The document presents an overview of automatic question paper generators (AQPG). It discusses how AQPGs work by gathering questions from banks and generating papers based on algorithms that consider factors like difficulty levels, topic weights, and syllabus coverage. The document reviews various algorithms used in AQPGs, such as randomized algorithms and artificial intelligence techniques like genetic algorithms and natural language processing. It also provides a literature survey summarizing over 20 research papers on AQPGs and the algorithms they employed. Finally, it concludes that AQPGs can help standardize the question paper generation process and reduce the workload for educators.
CRITERION BASED AUTOMATIC GENERATION OF QUESTION PAPERvivatechijri
In any educational course curriculum, the courses are defined with learning objectives. Teachers conduct assessments to know if students have achieved certain learning objectives or not. The Proposed System provides a solution to choose challenging, well framed questions and make it easy for the user to generate it within a short period of time. The existing tools are rigid and support very basic or limited parameters. In our system we allow admin and user to input a set of questions and mark them with parameters such as difficulty level, complexity, type of question, module, min and max weightage. It contains two modules namely admin module and user module and the question management makes it an effortless task. From the entered input the paper is generated and saved as a .pdf file which can be kept for own or distributed as per the user or admin requirements. The required software and hardware are easily available and easy to work with. The goal is to simplify its current manual method, by means of computerised equipment and complete computer applications, in order to meet its needs, so that its important data/information can be stored for a longer period of time with easy access and manipulation. Basically the project describes how to manage for good performance and better services for the clients.
Enhancing Video Understanding: NLP-Based Automatic Question GenerationIRJET Journal
The document describes a research project that aims to develop an autonomous question generation system to improve video comprehension. The system would use natural language processing techniques to transcribe audio from videos, identify main ideas, and generate questions at different cognitive levels about the video content. This could help students more deeply engage with videos and foster critical thinking skills. The system would combine computer vision to extract visual elements from videos with NLP to transcribe audio, allowing it to develop a comprehensive understanding of video content to generate a wide variety of contextually appropriate questions.
IRJET- Automated Exam Question Generator using Genetic AlgorithmIRJET Journal
The document describes a proposed system for automatically generating exam questions using genetic algorithms. The system would take in previous exam questions categorized by Bloom's Taxonomy levels and chapters selected by instructors. It would then use genetic algorithms to generate new exam questions that cover different Bloom's levels and avoid repeating questions from the past two years. This aims to ease instructor workload while producing high-quality exam questions at different difficulty levels to evaluate students. The proposed system is described to be implemented using Java, with questions and details stored in a MySQL database.
The document discusses the development of Grade Analyser, a web application that uses machine learning and natural language processing to automate the grading of subjective answer-type exams. It aims to address the inefficiencies and inaccuracies of manual grading by teachers. The application allows teachers to upload assignments and answer keys, and students to submit handwritten answer scripts digitally. Google Cloud Vision API converts handwriting to text for analysis using a Cosine similarity algorithm to determine similarity to the answers and grade responses fairly. The tool is intended to speed up grading, reduce errors, and ensure more impartial student assessments.
Manta ray optimized deep contextualized bi-directional long short-term memor...IJECEIAES
Complex question answering (CQA) is used for human knowledge answering and community questions answering. CQA system is essential to overcome the complexities present in the question answering system. The existing techniques ignores the queries structure and resulting a significant number of noisy queries. The complex queries, distributed knowledge, composite approaches, templates, and ambiguity are the common challenges faced by the CQA. To solve these issues, this paper presents a new manta ray foraging optimized deep contextualized bidirectional long-short term memory based adaptive galactic swarm optimization (MDCBiLSTMAGSO) for CQA. At first, the given input question is preprocessed and the similarity assessment is performed to eliminate the misclassification. Afterwards, the attained keywords are mapped into applicant results to improve the answer selection. Next, a new similarity approach named InfoSelectivity is introduced for semantic similarity evaluation based on the closeness among elements. Then, the relevant answers are classified through the MDCBiLSTM and optimized by a new manta ray foraging optimization (MRFO). Finally, adaptive galactic swarm optimization (AGSO) resultant is the best output. The proposed scheme is implemented on the JAVA platform and the outputs of designed approach achieved the better results when compared with the existing approaches in average accuracy (98.2%).
Survey on Techniques for Predictive Analysis of Student Grades and CareerIRJET Journal
This document discusses techniques for predictive analysis of student grades and careers. It first reviews the different types of data that can be used, such as demographic, academic performance, and social media data. Then, it summarizes several machine learning techniques commonly used for predictive modeling in education, including logistic regression, decision trees, naive Bayes, and neural networks. Finally, it discusses challenges with predictive analytics in education and potential future research directions. The literature review section summarizes 12 research articles that evaluate algorithms like decision trees, KNN, SVM, naive Bayes, linear regression, random forest, gradient boosting for predicting student grades and careers. Accuracy rates between 87-99% are reported depending on the algorithm and dataset used.
This document describes a proposed AI-based question answering system to generate and evaluate questions for students. Key points:
- The system would generate objective and subjective questions from course materials uploaded by instructors to provide automated assessments.
- It would use natural language processing and machine learning models to understand text, extract keywords to frame questions, and generate answer options for multiple-choice questions.
- Student responses would be evaluated by comparing them to ideal answers using similarity metrics like cosine similarity and Jaccard similarity to provide scores.
- An implementation tested on sample course materials found the model could accurately generate questions and evaluate student knowledge within the limitations of not handling diagrams, math formulations, or subjective literature evaluations.
The document describes project based learning methodologies for embedded systems design. It discusses how project based learning differs from traditional teaching approaches in engaging students through extended inquiry projects. It outlines the roles of instructors in facilitating student-led projects and of students in taking responsibility. Examples of embedded hardware and software development processes on platforms like 8051, AVR and ARM are provided. The document also discusses design complexities and related work before concluding that the methodology presents an approach combining traditional and project based learning for teaching embedded and intelligent systems.
CRITERION BASED AUTOMATIC GENERATION OF QUESTION PAPERvivatechijri
In any educational course curriculum, the courses are defined with learning objectives. Teachers conduct assessments to know if students have achieved certain learning objectives or not. The Proposed System provides a solution to choose challenging, well framed questions and make it easy for the user to generate it within a short period of time. The existing tools are rigid and support very basic or limited parameters. In our system we allow admin and user to input a set of questions and mark them with parameters such as difficulty level, complexity, type of question, module, min and max weightage. It contains two modules namely admin module and user module and the question management makes it an effortless task. From the entered input the paper is generated and saved as a .pdf file which can be kept for own or distributed as per the user or admin requirements. The required software and hardware are easily available and easy to work with. The goal is to simplify its current manual method, by means of computerised equipment and complete computer applications, in order to meet its needs, so that its important data/information can be stored for a longer period of time with easy access and manipulation. Basically the project describes how to manage for good performance and better services for the clients.
Enhancing Video Understanding: NLP-Based Automatic Question GenerationIRJET Journal
The document describes a research project that aims to develop an autonomous question generation system to improve video comprehension. The system would use natural language processing techniques to transcribe audio from videos, identify main ideas, and generate questions at different cognitive levels about the video content. This could help students more deeply engage with videos and foster critical thinking skills. The system would combine computer vision to extract visual elements from videos with NLP to transcribe audio, allowing it to develop a comprehensive understanding of video content to generate a wide variety of contextually appropriate questions.
IRJET- Automated Exam Question Generator using Genetic AlgorithmIRJET Journal
The document describes a proposed system for automatically generating exam questions using genetic algorithms. The system would take in previous exam questions categorized by Bloom's Taxonomy levels and chapters selected by instructors. It would then use genetic algorithms to generate new exam questions that cover different Bloom's levels and avoid repeating questions from the past two years. This aims to ease instructor workload while producing high-quality exam questions at different difficulty levels to evaluate students. The proposed system is described to be implemented using Java, with questions and details stored in a MySQL database.
The document discusses the development of Grade Analyser, a web application that uses machine learning and natural language processing to automate the grading of subjective answer-type exams. It aims to address the inefficiencies and inaccuracies of manual grading by teachers. The application allows teachers to upload assignments and answer keys, and students to submit handwritten answer scripts digitally. Google Cloud Vision API converts handwriting to text for analysis using a Cosine similarity algorithm to determine similarity to the answers and grade responses fairly. The tool is intended to speed up grading, reduce errors, and ensure more impartial student assessments.
Manta ray optimized deep contextualized bi-directional long short-term memor...IJECEIAES
Complex question answering (CQA) is used for human knowledge answering and community questions answering. CQA system is essential to overcome the complexities present in the question answering system. The existing techniques ignores the queries structure and resulting a significant number of noisy queries. The complex queries, distributed knowledge, composite approaches, templates, and ambiguity are the common challenges faced by the CQA. To solve these issues, this paper presents a new manta ray foraging optimized deep contextualized bidirectional long-short term memory based adaptive galactic swarm optimization (MDCBiLSTMAGSO) for CQA. At first, the given input question is preprocessed and the similarity assessment is performed to eliminate the misclassification. Afterwards, the attained keywords are mapped into applicant results to improve the answer selection. Next, a new similarity approach named InfoSelectivity is introduced for semantic similarity evaluation based on the closeness among elements. Then, the relevant answers are classified through the MDCBiLSTM and optimized by a new manta ray foraging optimization (MRFO). Finally, adaptive galactic swarm optimization (AGSO) resultant is the best output. The proposed scheme is implemented on the JAVA platform and the outputs of designed approach achieved the better results when compared with the existing approaches in average accuracy (98.2%).
Survey on Techniques for Predictive Analysis of Student Grades and CareerIRJET Journal
This document discusses techniques for predictive analysis of student grades and careers. It first reviews the different types of data that can be used, such as demographic, academic performance, and social media data. Then, it summarizes several machine learning techniques commonly used for predictive modeling in education, including logistic regression, decision trees, naive Bayes, and neural networks. Finally, it discusses challenges with predictive analytics in education and potential future research directions. The literature review section summarizes 12 research articles that evaluate algorithms like decision trees, KNN, SVM, naive Bayes, linear regression, random forest, gradient boosting for predicting student grades and careers. Accuracy rates between 87-99% are reported depending on the algorithm and dataset used.
This document describes a proposed AI-based question answering system to generate and evaluate questions for students. Key points:
- The system would generate objective and subjective questions from course materials uploaded by instructors to provide automated assessments.
- It would use natural language processing and machine learning models to understand text, extract keywords to frame questions, and generate answer options for multiple-choice questions.
- Student responses would be evaluated by comparing them to ideal answers using similarity metrics like cosine similarity and Jaccard similarity to provide scores.
- An implementation tested on sample course materials found the model could accurately generate questions and evaluate student knowledge within the limitations of not handling diagrams, math formulations, or subjective literature evaluations.
The document describes project based learning methodologies for embedded systems design. It discusses how project based learning differs from traditional teaching approaches in engaging students through extended inquiry projects. It outlines the roles of instructors in facilitating student-led projects and of students in taking responsibility. Examples of embedded hardware and software development processes on platforms like 8051, AVR and ARM are provided. The document also discusses design complexities and related work before concluding that the methodology presents an approach combining traditional and project based learning for teaching embedded and intelligent systems.
The document proposes a recruiter recommendation system for undergraduate students to improve college placement processes. It uses machine learning algorithms like logistic regression, random forest, KNN and SVM to analyze previous student data and predict placement probabilities based on marks. This would help students strengthen their skills and recommend eligible companies. The system architecture involves collecting student data like CGPA and technical test scores, training models, and generating recommendations to match students with appropriate recruiters. This automated process aims to make placements more efficient by reducing manual work and better notifying students.
Online Intelligent Semantic Performance Based Solution: The Milestone towards...AM Publications
As we analyse the computer application undergraduate logical-based courses in an assorted
environment of online assignments and exams and offline lectures, and exhibit the impact on academic routine of
factors such as classroom attendance, web-based course complement, and homework. We present grades from both
ordinary front ends and where the latter method controls for unobserved variation among students. A system
tailored intelligent instructional evaluation will generate the students, teachers & administration concepts,
discussing the predisposition in estimation when the ordinary evaluation method is used, resulting from the fact
that it ignores unobserved assorted. It also reduces the administrator’s load and helps provide the flexibility to
teacher’s need for mass evaluation. The Online Intelligent Semantic Performance based Solution is web
applications that ascertain an association between the institutes and the students. Institutes enter on the site, the
concepts they want in the exam. The questions based on the relevant concept and the syllabus is displayed as a test
to the eligible students. The answers entered by the students are then evaluated and their score is calculated and
saved. This score then can be accessed by the institutes to determine the passes students or to evaluate their
performance. It has been successfully applied to the distance evaluation of basic operating skills of computer
science, such as the course of computer skills in Universities and the local examination for the under graduates in
faridabad, Haryana.
Library management system ,
Has parts
Admin
Users
Admin can add user , add book, add member and can as well manage existing details
Users can issue books ,return books ,
The document describes the design and evaluation of an electronic class record system for Makiling National High School. It discusses:
1) The development of an electronic class record using Microsoft Excel that automatically computes student grades based on inputs from teachers.
2) Testing the functionality and accuracy of the electronic class record system.
3) Evaluating the acceptability of the electronic class record system through surveys of teachers, finding it was rated positively and would be implemented in the upcoming school year.
IRJET- Automatic Generation of Question Paper using Blooms TaxonomyIRJET Journal
This document describes a system for automatically generating question papers from a semantically tagged question bank or repository. The system allows users like teachers to specify parameters like topic coverage, question type distribution, cognitive levels, and difficulty levels. It then generates a question paper by selecting questions from the bank that match the specified parameters. This overcomes issues with existing methods of question paper creation, which depend heavily on a teacher's expertise and experience. The automatic system could generate question papers more quickly and consistently based on learning objectives. It also helps avoid duplicating questions across multiple exams while the question bank grows over time.
Java parser a fine grained indexing tool and its applicationRoya Hosseini
1) The document discusses an intelligent tutoring system called Knowledge Maximizer (KM) that uses fine-grained modeling of programming concepts to provide personalized exam preparation for students.
2) An evaluation of KM compared to other course tutoring systems found that students using KM attempted more complex questions, had a higher success rate, and achieved greater knowledge gains.
3) An automatic tool called JavaParser was developed to index programming questions by the underlying concepts, achieving over 98% accuracy compared to manual indexing. Future work aims to improve modeling and provide more adaptive support.
This document summarizes a study on developing an expert system called WittyCat to provide dynamic assessments of student exam quality. Survey data and course materials were collected and analyzed using association rule learning. Rules generated from a pilot study provided insights that helped instructors improve their teaching. The current state of WittyCat automates rule generation and seeks to explain conclusions. Contributions from additional course data and feedback are requested to evaluate WittyCat's assessments.
"Information and intelligence are two vital columns on which development of humankind rise and knowledge has significant impact on operating of society. Student assessment is a crucial part of teaching and is done through the process of examinations and preparation of exam question papers has consistently been a matter of interest. Present day technologies assist the teacher to stock the questions in a computer databases but the problem which emerges is how the present day technologies would also assist the teachers to automatically create the variety sets of questions from every now and then without worry about replication and duplication from the previous exam while the question bank keeps growing. Ms. R. Selvapriya M.Sc. MPhil | Ganesh. K ""Automatic Question Paper Generator System"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21646.pdf
Paper URL: https://www.ijtsrd.com/computer-science/other/21646/automatic-question-paper-generator-system/ms-r-selvapriya-msc-mphil"
NagaRaju Addanki is a software developer with over 7 years of experience seeking new project opportunities. He has extensive experience developing web applications using Microsoft technologies like ASP.NET, C#, and SQL Server. Currently he works as a module lead at Value Labs in Hyderabad, India where he supports payroll projects and applications. His background includes developing academic, e-commerce, and database applications for clients.
Online Examination and Evaluation SystemIRJET Journal
This document summarizes research on existing online examination and evaluation systems. It reviews 20 papers on different approaches for objective and subjective answer evaluation, including keyword matching, cosine similarity, machine learning algorithms, and natural language processing. The papers describe systems that automate the grading of exams through online proctoring, question banks, and tools to analyze student responses against model answers. The document concludes that a comprehensive examination system is needed that incorporates proctoring, online testing, and evaluation of both subjective and objective question types.
The document describes a proposed web application for automating project management tasks at an engineering institute. The application would allow students to form groups, get project approvals, submit work, and receive feedback and evaluations. It consists of two modules - one for online project work and another to evaluate student and project progress. The goal is to streamline project activities and provide a centralized platform for communication between students and guides.
Predictive models are quasi experimental structures used to determine the future
patterns in data. These meaningful data patterns form the building block of any
decision support system. Researchers all over the world have built many prediction
models for major industries. Research works in the educational sector has increased
steeply. This steep increase may be due to the high availability of data in the
educational domain. This survey tries to comprehend a few literary works on
academic performance prediction of engineering students with the focus on grade
predictions. Meaningful interpretations have been made and inferences are presented
at the end of this paper
Predicting User Ratings of Competitive ProgrammingContests using Decision Tre...IRJET Journal
This research paper presents a decision tree machine learning model for predicting future user ratings of competitive programming contests. The model was trained on a dataset containing past contest performance and achieved an MSE of 8494 and RMSE of 92 on test data. Decision trees can handle large datasets with numerical and categorical data, and limiting depth prevents overfitting. The model effectively predicted ratings, demonstrating decision trees as a useful tool for this task.
AUTOMATIC QUESTION GENERATION USING NATURAL LANGUAGE PROCESSINGIRJET Journal
The document describes a proposed method for automatic question generation using natural language processing and T5 text-to-text transfer transformer models. The method uses T5 models trained on the Stanford Question Answering Dataset to generate questions from paragraphs of text without requiring extensive grammar rules. The proposed system aims to assist students in learning by generating questions to test their understanding from provided materials.
This document summarizes a final year defense presentation on leveraging an interactive web-based virtual classroom. The presentation outlines the introduction, aim and objectives, hypothesis, research questions, literature review, proposed model, design and development, testing and evaluation, result analysis, performance analysis, and conclusion. It discusses designing a virtual classroom to allow interactive teaching and learning between teachers and students. Testing showed the classroom was an effective environment for both learning and teaching. The presentation concludes that a virtual classroom can benefit teachers and students and hopes it will support learning and teaching in the future.
Abhilash Kumar is a final year undergraduate student studying Computer Science and Engineering at IIT Kanpur. He has achieved high grades throughout his education and received several awards and fellowships for his academic performance and programming skills. His internship experiences include open source development at Facebook and data analysis projects. He is highly experienced in programming contests and open source contributions.
This document describes a student result analysis system that was developed to automatically parse student result data from excel files into a database. It allows teachers to log in and view analysis of student results including rankings, subject performance, and passing/failing rates. The system uses PHP, MySQL, and JavaScript to fetch and display the student data. It also generates PDF reports of individual student results. The goal was to create an easier way for teachers to analyze student performance compared to manual entry of results.
This document summarizes a project to automate exam hall seating arrangements using cloud computing. The project aims to simplify the process of allocating exam halls and seats to students. Currently, seating is assigned manually requiring significant work. The proposed system will automatically generate seating arrangements and hall assignments for invigilators based on student information stored in a database. It will reduce workload and the need for manual paperwork. The system will have modules for administration, student and staff registration, room and student allocation. It will use technologies like PHP, MySQL, and be hosted on XAMPP server. Data will be stored centrally and accessible anytime through the cloud.
This document describes an online examination system developed using Java web technologies. The system allows teachers to manage questions, generate quizzes, and enable students to take online tests. It has three main components - question management for adding, modifying and deleting questions; quiz generation to randomly select questions based on set criteria; and online testing for students to self-test and view their progress. The system aims to make the examination process more efficient by automating paper generation and grading while reducing instances of cheating. It is intended to help both teachers and students by improving assessment and providing insights into learning levels.
Eric Nyberg's Presentation "From Jeopardy! To Cognitive Agents: Effective Learning in the Wild" on Cognitive Systems Institute Group Speaker Series July 9, 2015
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
The document proposes a recruiter recommendation system for undergraduate students to improve college placement processes. It uses machine learning algorithms like logistic regression, random forest, KNN and SVM to analyze previous student data and predict placement probabilities based on marks. This would help students strengthen their skills and recommend eligible companies. The system architecture involves collecting student data like CGPA and technical test scores, training models, and generating recommendations to match students with appropriate recruiters. This automated process aims to make placements more efficient by reducing manual work and better notifying students.
Online Intelligent Semantic Performance Based Solution: The Milestone towards...AM Publications
As we analyse the computer application undergraduate logical-based courses in an assorted
environment of online assignments and exams and offline lectures, and exhibit the impact on academic routine of
factors such as classroom attendance, web-based course complement, and homework. We present grades from both
ordinary front ends and where the latter method controls for unobserved variation among students. A system
tailored intelligent instructional evaluation will generate the students, teachers & administration concepts,
discussing the predisposition in estimation when the ordinary evaluation method is used, resulting from the fact
that it ignores unobserved assorted. It also reduces the administrator’s load and helps provide the flexibility to
teacher’s need for mass evaluation. The Online Intelligent Semantic Performance based Solution is web
applications that ascertain an association between the institutes and the students. Institutes enter on the site, the
concepts they want in the exam. The questions based on the relevant concept and the syllabus is displayed as a test
to the eligible students. The answers entered by the students are then evaluated and their score is calculated and
saved. This score then can be accessed by the institutes to determine the passes students or to evaluate their
performance. It has been successfully applied to the distance evaluation of basic operating skills of computer
science, such as the course of computer skills in Universities and the local examination for the under graduates in
faridabad, Haryana.
Library management system ,
Has parts
Admin
Users
Admin can add user , add book, add member and can as well manage existing details
Users can issue books ,return books ,
The document describes the design and evaluation of an electronic class record system for Makiling National High School. It discusses:
1) The development of an electronic class record using Microsoft Excel that automatically computes student grades based on inputs from teachers.
2) Testing the functionality and accuracy of the electronic class record system.
3) Evaluating the acceptability of the electronic class record system through surveys of teachers, finding it was rated positively and would be implemented in the upcoming school year.
IRJET- Automatic Generation of Question Paper using Blooms TaxonomyIRJET Journal
This document describes a system for automatically generating question papers from a semantically tagged question bank or repository. The system allows users like teachers to specify parameters like topic coverage, question type distribution, cognitive levels, and difficulty levels. It then generates a question paper by selecting questions from the bank that match the specified parameters. This overcomes issues with existing methods of question paper creation, which depend heavily on a teacher's expertise and experience. The automatic system could generate question papers more quickly and consistently based on learning objectives. It also helps avoid duplicating questions across multiple exams while the question bank grows over time.
Java parser a fine grained indexing tool and its applicationRoya Hosseini
1) The document discusses an intelligent tutoring system called Knowledge Maximizer (KM) that uses fine-grained modeling of programming concepts to provide personalized exam preparation for students.
2) An evaluation of KM compared to other course tutoring systems found that students using KM attempted more complex questions, had a higher success rate, and achieved greater knowledge gains.
3) An automatic tool called JavaParser was developed to index programming questions by the underlying concepts, achieving over 98% accuracy compared to manual indexing. Future work aims to improve modeling and provide more adaptive support.
This document summarizes a study on developing an expert system called WittyCat to provide dynamic assessments of student exam quality. Survey data and course materials were collected and analyzed using association rule learning. Rules generated from a pilot study provided insights that helped instructors improve their teaching. The current state of WittyCat automates rule generation and seeks to explain conclusions. Contributions from additional course data and feedback are requested to evaluate WittyCat's assessments.
"Information and intelligence are two vital columns on which development of humankind rise and knowledge has significant impact on operating of society. Student assessment is a crucial part of teaching and is done through the process of examinations and preparation of exam question papers has consistently been a matter of interest. Present day technologies assist the teacher to stock the questions in a computer databases but the problem which emerges is how the present day technologies would also assist the teachers to automatically create the variety sets of questions from every now and then without worry about replication and duplication from the previous exam while the question bank keeps growing. Ms. R. Selvapriya M.Sc. MPhil | Ganesh. K ""Automatic Question Paper Generator System"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21646.pdf
Paper URL: https://www.ijtsrd.com/computer-science/other/21646/automatic-question-paper-generator-system/ms-r-selvapriya-msc-mphil"
NagaRaju Addanki is a software developer with over 7 years of experience seeking new project opportunities. He has extensive experience developing web applications using Microsoft technologies like ASP.NET, C#, and SQL Server. Currently he works as a module lead at Value Labs in Hyderabad, India where he supports payroll projects and applications. His background includes developing academic, e-commerce, and database applications for clients.
Online Examination and Evaluation SystemIRJET Journal
This document summarizes research on existing online examination and evaluation systems. It reviews 20 papers on different approaches for objective and subjective answer evaluation, including keyword matching, cosine similarity, machine learning algorithms, and natural language processing. The papers describe systems that automate the grading of exams through online proctoring, question banks, and tools to analyze student responses against model answers. The document concludes that a comprehensive examination system is needed that incorporates proctoring, online testing, and evaluation of both subjective and objective question types.
The document describes a proposed web application for automating project management tasks at an engineering institute. The application would allow students to form groups, get project approvals, submit work, and receive feedback and evaluations. It consists of two modules - one for online project work and another to evaluate student and project progress. The goal is to streamline project activities and provide a centralized platform for communication between students and guides.
Predictive models are quasi experimental structures used to determine the future
patterns in data. These meaningful data patterns form the building block of any
decision support system. Researchers all over the world have built many prediction
models for major industries. Research works in the educational sector has increased
steeply. This steep increase may be due to the high availability of data in the
educational domain. This survey tries to comprehend a few literary works on
academic performance prediction of engineering students with the focus on grade
predictions. Meaningful interpretations have been made and inferences are presented
at the end of this paper
Predicting User Ratings of Competitive ProgrammingContests using Decision Tre...IRJET Journal
This research paper presents a decision tree machine learning model for predicting future user ratings of competitive programming contests. The model was trained on a dataset containing past contest performance and achieved an MSE of 8494 and RMSE of 92 on test data. Decision trees can handle large datasets with numerical and categorical data, and limiting depth prevents overfitting. The model effectively predicted ratings, demonstrating decision trees as a useful tool for this task.
AUTOMATIC QUESTION GENERATION USING NATURAL LANGUAGE PROCESSINGIRJET Journal
The document describes a proposed method for automatic question generation using natural language processing and T5 text-to-text transfer transformer models. The method uses T5 models trained on the Stanford Question Answering Dataset to generate questions from paragraphs of text without requiring extensive grammar rules. The proposed system aims to assist students in learning by generating questions to test their understanding from provided materials.
This document summarizes a final year defense presentation on leveraging an interactive web-based virtual classroom. The presentation outlines the introduction, aim and objectives, hypothesis, research questions, literature review, proposed model, design and development, testing and evaluation, result analysis, performance analysis, and conclusion. It discusses designing a virtual classroom to allow interactive teaching and learning between teachers and students. Testing showed the classroom was an effective environment for both learning and teaching. The presentation concludes that a virtual classroom can benefit teachers and students and hopes it will support learning and teaching in the future.
Abhilash Kumar is a final year undergraduate student studying Computer Science and Engineering at IIT Kanpur. He has achieved high grades throughout his education and received several awards and fellowships for his academic performance and programming skills. His internship experiences include open source development at Facebook and data analysis projects. He is highly experienced in programming contests and open source contributions.
This document describes a student result analysis system that was developed to automatically parse student result data from excel files into a database. It allows teachers to log in and view analysis of student results including rankings, subject performance, and passing/failing rates. The system uses PHP, MySQL, and JavaScript to fetch and display the student data. It also generates PDF reports of individual student results. The goal was to create an easier way for teachers to analyze student performance compared to manual entry of results.
This document summarizes a project to automate exam hall seating arrangements using cloud computing. The project aims to simplify the process of allocating exam halls and seats to students. Currently, seating is assigned manually requiring significant work. The proposed system will automatically generate seating arrangements and hall assignments for invigilators based on student information stored in a database. It will reduce workload and the need for manual paperwork. The system will have modules for administration, student and staff registration, room and student allocation. It will use technologies like PHP, MySQL, and be hosted on XAMPP server. Data will be stored centrally and accessible anytime through the cloud.
This document describes an online examination system developed using Java web technologies. The system allows teachers to manage questions, generate quizzes, and enable students to take online tests. It has three main components - question management for adding, modifying and deleting questions; quiz generation to randomly select questions based on set criteria; and online testing for students to self-test and view their progress. The system aims to make the examination process more efficient by automating paper generation and grading while reducing instances of cheating. It is intended to help both teachers and students by improving assessment and providing insights into learning levels.
Eric Nyberg's Presentation "From Jeopardy! To Cognitive Agents: Effective Learning in the Wild" on Cognitive Systems Institute Group Speaker Series July 9, 2015
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
-------------------------------------------------------------------------------
Find out more about ISO training and certification services
Training: ISO/IEC 27001 Information Security Management System - EN | PECB
ISO/IEC 42001 Artificial Intelligence Management System - EN | PECB
General Data Protection Regulation (GDPR) - Training Courses - EN | PECB
Webinars: https://pecb.com/webinars
Article: https://pecb.com/article
-------------------------------------------------------------------------------
For more information about PECB:
Website: https://pecb.com/
LinkedIn: https://www.linkedin.com/company/pecb/
Facebook: https://www.facebook.com/PECBInternational/
Slideshare: http://www.slideshare.net/PECBCERTIFICATION
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
How to Setup Warehouse & Location in Odoo 17 Inventory
DEPT CONF (1) (1).pptx
1. Presented by
A . Vijaya Lakshmi,
Department of Computer Science ,Pondicherry University
Co-author
Dr. K. Suresh Joseph,
Department of Computer Science ,Pondicherry University
1
International Conference on
Technology Enabled Online & Distance Learning for Education: In the Context of NEP 2020
27th & 28th October 2020
Organized by
Directorate of Distance Education & Department of Computer Science
PONDICHERRY UNIVERSITY
03-11-2022
2. Agenda
Introduction
Why question Paper Generator?
How It works!
Important Design Factors for AQPG
Method Used
Randomised Algorithm
Artificial Intelligence Based Techniques
Literature Survey
Conclusion
References
03-11-2022 2
3. Introduction
• Examination plays a crucial role in the online education system.
• It relies heavily on the production of test questions.
• Automatic Question Paper Generator is special software which is
useful to schools, Institutes, publishers and test paper setters who want
to have a huge database of questions and generate test papers
frequently with ease [1].
• It mainly deals with the gathering, sorting and administration of a
large amount of questions about different levels of toughness .
03-11-2022 3
4. Why question Paper Generator?
• A quality question paper is a real combination of questions supervised by
varied criteria such as difficulty level, distribution of marks across the
question paper in form of paper pattern and the type of examination.
• The recent dispute regarding Class X and XII question papers has raised
quite a question and the need for a proper system for question paper setters
in the field of education [2].
• The traditional setting of the paper process needs revamping and utilizing
the emerging trends in technology to stay futuristic. So, changes from a
manual process to an automated one are necessary for question paper
setting.
03-11-2022 4
5. How It works!
03-11-2022
Fig. 1. Building Blocks of AQPG
ADMIN
EXAMINER
Question
Paper
Template
Blooms
Taxonomy
QUESTION
BANK
QUESTION PAPER
GENERATOR
ALGORITHM
Insert Questions,
Taxonomy, Templates,
Maintains System
Initiate QP Generation
Question Paper
5
6. Important Design Factors for AQPG
• Distribution of cognitive levels weights based on Blooms taxonomy.
• Distribution of topic weights.
• Toughness Level of Question.
• Syllabus Coverage [3]-[5] .
• Course Outcome
03-11-2022 6
7. Algorithms used
• Many researches being conducted on automated exam questions
generator. Automated exam questions generator can be categorized
based on the algorithms that are utilized in order to generate the
questions.
• Randomised Algorithms Techniques
• AI based Algorithms
03-11-2022 7
8. Algorithms used(cont.)
Randomised Algorithms Techniques
• Randomized algorithms use random numbers to
solve problems in their logic [6] .
• The randomized Algorithm in AQPG is worked in
two ways.
• Randomized algorithms ensure question paper
without duplication and randomness
AI based Algorithms
• Researchers started to adopt artificial intelligence in
their researches to improve on the performance of
Automated Exam Questions Generator and the
quality of exam questions
• It incorporate all the aspects of the syllabus and
made fully customizable
• Ant colony algorithm, simulated annealing
algorithm ,Genetic Algorithm ,Natural Language
Processing , Ontology [7] .
03-11-2022 8
9. Literature survey
Ref. no Year Author Algorithm /Method Features
[8] 2013
Dimple V. Paul, Jyoti D.
Pawar
Evolutionary Multi-Objective
Optimisation Algorithm (EMOOA)
Topic weightage is used for calculation in the initial population, and
multiple different question paper template for the same examination is
generated by multi-objective optimisation
[9] 2013 Vaibhav M. Kale Multi constraint Algorithm
Qp format, difficulty level, and syllabus coverage are considered for QP
generation. The system is modelled as a multi-constraint optimisation
problem
[10] 2014
Ibrahim Teo, Noor
Hasimah
Abu Bakar2
Genetic Algorithm
text matching is used to set questions depending on Bloom's framework,
and the author used a Genetic algorithm for producing questions with the
optimal combination of question sequence
[11] 2014 Dimple V. Paul
Multi-objective Differential Evolution
Approach (MDEA)
MDEA executes a global parallel search by applying its operators such as
mutation, cross over and selection to produce optimal solutions
[12] 2014 Naik, Kapil Sule, S. Randomisation Algorithm
The author developed a desktop and browser-based application system to
produce qp using a shuffling randomised algorithm without duplication
and repetition.
[13] 2014 Paul, Dimple V. Evolutionary Algorithm
AQPG is modelled as a multi-constraint optimisation problem and
proposed a new modified evolutionary algorithm to produce qP with
randomness.
[14] 2017
Kiran, Fenil
Gopal, Hital2 Randomisation Algorithm
This desktop-based software produces a unique set of question papers
based on a constraints table, leading to precise output with a minimum
probability of errors.
03-11-2022 9
10. Literature survey
Ref. no Year Author Algorithm /Method Features
[15] 2018
Naglot, Deepali
Gaikwad, Seema
Keyword-based Shuffling Algorithm
The author employed a logical keyword-based shuffling approach to
producing a question paper without duplication. Keyword is used for
checking the repetition of the question
[16] 2018 Song, Wanli Genetic Algorithm
The author developed a framework that dynamically produced composite
assessment questions depending on the difficulty of the subject, curriculum
coverage, and levels of the toughness of questions.
[17] 2017
Rahim, Tengku
Nurulhuda Tengku Abd
Genetic Algorithm
Generate Qp depending on Bloom's taxonomy and cognitive level of
students utilising a genetic algorithm
[18] 2018
Aanchal Jawere, Anchal
Soni
Natural language processing
It automatically generates questions from documents. The burden of
manual question insertion in the Question bank is eliminated
[19] 2020
Mohammed, Manal
Omar, Nazlia2
Support Vector Machine (SVM), K-
Nearest Neighbour and Logistic
Regression, and
TFPOS-IDF and word2vec features are employed to extract essential
words from documents to generate questions
[20] 2022
Das, Bidyut Majumder,
Mukta
natural language processing
The author produced QP by extracting critical concepts from the
curriculum, and later depending on those concepts, various kinds of
subjective questions were generated. Finally, a multi-criteria decision-
making strategy is employed to evaluate student response.
[21] 2022
Kusuma, Selvia Ferdiana
Siahaan
knowledge ontology
The author Concentrated on creating ontology and template generation
models, which can able applicable across domains. Integrating sentence
and taxonomy ontology to produce domain independent question
framework
03-11-2022 10
11. Conclusion
• The conventional method for generating exam questions is tedious and time-consuming.
• It is difficult for educators to cover every aspect of the course content and prevent
redundancy in future assessments. And there are no defined methodologies.
• Thus the quality of the question paper and classification of question toughness levels is
entirely dependent on the competence ,knowledge and perspectives of the particular
teacher.
• This paper compares and contrasts various algorithms employed in question paper
generation; this work can be a guide for new researchers in the field of automatic question
generation.
• Future Research direction includes employing AI techniques to reclassify the category of
the question toughness based on the student-answerable ratio of questions, which in turn
will provide an adaptable and robust platform to generate question papers for various
student levels.
03-11-2022 11
12. References
[1] “Attributes of a good question paper — deccan herald.”
[2] “Cbse term i controversy: How does the central board set questionpapers? — the financial express.”
[3] L. W. Anderson and D. R. Krathwohl, A taxonomy for learning, teaching, and assessing : a revision of Bloom’s taxonomy of educational objectives. Longman, 2001.
[4] “Taxonomy of educational objectives - google books.”
[5] D. V. Paul, S. B. Naik, P. Rane, and J. Pawar, “Use of an evolutionary approach for question paper template generation,” undefined, 2012.
[6] “Randomized algorithms - google books.”
[7] A. Darwish, “Bio-inspired computing: Algorithms review, deep analysis, and the scope of applications,” Future Computing and Informatics
Journal, vol. 3, pp. 231–246, 12 2018.
[8] D. V. Paul and J. D. Pawar, “Pareto-optimal solutions for question paper template generation,” Proceedings of the 2013 International Conference on Advances in
Computing, Communications and Informatics, ICACCI 2013, pp. 747–751, 2013.
[9] V. M. Kale and A. W. Kiwelekar, “An algorithm for question paper template generation in question paper generation system,” 2013 The International Conference on
Technological Advances in Electrical, Electronics and Computer Engineering, TAEECE 2013, pp. 256–261, 2013.
[10] N. H. I. Teo, N. A. Bakar, and M. R. A. Rashid, “Representing examination question knowledge into genetic algorithm,” IEEE Global Engineering Education
Conference, EDUCON, pp. 900–904, 2014.
03-11-2022 12
13. References(cont.)..
[11] D. V. Paul and J. D. Pawar, “A multi-objective differential evolution approach for the question selection problem,” 5th International Conference on the
Applications of Digital Information and Web Technologies, ICADIWT 2014, pp. 219–225, 2014.
[12] K. Naik, S. Sule, S. Jadhav, and S. Pandey, “Automatic question paper generation system using randomization algorithm,” International Journal of Engineering
and Technical Research (IJETR), 2014.
[13] D. V. Paul, S. B. Naik, and J. D. Pawar, “An evolutionary approach for question selection from a question bank,” International Journal of ICT Research and
Development in Africa, vol. 4, pp. 61–75, 2014.
[14] F. Kiran, H. Gopal, and A. Dalvi, “Automatic question paper generator system,” International Journal of Computer Applications, vol. 166, pp. 42–47, 2017.
[15] D. Naglot, S. Gaikwad, P. Gaikwad, A. Salvi, and S. Mutyal, “Keyword based shuffling algorithm for question paper generator,” International Journal of Computer
Applications, vol. 179, pp. 36–40, 2018.
[16] W. Song, “Online test paper composition based on genetic algorithm,” springer series, vol. 160, pp. 158–161, 2018.
[17] T. N. T. A. Rahim, Z. A. Aziz, R. H. A. Rauf, and N. Shamsudin, “Automated exam question generator using genetic algorithm,” 2017 IEEE Conference on e-
Learning, e-Management and e-Services, IC3e 2017, pp. 12–17, 2018.
[18] A. Jawere, A. Soni, and N. Tejra, “Implementation of automatic question paper generator system,” The International Journal of Creative Research Thoughts
(IJCRT), pp. 1–7, 2017.
[19] M. Mohammedid and N. Omar, “Question classification based on bloom’s taxonomy cognitive domain using modified tf-idf and word2vec,” PLOS ONE, vol. 15,
p. e0230442, 2020.
[20] B. Das, M. Majumder, A. A. Sekh, and S. Phadikar, “Automatic question generation and answer assessment for subjective examination,” Cognitive Systems
Research, vol. 72, pp. 14–22, 3 2022.
[21] S. F. Kusuma, D. O. Siahaan, and C. Fatichah, “Automatic question generation with various difficulty levels based on knowledge ontology using a query
template,” Knowledge-Based Systems, vol. 249, p. 108906, 8 2022.
03-11-2022 13