This study used multilevel analysis to determine the predictive value of selected intrinsic factors (gender,
computer ownership, mathematics background and computer experience) and institutional type (an
extrinsic factor) on undergraduates’ Self Efficacy in Java Computer Programming (SEiJCP) in South –
West, Nigeria. The study adopted a correlational design. Purposive Sampling was used to select 254
computer science undergraduates from four universities (three federal-owned and one state-owned) in
south-west, Nigeria. Three research questions were answered. Two research instruments namely,
Computer experience scale (r = 0.84) and Java Programming Self Efficacy Scale (JPSES, r = 0.96) were
used to collect data. Data were analysed using descriptive statistics, and null and linear growth model
(LGM) procedures. The intercorrelation coefficients among the extrinsic factor, intrinsic factors and
SEiJCP were moderate. Null model shows that the variations in SEiJCP accounted for by insitutional level
differences was 99.0%. The fixed part of the LGM of intrinsic factors showed that only mathematical
backgroung contributed significantly (p < 0.05) to the prediction of SEiJCP. The random part of the LGM
showed no significant contributions of the interactions of the intrinsic factors, to the prediction of SEiJCP.
About 60.0% of the student level variation in SEiJCP is explained by the differences in intrinsic factors.
The institution – level variable had large predictive value on programming self efficacy. Computer science
departments should increase the number of mathematics courses in their curriculum.
Influence of year of study on computer attitude of business education student...IJITE
The purpose of this study was to examine the attitude to computer among Business Education students in
Lagos State tertiary institutions. The effect of year of study of the Business Education students on
their attitude to computer was studied. Four institutions of higher learning (two universities and two
Colleges of Education) in Lagos State were selected for the study. The sample comprised of 520 Business
Education students. The subjects responded to a computer attitudinal scale and a questionnaire
comprising items on the biodata of respondents. The study adopted the expost-facto research approach as
none of the variables was manipulated. The data collected were analysed using mean, standard deviation
and ANOVA. The statistical package for social sciences (SPSS) software was used to carry out the
analysis. The result revealed the following: year of study had significant effect on the Business
Education students’ attitude to Computer. Useful recommendations as they affect government policies,
delivery of Business Education in our tertiary institutions as well as Business Education students were
made.
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.
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.
Data science for digital culture improvement in higher education using K-mean...IJECEIAES
This study aims to investigate the meaningful pattern that can be used to improve digital culture in higher education based on parameters of the technology acceptance model (TAM). The methodology used is the data mining technique with K-means algorithm and text analytics. The experiment using questionnaire data with 2887 respondents in Universitas Islam Negeri (UIN) Sunan Gunung Djati Bandung. The data analysis and clustering result show that the perceived usefulness and behavioral intention to use information systems are above the normal value, while the perceived ease of use and actual system use is quite low. Strengthened with text analytics, this research found that the EDA and K-means result in harmony with the hope or desire of academic society the information system implementation. This research also found how important the socialization and guidance of information systems, especially the new one information system, in order to improve digital culture in higher education.
The Influence of Participant Personality in Usability TestsCSCJournals
This paper presents the results of a study investigating the impact of participant personality on usability testing. Data were collected from 20 individuals who participated in a series of usability tests. The participants were grouped into 10 introverts and 10 extroverts, and were asked to complete a set of four experimental tasks related to the usability of an academic website. The results of the study revealed that extroverts were more successful than introverts in terms of finding information as well as discovering usability problems, although the types of problems found by both groups were mostly minor. It was also found that extroverts spent more time on tasks but made more mistakes than introverts. From these findings, it is evident that personality dimensions have significant impacts on usability testing outcomes, and thus should be taken into consideration as a key factor of usability testing.
Effects of Developers’ Training on User-Developer Interactions in Information...Jennifer McCauley
The importance of user-developer interactions during the development of an information system has been a long-running theme in information systems research. This research seeks to highlight a gap in the current literature: the contribution of the developer’s formal educational background to the relationship between developers and users. Using an interpretivist epistemology, the researchers employed qualitative interviews to examine how far developers’ perception of the importance of interacting with the user was influenced by their formal education, or the lack thereof. Interviewing both formally and informally trained developers, eleven categories of interest were identified as pertinent to determining the developers’ beliefs about the importance of user interaction. Three of these categories were explored as promising for future research: academic background, work experience, and developer’s access to user knowledge. This research has implications for education of information systems developers as well as for industry interested in hiring software developers.
Influence of year of study on computer attitude of business education student...IJITE
The purpose of this study was to examine the attitude to computer among Business Education students in
Lagos State tertiary institutions. The effect of year of study of the Business Education students on
their attitude to computer was studied. Four institutions of higher learning (two universities and two
Colleges of Education) in Lagos State were selected for the study. The sample comprised of 520 Business
Education students. The subjects responded to a computer attitudinal scale and a questionnaire
comprising items on the biodata of respondents. The study adopted the expost-facto research approach as
none of the variables was manipulated. The data collected were analysed using mean, standard deviation
and ANOVA. The statistical package for social sciences (SPSS) software was used to carry out the
analysis. The result revealed the following: year of study had significant effect on the Business
Education students’ attitude to Computer. Useful recommendations as they affect government policies,
delivery of Business Education in our tertiary institutions as well as Business Education students were
made.
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.
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.
Data science for digital culture improvement in higher education using K-mean...IJECEIAES
This study aims to investigate the meaningful pattern that can be used to improve digital culture in higher education based on parameters of the technology acceptance model (TAM). The methodology used is the data mining technique with K-means algorithm and text analytics. The experiment using questionnaire data with 2887 respondents in Universitas Islam Negeri (UIN) Sunan Gunung Djati Bandung. The data analysis and clustering result show that the perceived usefulness and behavioral intention to use information systems are above the normal value, while the perceived ease of use and actual system use is quite low. Strengthened with text analytics, this research found that the EDA and K-means result in harmony with the hope or desire of academic society the information system implementation. This research also found how important the socialization and guidance of information systems, especially the new one information system, in order to improve digital culture in higher education.
The Influence of Participant Personality in Usability TestsCSCJournals
This paper presents the results of a study investigating the impact of participant personality on usability testing. Data were collected from 20 individuals who participated in a series of usability tests. The participants were grouped into 10 introverts and 10 extroverts, and were asked to complete a set of four experimental tasks related to the usability of an academic website. The results of the study revealed that extroverts were more successful than introverts in terms of finding information as well as discovering usability problems, although the types of problems found by both groups were mostly minor. It was also found that extroverts spent more time on tasks but made more mistakes than introverts. From these findings, it is evident that personality dimensions have significant impacts on usability testing outcomes, and thus should be taken into consideration as a key factor of usability testing.
Effects of Developers’ Training on User-Developer Interactions in Information...Jennifer McCauley
The importance of user-developer interactions during the development of an information system has been a long-running theme in information systems research. This research seeks to highlight a gap in the current literature: the contribution of the developer’s formal educational background to the relationship between developers and users. Using an interpretivist epistemology, the researchers employed qualitative interviews to examine how far developers’ perception of the importance of interacting with the user was influenced by their formal education, or the lack thereof. Interviewing both formally and informally trained developers, eleven categories of interest were identified as pertinent to determining the developers’ beliefs about the importance of user interaction. Three of these categories were explored as promising for future research: academic background, work experience, and developer’s access to user knowledge. This research has implications for education of information systems developers as well as for industry interested in hiring software developers.
A STUDY ON COMPUTER FUNCTIONAL LITERACY AMONG HIGHER SECONDARY SCHOOL STUDENT...S. Raj Kumar
The present study focuses on Computer Functional Literacy of Higher Secondary School students. Computers are continuously being applied to new careers and used in innovative field all the occasion. The skill not only to use computers, but to adapt to progress and added changes in computing technology is essential to any professional-minded person. This ability to apply old information to latest milieu not just allows for the use of computers but can enhance productivity and even pleasure in one's work. This study steps to truly make aware the students for a computer intensive future and this study results revealed that computer functional literacy of higher secondary school students is in moderate level. Normative survey method was used in the present study and Random sampling technique was used. Variables such as types of management, medium of instruction, computer knowledge and locality of the students are significantly differ in this study.
Keywords: Computer, Literacy, Computer Functional Literacy, Higher Secondary School students.
Data Mining Application in Advertisement Management of Higher Educational Ins...ijcax
In recent years, Indian higher educational institute’s competition grows rapidly for attracting students to get enrollment in their institutes. To attract students educational institutes select a best advertisement method. There are different advertisements available in the market but a selection of them is very difficult
for institutes. This paper is helpful for institutes to select a best advertisement medium using some data mining methods.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Digital Tools for the Classroom --ISTE Standards StudentsNAFCareerAcads
Are you interested in engaging your academy students with web tools and apps that help them to solve problems, communicate effectively, and share their learning? Come see national educational technology expert Naomi Harm overview dozens of free online tools and mobile apps that can be used in academies across any theme. And, as a bonus, you’ll see how student technology standards for the International Society for Technology in Education (ISTE) can help guide technology goals and use in your academy.
THE USE OF CLOUD COMPUTING SYSTEMS IN HIGHER EDUCATION; The Lived Experiences of Faculty
Dr. Joseph K. Adjei
School of Technology (SOT)
Ghana Institute of Management and Public Administration (GIMPA)
2nd International Conference of the African Virtual University
PREDICTING ACADEMIC MAJOR OF STUDENTS USING BAYESIAN NETWORKS TO THE CASE OF ...ijcax
In this study, which took place current year in the city of Maragheh in IRAN. Number of high school students in the fields of study: mathematics, Experimental Sciences, humanities, vocational, business and science were studied and compared. The purpose of this research is to predict the academic major of high school students using Bayesian networks. The effective factors have been used in academic major selection for the first time as an effective indicator of Bayesian networks. Evaluation of Impacts of indicators on each other, discretization data and processing them was performed by GeNIe. The proper course would be advised for students to continue their education.
Educational Data Mining (EDM) is one of the crucial application areas of data mining which helps in predicting educational dropout and hence provides timely help to students. In Indian context, predicting educational dropouts is a major problem. By implementing EDM, we can predict the learning habits of the student. At present EDM has not been introduced at higher education level. Due to this we cannot recognize the genuine problems of students during their education. The objective of this analysis is to find the existing gaps in predicting educational dropout and find the missing attributes if any, which my further contribute for better prediction. After that we try to find the best attributes and DM techniques which are frequently used for dropout prediction. Based on the combination of missing attribute and best attribute of student data thus far, a new algorithm can be tested which may overcome the shortcomings of previous work done.
Understanding User’s Acceptance of Personal Cloud Computing: Using the Techno...Maurice Dawson
Personal Cloud Computing (PCC) is a rapidly growing technology, addressing the market demand of individual users for access to available and reliable resources. But like other new technologies, concerns and issues have surfaced with the adoption of PCC. Users deciding whether to adopt PCC may be concerned about the ease of use, usefulness, or security risks in the cloud. Negative attitudes toward using a technology have been found to negatively impact the success of that technology. The purpose of this study was to understand users’ acceptance of PCC. The population sample consisted of individual users within the United States between 18 and 80 years of age. The theoretical framework utilized in this study was based on the technology acceptance model (TAM). A web survey was conducted to assess the measurement and understanding of patterns demonstrated by participants. Our results shows that in spite of the potential benefits of PCC, security and privacy risks are deterring many users from moving towards PCC.
The Architecture of System for Predicting Student Performance based on the Da...Thada Jantakoon
The goals of this study are to develop the architecture of a system for predicting student performance based on data science approaches (SPPS-DSA Architecture) and evaluate the SPPS-DSA Architecture. The research process is divided into two stages: (1) context analysis and (2) development and assessment. The data is analyzed by means of standardized deviations statistically. The research findings suggested that the SPPS-DSA architecture, according to the research findings, consists of three key components: (i) data source, (ii) machine learning methods and attributes, and (iii) data science process. The SPPS-DSA architecture is rated as the highest appropriate overall. Predicting student performance helps educators and students improve their teaching and learning processes. Predicting student performance using various analytical methods is reviewed here. Most researchers used CGPA and internal assessment as data sets. In terms of prediction methods, classification is widely used in educational data science. Researchers most commonly used neural networks and decision trees to predict student performance under classification techniques.
High digital literacy is significantly needed by English teachers in the trend of industrial revolution 4.0 to promote a better quality of English teaching and learning. However, a significant number of English teachers, as well as pre-service teachers, still had low digital literacy scale and they were not ready to implement digital technologies into English teaching and learning process. This study was aimed to describe the digital literacy scale of graduate school students of English Education Department in a state university in Yogyakarta as pre-service teachers and their readiness toward the application of digital technologies in teaching and learning contexts. The research used mix-methods to collect both quantitative and qualitative data through Likert-scale questionnaires and interviews. The study revealed that the research participants had high digital literacy scales and readiness toward the application of digital technologies. Thus, those graduate school students as pre-service teachers could fulfill the requirements of professional English teachers in terms of digital literacy and improve the quality of English teaching and learning output by integrating digital technologies.
CRITERION BASED AUTOMATIC GENERATION OF QUESTION PAPERvivatechijri
In any educational course curriculum, the courses are defined with learning objectives. Teachers conduct assessments to know if students have achieved certain learning objectives or not. The Proposed System provides a solution to choose challenging, well framed questions and make it easy for the user to generate it within a short period of time. The existing tools are rigid and support very basic or limited parameters. In our system we allow admin and user to input a set of questions and mark them with parameters such as difficulty level, complexity, type of question, module, min and max weightage. It contains two modules namely admin module and user module and the question management makes it an effortless task. From the entered input the paper is generated and saved as a .pdf file which can be kept for own or distributed as per the user or admin requirements. The required software and hardware are easily available and easy to work with. The goal is to simplify its current manual method, by means of computerised equipment and complete computer applications, in order to meet its needs, so that its important data/information can be stored for a longer period of time with easy access and manipulation. Basically the project describes how to manage for good performance and better services for the clients.
An Analysis of Behavioral Intention toward Actual Usage of Open Source Softwa...IJAEMSJORNAL
This study focused on analyzing behavioral intention toward the actual usage of open source software in private universities in Tanzania. Questionnaires were used to collect quantitative data in two private universities namely Iringa University and Ruaha Catholic University. Stratified sampling technique was utilized to ensure sample representativeness among two universities where simple random sampling was used to draw a sample from each stratum during the survey. Finding Using Structural Equation Modeling indicated that performance expectancy (source code production and software localization) and social factor (Vendor, internet services provider and lecturer) have a significant influence toward behavioral intention while effort expectancy was found to be insignificant. In addition the behavioral intention was found to be significant toward student’s actual usage of open source software in Universities. This study recommended that for students to develop behavioral intention toward OSS actual usage, internet service provider have to increase the level of internet services that can assist the university communities to access and download open source software. In addition, to increase actual use, open source software vendors and lecturer or experts have to make sure that their software source code is free for distribution and localization, this will increase self-motivation and interest of the students toward actual usage of open source software.
A Survey on Research work in Educational Data Miningiosrjce
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.
INVESTIGATION OF ATTITUDES TOWARDS COMPUTER PROGRAMMING IN TERMS OF VARIOUS V...ijpla
This study aims to determine the attitudes of individuals towards computer programming in terms of
various variables. The study group consists of the students of Kastamonu University Department of
Computer Education and Instructional Technologies Teaching (CEIT), Department of Computer
Engineering, and Department of Computer Programming. Data were collected via Attitude towards
Computer Programming Scale (AtCPS).The results of this study show that students have neutral attitudes
towards computer programming in general. Male computer programming students have significantly
higher attitudes towards programming in comparison to female computer programming students. In
addition, attitude towards computer programming statistically varies by grade. The higher is grade, the
lower is attitude. The more time CEIT and computer programming students spend on computer for
programming purposes daily, the more positive attitudes they have towards programming. Attitude
significantly varies by graduated high school only among CEIT students.
Investigation of Attitudes Towards Computer Programming in Terms of Various V...ijpla
This study aims to determine the attitudes of individuals towards computer programming in terms of
various variables. The study group consists of the students of Kastamonu University Department of
Computer Education and Instructional Technologies Teaching (CEIT), Department of Computer
Engineering, and Department of Computer Programming. Data were collected via Attitude towards
Computer Programming Scale (AtCPS).The results of this study show that students have neutral attitudes
towards computer programming in general. Male computer programming students have significantly
higher attitudes towards programming in comparison to female computer programming students. In
addition, attitude towards computer programming statistically varies by grade. The higher is grade, the
lower is attitude. The more time CEIT and computer programming students spend on computer for
programming purposes daily, the more positive attitudes they have towards programming. Attitude
significantly varies by graduated high school only among CEIT students.
The International Journal of Mechanical Engineering Research and Technology is an international online journal published Quarterly offers fast publication schedule whilst maintaining rigorous peer review. The use of recommended electronic formats for article delivery expedites the process All submitted research articles are subjected to the immediate rapid screening by editors consultation with Editorial Board or others working in the field of appropriate to ensure that they are likely to be the level of interest and importance of appropriate for the journal.
ISSN 2454-535X
International Journal of Mechanical Engineering Research and Technology aims to provide the best possible service to authors of original research articles, and the fairest system of peer review.
The International Journal of Mechanical Engineering Research and Technology is an international online journal in English published Quarterly. This offers a fast publication schedule whilst maintaining rigorous peer review; the use of recommended electronic formats for article delivery expedites the process. All submitted research articles are subjected to immediate rapid screening by the editors, in consultation with the Editorial Board or others working in the field as appropriate, to ensure they are likely to be of the level of interest and importance appropriate for the journal.
Peer tutoring strategy changes the role of instructors no matter what the instructor is an educator or a peer. The well-known method in computer science education, pair programming, is some kind of effective collaborative peer tutoring activity. The advantages of peer tutoring method emphasize similar prior knowledge and languages among peers so as to achieve teaching goals. Data Structure is a very important basic curriculum, regarded as a mandatory course in relevant computer domains of university. However, most of students fail to present their coding skills after learning data structure course. Cooperative learning is an effective learning strategy in which is often applied to education field. Students must work in groups to complete tasks collectively toward academic goals. Pair Programming could decrease errors in coding, increase coding quality and promote programmers confidence, as well as enhance their coding ability. This study incorporates an experimental learning activity, in which the students are asked to write programming codes, which can enhance students’ learning motivation. Then, this study compares the performance of the students with different learning
styles in learning motivation. According the results of Two-way ANOVA, the proposed intervention could increase students learning performance. The reflective-style students could have better learning achievement than active-style ones.
A STUDY ON COMPUTER FUNCTIONAL LITERACY AMONG HIGHER SECONDARY SCHOOL STUDENT...S. Raj Kumar
The present study focuses on Computer Functional Literacy of Higher Secondary School students. Computers are continuously being applied to new careers and used in innovative field all the occasion. The skill not only to use computers, but to adapt to progress and added changes in computing technology is essential to any professional-minded person. This ability to apply old information to latest milieu not just allows for the use of computers but can enhance productivity and even pleasure in one's work. This study steps to truly make aware the students for a computer intensive future and this study results revealed that computer functional literacy of higher secondary school students is in moderate level. Normative survey method was used in the present study and Random sampling technique was used. Variables such as types of management, medium of instruction, computer knowledge and locality of the students are significantly differ in this study.
Keywords: Computer, Literacy, Computer Functional Literacy, Higher Secondary School students.
Data Mining Application in Advertisement Management of Higher Educational Ins...ijcax
In recent years, Indian higher educational institute’s competition grows rapidly for attracting students to get enrollment in their institutes. To attract students educational institutes select a best advertisement method. There are different advertisements available in the market but a selection of them is very difficult
for institutes. This paper is helpful for institutes to select a best advertisement medium using some data mining methods.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Digital Tools for the Classroom --ISTE Standards StudentsNAFCareerAcads
Are you interested in engaging your academy students with web tools and apps that help them to solve problems, communicate effectively, and share their learning? Come see national educational technology expert Naomi Harm overview dozens of free online tools and mobile apps that can be used in academies across any theme. And, as a bonus, you’ll see how student technology standards for the International Society for Technology in Education (ISTE) can help guide technology goals and use in your academy.
THE USE OF CLOUD COMPUTING SYSTEMS IN HIGHER EDUCATION; The Lived Experiences of Faculty
Dr. Joseph K. Adjei
School of Technology (SOT)
Ghana Institute of Management and Public Administration (GIMPA)
2nd International Conference of the African Virtual University
PREDICTING ACADEMIC MAJOR OF STUDENTS USING BAYESIAN NETWORKS TO THE CASE OF ...ijcax
In this study, which took place current year in the city of Maragheh in IRAN. Number of high school students in the fields of study: mathematics, Experimental Sciences, humanities, vocational, business and science were studied and compared. The purpose of this research is to predict the academic major of high school students using Bayesian networks. The effective factors have been used in academic major selection for the first time as an effective indicator of Bayesian networks. Evaluation of Impacts of indicators on each other, discretization data and processing them was performed by GeNIe. The proper course would be advised for students to continue their education.
Educational Data Mining (EDM) is one of the crucial application areas of data mining which helps in predicting educational dropout and hence provides timely help to students. In Indian context, predicting educational dropouts is a major problem. By implementing EDM, we can predict the learning habits of the student. At present EDM has not been introduced at higher education level. Due to this we cannot recognize the genuine problems of students during their education. The objective of this analysis is to find the existing gaps in predicting educational dropout and find the missing attributes if any, which my further contribute for better prediction. After that we try to find the best attributes and DM techniques which are frequently used for dropout prediction. Based on the combination of missing attribute and best attribute of student data thus far, a new algorithm can be tested which may overcome the shortcomings of previous work done.
Understanding User’s Acceptance of Personal Cloud Computing: Using the Techno...Maurice Dawson
Personal Cloud Computing (PCC) is a rapidly growing technology, addressing the market demand of individual users for access to available and reliable resources. But like other new technologies, concerns and issues have surfaced with the adoption of PCC. Users deciding whether to adopt PCC may be concerned about the ease of use, usefulness, or security risks in the cloud. Negative attitudes toward using a technology have been found to negatively impact the success of that technology. The purpose of this study was to understand users’ acceptance of PCC. The population sample consisted of individual users within the United States between 18 and 80 years of age. The theoretical framework utilized in this study was based on the technology acceptance model (TAM). A web survey was conducted to assess the measurement and understanding of patterns demonstrated by participants. Our results shows that in spite of the potential benefits of PCC, security and privacy risks are deterring many users from moving towards PCC.
The Architecture of System for Predicting Student Performance based on the Da...Thada Jantakoon
The goals of this study are to develop the architecture of a system for predicting student performance based on data science approaches (SPPS-DSA Architecture) and evaluate the SPPS-DSA Architecture. The research process is divided into two stages: (1) context analysis and (2) development and assessment. The data is analyzed by means of standardized deviations statistically. The research findings suggested that the SPPS-DSA architecture, according to the research findings, consists of three key components: (i) data source, (ii) machine learning methods and attributes, and (iii) data science process. The SPPS-DSA architecture is rated as the highest appropriate overall. Predicting student performance helps educators and students improve their teaching and learning processes. Predicting student performance using various analytical methods is reviewed here. Most researchers used CGPA and internal assessment as data sets. In terms of prediction methods, classification is widely used in educational data science. Researchers most commonly used neural networks and decision trees to predict student performance under classification techniques.
High digital literacy is significantly needed by English teachers in the trend of industrial revolution 4.0 to promote a better quality of English teaching and learning. However, a significant number of English teachers, as well as pre-service teachers, still had low digital literacy scale and they were not ready to implement digital technologies into English teaching and learning process. This study was aimed to describe the digital literacy scale of graduate school students of English Education Department in a state university in Yogyakarta as pre-service teachers and their readiness toward the application of digital technologies in teaching and learning contexts. The research used mix-methods to collect both quantitative and qualitative data through Likert-scale questionnaires and interviews. The study revealed that the research participants had high digital literacy scales and readiness toward the application of digital technologies. Thus, those graduate school students as pre-service teachers could fulfill the requirements of professional English teachers in terms of digital literacy and improve the quality of English teaching and learning output by integrating digital technologies.
CRITERION BASED AUTOMATIC GENERATION OF QUESTION PAPERvivatechijri
In any educational course curriculum, the courses are defined with learning objectives. Teachers conduct assessments to know if students have achieved certain learning objectives or not. The Proposed System provides a solution to choose challenging, well framed questions and make it easy for the user to generate it within a short period of time. The existing tools are rigid and support very basic or limited parameters. In our system we allow admin and user to input a set of questions and mark them with parameters such as difficulty level, complexity, type of question, module, min and max weightage. It contains two modules namely admin module and user module and the question management makes it an effortless task. From the entered input the paper is generated and saved as a .pdf file which can be kept for own or distributed as per the user or admin requirements. The required software and hardware are easily available and easy to work with. The goal is to simplify its current manual method, by means of computerised equipment and complete computer applications, in order to meet its needs, so that its important data/information can be stored for a longer period of time with easy access and manipulation. Basically the project describes how to manage for good performance and better services for the clients.
An Analysis of Behavioral Intention toward Actual Usage of Open Source Softwa...IJAEMSJORNAL
This study focused on analyzing behavioral intention toward the actual usage of open source software in private universities in Tanzania. Questionnaires were used to collect quantitative data in two private universities namely Iringa University and Ruaha Catholic University. Stratified sampling technique was utilized to ensure sample representativeness among two universities where simple random sampling was used to draw a sample from each stratum during the survey. Finding Using Structural Equation Modeling indicated that performance expectancy (source code production and software localization) and social factor (Vendor, internet services provider and lecturer) have a significant influence toward behavioral intention while effort expectancy was found to be insignificant. In addition the behavioral intention was found to be significant toward student’s actual usage of open source software in Universities. This study recommended that for students to develop behavioral intention toward OSS actual usage, internet service provider have to increase the level of internet services that can assist the university communities to access and download open source software. In addition, to increase actual use, open source software vendors and lecturer or experts have to make sure that their software source code is free for distribution and localization, this will increase self-motivation and interest of the students toward actual usage of open source software.
A Survey on Research work in Educational Data Miningiosrjce
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.
INVESTIGATION OF ATTITUDES TOWARDS COMPUTER PROGRAMMING IN TERMS OF VARIOUS V...ijpla
This study aims to determine the attitudes of individuals towards computer programming in terms of
various variables. The study group consists of the students of Kastamonu University Department of
Computer Education and Instructional Technologies Teaching (CEIT), Department of Computer
Engineering, and Department of Computer Programming. Data were collected via Attitude towards
Computer Programming Scale (AtCPS).The results of this study show that students have neutral attitudes
towards computer programming in general. Male computer programming students have significantly
higher attitudes towards programming in comparison to female computer programming students. In
addition, attitude towards computer programming statistically varies by grade. The higher is grade, the
lower is attitude. The more time CEIT and computer programming students spend on computer for
programming purposes daily, the more positive attitudes they have towards programming. Attitude
significantly varies by graduated high school only among CEIT students.
Investigation of Attitudes Towards Computer Programming in Terms of Various V...ijpla
This study aims to determine the attitudes of individuals towards computer programming in terms of
various variables. The study group consists of the students of Kastamonu University Department of
Computer Education and Instructional Technologies Teaching (CEIT), Department of Computer
Engineering, and Department of Computer Programming. Data were collected via Attitude towards
Computer Programming Scale (AtCPS).The results of this study show that students have neutral attitudes
towards computer programming in general. Male computer programming students have significantly
higher attitudes towards programming in comparison to female computer programming students. In
addition, attitude towards computer programming statistically varies by grade. The higher is grade, the
lower is attitude. The more time CEIT and computer programming students spend on computer for
programming purposes daily, the more positive attitudes they have towards programming. Attitude
significantly varies by graduated high school only among CEIT students.
The International Journal of Mechanical Engineering Research and Technology is an international online journal published Quarterly offers fast publication schedule whilst maintaining rigorous peer review. The use of recommended electronic formats for article delivery expedites the process All submitted research articles are subjected to the immediate rapid screening by editors consultation with Editorial Board or others working in the field of appropriate to ensure that they are likely to be the level of interest and importance of appropriate for the journal.
ISSN 2454-535X
International Journal of Mechanical Engineering Research and Technology aims to provide the best possible service to authors of original research articles, and the fairest system of peer review.
The International Journal of Mechanical Engineering Research and Technology is an international online journal in English published Quarterly. This offers a fast publication schedule whilst maintaining rigorous peer review; the use of recommended electronic formats for article delivery expedites the process. All submitted research articles are subjected to immediate rapid screening by the editors, in consultation with the Editorial Board or others working in the field as appropriate, to ensure they are likely to be of the level of interest and importance appropriate for the journal.
Peer tutoring strategy changes the role of instructors no matter what the instructor is an educator or a peer. The well-known method in computer science education, pair programming, is some kind of effective collaborative peer tutoring activity. The advantages of peer tutoring method emphasize similar prior knowledge and languages among peers so as to achieve teaching goals. Data Structure is a very important basic curriculum, regarded as a mandatory course in relevant computer domains of university. However, most of students fail to present their coding skills after learning data structure course. Cooperative learning is an effective learning strategy in which is often applied to education field. Students must work in groups to complete tasks collectively toward academic goals. Pair Programming could decrease errors in coding, increase coding quality and promote programmers confidence, as well as enhance their coding ability. This study incorporates an experimental learning activity, in which the students are asked to write programming codes, which can enhance students’ learning motivation. Then, this study compares the performance of the students with different learning
styles in learning motivation. According the results of Two-way ANOVA, the proposed intervention could increase students learning performance. The reflective-style students could have better learning achievement than active-style ones.
Graduates of computer science programs often lack skills that employers desire among software
developers. These include, for example, weaknesses in the areas of collaboration, communication, and
software testing. Further research can help to refine this list by providing insight into additional skills that
are of rising or regional importance. This paper therefore presents a study aimed at uncovering desirable
technical and soft skills for graduates of computer science in the Pacific Northwest region of the United
States. Interviews of 11 employers, including both managers and recruiters, highlighted the prominent
importance of skills related to web development, relational databases, and testing. Additionally, it
spotlighted not only widely-recognized soft skills such as those related to collaboration and
communication, but additionally on skills tied to personal attributes such as innovating, coping with
ambiguity and learning quickly. The results provide insights for what skills and personal attributes to
include in a future survey of employers aimed at quantifying the importance of skills on this list.
EMPLOYERS’ NEEDS FOR COMPUTER SCIENCE, INFORMATION TECHNOLOGY AND SOFTWARE EN...ijcseit
Graduates of computer science programs often lack skills that employers desire among software
developers. These include, for example, weaknesses in the areas of collaboration, communication, and
software testing. Further research can help to refine this list by providing insight into additional skills that
are of rising or regional importance. This paper therefore presents a study aimed at uncovering desirable
technical and soft skills for graduates of computer science in the Pacific Northwest region of the United
States. Interviews of 11 employers, including both managers and recruiters, highlighted the prominent
importance of skills related to web development, relational databases, and testing. Additionally, it
spotlighted not only widely-recognized soft skills such as those related to collaboration and
communication, but additionally on skills tied to personal attributes such as innovating, coping with
ambiguity and learning quickly. The results provide insights for what skills and personal attributes to
include in a future survey of employers aimed at quantifying the importance of skills on this list.
EMPLOYERS’ NEEDS FOR COMPUTER SCIENCE, INFORMATION TECHNOLOGY AND SOFTWARE EN...ijcseit
Graduates of computer science programs often lack skills that employers desire among software
developers. These include, for example, weaknesses in the areas of collaboration, communication, and
software testing. Further research can help to refine this list by providing insight into additional skills that
are of rising or regional importance. This paper therefore presents a study aimed at uncovering desirable
technical and soft skills for graduates of computer science in the Pacific Northwest region of the United
States. Interviews of 11 employers, including both managers and recruiters, highlighted the prominent
importance of skills related to web development, relational databases, and testing. Additionally, it
spotlighted not only widely-recognized soft skills such as those related to collaboration and
communication, but additionally on skills tied to personal attributes such as innovating, coping with
ambiguity and learning quickly. The results provide insights for what skills and personal attributes to
include in a future survey of employers aimed at quantifying the importance of skills on this list.
EMPLOYERS’ NEEDS FOR COMPUTER SCIENCE, INFORMATION TECHNOLOGY AND SOFTWARE EN...ijcseit
Graduates of computer science programs often lack skills that employers desire among software
developers. These include, for example, weaknesses in the areas of collaboration, communication, and
software testing. Further research can help to refine this list by providing insight into additional skills that
are of rising or regional importance. This paper therefore presents a study aimed at uncovering desirable
technical and soft skills for graduates of computer science in the Pacific Northwest region of the United
States. Interviews of 11 employers, including both managers and recruiters, highlighted the prominent
importance of skills related to web development, relational databases, and testing. Additionally, it
spotlighted not only widely-recognized soft skills such as those related to collaboration and
communication, but additionally on skills tied to personal attributes such as innovating, coping with
ambiguity and learning quickly. The results provide insights for what skills and personal attributes to
include in a future survey of employers aimed at quantifying the importance of skills on this list.
Test Anxiety as a Predictor of Secondary School Students’ Achievement in Comp...ijtsrd
The study investigated test anxiety as a predictor of secondary school students’ achievement in computer studies. Two research questions guided the study and two hypotheses were tested at 0.05 level of significance. Correlation design was adopted for the study. The population of the study was 11, 789 senior secondary year two SS2 students offering Computer studies in Delta North Senatorial district of Delta state. A sample of 600 students obtained using multi stage sampling procedure was involved in the study. The instrument for data collection was Test Anxiety Questionnaire TAQ validated by lecturers in Departments of Science Education and Educational Foundations, from Nnamdi Azikiwe University, Awka. The reliability of the instruments were established using Cronbach Alpha which yielded coefficient values of 0.77. Data were generated for the study through the administration of the instruments with the aid of five research assistants. The data obtained were analyzed using simple and multiple linear regressions. The findings of the study revealed that 0.6 of the variance in computer studies achievement was predicted by students’ test anxiety. Also, achievement in computer studies was significantly predicted by test anxiety. It was recommended that school teachers should ensure to cover the scheme of work at the appropriate time, to enable students study them in sequential order and in a way that will enable prepare for test. This should be done to reduce the study load that result in cognitive overload and test anxiety. Imene, Akpoguma Lugard | Prof. A. M. Osuafor "Test Anxiety as a Predictor of Secondary School Students’ Achievement in Computer Studies in Delta State" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-2 , April 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd56250.pdf Paper URL: https://www.ijtsrd.com.com/humanities-and-the-arts/education/56250/test-anxiety-as-a-predictor-of-secondary-school-students’-achievement-in-computer-studies-in-delta-state/imene-akpoguma-lugard
Multiple educational data mining approaches to discover patterns in universit...IJICTJOURNAL
This paper presented the utilization of pattern discovery techniques by using multiple relationships and clustering educational data mining approaches to establish a knowledge base that will aid in the prediction of ideal college program selection and enrollment forecasting for incoming freshmen. Results show a significant level of accuracy in predicting college programs for students by mining two years of student college admission and graduation final grade scholastic records. The results of educational predictive data mining methods can be applied in improving the services of the admission department of an educational institution, particularly in its course alignment, student mentoring, admission forecast, marketing, and enrollment preparedness.
A SURVEY OF EMPLOYERS’ NEEDS FOR TECHNICAL AND SOFT SKILLS AMONG NEW GRADUATESijcseit
ABSTRACT
Motivated by concern about the ability of graduates to succeed in the workforce, universities frequently conduct surveys of local and regional employers, to understand those companies’ expectations. These can uncover specific needs not being addressed. Following a similar line of inquiry, prior research at Oregon State University interviewed employers, with the aim of identifying skills of concern. The current paper takes this research another step further by presenting a survey-based study aimed at quantifying the prevalence and level of employers’ desire for workers who have these identified skills. Although all skills were rated as moderately useful or better, most soft skills scored higher than most technical skills. Nonetheless, three technical skills (source code versioning, testing and agile methods) scored approximately as well as the soft skills; these three technical skills, like soft skills, were cross-cutting and applicable to more than one software development context. Further survey questions revealed that employers preferred that, to the extent that students focus on building technical skill, these learning experiences ideally should involve creating software that students can use as evidence of their qualifications.
A SURVEY OF EMPLOYERS’ NEEDS FOR TECHNICAL AND SOFT SKILLS AMONG NEW GRADUATES ijcseit
Motivated by concern about the ability of graduates to succeed in the workforce, universities frequently
conduct surveys of local and regional employers, to understand those companies’ expectations. These can
uncover specific needs not being addressed. Following a similar line of inquiry, prior research at Oregon
State University interviewed employers, with the aim of identifying skills of concern. The current paper
takes this research another step further by presenting a survey-based study aimed at quantifying the
prevalence and level of employers’ desire for workers who have these identified skills. Although all skills
were rated as moderately useful or better, most soft skills scored higher than most technical skills.
Nonetheless, three technical skills (source code versioning, testing and agile methods) scored
approximately as well as the soft skills; these three technical skills, like soft skills, were cross-cutting and
applicable to more than one software development context. Further survey questions revealed that
employers preferred that, to the extent that students focus on building technical skill, these learning
experiences ideally should involve creating software that students can use as evidence of their
qualifications.
A SURVEY OF EMPLOYERS’ NEEDS FOR TECHNICAL AND SOFT SKILLS AMONG NEW GRADUATES ijcseit
Motivated by concern about the ability of graduates to succeed in the workforce, universities frequently
conduct surveys of local and regional employers, to understand those companies’ expectations. These can
uncover specific needs not being addressed. Following a similar line of inquiry, prior research at Oregon
State University interviewed employers, with the aim of identifying skills of concern. The current paper
takes this research another step further by presenting a survey-based study aimed at quantifying the
prevalence and level of employers’ desire for workers who have these identified skills. Although all skills
were rated as moderately useful or better, most soft skills scored higher than most technical skills.
Nonetheless, three technical skills (source code versioning, testing and agile methods) scored
approximately as well as the soft skills; these three technical skills, like soft skills, were cross-cutting and
applicable to more than one software development context. Further survey questions revealed that
employers preferred that, to the extent that students focus on building technical skill, these learning
experiences ideally should involve creating software that students can use as evidence of their
qualifications.
A SURVEY OF EMPLOYERS’ NEEDS FOR TECHNICAL AND SOFT SKILLS AMONG NEW GRADUATES ijcseit
Motivated by concern about the ability of graduates to succeed in the workforce, universities frequently
conduct surveys of local and regional employers, to understand those companies’ expectations. These can
uncover specific needs not being addressed. Following a similar line of inquiry, prior research at Oregon
State University interviewed employers, with the aim of identifying skills of concern. The current paper
takes this research another step further by presenting a survey-based study aimed at quantifying the
prevalence and level of employers’ desire for workers who have these identified skills. Although all skills
were rated as moderately useful or better, most soft skills scored higher than most technical skills.
Nonetheless, three technical skills (source code versioning, testing and agile methods) scored
approximately as well as the soft skills; these three technical skills, like soft skills, were cross-cutting and
applicable to more than one software development context. Further survey questions revealed that
employers preferred that, to the extent that students focus on building technical skill, these learning
experiences ideally should involve creating software that students can use as evidence of their
qualifications.
A SURVEY OF EMPLOYERS’ NEEDS FOR TECHNICAL AND SOFT SKILLS AMONG NEW GRADUATES ijcseit
Motivated by concern about the ability of graduates to succeed in the workforce, universities frequently
conduct surveys of local and regional employers, to understand those companies’ expectations. These can
uncover specific needs not being addressed. Following a similar line of inquiry, prior research at Oregon
State University interviewed employers, with the aim of identifying skills of concern. The current paper
takes this research another step further by presenting a survey-based study aimed at quantifying the
prevalence and level of employers’ desire for workers who have these identified skills. Although all skills
were rated as moderately useful or better, most soft skills scored higher than most technical skills.
Nonetheless, three technical skills (source code versioning, testing and agile methods) scored
approximately as well as the soft skills; these three technical skills, like soft skills, were cross-cutting and
applicable to more than one software development context. Further survey questions revealed that
employers preferred that, to the extent that students focus on building technical skill, these learning
experiences ideally should involve creating software that students can use as evidence of their
qualifications.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
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
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.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
MULTILEVEL ANALYSIS OF FACTORS PREDICTING SELF EFFICACY IN COMPUTER PROGRAMMING
1. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.2, June 2014
DOI :10.5121/ijite.2014.3203 19
MULTILEVEL ANALYSIS OF FACTORS
PREDICTING SELF EFFICACY IN
COMPUTER PROGRAMMING
1
Owolabi J. And 2
Adegoke B.A
1
Federal College of Education (Technical), Akoka, Lagos,
Nigeria
2
University of Ibadan, Ibadan, Oyo State, Nigeria
ABSTRACT
This study used multilevel analysis to determine the predictive value of selected intrinsic factors (gender,
computer ownership, mathematics background and computer experience) and institutional type (an
extrinsic factor) on undergraduates’ Self Efficacy in Java Computer Programming (SEiJCP) in South –
West, Nigeria. The study adopted a correlational design. Purposive Sampling was used to select 254
computer science undergraduates from four universities (three federal-owned and one state-owned) in
south-west, Nigeria. Three research questions were answered. Two research instruments namely,
Computer experience scale (r = 0.84) and Java Programming Self Efficacy Scale (JPSES, r = 0.96) were
used to collect data. Data were analysed using descriptive statistics, and null and linear growth model
(LGM) procedures. The intercorrelation coefficients among the extrinsic factor, intrinsic factors and
SEiJCP were moderate. Null model shows that the variations in SEiJCP accounted for by insitutional level
differences was 99.0%. The fixed part of the LGM of intrinsic factors showed that only mathematical
backgroung contributed significantly (p < 0.05) to the prediction of SEiJCP. The random part of the LGM
showed no significant contributions of the interactions of the intrinsic factors, to the prediction of SEiJCP.
About 60.0% of the student level variation in SEiJCP is explained by the differences in intrinsic factors.
The institution – level variable had large predictive value on programming self efficacy. Computer science
departments should increase the number of mathematics courses in their curriculum.
KEYWORDS
Multilevel analysis, Self Efficacy, Java Computer Programming, Intrinsic factors, Extrinsic factors
1.INTRODUCTION
Self-efficacy is an important psychological construct which requires attention in research as it
influences (i) the choice of activities that an individual takes part in; (ii) the amount of effort they
will expend in performing a task and (iii) how long they will persevere in the face of stressful
situations in completing that task [1]. Social cognitive theory posits that a strong sense of self-
efficacy leads individuals to undertake challenging tasks, expend greater effort in accomplishing
a given task, persist longer in the face of adversaries [2].
Of the various factors that affects individual’s willingness and ability to interact with computers
examined in past research, computer self-efficacy (CSE) has been identified as a key determinant
of computer related ability (including programming) and use of computer [3].
Research findings show that higher levels of perceived self-efficacy correlate to greater
motivational efforts and perseverance [4]. Self efficacy theory, according to has emerged as an
2. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.2, June 2014
20
important means of understanding and predicting a person’s performance [5]. According to [6],
higher levels of computer self-efficacy correspond to greater achievement of computer
competence. Given the research evidence on the influence of self-efficacy outlined above, it is
reasonable to think that high self-efficacy in computer programming might play an important role
in learning and writing programs and consequently producing competent and effective
programmers in our nation. There is therefore the need to study factors that influence self efficacy
itself.
Perceived self-efficacy in programming was seen to affect performance in programming courses
[7]. There seems to be no research report yet on factors predicting self efficacy in computer
programming in Nigeria. No doubt, computer undergradutes’ self efficacy are functions of many
factors ranging from intrinsic to extrinsic factors. The intrinsic factors are those in which the
student himself or herself has a significant input or part of the real nature of the student such as
his or her gender, computer experience, locus of control, mathematics background, computer
ownership and number of programming courses before entering JAVA class; while the extrinsic
factors are those in which the student has little or no significant input, or not part of real nature of
the student such as the type of institution which he or she attends.
Studies on the relationship between computer experience and computer programming self-
efficacy and achievement are very rare. In a study of factors related to JAVA programming self
efficacy among engineering students in Turkey it was discovered that the number of years of
computer experience had a significant linear contribution to JAVA programming self efficacy
scores [5]. However, in a similar study among engineering students in a University in south- west,
Nigeria it was found that the number of years of experience in programming did not significantly
predict JAVA programming self-efficacy scores [8].
In research, relationship between gender and computer self-efficacy has been of regular interest,
possibly because the computer was seen as a skill area for the male folks. So far, findings on
gender influence on computer self-efficacy are mixed. [6] found no gender differences in
computer self-efficacy. [9] observed gender differences in perceived self-efficacy regarding
completion of complex tasks in both word processing and spreadsheet software (with males
having higher CSE scores). In the same study, no gender differences were found in self-efficacy
regarding simple computer tasks. In another study of factors related to self efficacy for Java
programming among engineering students in Turkey males had higher programming self-efficacy
[5].
Mathematics achievement has also been identified in literature as a factor that affects computer
programming [10,11,12]. A possible reason for this could be because mathematics problem
solving and programming require similar skills and ability to succeed. Mathematics ability,
measured as achievement is however different from mathematics background. The number of
mathematics courses taken by the respondents before the study was used as the mathematics
background.
The relationship between computer ownership and computer self-efficacy has never been found
to be consistent in previous findings. [13] in in a study found that owning a computer is
significantly correlated with computer self efficacy. [9]found that students who have access to
their own computer cooperated more in front of the computer than any other group. However,
owning a computer was not found to be a significant predictor of computer self-efficacy [4].
3. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.2, June 2014
21
In this study, the data is multilevel in nature, because respondents ( the students) are nested within
their institutions. When this happens, one option will be to carry out institutional analysis by
aggregating students’ characteristics over their institutions. There is no doubt that in the process,
all individual information is lost. Most times, within group variation which accounts for most of
the total variation in the outcome is lost. The loss of individual information therefore can have an
adverse effect on the analysis and also lead to distortion of relationships between variables.
Another option is to disaggregate the data by assigning institutional data to individual students.
By this, the assumption of independent observation would no longer hold. In hierarchical data,
individuals in the same group are also likely to be more similar than individuals in the different
groups. Therefore the variations in outcome may be due to difference between groups and to
individual difference within a group.
Researchers have shown little or no interest in identifying variables that are likely to influence
undergraduates’ computer programming self-efficacy. Also multilevel data collected for this
study is best analysed using multilevel data analysis approach. This study therefore sought to use
multilevel analysis to determine the extent to which selected students’ intrinsic factors (gender,
computer ownership, mathematics background and computer experience) and type of institutions
can predict undergraduates’ self efficacy in programming.
1.1Research Questions
1. The study sought answers to the following research questions.
2. What type of relationship exist among students’ gender, computer ownership,
mathematics background, computer experience, institution type and SEiJCP ?
3. How much of the total variance in SEiJCP of computer undergraduates is accounted for
by institution-level and student-level differences?
4. How much of the student-level variance in SEiJCP of computer undergraduates is
associated with gender, computer ownership, mathematics background and computer
experience?
2.METHODOLOGY
2.1Participants
This study adopted purposive sampling for the selection of participants’ universities and levels of
study. The Universities of respondents were selected based on the following criteria: (i)The
university is owned by federal or state government, (ii) There is a computer science department
where computer professionals are being trained, (iii) Java programming language is taught in the
computer science department of the university. In all, at the time of the study, five (5)
Universities within the South – West, Nigeria satisfied the three criteria above. One of the five
was used for the trial testing, validation and reliability of the instruments before the main study.
The remaining four (4) Universities were used for the real study. The computer undergraduates in
the four Universities, who had been taught JAVA programming language and were willing to
participate in the study formed the sample for this study.
4. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.2, June 2014
22
The levels of the participants for the study were selected based on the following criterium (i) the
students at that level had been taught Java in the previous or current semester, For those who are
currently on it, they had covered enough ground to enable them answer the questions set.
Different levels based on the programmes and peculiarities of each Universities were therefore
used. Each participant used was selected based on the following criteria: (i.) he / she is a full time
student in the department of computer science in any of the chosen Universities, (ii.) he / she had
been taught Java programming Language, (iii.) he / she is available at the time of data collection,
(iv.) he / she is patient and willing to participate in the study. All the students in the selected
levels that were available were served the questionnaire. Some of the questionnaires were
however not returned. Some that were returned were not properly filled. After scrutinisng the
returned questionnaires, those that were properly filled were used for the study. A total of 254
questionnaires that were properly filled were used for the study.
2.2Variables and Measurement Instruments
The variables involved in the study are as follows:
Predictor variables: (i) Gender (ii) Computer Ownership (iii) Mathematics Background,
(iv) Computer Experiences (v) Type of institution
Criterion variable: Self Efficacy in Java Computer Programming (SEiJCP).
Two instruments were used in the study. They were: (i) Student background questionnaire (SBQ)
and (ii) JAVA Programming Self Efficacy Scale (JPSES).
2.2.1Student background questionnaire (SBQ)
Student background questionnaire (SBQ) was used to obtain data on the biography of
undergraduate computer students. Specifically, data on the following variables were collected
with the use of the SBQ: (i) Gender (ii) Computer Ownership (iii) Mathematics Background (iv)
Computer Experience and (v)student’s institution. Computer experience is multidimensional.
Different aspects of this variable is therefore highlighted in this work.Specifically the following
10 areas of computing were highlighted:Word Processing, Spread Sheet, Data Base, Presentation
Software, Operating System Software, Computer Graphics, Computer Games, Internet, Statistical
Package, Programming. The participants were given instruction to rate their experiences in the
different areas of computing using a scale of 1 to 10. Maximum score obtainable is 100 while the
minimum score is 10. The scale was also trial – tested on computer undergraduates (a group
parallel to the subjects of the main study). The aim was to establish its reliability among computer
undergraduates in South –West, Nigeria. The reliability coefficient using Cronbach Alpha was
found to be 0.84. It was therefore found to be very reliable and fit for the study. For Mathematics
background, the study considered the number of mathematics courses taken in the University
before entering the Java class.
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2.2.2Java Programming Self Efficacy Scale (JPSES)
The Java Programming Self Efficacy Scale (JPSES) is the adapted version of the C++
programming self Efficacy scale of [7]. It was designed by [5]. It consisted of 32 items bothering
on respondents’ understanding of certain concepts in the language, possession and the ability to
display certain skills as well as the will to persevere when writing the programs in JAVA. The
participants were given instructions to rate their confidence in understanding and doing the JAVA
programming related tasks using a scale of 1 (Not confident at all) to 7 (Absolutely confident).
Maximum score obtainable is 224, while the minimum score is 32. [5] administered it to
Engineering undergraduates in Turkey who had been instructed in JAVA programming. The
reliability was found to be 0.99. The same instrument was trial tested on Computer
undergraduates on a group parallel to the subjects of the main study who had also been instructed
on JAVA programming. The aim was to establish its reliability among Computer undergraduates
in South-West, Nigeria. The reliabilty coefficient was found to be 0.96. It was found to be very
reliable and fit to be used. The instrument was therefore adopted for the study.
2.2.3Data Analysis Procedure
The data collected was analysed using the Statistical Package for Social Sciences (SPSS) version
17.0 and Linear Structural Relations (LISREL) version 8.80 (Jӧreskog & Sӧrbom, 2006). The
following statistical procedures were used: Mean, Standard Deviation, Pearson Product Moment
Correlation (PPMC) Coefficient (Research Questions 1) and Multilevel Analysis using LISREL
(Research Questions 2 and 3).
3.RESULT AND DISCUSSION
Table 1 presents the intercorrelation matrix of the correlation coefficients of the selected student
background variable (gender, computer ownership, mathematics background and computer
experience), type of institution and SEiJCP .
Table 1: Inter correlation Matrix of Intrinsic and Extrinsic factors and SEiJCP.
Var GD MB CE CO INST SEiJCP
Gd 1.000
MB 0.091 1.000
CE 0.226* 0.232* 1.000
CO 0.009 -0.225* 0.024 1.000
INST 0.010 .481* .214* 0.260* 1.000
SEiJCP 0.104 0.270* 0.468* 0.081 0.431* 1.000
Mean 1.30 4.58 53.07 1.17 1.24 139.55
SD 0.46 2.40 14.98 0.38 0.26 44.15
Note: Gd = Gender; CO = Computer Ownership; MB = Mathematics Bachground; CE = Computer
Experience; JPSES = JAVA programming Self Efficacy Scores; INS Institution-level differences.. * p < .05
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Table 1 above showed that the main criterion which is SEiJCP, has positive and significant
relationship with mathematics background (r = 0.270, p < 0.05) and computer experience (r =
0.468, p < 0.05), therefore as the number of mathematics courses taken and the computer
experiences increase, there is the tendency for increase in programming self efficacy among
computer undergraduates. The relationship between institution-level differences and mathematics
background (r = 0.481, p < 0.05), computer owneship (r = 0.260, p < 0.05), and computer
experience (r = 0.214, p < 0.05) are statistically significant.
This finding of a significant relationship between computer experience and SEiJCP is in
agreement with the findings of [14]. [8] however found out that number of years of programming
experience and SEiJCP were not significantly related. The inconsistency in the finding of this
study and that of [8] might have occured because Jegede’s respondents were non computer
majors (Engineering students) while this study used computer majors. For a non – computer
major, longer years of programming experience may not be a good predictor of skill acquisition
or self confidence in programming. Where there is no consistency in computer usage, years of
computer usage might not be a good measure of computer experience. Also, consistency in
utilisation of computer should be better among computer majors compared to their non computer
major counterparts.
Mathematics background in this study was also found to have a relationship which is positive and
significant with Java programming self efficacy. This finding could be because mathematics
problem solving and programming require similar skills and ability to succeed. According to [10],
problem solving strategies employed in a traditional college mathematics course are essentially
the same in a first course in computer programming.
To answer research question two, a multilevel analysis was conducted with ordinary least square
option of LISREL. The model used is known as null model in that only the intercept of
institution-level (macro level) was entered. That is, the focus was on variance decomposition of
SEiJCP on the basis of student-level differences (level 1) and institution-level differences (level
2).
Statistically, the null modelling for variance decomposition of self efficacy is given by
SEiJCP ij = β0 + u0i + eij ; Where SEiJCP ij represents score “j” for student “i”; β0 represents the
intercept of the fixed part of the model and uoi represents the random variation in intercepts at
level – 2 of the model and eij denotes the random variation at level – 1 of the model. Tables 2 and
3 present the fixed part of the model and random part of the model.
Table 2: Fixed Part of the Null Model for SEiJCP
Co-efficients BETA-HAT STD.ERR Z – VALUE PROB MODEL-FIT
Intercept 9.15 6.00 1.52 0.13 2495.86
The results in Table 2 indicate that the intercept of the fixed part of the model is 9.15 and it is not
statistically significant (p > .05).
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Table 3: Random Part of the Null Model for SEiJCP
LEVEL THAU – HAT STD.ERROR Z – VALUE PROB
LEVEL2
Intercept / intercept
4.01 15.40 0.26 0.795
LEVEL 1
Intercept / intercept
301.37 0.00 0.00 0.000
We estimate the total variance in Java programming Self efficacy by using equation 1 below:
= Total Variance .............................................................................................(1)
Where represent between group variability (Variance of level-2) and represent within group
variability (variance of level-1).
From table 3, = 4.01 and = 301.37
:. Total variance in Programming self efficacy = ........................................(2)
This is given as = = 0.99
Therefore the total variance in SEiJCP accounted for by institution-level differences is 0.99. This
result indicates that about 99.0% of the total variation in programming self efficacy is explained
by the differences in institution.
To obtain total variance accounted for by student-level differences (level 1) we use the formula.
Micro level differences for null model = 1 – Total variance at level 2
This gives 1 – 0.99 = 0.01
Therefore total variance accounted for by student-level differences is about 1.0%.
The results of this study indicated that 99.0% of the total variation in SEiJCP was accounted for
by institution–level differences. The remaining 1.0% was accounted for by the student-level
differences. Institutional – level differences contributed more to variation in SEiJCP in this study
compared to student level contributions. It then follows that institution – level differences play a
significant role in determining the confidence computer undergraduates have in their ability to
program. This claim could be supported by the finding of [15] in a study carried out to determine
the extent to which teacher self efficacy and students mathematics self efficacy could enhance
secondary school students’ achievement. In that study, it was found that teachers frequent use of
mathematics homework and level of interest and enjoyment of mathematics as well as their
ability and competence in teaching mathematics played a key role in promoting students
mathematics self efficacy. To boost students’ SEiJCP, students should not only be the focus, the
institutions must also create an enabling environment.
To answer research question three, a multilevel analysis was conducted with ordinary least square
option of LISREL. The model used is known as model 1 in that explanatory variables of student-
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level differences plus the intercept of institution-level (macro level) were entered. That is, the
focus was on linear growth model with random intercepts and their slopes
Statistically, the null modelling for variance decomposition of SEiJCP is given by
SEiJCP ij = β0 +β1 X Gdij +u0i +uij XGdij+ β2 X COij +u0i +uij XCOij + β3 X CEij +u0i +uij XCEij
+β4X MBij +u0i +uij XMBijeij
Where SEiJCP ij represents score “j” for student “i”; β0 represents the intercept of the fixed part of
the model and uoi represents the random variation in intercepts at level – 2 of the model and eij
denotes the random variation at level – 1 of the model,uij represents the random variation in
slopes for each of the intrinsic factors. Tables 4 and 5 present the fixed part of the model and
random part of the model.
Table 4: Fixed Part of the Linear Growth Model 1 of Intrinsic factors
COEFFICIENTS BETA-HAT STD.ERR Z-VALUE PR > |Z|
Intcept 7.81 8.34 0.94 0.349
Gender 2.43 2.58 0.94 0.347
Owncomp 1.57 3.59 -0.44 0.661
Mathematics bgd 1.34 0.64 2.10 0.040
COMPEXP -0.02 0.09 -0.18 0.856
DEVIANCE= -2*LOG (LIKELIHOOD) = 2183.65
NUMBER OF FREE PARAMETERS = 21
Table 4 showed that out of the four student related variables, only mathematics background
significantly contributed to the prediction model, that is undergraduates SEiJCP. None of the
other variables contributed significantly to the prediction model 1
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Table 5: Random Part of the Linear Growth Model 1 of Intrinsic Factor
LEVEL 1 TAU-HAT STD.ERR. Z-VALUE PR > |Z|
intcept /intcept 15.25 16.55 0.92 0.36
We estimate the student-level (student background variables) variance in SEiJCP by using
equation 1
= Total Variance ...........................................................................................................(1)
Where represent between group variability (Variance of level-2) and represent within group
variability (variance of level-1).
From table 4.4, = 15.25 and = 23.08
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:. Total variance in Programming self efficacy = ...........................................(2)
This is given as = = 0.60
Therefore the total variance in SEiJCP accounted for by student-level differences is 0.60. This
result indicates that about 60.0% of the student-level variation in SEiJCP is explained by the
differences in intrinsic factors under study. However, none of the interactions contributed
significantly to the observed variance in computer programming self efficacy.
Computer experience in this study did not contribute significantly to the variation in SEiJCP. This
finding contradicts that of [5]. In a study of factors related to Java programming self efficacy
among engineering students in Turkey they found that the number of years of computer
experience had a significant linear contribution to Java programming self-efficacy scores. The
non-significance in the contribution of computer experience to variation in self efficacy scores
might be due to the measurement scale used for computer experience in this study where students
rated their experiences in 10 areas of computing (one of which is programming) on a 7-likert
scale.
4.CONCLUSION AND RECOMMENDATION
Computer experience in this study did not contribute significantly to the variation in SEiJCP. This
therefore suggests that their experiences were more pronounced in other areas of computing than
programming. It is therefore suggested that computer undergraduates are made to take more
programming courses and given more tasks in programming in order to engage them more in
programming than other computer related activities that are not related to their core tasks as
computer majors.
5.FUTURE WORK TO BE DONE
This study was limited to government-owned universities in south-western Nigeria. There is the
need to replicate the study in other geo-political zones in the country as well as in private
universities in the country.
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AUTHORS
Josiah Owolabi is currently a Principal Lecturer and the Head of Mathematics/Statistics
Department at the Federal College of Education(Technical),Akoka,Lagos,Nigeria. He
holdsa B.Sc(Ed)and M.Sc in Mathematics.He is currently a research student at the
Institute of Education, University of Ibadan, Nigeria.His previous work
experiencebeforethe presentappointmentincludes teaching Mathematics, Further
Mathematics and Computer in a secondary School.Josiah has about 20 publications in
local andinternational Journals. He hadalsoauthored/co- authoredthreetextbooksinMathematicsand one in
Computer Studies.Hisresearchinterestsare: Mathematics and Computer
Benson AdesinaAdegoke PhD holds B.Ed Physics/Education, M.Ed and PhD degrees in
Educational Evaluation of the University of Ibadan. He had taught Physics and
Mathematics for about 19years before he joined the Institute of Education,University of
Ibadan as a Research Fellow. He is currently a Senior Research Fellow in the Institute of
Education, University of Ibadan, Nigeria. He teaches research and statistical methods to
higher degree students at the Institute of Education University of Ibadan. Benson has close
to 30 publications in local and international journals. He has also authored two textbooks
on statistics and statistical analysis. He has chapter contributions in four textbooks and was involved in the
writing of 2 technical reports. Presently, his research focus is on “Improving Achievement Test Items’
Construction – Emphasis on Comparing the Item Response Theory and Classical Response Theory
Frameworks”.