CLASSIFICATION OF QUESTIONS AND LEARNING OUTCOME STATEMENTS (LOS) INTO BLOOM’S TAXONOMY (BT) BY SIMILARITY MEASUREMENTS TOWARDS EXTRACTING OF LEARNING OUTCOME FROM LEARNING MATERIAL
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.
Decision-Making Model for Student Assessment by Unifying Numerical and Lingui...IJECEIAES
Learning assessment deals with the process of making a decision on the quality or performance of student achievement in a number of competency standards. In the process, teacher’s preferences are provided through both test and non-test, generally in a numeric value, from which the final results are then converted into letters or linguistic value. In the proposed model, linguistic variables are exploited as a form of teacher’s preferences in nontest techniques. Consequently, the assessment data set will consist of numerical and linguistic information, so it requires a method to unify them to obtain the final value. A model that uses the 2-tuple linguistic approach and based on matrix operations is proposed to solve the problem. This study proposed a new procedure that consists of four stages: preprocessing, transformation, aggregation and exploitation. The final result is presented in 2-tuple linguistic representation and its equivalent number, accompanied by a description of the achievement of each competency. The α value of 2-tuple linguistic in the final result and in the description of each competency becomes meaningful information that can be interpreted as a comparative ability one student has related to other students, and shows how much potential is achieved to reach higher ranks. The proposed model contributes to enrich the learning assessment techniques, since the exploitation of linguistic variable as representation preferences provides flexible space for teachers in their assessments. Moreover, using the result with respect to students’ levels of each competency, students’ mastery of each attribute can be diagnosed and their progress of learning can be estimated.
CONCEPTUAL APPROACH AND SOLVING WORD PROBLEM INVOLVING MULTIPLICATION OF WHOL...WayneRavi
This study was conducted to determine the effect of conceptual approach on solving word problems involving multiplication of whole numbers as well as addition and subtraction. The study was carried out in Tambongon Elementary School to Fourty-one Grade Two students. Descriptive statistics (mean & SD), paired-sample T-test and ETA2 were used as tools in the analysis of data. Results revealed that there was a significant difference on the pretest and post test scores of conceptual approach. Further, conceptual approach has large effect.
A Study on Learning Factor Analysis – An Educational Data Mining Technique fo...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
In the discovery with models method identification relationships among students behaviors and characteristics or contextual variables are key applications.
At the Social Simulation and Serious Games special track at ESSA 2014, Setsuya Kurahashi gave this talk on the effects of different kinds of collaborative learning on different kinds of school classes.
Decision-Making Model for Student Assessment by Unifying Numerical and Lingui...IJECEIAES
Learning assessment deals with the process of making a decision on the quality or performance of student achievement in a number of competency standards. In the process, teacher’s preferences are provided through both test and non-test, generally in a numeric value, from which the final results are then converted into letters or linguistic value. In the proposed model, linguistic variables are exploited as a form of teacher’s preferences in nontest techniques. Consequently, the assessment data set will consist of numerical and linguistic information, so it requires a method to unify them to obtain the final value. A model that uses the 2-tuple linguistic approach and based on matrix operations is proposed to solve the problem. This study proposed a new procedure that consists of four stages: preprocessing, transformation, aggregation and exploitation. The final result is presented in 2-tuple linguistic representation and its equivalent number, accompanied by a description of the achievement of each competency. The α value of 2-tuple linguistic in the final result and in the description of each competency becomes meaningful information that can be interpreted as a comparative ability one student has related to other students, and shows how much potential is achieved to reach higher ranks. The proposed model contributes to enrich the learning assessment techniques, since the exploitation of linguistic variable as representation preferences provides flexible space for teachers in their assessments. Moreover, using the result with respect to students’ levels of each competency, students’ mastery of each attribute can be diagnosed and their progress of learning can be estimated.
CONCEPTUAL APPROACH AND SOLVING WORD PROBLEM INVOLVING MULTIPLICATION OF WHOL...WayneRavi
This study was conducted to determine the effect of conceptual approach on solving word problems involving multiplication of whole numbers as well as addition and subtraction. The study was carried out in Tambongon Elementary School to Fourty-one Grade Two students. Descriptive statistics (mean & SD), paired-sample T-test and ETA2 were used as tools in the analysis of data. Results revealed that there was a significant difference on the pretest and post test scores of conceptual approach. Further, conceptual approach has large effect.
A Study on Learning Factor Analysis – An Educational Data Mining Technique fo...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
In the discovery with models method identification relationships among students behaviors and characteristics or contextual variables are key applications.
At the Social Simulation and Serious Games special track at ESSA 2014, Setsuya Kurahashi gave this talk on the effects of different kinds of collaborative learning on different kinds of school classes.
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.
Artificial intelligence to support human instruction Michael C. Mozera,b,c,, ...eraser Juan José Calderón
Artificial intelligence to support human instruction
Michael C. Mozera,b,c,, Melody Wiseheartd and Timothy P. Novikoff.
PNAS March 5, 2019 116 (10) 3953-3955; first published February 19, 2019 https://doi.org/10.1073/pnas.1900370116
Dynamic Question Answer Generator An Enhanced Approach to Question Generationijtsrd
Teachers and educational institutions seek new questions with different difficulty levels for setting up tests for their students. Also, students long for distinct and new questions to practice for their tests as redundant questions are found everywhere. However, setting up new questions every time is a tedious task for teachers. To overcome this conundrum, we have concocted an artificially intelligent system which generates questions and answers for the mathematical topic –Quadratic equations. The system uses i Randomization technique for generating unique questions each time and ii First order logic and Automated deduction to produce solution for the generated question. The goal was achieved and the system works efficiently. It is robust, reliable and helpful for teachers, students and other organizations for retrieving Quadratic equations questions, hassle free. Rahul Bhatia | Vishakha Gautam | Yash Kumar | Ankush Garg ""Dynamic Question Answer Generator: An Enhanced Approach to Question Generation"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23730.pdf
Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/23730/dynamic-question-answer-generator-an-enhanced-approach-to-question-generation/rahul-bhatia
Iris Publishers - Journal of Addiction and Psychology | Meaningful Learning E...IrisPublishers
One of the characteristics of students with Autism Spectrum Disorder (ASD) is significant deficits in coding global learning. Simmons Barsalou [1] propose a cognitive structure corresponding to different subsystems configured by interconnected conceptual phases, which people with ASD are important delays in semantic processing. From Vigostkian perspective, students assimilate all the concepts that make sense and are meaningful them, so this research main aim is to investigate effectiveness of creating meaningful relationships between concepts to improve learning integrated into curriculum in people with ASD. There ́s few evaluation studies of this theoretical principles integration into curriculum, so this research ́s main aim ́s to investigate effectiveness of creating meaningful relationships.A total of 12 students with ASD of first secondary education participated in this study, which were divided proportionally in three groups with three didactic models to facilitate Geography and History learning: 1 Nets Group (n= 4), 1 Specific Group (n= 4) and 1 Regular Group (n= 4). The comparative results of the three groups performed along three measurements, found through the Between- Subjects and Within- Subjects Repeated Measures Analysis (ANOVA), exhibit that students belonging to Nets Group get better data than your peers from other two groups. Likewise, Specific Group improve above the Regular Group. Improvements found don ́t depend on the data of the disorder level neither cognitive- perceptive degree
The increasing need for data driven decision making recently has resulted in the application of data mining in various fields including the educational sector which is referred to as educational data mining. The need for improving the performance of data mining models has also been identified as a gap for future researcher. In Nigeria, higher educational institutions collect various students’ data, but these data are rarely used in any decision or policy making to improve the academic performance of students. This research work, attempts to improve the performance of data mining models for predicting students’ academic performance using stacking classifiers ensemble and synthetic minority over-sampling techniques. The research was conducted by adopting and evaluating the performance of J48, IBK and SMO classifiers. The individual classifiers models, standard stacking classifier ensemble model and stacking classifiers ensemble model were trained and tested on 206 students’ data set from the faculty of science federal university Dutse. Students’ specific previous academic performance records at Unified Tertiary Matriculation Examination, Senior Secondary Certificate Examination and first year Cumulative Grade Point Average of students are used as data inputs in WEKA 3.9.1 data mining tool to predict students’ graduation classes of degrees at undergraduate level. The result shows that application of synthetic minority over-sampling technique for class balancing improves all the various models performance with the proposed modified stacking classifiers ensemble model outperforming the various classifiers models in both performance accuracy and RSME values making it the best model.
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.
Clustering Students of Computer in Terms of Level of ProgrammingEditor IJCATR
Educational data mining (EDM) is one of the applications of data mining. In educational data mining, there are two key domains, i.e. student domain and faculty domain. Different type of research work has been done in both domains.
In existing system the faculty performance has calculated on the basis of two parameters i.e. Student feedback and the result of student in that subject. In existing system we define two approaches one is multiple classifier approach and the other is a single classifier approach and comparing them, for relative evaluation of faculty performance using data mining
Techniques. In multiple classifier approach K-nearest neighbor (KNN) is used in first step and Rule based classification is used in the second step of classification while in single classifier approach only KNN is used in both steps of classification.
But in proposed system, I will analyse the faculty performance using 4 parameters i.e., student complaint about faculty, Student review feedback for faculty, students feedback, and students result etc.
For this proposed system I will be going to use opinion mining technique for analyzing performance of faculty and calculating score of each faculty.
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.
IOSR Journal of Mathematics(IOSR-JM) is an open access international journal that provides rapid publication (within a month) of articles in all areas of mathemetics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in mathematics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
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.
Artificial intelligence to support human instruction Michael C. Mozera,b,c,, ...eraser Juan José Calderón
Artificial intelligence to support human instruction
Michael C. Mozera,b,c,, Melody Wiseheartd and Timothy P. Novikoff.
PNAS March 5, 2019 116 (10) 3953-3955; first published February 19, 2019 https://doi.org/10.1073/pnas.1900370116
Dynamic Question Answer Generator An Enhanced Approach to Question Generationijtsrd
Teachers and educational institutions seek new questions with different difficulty levels for setting up tests for their students. Also, students long for distinct and new questions to practice for their tests as redundant questions are found everywhere. However, setting up new questions every time is a tedious task for teachers. To overcome this conundrum, we have concocted an artificially intelligent system which generates questions and answers for the mathematical topic –Quadratic equations. The system uses i Randomization technique for generating unique questions each time and ii First order logic and Automated deduction to produce solution for the generated question. The goal was achieved and the system works efficiently. It is robust, reliable and helpful for teachers, students and other organizations for retrieving Quadratic equations questions, hassle free. Rahul Bhatia | Vishakha Gautam | Yash Kumar | Ankush Garg ""Dynamic Question Answer Generator: An Enhanced Approach to Question Generation"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23730.pdf
Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/23730/dynamic-question-answer-generator-an-enhanced-approach-to-question-generation/rahul-bhatia
Iris Publishers - Journal of Addiction and Psychology | Meaningful Learning E...IrisPublishers
One of the characteristics of students with Autism Spectrum Disorder (ASD) is significant deficits in coding global learning. Simmons Barsalou [1] propose a cognitive structure corresponding to different subsystems configured by interconnected conceptual phases, which people with ASD are important delays in semantic processing. From Vigostkian perspective, students assimilate all the concepts that make sense and are meaningful them, so this research main aim is to investigate effectiveness of creating meaningful relationships between concepts to improve learning integrated into curriculum in people with ASD. There ́s few evaluation studies of this theoretical principles integration into curriculum, so this research ́s main aim ́s to investigate effectiveness of creating meaningful relationships.A total of 12 students with ASD of first secondary education participated in this study, which were divided proportionally in three groups with three didactic models to facilitate Geography and History learning: 1 Nets Group (n= 4), 1 Specific Group (n= 4) and 1 Regular Group (n= 4). The comparative results of the three groups performed along three measurements, found through the Between- Subjects and Within- Subjects Repeated Measures Analysis (ANOVA), exhibit that students belonging to Nets Group get better data than your peers from other two groups. Likewise, Specific Group improve above the Regular Group. Improvements found don ́t depend on the data of the disorder level neither cognitive- perceptive degree
The increasing need for data driven decision making recently has resulted in the application of data mining in various fields including the educational sector which is referred to as educational data mining. The need for improving the performance of data mining models has also been identified as a gap for future researcher. In Nigeria, higher educational institutions collect various students’ data, but these data are rarely used in any decision or policy making to improve the academic performance of students. This research work, attempts to improve the performance of data mining models for predicting students’ academic performance using stacking classifiers ensemble and synthetic minority over-sampling techniques. The research was conducted by adopting and evaluating the performance of J48, IBK and SMO classifiers. The individual classifiers models, standard stacking classifier ensemble model and stacking classifiers ensemble model were trained and tested on 206 students’ data set from the faculty of science federal university Dutse. Students’ specific previous academic performance records at Unified Tertiary Matriculation Examination, Senior Secondary Certificate Examination and first year Cumulative Grade Point Average of students are used as data inputs in WEKA 3.9.1 data mining tool to predict students’ graduation classes of degrees at undergraduate level. The result shows that application of synthetic minority over-sampling technique for class balancing improves all the various models performance with the proposed modified stacking classifiers ensemble model outperforming the various classifiers models in both performance accuracy and RSME values making it the best model.
Similar to CLASSIFICATION OF QUESTIONS AND LEARNING OUTCOME STATEMENTS (LOS) INTO BLOOM’S TAXONOMY (BT) BY SIMILARITY MEASUREMENTS TOWARDS EXTRACTING OF LEARNING OUTCOME FROM LEARNING MATERIAL
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.
Clustering Students of Computer in Terms of Level of ProgrammingEditor IJCATR
Educational data mining (EDM) is one of the applications of data mining. In educational data mining, there are two key domains, i.e. student domain and faculty domain. Different type of research work has been done in both domains.
In existing system the faculty performance has calculated on the basis of two parameters i.e. Student feedback and the result of student in that subject. In existing system we define two approaches one is multiple classifier approach and the other is a single classifier approach and comparing them, for relative evaluation of faculty performance using data mining
Techniques. In multiple classifier approach K-nearest neighbor (KNN) is used in first step and Rule based classification is used in the second step of classification while in single classifier approach only KNN is used in both steps of classification.
But in proposed system, I will analyse the faculty performance using 4 parameters i.e., student complaint about faculty, Student review feedback for faculty, students feedback, and students result etc.
For this proposed system I will be going to use opinion mining technique for analyzing performance of faculty and calculating score of each faculty.
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.
IOSR Journal of Mathematics(IOSR-JM) is an open access international journal that provides rapid publication (within a month) of articles in all areas of mathemetics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in mathematics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Improving Communication about Limit Concept in Mathematics through Inquisitio...IOSR Journals
In this action research study, where the subjects are our undergraduate grade mathematics students,
w e try to investigate the impact of direct ‘inquisition’ instruction on their communication and achievement.
We will strategically implement the addition of ‘replication’ study into each concept of limit over a four-month
time period and thus conclusion can be making for the rest of the Mathemat ics . The students practiced using
inquiry in verbal discussions, review activities, and in mathematical problem explanations. We discovered
that a majority of students improved their overall understanding of mathematical concepts based on an analysis
of the data we collected. We also found that in general, students felt that knowing the definition of
mathematical words are important and that it increased their achievement when they understood the concept as a
whole. In addition, students will be more exact in their communication after receiving inquiry instructions. As
a result of this research, we plan to continue to implement inquisition into daily lessons and keep replication
communication as a focus of the mathematics class
Tutorial on qualitative approaches to learning analytics given by Rebecca Ferguson of The Open University UK at the Learning Analytics Summer Institute (LASI) run by the Society for Learning Analytics Research (SoLAR) at the University of British Columbia (UBC) in Vancouver, Canada, on 17 June 2019
A Mamdani Fuzzy Model to Choose Eligible Student EntryTELKOMNIKA JOURNAL
This paper presented about study that have been created a new student choosing system by
using fuzzy mamdani inference systems method. Fuzzy mamdani is used because it has characteristics
such as human perceptions on choosing of students with some specified criteria. The choosing students
who want entry to the school have been difficult if it is manually process. With the fuzzy mamdani, the
process can be possible completed execute and can be reduced the time of choose. To accomplish the
process, the fuzzy variable is created by the national final exam scores, report grade, general competency
test, physical test, interview and psychological test. Based on testing 270 data, the fuzzy mamdani has
been reached 75.63% accuracy.
Exploring Semantic Question Generation Methodology and a Case Study for Algor...IJCI JOURNAL
Assessment of student performance is one of the most important tasks in the educational process. Thus, formulating questions and creating tests takes the instructor a lot of time and effort. However, the time spent for learning acquisition and on exam preparation could be utilized in better ways. With the technical development in representing and linking data, ontologies have been used in academic fields to represent the terms in a field by defining concepts and categories classifies the subject. Also, the emergence of such methods that represent the data and link it logically contributed to the creation of methods and tools for creating questions. These tools can be used in existing learning systems to provide effective solutions to assist the teacher in creating test questions. This research paper introduces a semantic methodology for automating question generation in the domain of Algorithms. The primary objective of this approach is to support instructors in effectively incorporating automatically generated questions into their instructional practice, thereby enhancing the teaching and learning experience.
A Know-How vs. Know-What Approach in the Teaching-Learning.pdfAliZarif1
A Know-How vs. Know-What Approach in the Teaching-Learning
Similar to CLASSIFICATION OF QUESTIONS AND LEARNING OUTCOME STATEMENTS (LOS) INTO BLOOM’S TAXONOMY (BT) BY SIMILARITY MEASUREMENTS TOWARDS EXTRACTING OF LEARNING OUTCOME FROM LEARNING MATERIAL (20)
MULTIMODAL COURSE DESIGN AND IMPLEMENTATION USING LEML AND LMS FOR INSTRUCTIO...IJMIT JOURNAL
Traditionally, teaching has been centered around classroom delivery. However, the onslaught of the
COVID-19 pandemic has cultivated usage of technology, teaching, and learning methodologies for course
delivery. We investigate and describe different modes of course delivery that maintain the integrity of
teaching and learning. This paper answers to the research questions: 1) What course delivery method our
academic institutions use and why? 2) How can instructors validate the guidelines of the institutions? 3)
How courses should be taught to provide student learning outcomes? Using the Learning Environment
Modeling Language (LEML), we investigate the design and implementation of courses for delivery in the
following environments: face-to-face, online synchronous, asynchronous, hybrid, and hyflex. A good
course design and implementation are key components of instructional alignment. Furthermore, we
demonstrate how to design, implement, and deliver courses in synchronous, asynchronous, and hybrid
modes and describe our proposed enhancements to LEML.
Novel R&D Capabilities as a Response to ESG Risks-Lessons From Amazon’s Fusio...IJMIT JOURNAL
Environmental, Social, and Governance (ESG) management is essential for transforming corporate
financial performance-oriented business strategies into Finance (F) + ESG optimization strategies to
achieve the Sustainable Development Goals (SDGs).
In this trend, the rise of ESG risks has divided firms into two categories. Former incorporates a growthmindset that creates a passion for learning, and urges it to improve itself by endeavoring Research and
development (R&D) -driven challenges, while the other category, characterized by risk aversion, avoids
challenging highly uncertain R&D activities and seeks more manageable endeavors.
This duality underscores the complexity of corporate R&D strategies in addressing ESG risks and
necessitates the development of novel R&D capabilities for corporate R&D transformation strategies
towards F + ESG optimization.
International Journal of Managing Information Technology (IJMIT) ** WJCI IndexedIJMIT JOURNAL
The International Journal of Managing Information Technology (IJMIT) is a quarterly open access peer-reviewed journal that publishes articles that contribute new results in all areas of the strategic application of information technology (IT) in organizations. The journal focuses on innovative ideas and best practices in using IT to advance organizations – for-profit, non-profit, and governmental. The goal of this journal is to bring together researchers and practitioners from academia, government, and industry to focus on understanding both how to use IT to support the strategy and goals of the organization and to employ IT in new ways to foster greater collaboration, communication, and information sharing both within the organization and with its stakeholders. The International Journal of Managing Information Technology seeks to establish new collaborations, new best practices, and new theories in these areas.
International Journal of Managing Information Technology (IJMIT) ** WJCI IndexedIJMIT JOURNAL
The International Journal of Managing Information Technology (IJMIT) is a quarterly open access peer-reviewed journal that publishes articles that contribute new results in all areas of the strategic application of information technology (IT) in organizations. The journal focuses on innovative ideas and best practices in using IT to advance organizations – for-profit, non-profit, and governmental. The goal of this journal is to bring together researchers and practitioners from academia, government, and industry to focus on understanding both how to use IT to support the strategy and goals of the organization and to employ IT in new ways to foster greater collaboration, communication, and information sharing both within the organization and with its stakeholders. The International Journal of Managing Information Technology seeks to establish new collaborations, new best practices, and new theories in these areas.
NOVEL R & D CAPABILITIES AS A RESPONSE TO ESG RISKS- LESSONS FROM AMAZON’S FU...IJMIT JOURNAL
Environmental, Social, and Governance (ESG) management is essential for transforming corporate
financial performance-oriented business strategies into Finance (F) + ESG optimization strategies to
achieve the Sustainable Development Goals (SDGs).
In this trend, the rise of ESG risks has divided firms into two categories. Former incorporates a growthmindset that creates a passion for learning, and urges it to improve itself by endeavoring Research and
development (R&D) -driven challenges, while the other category, characterized by risk aversion, avoids
challenging highly uncertain R&D activities and seeks more manageable endeavors.
This duality underscores the complexity of corporate R&D strategies in addressing ESG risks and
necessitates the development of novel R&D capabilities for corporate R&D transformation strategies
towards F + ESG optimization.
Building on this premise, this paper conducts an empirical analysis, utilizing reliable firms data on ESG
risk and brand value, with a focus on 100 global R&D leader firms. It analyzes R&D and actions for ESG
risk mitigation, and assesses the development of new functions that fulfill F + ESG optimization through
R&D. The analysis also highlights the significance of network externality effects, with a specific focus on
Amazon, a leading R&D company, providing insights into the direction for transforming R&D strategies
towards F + ESG optimization.
The dynamics of stakeholder engagement in F + ESG optimization are indicated with the example of
amazon's activities. Through the analysis, it became evident that Amazon's capacity encompassing growth
and scalability, specifically its ability to grow and expand, is accelerating high-level research and
development by gaining the trust of stakeholders in the "synergy through R&D-driven ESG risk
mitigation."
Finally, as examples of these initiatives, the paper discussed the Climate Pledge led by Amazon and the
transformation of Japan's management system.
A REVIEW OF STOCK TREND PREDICTION WITH COMBINATION OF EFFECTIVE MULTI TECHNI...IJMIT JOURNAL
It is important for investors to understand stock trends and market conditions before trading stocks. Both
these capabilities are very important for an investor in order to obtain maximized profit and minimized
losses. Without this capability, investors will suffer losses due to their ignorance regarding stock trends
and market conditions. Technical analysis helps to understand stock prices behavior with regards to past
trends, the signals given by indicators and the major turning points of the market price. This paper reviews
the stock trend predictions with a combination of the effective multi technical indicator strategy to increase
investment performance by taking into account the global performance and the proposed combination of
effective multi technical indicator strategy model.
INTRUSION DETECTION SYSTEM USING CUSTOMIZED RULES FOR SNORTIJMIT JOURNAL
These days the security provided by the computer systems is a big issue as it always has the threats of
cyber-attacks like IP address spoofing, Denial of Service (DOS), token impersonation, etc. The security
provided by the blue team operations tends to be costly if done in large firms as a large number of systems
need to be protected against these attacks. This leads these firms to turn to less costly security
configurations like IDS Suricata and IDS Snort. The main theme of the project is to improve the services
provided by Snort which is a tool used in creating a vague defense against cyber-attacks like DDOS
attacks which are done on both physical and network layers. These attacks in turn result in loss of
extremely important data. The rules defined in this project will result in monitoring traffic, analyzing it,
and taking appropriate action to not only stop the attack but also locate its source IP address. This whole
process uses different tools other than Snort like Wireshark, Wazuh and Splunk. The product of this will
result in not only the detection of the attack but also the source IP address of the machine on which the
attack is initiated and completed. The end product of this research will result in sets of default rules for the
Snort tool which will not only be able to provide better security than its previous versions but also be able
to provide the user with the IP address of the attacker or the person conducting the attack. The system
involves the integration of Wazuh with Snort tool in order to make it more efficient than IDS Suricata
which is another intrusion detection system capable of detecting all these types of attacks as mentioned.
Splunk is another tool used in this project which increases the firewall efficiency to pass the no. of bits to
be scanned and the no. of bits scanned successfully. Wazuh is used in this system as it is the best choice for
traffic monitoring and incident response than any other of its alternatives in the market. Since this system
is used in firms which are known to handle big amounts of data and for this purpose, we use Splunk tool as
it is very efficient in handling big amounts of data. Wireshark is used in this system in order to give the IDS
automation in its capability to capture and report the malicious packets found during the network scan. All
of this gives the IDS a capability of a low budget automated threat detection system. This paper gives
complete guidelines for authors submitting papers for the AIRCC Journals.
Artificial Intelligence (AI) has rapidly become a critical technology for businesses seeking to improve
efficiency and profitability. One area where AI is proving particularly impactful is in service operations
management, where it is used to create AI-powered service operations (AIServiceOps) that deliver highvalue services to customers. AIServiceOps involve the use of AI to automate and optimize various business
processes, such as customer service, sales, marketing, and supply chain management. The rapid
development of Artificial Intelligence has prompted many changes in the field of Information Technology
(IT) Service Operations. IT Service Operations are driven by AI, i.e., AIServiceOps. AI has empowered
new vitality and addressed many challenges in IT Service Operations. However, there is a literature gap on
the Business Value Impact of Artificial intelligence (AI) Powered IT Service Operations. It can help IT
build optimized business resilience by creating value in complex and ever-changing environments as
product organizations move faster than IT can handle. So, this research paper examines how AIServiceOps
creates business value and sustainability, basically how AIServiceOps makes the IT staff liberation from a
low-level, repetitive workout and traditional IT practices for a continuously optimized process. One of the
research objectives is to compare Traditional IT Service Operations with AIServiceOPs. This paper
provides the basis for how enterprises can evaluate AIServiceOps and consider it a digital transformation
tool. The paper presents a case study of a company that implemented AI-powered service operations
(AIServiceOps) and analyzes the resulting business outcomes. The study shows that AIServiceOps can
significantly improve service delivery, reduce response times, and increase customer satisfaction.
Furthermore, it demonstrates how AIServiceOps can deliver substantial cost savings, such as reducing
labor costs and minimizing downtime.
MEDIATING AND MODERATING FACTORS AFFECTING READINESS TO IOT APPLICATIONS: THE...IJMIT JOURNAL
Although IOT seems to be the upcoming trend, it is still in its infancy; especially in the banking industry.
There is a clear gap in literature, as only few studies identify factors affecting readiness to IOT
applications in banks in general, and almost negligible investigations on mediating and moderating
factors. Accordingly, this research aims to investigate the main factors that affect employees’ readiness to
IOT applications, while highlighting the mediating and moderating factors in the Egyptian banking sector.
The importance of Egypt stems from its high population and steady steps taken towards technology
adoption. 479 valid questionnaires were distributed over HR employees in banks. Data collected was
statistically analysed using Regression and SEM. Results showed a significant impact of ‘Security’,
‘Networking’, ‘Software Development’ and ‘Regulations’ on ‘readiness to IOT applications. Thus, the
readiness acceptance level is high‘Security’ and ‘User Intention’ were proven to mediate the relationship
between research variables and readiness to IOT applications, and only a partial moderation role was
proven for ‘Efficiency’. The study contributes to increasing literature on IOT applications in general, and
fills a gap on the Egyptian banking context in particular. Finally, it provides decision makers at banks with
useful guidelines on how to optimally promote IOT applications among employees.
EFFECTIVELY CONNECT ACQUIRED TECHNOLOGY TO INNOVATION OVER A LONG PERIODIJMIT JOURNAL
IT (Information and Communication Technology) companies are facing the dilemma of decreasing
productivity despite increasing research and development efforts. M&A (Merger and Acquisition) is being
considered as a breakthrough solution. From existing research, it has been pointed out that M&A leads to
the emergence of new innovations. Purpose of this study was to discuss the efficient ways of acquisition and
to resolve the dilemma of productivity decline by clarifying how the technology obtained through M&A
leads to the creation of new innovations. Hypothesis 1 was that the technology acquired through M&A is
utilized for innovation creation, Hypothesis 2 was that the acquired technology is utilized over a long
period of time, and Hypothesis 3 was that a long-term utilization has a positive impact on corporate
performance. The results, using sports prosthetics as a case study and using patents as a proxy variable,
confirmed all the hypotheses set. We have revealed that long-term utilization of technology obtained
through M&A is effective for creating new innovations.
International Journal of Managing Information Technology (IJMIT) ** WJCI IndexedIJMIT JOURNAL
The International Journal of Managing Information Technology (IJMIT) is a quarterly open access peer-reviewed journal that publishes articles that contribute new results in all areas of the strategic application of information technology (IT) in organizations. The journal focuses on innovative ideas and best practices in using IT to advance organizations – for-profit, non-profit, and governmental. The goal of this journal is to bring together researchers and practitioners from academia, government, and industry to focus on understanding both how to use IT to support the strategy and goals of the organization and to employ IT in new ways to foster greater collaboration, communication, and information sharing both within the organization and with its stakeholders. The International Journal of Managing Information Technology seeks to establish new collaborations, new best practices, and new theories in these areas.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of information technology and management
4th International Conference on Cloud, Big Data and IoT (CBIoT 2023)IJMIT JOURNAL
4th International Conference on Cloud, Big Data and IoT (CBIoT 2023) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Cloud, Big Data and IoT.
TRANSFORMING SERVICE OPERATIONS WITH AI: A CASE FOR BUSINESS VALUEIJMIT JOURNAL
Artificial Intelligence (AI) has rapidly become a critical technology for businesses seeking to improve
efficiency and profitability. One area where AI is proving particularly impactful is in service operations
management, where it is used to create AI-powered service operations (AIServiceOps) that deliver highvalue services to customers. AIServiceOps involve the use of AI to automate and optimize various business
processes, such as customer service, sales, marketing, and supply chain management. The rapid
development of Artificial Intelligence has prompted many changes in the field of Information Technology
(IT) Service Operations. IT Service Operations are driven by AI, i.e., AIServiceOps. AI has empowered
new vitality and addressed many challenges in IT Service Operations. However, there is a literature gap on
the Business Value Impact of Artificial intelligence (AI) Powered IT Service Operations. It can help IT
build optimized business resilience by creating value in complex and ever-changing environments as
product organizations move faster than IT can handle. So, this research paper examines how AIServiceOps
creates business value and sustainability, basically how AIServiceOps makes the IT staff liberation from a
low-level, repetitive workout and traditional IT practices for a continuously optimized process. One of the
research objectives is to compare Traditional IT Service Operations with AIServiceOPs. This paper
provides the basis for how enterprises can evaluate AIServiceOps and consider it a digital transformation
tool. The paper presents a case study of a company that implemented AI-powered service operations
(AIServiceOps) and analyzes the resulting business outcomes. The study shows that AIServiceOps can
significantly improve service delivery, reduce response times, and increase customer satisfaction.
Furthermore, it demonstrates how AIServiceOps can deliver substantial cost savings, such as reducing
labor costs and minimizing downtime.
DESIGNING A FRAMEWORK FOR ENHANCING THE ONLINE KNOWLEDGE-SHARING BEHAVIOR OF ...IJMIT JOURNAL
The main objective of this paper is to identify the factors that influence academic staff's digital knowledgesharing behaviors in Ethiopian higher education. A structural equation model was used to validate the
research framework using survey data from 210 respondents. The collected data has been analyzed using
Smart PLS software. The results of the study show that trust, self-motivation, and altruism are positively
related to attitude. Contrary to our expectations, knowledge technology negatively affects attitude.
However, reward systems and empowerment by leaders are significantly associated with knowledgesharing intentions.Knowledge-sharing intention, in turn, was significantly related to digital knowledgesharing behavior. The contributions of this study are twofold. The framework may serve as a roadmap for
future researchers and managers considering their strategy to enhance digital knowledge sharing in HEI.
The findings will benefit academic staff and university administrations.The study will also help academic
staff enhance their knowledge-sharing practices.
BUILDING RELIABLE CLOUD SYSTEMS THROUGH CHAOS ENGINEERINGIJMIT JOURNAL
Cloud computing systems need to be reliable so that they can be accessed and used for computing at any
given point in time. The complex nature of cloud systems is the motivation to conduct research in novel
ways of ensuring that cloud systems are built with reliability in mind. In building cloud systems, it is
expected that the cloud system will be able to deal with high demands and unexpected events that affect the
reliability and performance of the system.
In this paper, chaos engineering is considered a heuristic method that can be used to build reliable cloud
systems. Chaos engineering is aimed at exposing weaknesses in systems that are in production. Chaos
engineering will help identify system weaknesses and strengths when a system is exposed to unexpected
knocks and shocks while it is in production.
Chaos engineering allows system developers and administrators to get insights into how the cloud system
will behave when it is exposed to unexpected occurrences.
A REVIEW OF STOCK TREND PREDICTION WITH COMBINATION OF EFFECTIVE MULTI TECHNI...IJMIT JOURNAL
It is important for investors to understand stock trends and market conditions before trading stocks. Both
these capabilities are very important for an investor in order to obtain maximized profit and minimized
losses. Without this capability, investors will suffer losses due to their ignorance regarding stock trends
and market conditions. Technical analysis helps to understand stock prices behavior with regards to past
trends, the signals given by indicators and the major turning points of the market price. This paper reviews
the stock trend predictions with a combination of the effective multi technical indicator strategy to increase
investment performance by taking into account the global performance and the proposed combination of
effective multi technical indicator strategy model.
NETWORK MEDIA ATTENTION AND GREEN TECHNOLOGY INNOVATIONIJMIT JOURNAL
This paper will provide a novel empirical study for the relationship between network media attention and
green technology innovation and examine how network media attention can ease financing constraints. It
collected data from listed companies in China's heavy pollution industry and performed rigorous
regression analysis, in order to innovatively explore the environmental governance functions of the media.
It found that network media attention significantly promotes green technology innovation. By analyzing the
inner mechanism further, it found that network media attention can promote green innovation by easing
financing constraints. Besides, network media attention has a significant positive impact on green invention
patents while not affecting green utility model patents.
INCLUSIVE ENTREPRENEURSHIP IN HANDLING COMPETING INSTITUTIONAL LOGICS FOR DHI...IJMIT JOURNAL
Information System (IS) research advocates employing collaborative and loose coupling strategies to address contradictory issues to address diversified actors’ interests than the prescriptive and unilateral Information Technology (IT) governance mechanisms’, yet it is rarely depicting how managers employ these strategies in Health Information System (HIS) implementation, particularly in a resource-constrained setting where IS implementation activities have highly relied on multiple international organizations resources. This study explored how managers in resource-constrained settings employ collaborative IT governance mechanisms in the case of District Health Information System 2 (DHIS2) adoption with an interpretative case study approach and the institutional logic concept. The institutional logic concept was used to identify the major actors’ logics underpinning the DHIS2 adoption. The study depicted the importance of high-level officials' distance from the dominant systemic logic to consider new alternative, and to employ inclusive IT governance mechanisms which separated resource from the system that facilitated stakeholders’ collaboration in DHIS2 adoption based on their capacity and interest.
DEEP LEARNING APPROACH FOR EVENT MONITORING SYSTEMIJMIT JOURNAL
With an increasing number of extreme events and complexity, more alarms are being used to monitor
control rooms. Operators in the control rooms need to monitor and analyze these alarms to take suitable
actions to ensure the system’s stability and security. Security is the biggest concern in the modern world. It
is important to have a rigid surveillance that should guarantee protection from any sought of hazard.
Considering security, Closed Circuit TV (CCTV) cameras are being utilized for reconnaissance, but these
CCTV cameras require a person for supervision. As a human being, there can be a possibility to be tired
off in supervision at any point of time. So, we need a system to detect automatically. Thus, we came up with
a solution using YOLO V5. We have taken a data set and used robo-flow framework to enhance the existing
images into numerous variations where it will create a copy of grey scale image, a copy of its rotation and
a copy of its blurred version which will be used to get an enlarged data set. This work mainly focuses on
providing a secure environment using CCTV live footage as a source to detect the weapons. Using YOLO
algorithm, it divides an image from the video into grid system and each grid detects an object within itself
MULTIMODAL COURSE DESIGN AND IMPLEMENTATION USING LEML AND LMS FOR INSTRUCTIO...IJMIT JOURNAL
Traditionally, teaching has been centered around classroom delivery. However, the onslaught of the
COVID-19 pandemic has cultivated usage of technology, teaching, and learning methodologies for course
delivery. We investigate and describe different modes of course delivery that maintain the integrity of
teaching and learning. This paper answers to the research questions: 1) What course delivery method our
academic institutions use and why? 2) How can instructors validate the guidelines of the institutions? 3)
How courses should be taught to provide student learning outcomes? Using the Learning Environment
Modeling Language (LEML), we investigate the design and implementation of courses for delivery in the
following environments: face-to-face, online synchronous, asynchronous, hybrid, and hyflex. A good
course design and implementation are key components of instructional alignment. Furthermore, we
demonstrate how to design, implement, and deliver courses in synchronous, asynchronous, and hybrid
modes and describe our proposed enhancements to LEML.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
CLASSIFICATION OF QUESTIONS AND LEARNING OUTCOME STATEMENTS (LOS) INTO BLOOM’S TAXONOMY (BT) BY SIMILARITY MEASUREMENTS TOWARDS EXTRACTING OF LEARNING OUTCOME FROM LEARNING MATERIAL
1. International Journal of Managing Information Technology (IJMIT) Vol.9, No.2, May 2017
DOI : 10.5121/ijmit.2017.9201 1
CLASSIFICATION OF QUESTIONS AND LEARNING
OUTCOME STATEMENTS (LOS) INTO BLOOM’S
TAXONOMY (BT) BY SIMILARITY MEASUREMENTS
TOWARDS EXTRACTING OF LEARNING OUTCOME
FROM LEARNING MATERIAL
Shadi Diab1
and Badie Sartawi2
1
Information and Communication Technology Center, Al-Quds Open University,
Ramallah - Palestine
2
Associate Professor of Computer Science, Al-Quds University, Jerusalem - Palestine
ABSTRACT
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.
KEYWORDS
Learning outcome; Natural Language Processing, Similarity Measurement; Questions Classification
1. INTRODUCTION
The new international trends in education show a shift from traditional teacher-centred approach
to a “student-centred” approach, which focuses, in turn, on what the students are expected to do at
the end of the learning process! Therefore, this approach is commonly referred to as an outcome-
based approach. Statements called intended learning outcomes, commonly shortened to learning
outcomes, are being used to express what the students are expected to be able to do at the end of
the learning period [1]. Learning is defined, in term of its outcome, in different contexts and for
difference purposes or settings e.g. in terms of education, work, guidance and personnel context
[2]. As for our research, it focuses on the education context presented in the form of textbooks
deployed by the teaching staff. Learning outcomes can be defined for a single course taught by
several teachers, or be standardized across universities or whole domains. Instructional designers
(represented by the author of the textbook itself) should be provided a list of relevant learning
2. International Journal of Managing Information Technology (IJMIT) Vol.9, No.2, May 2017
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outcome definitions they can link to their courses [3]. There are many useful guides for
developing a comprehensive list of student outcomes. For example, Bloom's taxonomy is used to
define the objective of learning and teaching as well as to divide learning into three types of
domains: cognitive, affective and psychomotor. Then, it defines the level of performance for each
domain [4]. Former students of blooms and a group of cognitive psychologists, curriculum
theorists and instructional researchers have released a new version of bloom’s taxonomy in 2001
[5]. Our research will focus on the cognitive domain of bloom’s taxonomy 1.
It is a truism for educators that questions play an important role in teaching [6]. Our research
focuses on questions classification into a cognitive level of bloom’s taxonomy, which is a
framework for classifying educational goals and objectives into a hierarchical structure
representing levels of learning. BT is of three different domains: the cognitive domain, the
affective domain and the psychomotor domain. Each of these has a multi-tiered hierarchical
structure for classifying learning [5]. The Cognitive Domain (Bloom et al., 1956) has become
widely used throughout the world to assist in the preparation of evaluation materials [1].
There are six major categories (levels). The levels are Knowledge; Comprehension; Application;
Analysis; Synthesis and Evaluation [7]. In our proposed approach, we will use the action verb of
the question or (LOS) which represents the cognitive skill to classify the question into one or
more levels.
2. LITERATURE AND RELATED WORK
Many researchers attempted to classify questions into different classes and for different purposes.
In [8] they classified learning questions through a machine learning approach, and learned a
hierarchical classifier guided by a layered semantic hierarchy of answer types. They eventually
classified questions into fine-grained classes. Their hierarchal classifier achieved 98.80% precision
for coarse classes with all the features, and 95% for the fine classes.
Keywords database matching with the verb of the question method has been developed, piloted
and tested for automatic Bloom's taxonomy analysis, that matches all levels of cognitive domain of
bloom [9], the results have shown that the knowledge level achieved 75% correct match in
comparison with the expert’s results. The researchers system allows both teachers and students
work together in the same platform to insert questions and review learning-outcome matches with
the cognitive domain of BT.
[10] They proposed natural language processing-based automatic concept extraction and outlines
rule-based approach for separation of prerequisite concepts and learning outcomes covered in
learning document, by their manual creation of domain ontology. Their system achieved Precision:
0.67 Recall: 0.83 F-score: 0.75.
[11] They also proposed rule-based approach to analyse and classify written examination questions
through natural language processing for computer programming subjects, the rules were developed
using the syntactic structure of each question to apply the pattern of each question to the cognitive
level of bloom. Their evaluation achieved macro F1 of 0.77. The researchers, in their other
research, [12] proposed Bloom's Taxonomy Question Categorization Using Rules and N-Gram
Approaches. In their experiment; 100 questions were selected for training and 35 were used for
testing and both were based on programming domain. The categorization uses rule-based
approach, N-gram and a combination of both. Their result demonstrated that combination rule-
based and n-gram approaches obtained the highest and the best score of precision of average of
88%.
[13] researchers have taken data of Li and Roth in [8] to classify the questions into three broad
categoris instead of 6 course grain and and 50 fine grained categories. They analyzed the questions
3. International Journal of Managing Information Technology (IJMIT) Vol.9, No.2, May 2017
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syntacically to expect the answer type for every particuler category of the questions. [14] They also
classified questions with different five machine learning algorithms: Nearest Neighbours (NN);
Naïve Bayes (NB); Decision Tree (DT); Sparse Network of Winnows (SNoW); and Support
Vector Machines (SVM). They did the classification using two features: bag-of-words and bag-of
n-grams. They proposed a special kernel function to enable (SVM) take advantages of the syntactic
structure of the questions. In their experiment, the questions classification accuracy reached 90%.
[15] They proposed two Level Question Classification based on SVM and Question Semantic
Similarity in computer service & support domain, their results showed that question classification
dramatically improves when complementing the domain ontology knowledge with question-
specific domain concepts. They also presented a two level classification approach based on SVM
and question semantic similarity. [16] They also explored the effectiveness of support vector
machines (SVMs) to classify questions, their evaluation showed the micro was 87.4 accuracy,
83.33 precision and 44.64 F1.
Most of the researchers in our literature review had focused on classifying questions into different
classes, including the classes of cognitive levels of BT... Purely machine learning and rules based
approaches has been applied. Most of these researchers used huge amount of data and domain
ontology to run their experiments, including the need to domain-experts to evaluate the
performance, we consider [17] is the most related research to our approach. They used WordNet
with cosine algorithm to classify exams question into bloom taxonomy. Questions pattern
identification was required as a step to measure the cosine similarity by finding the total number of
WordNet values for questions and run cosine similarity twice; first for pattern detection and second
after calculating the WordNet value. Their evaluation achieved 32 questions out of 45 correctly
classified. However, in our research, we proposed one similarity algorithm to measure the
semantic similarity between the action verb of the question and the action verb list categorized by
domain experts to find out the most accurate level for the question. Moreover, our algorithm was
evaluated using confusion matrix. It was applied to both the cognitive domain of BT and the
remaining two domains
3. SEMANTIC SIMILARITY MEASUREMENT
3.1 Semantic Similarity
Semantic similarity has attracted great concern for a long time in artificial intelligence, psychology
and cognitive science. In recent years, the measures based on WordNet have shown its capabilities
and attracted great concern [18]. Researchers used measure of semantic relatedness to perform the
task of word sense disambiguation [19]. Semantic similarity measures can be generally partitioned
based on four grounds: based on the distance similarity between two concepts; based on
information the two concepts share; based on the properties of the concepts; and based on a
combination of the previous options [20].
3.2 Wordnet
WordNet is a large lexical database of English. Nouns, verbs, adjectives and adverbs are grouped
into sets of synonyms (Synsets). Synsets are interlinked by means of conceptual-semantic and
lexical relations. It includes 82115 nouns, 13767 verbs, 18156 adjectives, 3621 adverbs [21]. The
Wu and Palmer (Wu and Palmer, 1994) similarity metric measures semantic similarity through the
depth of the two concepts in the WordNet taxonomy [22]. However, there are some important
distinctions: First, WordNet interlinks not just word forms strings of letters but also specific senses
of words. As a result, words found in close proximity to one another in the network are
semantically disambiguated. Second, WordNet labels the semantic relations among words,
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whereas the groupings of words in a thesaurus does not follow any explicit pattern other than
meaning similarity [22]. Wu-Palmer representation scheme does not only take care of the
semantic-syntactic correspondence, but it also provides similarity measures for the system for the
performance of inexact matches based on verb meanings [23]. Wu-Palmer algorithm uses the
following equation to measure the similarity:
4. RESEARCH’S METHODOLOGY
Analysing questions and LOS to determine the most accurate level in BT domains is a challenge.
This will lead us to discover the intended learning outcome that will be achieved by the students.
In our research, we concentrated on the action verbs that should be used to write questions and
LOS based on cognitive domain through analysing the questions and LOS.
We have observed that categorization of the actions verbs may occur in different levels of the
cognitive domain, thus, you may find the verb write in knowledge, application, comprehension or
analysis levels, such this classification depends on the understanding of the action verb classified
by domain experts. Academicians would manually classify the question into taxonomy level based
on their styles [11]. Through our research, we will answer the following questions:
How can we classify the question and LOS into one or more of level of the cognitive domain using
semantic similarity measurements? Does our proposed approach apply to the two remaining
domains of BT? Will semantic similarity between action verbs of the question and the action verb
lists assist in the enhancement of classifying questions and the writing of more accurate LOS?
5. COLLECTING DATA FROM DOMAIN EXPERTS
We have observed that many universities, worldwide, prepared guides papers and publications to
be used for their teachers, in order to support them to write questions and LOS based on BT. The
guides that classify the action verb is used as reference to classify the action verbs into BT. By
assuming that the teachers use guides and supportive publications of their schools and universities
in order to write questions and LOS, We collected 605 different action verbs that describe the
cognitive skills in each level from websites of different universities [24] [25] [26] [27]. To gain
more accurate and precise data, we filtered and modified the data lists by collecting the verbs
intersecting with three or four lists (threshold 75-100%). We also added verbs intersecting with
two resources if and only if having no conflict with other lists (threshold 50%). The result was a
new dataset that contains 77 different action verbs distributed on the six levels of cognitive domain
of BT. Moreover, questions starters from [28], which organize the starters of questions that cover
each level of the cognitive domain of BT, has been collected.
6. STRUCTURAL INDUCTION OF THE QUESTION
Structural induction may be defined as the process of extracting structural information using
machine learning techniques and the patterns found may use to classify the questions [29]. This
allows us to take some parts of question and leave the others for further processing. Our
experiment aims to extract the action verb of the question by using the structural induction. Using
the questions starters collected from [28], we were able to extract the action verb of the questions
throughout implementing the following steps:
5. International Journal of Managing Information Technology (IJMIT) Vol.9, No.2, May 2017
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splitting the questions into separate lines, tokenization, lemmatization, POS tagging, partial parser
over grammar which detect main action verb of the question , we were able to convert such
question in form of POS tags patters contain the action verb of the question.
For example, running partial parsing over manually built in grammar to detect the knowledge level
of the cognitive domain based on starters of [28]: Q: How would you explain computer science to
a five-year-old? Steps will return the chunked tree labelled with "KNOW" as in Figure 1, while the
main action verb explain refers to the knowledge level of BT
Figure 1: Chunked Tree Example
We have observed, after the implementation of our experiment, that adapting partial parser over
built in grammars is applicable and effective to extract the action verb in order to move forward
in our next experiments and analysis.
7. THE PROPOSED ACTION VERBS CLASSIFICATION ALGORITHM
Different verbs can be used to demonstrate different levels of learning, for example: the basic
level the learning outcomes may require learners to be able to define, recall, list, describe, explain
or discuss [2]. In addition to that, the verb is considered the center, the fulcrum and the engine of
a learning outcome statement. We should note that verbs refer to events, not to states; events are
specific actions [30]. Thus, our proposed solution is based on the classification of action verb of
the questions or LOS, in order to classify the whole question or LOS into more accurate level.
The following definitions and steps describe our algorithm:
BTD (Bloom’s Taxonomy Dimensions) = [C, A, P] where denotes for cognitive, affective and the
psychomotor domains respectively.
Based on BT classification each dimension of BT contains different levels (L), where the
cognitive domain (C) contains six levels, and each affective (A) and psychomotor (P) domain
contains 5 levels, thus C= [L1...L6], A= [L1… L5], and P= [L1… L5], for each level (L) in any
dimension there are some groups of action verbs represent the particular level, these verbs assist
and support the academicians to write LOS and questions based on BT.
Classification of the action verb of the question or LOS (VQ) into one or more of dimension of
BTD by similarity measurement between the action verb in VQ and each verbs of L in C, A or P
by calculating similarity (sim) measurements, maximum similarity (Maxsim) and the total of
similarities in each level, our algorithm will find three main measurements as follow:
• Similarity measurement between the obtained action verb of the question or LOS and each
of verbs represent the level of BT, Sim = Similarity_algorithm (VQ, N), where N is number
of verbs represent the particular level.
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• Maximum similarity value between the action verb of the question or LOS and the verbs
represent each level of BT, Maxsim = Maximum of semantic similarities between (VQ, N)
for each L.
• Maximum area represent the total amount of similarity values for the action verb of the
question or LOS in each level, Maxarea of L in C, A or P = MAX ( = sim (0) +
sim (1) +… + sim (n), where i >=0 and n is the list of action verbs.
8. ACTION VERBS CLASSIFICATION ALGORITHM (AVCA)
For the sake of simplicity, our algorithm and implementation applied on the cognitive domain,
while the data (verbs) represent the cognitive domain are same type of data represent the other
domains but with different verbs, furthermore our algorithm may accept any input data in form of
verbs regardless if its related to cognitive, affective or psychomotor verbs, the proposed algorithm
Pseudo code and step as follow:
(Pseudo code):
Algorithm AVCA (VQ [0...M], CL [1...N], Maxsim [1…6], Maxarea):
// the algorithm measure the similarity between groups of verbs
//by calculating the high similarity and total amount of similarity values
// Input: List of action verbs obtained from questions or LOS, VQ [1...M], and list of verbs
//represent the cognitive domain CL, where CL= [L1...L6] and each contains group of verbs L=
//[1...N]
//Output: The maximum similarity between each verb of VQ list and L in CL, and maximum
similarity area for each verb of VQ in each L in CL
For each L in CL:
Compute Sim = [Similarity_algorithm (M, N)]
Compute Maxsim = [Max (sim)]
Classification result = L with greatest (Max (sim))
IF Len (Maxsim) >1 //have more than one max similarity appears in more than one level L
For each L in CL:
Maxarea = Sum (sim1, sim2….Sim...n)
Classification result = L with greatest (Maxarea)
STOP
While there are a few similarity algorithms adapted in WORDNET, we implemented our algorithm
on Wu-Palmer similarity algorithm to measure the similarity values, maximum similarities and
similarity area, in additional, our algorithm will remain correct and applicable on the other
similarity algorithms, and while the input data types are all in form of action verbs regardless if
belong to cognitive, affective or psychomotor, our algorithm also will generate correct results and
remain applicable for any dimension of BT.
9. EXPERIMENT AND ANALYSIS
Our classification algorithm applied the constructed verb lists from questions and LOS to compute
the maximum similarity for each level of the cognitive domain. Then it compares the maximum
similarities to nominate (the greater) one and only one level as accurate level for the classified
verb. Our experiment was built based on the collected data from [24] [25] [26] [27]. Such data has
7. International Journal of Managing Information Technology (IJMIT) Vol.9, No.2, May 2017
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been built to support the academicians to write questions and LOS, we observed the following
behaviours and cases:
Identical similarity will appear when the Synsets of the action verb has 1 similarity value with
one or more verbs in the lists of cognitive domain. For example, figure 2 shows that the verb
compile has 1 similarity value with the verb roll up in the synthesis level. We may conclude that
the verb compile is way closer to the synthesis level than the other levels.
Figure 2: Maximum Similarity for the verb <compile>
Higher similarity value will appear when the action verb has less than 1 maximum similarity
value. It also appears in one and only one level of cognitive domain. For example, figure 3 shows
that the verb write has higher similarity value (0.857) with the verb dramatize in the application
level. Thus, we may conclude that the verb dramatize belongs to application level more than the
others do.
Obtaining same maximum similarity for some action verbs in more than one cognitive level may
mean that the verb of the question could be applied to more than one level, see figure 4, Such
case, in the point of view of some academicians may make sense. Moreover, we could prove that
the action verb of the question may belong to one and only one level of the cognitive domain and
have greater similarity semantically than the others. Figure 4 shows that the verb manipulate have
maximum similarity (0.28) in all levels.
Figure 3: Maximum similarity for the verb <write>
8. International Journal of Managing Information Technology (IJMIT) Vol.9, No.2, May 2017
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In order to check if the similarity values have bias to one level more than the others. We
calculated the similarity values for each one sixth. Figure 5 shows that the bias will appear in
application level where the total amount of all similarities values in application level is
greater than the others. In all expirements we conducted, we were not able to find two verbs
of the same total similarity values in more than one sixth. This leads us to measure and
classify the verb in one and only one level of the cognitive domain of BT.
10. ENHANCEMENT OF THE ACTION VERBS LIST
We validate our proposed algorithm on new data sets of action verbs collected from different
resources from [31] [32]. All verbs were tested against each verb in our collected data [24] [25]
[26] [27]. We found that our proposed algorithm can improve the correctness of the categorization
based on cognitive blooms taxonomy from average of 71% to 97%.
However, our algorithm was able to find that (34%) were incorrectly manually classified, on its
part, has reduced the incorrectly classified verbs percentage from 34% to 8%. The improvement
Figure 5: Computing of similarities in each one six
Figure 4: Maximum Similarity for the verb < manipulate >
9. International Journal of Managing Information Technology (IJMIT) Vol.9, No.2, May 2017
9
average detected was 97% for both data sets as a result of applying a threshold ≥ 50% as an
evidence from our source data.
11. EVALUATION AND RESULTS
We evaluated our algorithm to measure the performance and our obtained results. We used
confusion matrix, which is often used to describe the performance of classification model [33] in
order to measure the following values:
• True Positives (TP) is the count of correctly predicted positive values. We count the
number of TP for each verb in our implementation as if the actual verb is classified in
the same class or level (both of the two verbs belong to the same cognitive level)
• True Negatives (TN) is the count of correctly predicted negative values; the total
amount of cases when the result of classification is false and the actual verb is also in
different class. (Both of our predicted result and the actual classified verb are not in
the correct level.)
• False Positives (FP): when the prediction result is yes and the actual verb is in
different class.
• False Negatives (FN): when the prediction return negative result but the actual is true.
Evaluation of our algorithm was based on unseen data collected from [31] [32]. Moreover, a
threshold of ≥ 50% used to measure the actual level of each verb in [24] [25] [26] [27]. By
comparing the result and the actual level for each verb, we were able to create the confusion matrix
in order to measure the most common measures used to evaluate the performance:
• Accuracy: The simplest metric that can be used for evaluation; it measures the percentage
of inputs in the test set that the classifier correctly labeled [33]. it also can be measured by
calculating TP+TN/TP+FP+FN+TN [34]
• Precision: Indicates how many of our items that we identified were relevant and can be
measured by calculating TP/ (TP+FP) [33].
• Recall: Indicates how many of the relevant items that we identified, and measured by TP/
(TP+FN) [33].
• F1 (or F-Score): combines the precision and recall to give a single score. F1 is defined to
be the harmonic mean of the precision and recall and measured as follow:
(2 × Precision × Recall)/ (Precision Recall) [33].
• Error-Rate (ERR): the calculated number of all incorrect prediction divided by the total
number of the dataset = FP + FN / N [35]
• Macro-Average: To calculate the harmonic mean of precision, recall for all classes
(levels).
The obtained results after processing the test sets in [31] and [32] are summarized in table 1
and table 2.
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Table 1: Evaluation Summary for processing dataset 1
Level /
Measures
Accuracy Precision Recall F1 Error Rate
Knowledge 91% 100% 0.90909909 0.952380952 0.09090909
Comprehensio
n
69% 100% 0.69237692 0.818181818 0.30769231
Application 71% 91% 0.76923769 0.833333333 0.28571429
Analysis 93% 92% 1 0.956521739 0.07142857
Synthesis 76% 100% 0.73684215 0.848484848 0.23809524
Evaluation 100% 100% 1 1 0
Macro-
Average
83% 97% 85% 90% 0.16563992
Table 2: Evaluation Summary for processing dataset 2
Level /
Measures
Accuracy Precision Recall F1 Error rate
Knowledge 91% 100% 91% 0.952380952 0.09090909
Comprehension 69% 100% 67% 0.8 0.30769231
Application 93% 100% 93% 0.962962963 0.07142857
Analysis 93% 75% 100% 0.857142857 0.07142857
Synthesis 76% 93% 76% 0.838709677 0.23809524
Evaluation 75% 100% 73% 0.842105263 0.25
Macro-Average 83% 95% 83% 0.875550286 0.1715923
It can be concluded that the accuracy, precision and recall in each level in our two evaluation tests
are very satisfactory. Moreover, our algorithms’ evaluation overall is very satisfactory as well. In
both our validation and evaluation, we were able to prove that the classification of the action verb
into one or more level of cognitive domain of BT will increase the efficiency of such classification.
This can be used to enhance not only writing learning outcome statements but also classifying the
question into more accurate level semantically.
12. CONCLUSION
We introduced in this work, the classification problem of the questions and LOS into bloom
taxonomy. Our research explored the rules-based approach to induct the most important part of the
question. Such parts, which include the action verb of the question, will lead us to measure the
accurate level of the action verb in the cognitive domain. We also conducted an analysis of
currently used action-verb lists as guides for academicians and proposed a new method to measure
the relation between these verbs, the verb of the question and the learning outcome statements
(LOS). We, as well, adapted similarity measures to provide accurate classification for such verbs
by two methods; using the maximum similarity and calculating the whole similarity area for each
one six of the cognitive domain hierarchy. We have validated and proved that our proposed
solution will improve the classified action verbs into more accurate levels. Later, we evaluated our
proposed method by using the confusion matrix and measured a very high Macro-average of
precisions for all one six of the cognitive domain of BT. In conclusion, this will enhance the
cognitive action verb lists. These lists, however, are being used and cited by academicians to write
LOS and classify their questions based on blooms taxonomy as this work helps provide more
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AUTHORS
Shadi Diab received his M.Sc. degree in computer science from Al-Quds University -
Jerusalem - Palestine in 2017, and his B.Sc. in computer information systems from Al-Quds
Open University, since 2008 he is head of accreditations and internet based testing unit in
Information and Communication Technology Center (ICTC) in Al-Quds Open University -
Palestine
Badie Sartawi received his PhD in Systems Theory and Engineering with major in Computer
Engineering, University of Toledo, Ohio. 1993, Associate Professor at CS & IT department of
Al-Quds University - Jerusalem - Palestine for the past 20 years. He has been involved in the
design of various education and professional ICT programs and he is among those active and
visionary person in the education and ICT community.