different attributes such as the face, eye and nose of humans. In order to evaluate the performance of different face recognition system, different real-time situations are considered. This paper also suggests the technique for handling the technique such as spoofing and avoiding student proxy. This system helps track students compared to traditional or current systems and thereby saves time.

scholarly journals Automated Locking based on Thermal Camera and Artificial Intelligence

2020 ◽  
Vol 9 (4) ◽  
pp. 1437-1443
Keyword(s):  
Artificial Intelligence ◽  
Face Detection ◽  
Digital System ◽  
Thermal Camera ◽  
Leaving Home ◽  
Face Detection And Recognition ◽  
The Mind ◽  
Detection And Recognition

In the fast lifestyle of today where work and learning consumes most of people's time. We through this paper look forward to providing further convenience to people through automated locking of house doors on detecting no person inside the house. This will ease pressure on the mind to lock or unlock the gate and carry keys or keep track of the digital system installed in the required events of leaving home or coming back. We recommend a thermal camera along with artificial intelligence means to detect humans inside the house and take action accordingly. If no human is found inside the house and no member(s) are facing the door then lock doors immediately. System of face detection and recognition of member(s) to unlock the house in the event of returning or going back inside the house is to be incorporated as well.

scholarly journals Smart Way to Inspect Student Performance Using Emotional State on Learning Analytics

2019 ◽  
Vol 8 (3) ◽  
pp. 5352-5357
Keyword(s):  
Student Performance ◽  
Learning Style ◽  
Calculated Data ◽  
Outcome Data ◽  
Learning Ability ◽  
Individual Student ◽  
Online Test ◽  
Analytical Test ◽  
Recorded Data ◽  
The Individual

The paper describes the research of the students pursuing higher technical education calculating their skills, behavior, emotion, learning style and methods of the students using learning inspect in smart way. The learning inspect is the smart and innovative way of detecting the student aspects. In this we consider a group of students who taking the online test and record the students interaction with each part of the test by providing the option to each and every questions. The recorded data is stored in the data base. After the completion of the analytical test the outcome data of the individual student is calculated. The calculated data may provide the students learning ability and how they tackle the exam and how they prepare themselves in the exam. It also shows that the handling of pressure during the time of exam. The exception outcome is being correlated with the various parameters to detect the student survival and the performance in their academics. This method is being expected and made to turn all of their intention towards it

scholarly journals Class Monitoring System Tools MTCNN and Haarcascade Classifier

2018 ◽  
Vol 7 (3.12) ◽  
pp. 951
Author(s):  
Aditya Vikram Bhattacharya ◽  
Mrinalini Khanna ◽  
Akshay Tripathi ◽  
S Murugaveni
Keyword(s):  
Face Recognition ◽  
Monitoring System ◽  
Face Detection ◽  
Cognitive Tools ◽  
Time Stamp ◽  
Time Stamps ◽  
Face Detection And Recognition ◽  
Further Development ◽  
Detection And Recognition

The project aims towards the assistance of teachers at the time of taking attendance. The system solely focuses on face detection and recognition. The tools used to device the system are API’s offered by Python 3.6, Open CV(for detection) and a few cognitive tools provided by Azure.The basic idea behind the project is face recognition linked to a database backend. The information of the student attending the class is stored here. The entire attendance is associated with two types of time stamps incorporated at the server end. The time stamp helps to keep a track of the hour conducted and the time for which number of people attended the class. Exceptions in the time stamp would be incorporated in order to cater for the students leaving the class or trying to bunk the class. In case of further exceptionsin the time stamp will be scope of further development of the system. All queries or conditions of the students will be answered by the system on communication with the admin. If the admin finds that the system was at fault then it can always be fixed by the admin for smooth functioning of the class monitoring system.

scholarly journals ReFresh: Retaining First Year Engineering Students and Retraining for Success

2013 ◽  
Author(s):  
Neil Shyminsky ◽  
Lesley Mak
Keyword(s):  
Student Performance ◽  
Student Development ◽  
Classroom Environment ◽  
Engineering Students ◽  
Retention Rate ◽  
Study Groups ◽  
Individual Student ◽  
First Year ◽  
The Individual ◽  
The Impact

Student retention and support are key priorities at the University of Toronto Faculty of Applied Science and Engineering, as is evidenced by a first year to second year average retention rate of 91% over the past 4 years. At U of T Engineering, academic standing and registration are determined on a term-by-term basis. As a result, student performance in the fall term can result in obligatory withdrawal from their studies in January, including first year students. While approximately only 4% of the first year class have to withdraw, the impact can be very distressing for the individual student, as his/her plans for the year are disrupted and their confidence shaken. Withdrawal from studies can occur for many reasons such as insufficient academic background from their high school, personal crisis, low resilience and lack of study skills and these struggles can be especially acute for international students. The ReFresh Program gives these students an opportunity to continue their education while learning from their mistakes. A small classroom environment allows students to integrate into a collaborative community, create study groups with classmates, communicate easily with their instructors and TA’s and benefit from constant support from First Year Office staff. This format helps students deal with the personal and academic challenges that prevented them from performing at their best in the fall term, relearn the foundations and key concepts of Calculus, Physics, Computer Programming, Chemistry and Linear Algebra and develop a plan to be successful for the next fall to repeat their first semester. This paper will discuss the structure of the ReFresh program as well as the impact on student success, student development and retention.

Sign in / Sign up

Export Citation Format

Share Document