This document discusses using natural language processing (NLP) tools to model students' vocabulary knowledge based on the lexical properties of their essays. The study analyzed essays from college sophomores and high school students. NLP tool TAALES was used to calculate 135 lexical indices from the essays. Correlations found that two indices accounted for 44% of the variance in sophomores' vocabulary scores, and were also predictive of high school students' scores. The results suggest NLP can inform "stealth assessments" to improve student models in computer-based learning environments.
AN AUTOMATED MULTIPLE-CHOICE QUESTION GENERATION USING NATURAL LANGUAGE PROCE...kevig
Automatic multiple-choice question generation (MCQG) is a useful yet challenging task in Natural Language
Processing (NLP). It is the task of automatic generation of correct and relevant questions from textual data.
Despite its usefulness, manually creating sizeable, meaningful and relevant questions is a time-consuming
and challenging task for teachers. In this paper, we present an NLP-based system for automatic MCQG for
Computer-Based Testing Examination (CBTE).We used NLP technique to extract keywords that are
important words in a given lesson material. To validate that the system is not perverse, five lesson materials
were used to check the effectiveness and efficiency of the system. The manually extracted keywords by the
teacher were compared to the auto-generated keywords and the result shows that the system was capable of
extracting keywords from lesson materials in setting examinable questions. This outcome is presented in a
user-friendly interface for easy accessibility.
IRJET - Analysis of Student Feedback on Faculty Teaching using Sentiment Anal...IRJET Journal
This document summarizes a research paper that analyzed student feedback on faculty teaching using sentiment analysis and natural language processing techniques. The researchers collected qualitative feedback from students on a course and preprocessed the comments by tokenizing, removing stop words, and stemming words. They then classified the sentiments using a sentiment word database and identified topics that were discussed positively or negatively. The proposed system aimed to automatically analyze unstructured student feedback to help faculty improve their teaching performance based on student opinions.
Personalization is an alternative to improve the learning process for an e-Learning environment. It is a useful strategy to adjust the student' needs based on their characteristics to make learning more effectively. In this study, we propose the step-function approach for personalization in e-learning. It provides the students with adopting the knowledge-ability factor (Novice, Average, or Good category) that matches with their learning materials levels (Level1, Level2, or Level3). The approach implemented into an e-learning which called SCELE-PDE and used as the experimental group in two stages with different scenarios. In the first, without a step-function approach, but the SCELE-PDE can identify an initial of student's ability to knowledge category. The second stage has used the approach to providing students with personalization in e-Learning to adapt learning material based on a knowledge category. As a result, the step-function approach has successfully to improve the student performance in the learning process during the course. Thus, the approach has shown an increase in the level of students’ knowledge. So, it can be used as a guide when designing an e-learning personalization for students to enhance learning and achievement.
S ENTIMENT A NALYSIS F OR M ODERN S TANDARD A RABIC A ND C OLLOQUIAlijnlc
The rise of social media such as blogs and social n
etworks has fueled interest in sentiment analysis.
With
the proliferation of reviews, ratings, recommendati
ons and other forms of online expression, online op
inion
has turned into a kind of virtual currency for busi
nesses looking to market their products, identify n
ew
opportunities and manage their reputations, therefo
re many are now looking to the field of sentiment
analysis. In this paper, we present a feature-based
sentence level approach for Arabic sentiment analy
sis.
Our approach is using Arabic idioms/saying phrases
lexicon as a key importance for improving the
detection of the sentiment polarity in Arabic sente
nces as well as a number of novels and rich set of
linguistically motivated features (contextual Inten
sifiers, contextual Shifter and negation handling),
syntactic features for conflicting phrases which en
hance the sentiment classification accuracy.
Furthermore, we introduce an automatic expandable w
ide coverage polarity lexicon of Arabic sentiment
words. The lexicon is built with gold-standard sent
iment words as a seed which is manually collected a
nd
annotated and it expands and detects the sentiment
orientation automatically of new sentiment words us
ing
synset aggregation technique and free online Arabic
lexicons and thesauruses. Our data focus on modern
standard Arabic (MSA) and Egyptian dialectal Arabic
tweets and microblogs (hotel reservation, product
reviews, etc.). The experimental results using our
resources and techniques with SVM classifier indica
te
high performance levels, with accuracies of over 95
%.
A scoring rubric for automatic short answer grading systemTELKOMNIKA JOURNAL
During the past decades, researches about automatic grading have become an interesting issue. These studies focuses on how to make machines are able to help human on assessing students’ learning outcomes. Automatic grading enables teachers to assess student's answers with more objective, consistent, and faster. Especially for essay model, it has two different types, i.e. long essay and short answer. Almost of the previous researches merely developed automatic essay grading (AEG) instead of automatic short answer grading (ASAG). This study aims to assess the sentence similarity of short answer to the questions and answers in Indonesian without any language semantic's tool. This research uses pre-processing steps consisting of case folding, tokenization, stemming, and stopword removal. The proposed approach is a scoring rubric obtained by measuring the similarity of sentences using the string-based similarity methods and the keyword matching process. The dataset used in this study consists of 7 questions, 34 alternative reference answers and 224 student’s answers. The experiment results show that the proposed approach is able to achieve a correlation value between 0.65419 up to 0.66383 at Pearson's correlation, with Mean Absolute Error (푀퐴퐸) value about 0.94994 until 1.24295. The proposed approach also leverages the correlation value and decreases the error value in each method.
A Method of Designing Student Model in Ubiquitous Environment ijujournal
Context-aware ubiquitous learning combines context-awareness with wireless and mobile technologies to
observe the situation of students in the real world and provides personalized guidance accordingly.
Student Model creates student's history logs automatically and maintains history of subject content
requested. It also offers information on student's hardware capabilities, students preferences, knowledge
level and student status. This information can be utilized to respond to new student's request from previous
similar request. A Ubiquitous student model aims to identify student’s needs, characteristics and situations.
In this paper, we have proposed a method of designing student model, that provides personalized subject
content adaptation.
Prasath P is seeking a challenging position that provides learning opportunities. He has a M.E. in Computer Science and Engineering from University College of Engineering, Trichy with a 7.1 CGPA and a B.E. in Computer Science and Engineering from Maamallan Institute of Technology, Chennai with a 7.5 CGPA. His technical skills include Python, Django, JavaScript, jQuery, MySQL, and Windows and Ubuntu. He has experience with a project involving building an intrusion detection system to evaluate trust between nodes in a mobile ad hoc network.
A new-method-of-adaptation-in-integrated-learning-environmentCemal Ardil
This document describes a new method of adaptation in a partially integrated learning environment that includes an electronic textbook and integrated tutoring system. The method establishes interconnections between operations and concepts to determine relevant educational material based on tutorial problem results. The algorithm estimates concept mastery levels, student non-mastery on textbook pages, and creates a ranked list of textbook pages for repeated study. The method was integrated into software tools to dynamically determine relevant educational content for each student step.
AN AUTOMATED MULTIPLE-CHOICE QUESTION GENERATION USING NATURAL LANGUAGE PROCE...kevig
Automatic multiple-choice question generation (MCQG) is a useful yet challenging task in Natural Language
Processing (NLP). It is the task of automatic generation of correct and relevant questions from textual data.
Despite its usefulness, manually creating sizeable, meaningful and relevant questions is a time-consuming
and challenging task for teachers. In this paper, we present an NLP-based system for automatic MCQG for
Computer-Based Testing Examination (CBTE).We used NLP technique to extract keywords that are
important words in a given lesson material. To validate that the system is not perverse, five lesson materials
were used to check the effectiveness and efficiency of the system. The manually extracted keywords by the
teacher were compared to the auto-generated keywords and the result shows that the system was capable of
extracting keywords from lesson materials in setting examinable questions. This outcome is presented in a
user-friendly interface for easy accessibility.
IRJET - Analysis of Student Feedback on Faculty Teaching using Sentiment Anal...IRJET Journal
This document summarizes a research paper that analyzed student feedback on faculty teaching using sentiment analysis and natural language processing techniques. The researchers collected qualitative feedback from students on a course and preprocessed the comments by tokenizing, removing stop words, and stemming words. They then classified the sentiments using a sentiment word database and identified topics that were discussed positively or negatively. The proposed system aimed to automatically analyze unstructured student feedback to help faculty improve their teaching performance based on student opinions.
Personalization is an alternative to improve the learning process for an e-Learning environment. It is a useful strategy to adjust the student' needs based on their characteristics to make learning more effectively. In this study, we propose the step-function approach for personalization in e-learning. It provides the students with adopting the knowledge-ability factor (Novice, Average, or Good category) that matches with their learning materials levels (Level1, Level2, or Level3). The approach implemented into an e-learning which called SCELE-PDE and used as the experimental group in two stages with different scenarios. In the first, without a step-function approach, but the SCELE-PDE can identify an initial of student's ability to knowledge category. The second stage has used the approach to providing students with personalization in e-Learning to adapt learning material based on a knowledge category. As a result, the step-function approach has successfully to improve the student performance in the learning process during the course. Thus, the approach has shown an increase in the level of students’ knowledge. So, it can be used as a guide when designing an e-learning personalization for students to enhance learning and achievement.
S ENTIMENT A NALYSIS F OR M ODERN S TANDARD A RABIC A ND C OLLOQUIAlijnlc
The rise of social media such as blogs and social n
etworks has fueled interest in sentiment analysis.
With
the proliferation of reviews, ratings, recommendati
ons and other forms of online expression, online op
inion
has turned into a kind of virtual currency for busi
nesses looking to market their products, identify n
ew
opportunities and manage their reputations, therefo
re many are now looking to the field of sentiment
analysis. In this paper, we present a feature-based
sentence level approach for Arabic sentiment analy
sis.
Our approach is using Arabic idioms/saying phrases
lexicon as a key importance for improving the
detection of the sentiment polarity in Arabic sente
nces as well as a number of novels and rich set of
linguistically motivated features (contextual Inten
sifiers, contextual Shifter and negation handling),
syntactic features for conflicting phrases which en
hance the sentiment classification accuracy.
Furthermore, we introduce an automatic expandable w
ide coverage polarity lexicon of Arabic sentiment
words. The lexicon is built with gold-standard sent
iment words as a seed which is manually collected a
nd
annotated and it expands and detects the sentiment
orientation automatically of new sentiment words us
ing
synset aggregation technique and free online Arabic
lexicons and thesauruses. Our data focus on modern
standard Arabic (MSA) and Egyptian dialectal Arabic
tweets and microblogs (hotel reservation, product
reviews, etc.). The experimental results using our
resources and techniques with SVM classifier indica
te
high performance levels, with accuracies of over 95
%.
A scoring rubric for automatic short answer grading systemTELKOMNIKA JOURNAL
During the past decades, researches about automatic grading have become an interesting issue. These studies focuses on how to make machines are able to help human on assessing students’ learning outcomes. Automatic grading enables teachers to assess student's answers with more objective, consistent, and faster. Especially for essay model, it has two different types, i.e. long essay and short answer. Almost of the previous researches merely developed automatic essay grading (AEG) instead of automatic short answer grading (ASAG). This study aims to assess the sentence similarity of short answer to the questions and answers in Indonesian without any language semantic's tool. This research uses pre-processing steps consisting of case folding, tokenization, stemming, and stopword removal. The proposed approach is a scoring rubric obtained by measuring the similarity of sentences using the string-based similarity methods and the keyword matching process. The dataset used in this study consists of 7 questions, 34 alternative reference answers and 224 student’s answers. The experiment results show that the proposed approach is able to achieve a correlation value between 0.65419 up to 0.66383 at Pearson's correlation, with Mean Absolute Error (푀퐴퐸) value about 0.94994 until 1.24295. The proposed approach also leverages the correlation value and decreases the error value in each method.
A Method of Designing Student Model in Ubiquitous Environment ijujournal
Context-aware ubiquitous learning combines context-awareness with wireless and mobile technologies to
observe the situation of students in the real world and provides personalized guidance accordingly.
Student Model creates student's history logs automatically and maintains history of subject content
requested. It also offers information on student's hardware capabilities, students preferences, knowledge
level and student status. This information can be utilized to respond to new student's request from previous
similar request. A Ubiquitous student model aims to identify student’s needs, characteristics and situations.
In this paper, we have proposed a method of designing student model, that provides personalized subject
content adaptation.
Prasath P is seeking a challenging position that provides learning opportunities. He has a M.E. in Computer Science and Engineering from University College of Engineering, Trichy with a 7.1 CGPA and a B.E. in Computer Science and Engineering from Maamallan Institute of Technology, Chennai with a 7.5 CGPA. His technical skills include Python, Django, JavaScript, jQuery, MySQL, and Windows and Ubuntu. He has experience with a project involving building an intrusion detection system to evaluate trust between nodes in a mobile ad hoc network.
A new-method-of-adaptation-in-integrated-learning-environmentCemal Ardil
This document describes a new method of adaptation in a partially integrated learning environment that includes an electronic textbook and integrated tutoring system. The method establishes interconnections between operations and concepts to determine relevant educational material based on tutorial problem results. The algorithm estimates concept mastery levels, student non-mastery on textbook pages, and creates a ranked list of textbook pages for repeated study. The method was integrated into software tools to dynamically determine relevant educational content for each student step.
Study Support and Feedback System Using Natural Language ProcessingIRJET Journal
The document discusses developing a study support and feedback system using natural language processing (NLP). It would analyze student responses to structured essay questions through NLP techniques like keyword extraction and ontology mapping. This would allow the system to accurately assess responses and provide personalized feedback to students. The document outlines the methodology, including collecting a dataset of past questions and answers, preprocessing the data, developing NLP and machine learning algorithms to evaluate responses and generate feedback, and evaluating the system's effectiveness. The goal is to enhance the learning experience and provide a more efficient way for teachers to give feedback.
A hybrid composite features based sentence level sentiment analyzerIAESIJAI
Current lexica and machine learning based sentiment analysis approaches
still suffer from a two-fold limitation. First, manual lexicon construction and
machine training is time consuming and error-prone. Second, the
prediction’s accuracy entails sentences and their corresponding training text
should fall under the same domain. In this article, we experimentally
evaluate four sentiment classifiers, namely support vector machines (SVMs),
Naive Bayes (NB), logistic regression (LR) and random forest (RF). We
quantify the quality of each of these models using three real-world datasets
that comprise 50,000 movie reviews, 10,662 sentences, and 300 generic
movie reviews. Specifically, we study the impact of a variety of natural
language processing (NLP) pipelines on the quality of the predicted
sentiment orientations. Additionally, we measure the impact of incorporating
lexical semantic knowledge captured by WordNet on expanding original
words in sentences. Findings demonstrate that the utilizing different NLP
pipelines and semantic relationships impacts the quality of the sentiment
analyzers. In particular, results indicate that coupling lemmatization and
knowledge-based n-gram features proved to produce higher accuracy results.
With this coupling, the accuracy of the SVM classifier has improved to
90.43%, while it was 86.83%, 90.11%, 86.20%, respectively using the three
other classifiers.
Identifying e learner’s opinion using automated sentiment analysis in e-learningeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
A COMPREHENSIVE STUDY FOR IDENTIFICATION OF FAST AND SLOW LEARNERS USING MACH...IRJET Journal
This document presents a study that uses machine learning models to classify students as fast, slow, or average learners based on their academic performance and study habits. Five machine learning models (logistic regression, decision tree, random forest, support vector machine, and K-nearest neighbors) were trained and evaluated on a dataset of 1000 students. The support vector machine model achieved the highest accuracy of 97% at classifying learners. The results indicate that machine learning can effectively identify different learner types and provide insights to help educators tailor their teaching approaches to better support all students.
Applying adaptive learning by integrating semantic and machine learning in p...IJECEIAES
Adaptive learning is one of the most widely used data driven approach to teaching and it received an increasing attention over the last decade. It aims to meet the student’s characteristics by tailoring learning courses materials and assessment methods. In order to determine the student’s characteristics, we need to detect their learning styles according to visual, auditory or kinaesthetic (VAK) learning style. In this research, an integrated model that utilizes both semantic and machine learning clustering methods is developed in order to cluster students to detect their learning styles and recommend suitable assessment method(s) accordingly. In order to measure the effectiveness of the proposed model, a set of experiments were conducted on real dataset (Open University Learning Analytics Dataset). Experiments showed that the proposed model is able to cluster students according to their different learning activities with an accuracy that exceeds 95% and predict their relative assessment method(s) with an average accuracy equals to 93%.
IRJET- Automated Essay Evaluation using Natural Language ProcessingIRJET Journal
This document discusses research on automated essay evaluation using natural language processing. It provides background on previous systems for automated essay scoring like Project Essay Grader (PEG) from the 1960s and more recent systems like e-Rater, IntelliMetric, and Intelligent Essay Assessors. The researchers extracted features from essays like word count, sentence count, spelling, and part-of-speech to train machine learning models. They achieved correlation scores between 0.86-0.87 when comparing predicted scores to human scores, showing the models can perform at similar reliability levels to human graders. The researchers conclude the models could be improved by incorporating features like parse trees and accounting for different essay prompts.
E Assessment Presentation Ver2 June 2008Jo Richler
The document discusses the history and types of assessment including diagnostic, formative, and summative assessment. It then discusses guidelines for e-assessment including ensuring students have experience with the exam format and technology prior to summative exams. The document also discusses advantages of e-assessment such as richer assessment experience through multimedia, increased flexibility, and instant feedback.
STUDENTS’PATTERNS OF INTERACTION WITH A MATHEMATICS INTELLIGENT TUTOR:LEARNIN...IJITE
Purpose: The purpose of this paper is to determine potential identifiers of students’ academic success in
foundation mathematics course by analyzing the data logs of an intelligent tutor.
Design/ methodology/approach: A cross-sectional study design was used. A sample of 58 records was
extracted from the data-logs of the intelligent tutor, ALEKS. This data was triangulated with the data
collected from surveys. Two-step clustering, correlation and regression analysis, Chi-square analysis and
paired sample t-tests were applied to address the research questions.
Findings: The data-logs of ALEKS include information about number of topics practiced and number of
topics mastered by each student. Prior knowledge and derived attribute, which is the ratio of number of
topics mastered to number of topics practiced(denoted by the variable m top in this paper) are found to be
predictors of final marks in the foundation mathematics course with
= 42%.
Students were asked to report their preferred way of selecting topics as either sequential or random.
Results of paired sample t-test demonstrated that the students who selected topics in a sequential manner
were able to retain their mastery of learning after the summative assessment whereas the students who
chose topics randomly were not able to retain their mastery of learning.
Originality and value: This research has established three indicators of academic success in the course of
foundation mathematics which is delivered using the intelligent tutor ALEKS. Instructors can monitor
students’ progress and detect students at-risk who are not able to attain desired pace of learning and guide
them to choose the correct sequence of topics.
STUDENTS’PATTERNS OF INTERACTION WITH A MATHEMATICS INTELLIGENT TUTOR:LEARNIN...IJITE
Purpose: The purpose of this paper is to determine potential identifiers of students’ academic success in
foundation mathematics course by analyzing the data logs of an intelligent tutor.
Design/ methodology/approach: A cross-sectional study design was used. A sample of 58 records was
extracted from the data-logs of the intelligent tutor, ALEKS. This data was triangulated with the data
collected from surveys. Two-step clustering, correlation and regression analysis, Chi-square analysis and
paired sample t-tests were applied to address the research questions.
Findings: The data-logs of ALEKS include information about number of topics practiced and number of
topics mastered by each student. Prior knowledge and derived attribute, which is the ratio of number of
topics mastered to number of topics practiced(denoted by the variable m top in this paper) are found to be
predictors of final marks in the foundation mathematics course with
= 42%.
Students were asked to report their preferred way of selecting topics as either sequential or random.
Results of paired sample t-test demonstrated that the students who selected topics in a sequential manner
were able to retain their mastery of learning after the summative assessment whereas the students who
chose topics randomly were not able to retain their mastery of learning.
Originality and value: This research has established three indicators of academic success in the course of
foundation mathematics which is delivered using the intelligent tutor ALEKS. Instructors can monitor
students’ progress and detect students at-risk who are not able to attain desired pace of learning and guide
them to choose the correct sequence of topics.
Student's Patterns of Interaction with a Mathematics Intelligent Tutor: Learn...IJITE
Purpose: The purpose of this paper is to determine potential identifiers of students’ academic success in foundation mathematics course by analyzing the data logs of an intelligent tutor.
Design/ methodology/approach: A cross-sectional study design was used. A sample of 58 records was extracted from the data-logs of the intelligent tutor, ALEKS. This data was triangulated with the data collected from surveys. Two-step clustering, correlation and regression analysis, Chi-square analysis and paired sample t-tests were applied to address the research questions.
Findings: The data-logs of ALEKS include information about number of topics practiced and number of topics mastered by each student. Prior knowledge and derived attribute, which is the ratio of number of topics mastered to number of topics practiced(denoted by the variable m top in this paper) are found to be predictors of final marks in the foundation mathematics course with = 42%.
Students were asked to report their preferred way of selecting topics as either sequential or random. Results of paired sample t-test demonstrated that the students who selected topics in a sequential manner were able to retain their mastery of learning after the summative assessment whereas the students who chose topics randomly were not able to retain their mastery of learning.
Originality and value: This research has established three indicators of academic success in the course of foundation mathematics which is delivered using the intelligent tutor ALEKS. Instructors can monitor students’ progress and detect students at-risk who are not able to attain desired pace of learning and guide them to choose the correct sequence of topics.
Student's Patterns of Interaction with a Mathematics Intelligent Tutor: Learn...IJITE
Purpose: The purpose of this paper is to determine potential identifiers of students’ academic success in
foundation mathematics course by analyzing the data logs of an intelligent tutor.
Design/ methodology/approach: A cross-sectional study design was used. A sample of 58 records was
extracted from the data-logs of the intelligent tutor, ALEKS. This data was triangulated with the data
collected from surveys. Two-step clustering, correlation and regression analysis, Chi-square analysis and
paired sample t-tests were applied to address the research questions.
Findings: The data-logs of ALEKS include information about number of topics practiced and number of
topics mastered by each student. Prior knowledge and derived attribute, which is the ratio of number of
topics mastered to number of topics practiced(denoted by the variable m top in this paper) are found to be
predictors of final marks in the foundation mathematics course with
= 42%.
Students were asked to report their preferred way of selecting topics as either sequential or random.
Results of paired sample t-test demonstrated that the students who selected topics in a sequential manner
were able to retain their mastery of learning after the summative assessment whereas the students who
chose topics randomly were not able to retain their mastery of learning.
Originality and value: This research has established three indicators of academic success in the course of
foundation mathematics which is delivered using the intelligent tutor ALEKS. Instructors can monitor
students’ progress and detect students at-risk who are not able to attain desired pace of learning and guide
them to choose the correct sequence of topics.
Semi Automated Text Categorization Using Demonstration Based Term SetIJCSEA Journal
Manual Analysis of huge amount of textual data requires a tremendous amount of processing time and effort in reading the text and organizing them in required format. In the current scenario, the major problem is with text categorization because of the high dimensionality of feature space. Now-a-days there are many methods available to deal with text feature selection. This paper aims at such semi automated text categorization feature selection methodology to deal with a massive data using one of the phases of David Merrill’s First principles of instruction (FPI). It uses a pre-defined category group by providing them with the proper training set based on the demonstration phase of FPI. The methodology involves the text tokenization, text categorization and text analysis.
CLASSIFICATION OF QUESTIONS AND LEARNING OUTCOME STATEMENTS (LOS) INTO BLOOM’...IJMIT JOURNAL
Bloom’s Taxonomy (BT) have been used to classify the objectives of learning outcome by dividing the
learning into three different domains; the cognitive domain, the effective domain and the psychomotor
domain. In this paper, we are introducing a new approach to classify the questions and learning outcome
statements (LOS) into Blooms taxonomy (BT) and to verify BT verb lists, which are being cited and used by
academicians to write questions and (LOS). An experiment was designed to investigate the semantic
relationship between the action verbs used in both questions and LOS to obtain more accurate
classification of the levels of BT. A sample of 775 different action verbs collected from different universities
allows us to measure an accurate and clear-cut cognitive level for the action verb. It is worth mentioning
that natural language processing techniques were used to develop our rules as to induce the questions into
chunks in order to extract the action verbs. Our proposed solution was able to classify the action verb into
a precise level of the cognitive domain. We, on our side, have tested and evaluated our proposed solution
using confusion matrix. The results of evaluation tests yielded 97% for the macro average of precision and
90% for F1. Thus, the outcome of the research suggests that it is crucial to analyse and verify the action
verbs cited and used by academicians to write LOS and classify their questions based on blooms taxonomy
in order to obtain a definite and more accurate classification.
CLASSIFICATION OF QUESTIONS AND LEARNING OUTCOME STATEMENTS (LOS) INTO BLOOM’...IJMIT JOURNAL
Bloom’s Taxonomy (BT) have been used to classify the objectives of learning outcome by dividing the learning into three different domains; the cognitive domain, the effective domain and the psychomotor domain. In this paper, we are introducing a new approach to classify the questions and learning outcome
statements (LOS) into Blooms taxonomy (BT) and to verify BT verb lists, which are being cited and used by academicians to write questions and (LOS). An experiment was designed to investigate the semantic relationship between the action verbs used in both questions and LOS to obtain more accurate
classification of the levels of BT. A sample of 775 different action verbs collected from different universities allows us to measure an accurate and clear-cut cognitive level for the action verb. It is worth mentioning that natural language processing techniques were used to develop our rules as to induce the questions into
chunks in order to extract the action verbs. Our proposed solution was able to classify the action verb into a precise level of the cognitive domain. We, on our side, have tested and evaluated our proposed solution using confusion matrix. The results of evaluation tests yielded 97% for the macro average of precision and 90% for F1. Thus, the outcome of the research suggests that it is crucial to analyse and verify the action
verbs cited and used by academicians to write LOS and classify their questions based on blooms taxonomy in order to obtain a definite and more accurate classification.
LEMON : THE LEARNING EFFICIENCY COMPUTATION MODEL FOR ASSESSING LEARNER CONTE...IJITE
Current E-learning systems are focusing on providing learning solutions depending upon the context of the
learner. Efforts have been put in the delivery of contents, learning path and support based on the learner
context. As the learner’s context serves as base for triggering adaptation of learning solutions, a clear
understanding and an accurate definition of learner context is necessary. Different perspectives of context
have been discussed in literature. In this paper a different perspective for defining learner context is
employed and a feature viz. Learning Efficiency that consolidates the learner context has been arrived. The
different elements that constitute Learning efficiency have been identified using which a computational
model of Learning Efficiency called LEMOn has been proposed in order to quantify the learner context.
The model has been subjected to statistical evaluation in order to check for its correctness and was found
to represent the learner context efficiently.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
This document summarizes a study that used a back-propagation neural network to estimate students' word recognition abilities based on their performance on a vocabulary test. The study collected test results from 83 elementary school students and used their scores on different word frequency groups as input for the neural network model. The model was trained and tested, showing high correlation between estimated and actual vocabulary volumes. The results demonstrated that a back-propagation neural network can accurately estimate word recognition and could be an effective alternative to traditional statistical methods.
IRJET- Sentimental Analysis for Students’ Feedback using Machine Learning App...IRJET Journal
This document discusses using machine learning approaches to perform sentiment analysis on students' feedback. Specifically, it proposes using a random forest classifier to analyze descriptive feedback collected through an online student portal and classify it as having positive, negative, or neutral sentiment. The proposed system would collect real-time feedback, preprocess it by removing stop words and tagging parts of speech, extract sentiment-related features, and use the trained random forest model to classify unseen feedback with 90% accuracy. The goal is to more accurately analyze both objective and descriptive feedback to evaluate teacher performance.
Mc collum, dixie effects of a speech to-text software nfsej v25 n1 2014William Kritsonis
NATIONAL FORUM JOURNALS are a group of national and international refereed, blind-reviewed academic journals. NFJ publishes articles academic intellectual diversity, multicultural issues, management, business, administration, issues focusing on colleges, universities, and schools, all aspects of schooling, special education, counseling and addiction, international issues of education, organizational behavior, theory and development, and much more. DR. WILLIAM ALLAN KRITSONIS is Editor-in-Chief (Since 1982). See: www.nationalforum.com
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
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Study Support and Feedback System Using Natural Language ProcessingIRJET Journal
The document discusses developing a study support and feedback system using natural language processing (NLP). It would analyze student responses to structured essay questions through NLP techniques like keyword extraction and ontology mapping. This would allow the system to accurately assess responses and provide personalized feedback to students. The document outlines the methodology, including collecting a dataset of past questions and answers, preprocessing the data, developing NLP and machine learning algorithms to evaluate responses and generate feedback, and evaluating the system's effectiveness. The goal is to enhance the learning experience and provide a more efficient way for teachers to give feedback.
A hybrid composite features based sentence level sentiment analyzerIAESIJAI
Current lexica and machine learning based sentiment analysis approaches
still suffer from a two-fold limitation. First, manual lexicon construction and
machine training is time consuming and error-prone. Second, the
prediction’s accuracy entails sentences and their corresponding training text
should fall under the same domain. In this article, we experimentally
evaluate four sentiment classifiers, namely support vector machines (SVMs),
Naive Bayes (NB), logistic regression (LR) and random forest (RF). We
quantify the quality of each of these models using three real-world datasets
that comprise 50,000 movie reviews, 10,662 sentences, and 300 generic
movie reviews. Specifically, we study the impact of a variety of natural
language processing (NLP) pipelines on the quality of the predicted
sentiment orientations. Additionally, we measure the impact of incorporating
lexical semantic knowledge captured by WordNet on expanding original
words in sentences. Findings demonstrate that the utilizing different NLP
pipelines and semantic relationships impacts the quality of the sentiment
analyzers. In particular, results indicate that coupling lemmatization and
knowledge-based n-gram features proved to produce higher accuracy results.
With this coupling, the accuracy of the SVM classifier has improved to
90.43%, while it was 86.83%, 90.11%, 86.20%, respectively using the three
other classifiers.
Identifying e learner’s opinion using automated sentiment analysis in e-learningeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
A COMPREHENSIVE STUDY FOR IDENTIFICATION OF FAST AND SLOW LEARNERS USING MACH...IRJET Journal
This document presents a study that uses machine learning models to classify students as fast, slow, or average learners based on their academic performance and study habits. Five machine learning models (logistic regression, decision tree, random forest, support vector machine, and K-nearest neighbors) were trained and evaluated on a dataset of 1000 students. The support vector machine model achieved the highest accuracy of 97% at classifying learners. The results indicate that machine learning can effectively identify different learner types and provide insights to help educators tailor their teaching approaches to better support all students.
Applying adaptive learning by integrating semantic and machine learning in p...IJECEIAES
Adaptive learning is one of the most widely used data driven approach to teaching and it received an increasing attention over the last decade. It aims to meet the student’s characteristics by tailoring learning courses materials and assessment methods. In order to determine the student’s characteristics, we need to detect their learning styles according to visual, auditory or kinaesthetic (VAK) learning style. In this research, an integrated model that utilizes both semantic and machine learning clustering methods is developed in order to cluster students to detect their learning styles and recommend suitable assessment method(s) accordingly. In order to measure the effectiveness of the proposed model, a set of experiments were conducted on real dataset (Open University Learning Analytics Dataset). Experiments showed that the proposed model is able to cluster students according to their different learning activities with an accuracy that exceeds 95% and predict their relative assessment method(s) with an average accuracy equals to 93%.
IRJET- Automated Essay Evaluation using Natural Language ProcessingIRJET Journal
This document discusses research on automated essay evaluation using natural language processing. It provides background on previous systems for automated essay scoring like Project Essay Grader (PEG) from the 1960s and more recent systems like e-Rater, IntelliMetric, and Intelligent Essay Assessors. The researchers extracted features from essays like word count, sentence count, spelling, and part-of-speech to train machine learning models. They achieved correlation scores between 0.86-0.87 when comparing predicted scores to human scores, showing the models can perform at similar reliability levels to human graders. The researchers conclude the models could be improved by incorporating features like parse trees and accounting for different essay prompts.
E Assessment Presentation Ver2 June 2008Jo Richler
The document discusses the history and types of assessment including diagnostic, formative, and summative assessment. It then discusses guidelines for e-assessment including ensuring students have experience with the exam format and technology prior to summative exams. The document also discusses advantages of e-assessment such as richer assessment experience through multimedia, increased flexibility, and instant feedback.
STUDENTS’PATTERNS OF INTERACTION WITH A MATHEMATICS INTELLIGENT TUTOR:LEARNIN...IJITE
Purpose: The purpose of this paper is to determine potential identifiers of students’ academic success in
foundation mathematics course by analyzing the data logs of an intelligent tutor.
Design/ methodology/approach: A cross-sectional study design was used. A sample of 58 records was
extracted from the data-logs of the intelligent tutor, ALEKS. This data was triangulated with the data
collected from surveys. Two-step clustering, correlation and regression analysis, Chi-square analysis and
paired sample t-tests were applied to address the research questions.
Findings: The data-logs of ALEKS include information about number of topics practiced and number of
topics mastered by each student. Prior knowledge and derived attribute, which is the ratio of number of
topics mastered to number of topics practiced(denoted by the variable m top in this paper) are found to be
predictors of final marks in the foundation mathematics course with
= 42%.
Students were asked to report their preferred way of selecting topics as either sequential or random.
Results of paired sample t-test demonstrated that the students who selected topics in a sequential manner
were able to retain their mastery of learning after the summative assessment whereas the students who
chose topics randomly were not able to retain their mastery of learning.
Originality and value: This research has established three indicators of academic success in the course of
foundation mathematics which is delivered using the intelligent tutor ALEKS. Instructors can monitor
students’ progress and detect students at-risk who are not able to attain desired pace of learning and guide
them to choose the correct sequence of topics.
STUDENTS’PATTERNS OF INTERACTION WITH A MATHEMATICS INTELLIGENT TUTOR:LEARNIN...IJITE
Purpose: The purpose of this paper is to determine potential identifiers of students’ academic success in
foundation mathematics course by analyzing the data logs of an intelligent tutor.
Design/ methodology/approach: A cross-sectional study design was used. A sample of 58 records was
extracted from the data-logs of the intelligent tutor, ALEKS. This data was triangulated with the data
collected from surveys. Two-step clustering, correlation and regression analysis, Chi-square analysis and
paired sample t-tests were applied to address the research questions.
Findings: The data-logs of ALEKS include information about number of topics practiced and number of
topics mastered by each student. Prior knowledge and derived attribute, which is the ratio of number of
topics mastered to number of topics practiced(denoted by the variable m top in this paper) are found to be
predictors of final marks in the foundation mathematics course with
= 42%.
Students were asked to report their preferred way of selecting topics as either sequential or random.
Results of paired sample t-test demonstrated that the students who selected topics in a sequential manner
were able to retain their mastery of learning after the summative assessment whereas the students who
chose topics randomly were not able to retain their mastery of learning.
Originality and value: This research has established three indicators of academic success in the course of
foundation mathematics which is delivered using the intelligent tutor ALEKS. Instructors can monitor
students’ progress and detect students at-risk who are not able to attain desired pace of learning and guide
them to choose the correct sequence of topics.
Student's Patterns of Interaction with a Mathematics Intelligent Tutor: Learn...IJITE
Purpose: The purpose of this paper is to determine potential identifiers of students’ academic success in foundation mathematics course by analyzing the data logs of an intelligent tutor.
Design/ methodology/approach: A cross-sectional study design was used. A sample of 58 records was extracted from the data-logs of the intelligent tutor, ALEKS. This data was triangulated with the data collected from surveys. Two-step clustering, correlation and regression analysis, Chi-square analysis and paired sample t-tests were applied to address the research questions.
Findings: The data-logs of ALEKS include information about number of topics practiced and number of topics mastered by each student. Prior knowledge and derived attribute, which is the ratio of number of topics mastered to number of topics practiced(denoted by the variable m top in this paper) are found to be predictors of final marks in the foundation mathematics course with = 42%.
Students were asked to report their preferred way of selecting topics as either sequential or random. Results of paired sample t-test demonstrated that the students who selected topics in a sequential manner were able to retain their mastery of learning after the summative assessment whereas the students who chose topics randomly were not able to retain their mastery of learning.
Originality and value: This research has established three indicators of academic success in the course of foundation mathematics which is delivered using the intelligent tutor ALEKS. Instructors can monitor students’ progress and detect students at-risk who are not able to attain desired pace of learning and guide them to choose the correct sequence of topics.
Student's Patterns of Interaction with a Mathematics Intelligent Tutor: Learn...IJITE
Purpose: The purpose of this paper is to determine potential identifiers of students’ academic success in
foundation mathematics course by analyzing the data logs of an intelligent tutor.
Design/ methodology/approach: A cross-sectional study design was used. A sample of 58 records was
extracted from the data-logs of the intelligent tutor, ALEKS. This data was triangulated with the data
collected from surveys. Two-step clustering, correlation and regression analysis, Chi-square analysis and
paired sample t-tests were applied to address the research questions.
Findings: The data-logs of ALEKS include information about number of topics practiced and number of
topics mastered by each student. Prior knowledge and derived attribute, which is the ratio of number of
topics mastered to number of topics practiced(denoted by the variable m top in this paper) are found to be
predictors of final marks in the foundation mathematics course with
= 42%.
Students were asked to report their preferred way of selecting topics as either sequential or random.
Results of paired sample t-test demonstrated that the students who selected topics in a sequential manner
were able to retain their mastery of learning after the summative assessment whereas the students who
chose topics randomly were not able to retain their mastery of learning.
Originality and value: This research has established three indicators of academic success in the course of
foundation mathematics which is delivered using the intelligent tutor ALEKS. Instructors can monitor
students’ progress and detect students at-risk who are not able to attain desired pace of learning and guide
them to choose the correct sequence of topics.
Semi Automated Text Categorization Using Demonstration Based Term SetIJCSEA Journal
Manual Analysis of huge amount of textual data requires a tremendous amount of processing time and effort in reading the text and organizing them in required format. In the current scenario, the major problem is with text categorization because of the high dimensionality of feature space. Now-a-days there are many methods available to deal with text feature selection. This paper aims at such semi automated text categorization feature selection methodology to deal with a massive data using one of the phases of David Merrill’s First principles of instruction (FPI). It uses a pre-defined category group by providing them with the proper training set based on the demonstration phase of FPI. The methodology involves the text tokenization, text categorization and text analysis.
CLASSIFICATION OF QUESTIONS AND LEARNING OUTCOME STATEMENTS (LOS) INTO BLOOM’...IJMIT JOURNAL
Bloom’s Taxonomy (BT) have been used to classify the objectives of learning outcome by dividing the
learning into three different domains; the cognitive domain, the effective domain and the psychomotor
domain. In this paper, we are introducing a new approach to classify the questions and learning outcome
statements (LOS) into Blooms taxonomy (BT) and to verify BT verb lists, which are being cited and used by
academicians to write questions and (LOS). An experiment was designed to investigate the semantic
relationship between the action verbs used in both questions and LOS to obtain more accurate
classification of the levels of BT. A sample of 775 different action verbs collected from different universities
allows us to measure an accurate and clear-cut cognitive level for the action verb. It is worth mentioning
that natural language processing techniques were used to develop our rules as to induce the questions into
chunks in order to extract the action verbs. Our proposed solution was able to classify the action verb into
a precise level of the cognitive domain. We, on our side, have tested and evaluated our proposed solution
using confusion matrix. The results of evaluation tests yielded 97% for the macro average of precision and
90% for F1. Thus, the outcome of the research suggests that it is crucial to analyse and verify the action
verbs cited and used by academicians to write LOS and classify their questions based on blooms taxonomy
in order to obtain a definite and more accurate classification.
CLASSIFICATION OF QUESTIONS AND LEARNING OUTCOME STATEMENTS (LOS) INTO BLOOM’...IJMIT JOURNAL
Bloom’s Taxonomy (BT) have been used to classify the objectives of learning outcome by dividing the learning into three different domains; the cognitive domain, the effective domain and the psychomotor domain. In this paper, we are introducing a new approach to classify the questions and learning outcome
statements (LOS) into Blooms taxonomy (BT) and to verify BT verb lists, which are being cited and used by academicians to write questions and (LOS). An experiment was designed to investigate the semantic relationship between the action verbs used in both questions and LOS to obtain more accurate
classification of the levels of BT. A sample of 775 different action verbs collected from different universities allows us to measure an accurate and clear-cut cognitive level for the action verb. It is worth mentioning that natural language processing techniques were used to develop our rules as to induce the questions into
chunks in order to extract the action verbs. Our proposed solution was able to classify the action verb into a precise level of the cognitive domain. We, on our side, have tested and evaluated our proposed solution using confusion matrix. The results of evaluation tests yielded 97% for the macro average of precision and 90% for F1. Thus, the outcome of the research suggests that it is crucial to analyse and verify the action
verbs cited and used by academicians to write LOS and classify their questions based on blooms taxonomy in order to obtain a definite and more accurate classification.
LEMON : THE LEARNING EFFICIENCY COMPUTATION MODEL FOR ASSESSING LEARNER CONTE...IJITE
Current E-learning systems are focusing on providing learning solutions depending upon the context of the
learner. Efforts have been put in the delivery of contents, learning path and support based on the learner
context. As the learner’s context serves as base for triggering adaptation of learning solutions, a clear
understanding and an accurate definition of learner context is necessary. Different perspectives of context
have been discussed in literature. In this paper a different perspective for defining learner context is
employed and a feature viz. Learning Efficiency that consolidates the learner context has been arrived. The
different elements that constitute Learning efficiency have been identified using which a computational
model of Learning Efficiency called LEMOn has been proposed in order to quantify the learner context.
The model has been subjected to statistical evaluation in order to check for its correctness and was found
to represent the learner context efficiently.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
This document summarizes a study that used a back-propagation neural network to estimate students' word recognition abilities based on their performance on a vocabulary test. The study collected test results from 83 elementary school students and used their scores on different word frequency groups as input for the neural network model. The model was trained and tested, showing high correlation between estimated and actual vocabulary volumes. The results demonstrated that a back-propagation neural network can accurately estimate word recognition and could be an effective alternative to traditional statistical methods.
IRJET- Sentimental Analysis for Students’ Feedback using Machine Learning App...IRJET Journal
This document discusses using machine learning approaches to perform sentiment analysis on students' feedback. Specifically, it proposes using a random forest classifier to analyze descriptive feedback collected through an online student portal and classify it as having positive, negative, or neutral sentiment. The proposed system would collect real-time feedback, preprocess it by removing stop words and tagging parts of speech, extract sentiment-related features, and use the trained random forest model to classify unseen feedback with 90% accuracy. The goal is to more accurately analyze both objective and descriptive feedback to evaluate teacher performance.
Mc collum, dixie effects of a speech to-text software nfsej v25 n1 2014William Kritsonis
NATIONAL FORUM JOURNALS are a group of national and international refereed, blind-reviewed academic journals. NFJ publishes articles academic intellectual diversity, multicultural issues, management, business, administration, issues focusing on colleges, universities, and schools, all aspects of schooling, special education, counseling and addiction, international issues of education, organizational behavior, theory and development, and much more. DR. WILLIAM ALLAN KRITSONIS is Editor-in-Chief (Since 1982). See: www.nationalforum.com
Similar to IRJET- Modeling Student’s Vocabulary Knowledge with Natural (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.