1) The document proposes a tiered architecture to transform institutional knowledge in higher educational institutions into institutional intelligence through knowledge management and data mining techniques.
2) A three-phase approach is used: phase 1 identifies functional domains and performance indicators through interviews; phase 2 proposes the tiered architecture; phase 3 will model the architecture using KM and data mining methods.
3) The architecture aims to better access, analyze, and utilize institutional knowledge to extract relationships and patterns to enhance performance, decision making, and processes in higher education.
The influence of information technology capability, organizational learning, ...Alexander Decker
This document reports on a study that examined the influence of information technology capability, organizational learning, and knowledge management capability on organizational performance in banking branches in Southern Kalimantan Province, Indonesia. The study hypothesized that information technology capability positively impacts organizational learning, knowledge management capability, and organizational performance. It also hypothesized that organizational learning positively impacts knowledge management capability and organizational performance. Survey data were collected from 69 banking branches and analyzed using partial least squares. The results supported most of the hypotheses, finding significant positive relationships between the variables except for the relationship between organizational learning and knowledge management capability.
Assessment and Evaluation System in Engineering Education of UG Programmes at...ijtsrd
Assessment is one of the most critical dimensions in engineering education process it focuses not only on identifying how many of the predefined education goals and objectives outcomes have been achieved but also works as a feedback component for educators to upgrade their teaching practices. The assessment can be seen as a link that it forms with other education processes. Lamprianou et al. 2009 point out that assessment is associated with the educational objectives of "evaluation, diagnosis, guidance, selection, placement, administration, prediction or grading. Assessment is one main factors that contribute to a high quality teaching and learning environment and student's performance as whole. It also makes clearer what teachers expect from students Biggs et al., 1999 . The perceived difficulty in this process is how assessment system, approaches and schemes can be standardized and adapted across the premier institutes NITs of in the country. Credit system has been used widely by many HEIs in India for over 20 years but no nationally agreed and rationalized framework of credit and Credit Transfer and Accumulation System is developed. The purpose of the literature review is to outline research studies in the assessment and evaluation systems being practicedand to highlight the studies that can be used in the research project undertaken. Specifically, the literature review attempts to address the following research questions What researches are undertaken nationally and internationally into the assessment system in higher education, especially engineering education What are the key findings from these researches What are the limits delimitations of these researches Are there research findings could be applied to engineering education at UG in NITs in India Are there any prime concern for future research in this area From this literature review, it is apparent that a very few number of studies have been conducted in higher education institutions but no research was found in the context of Engineering Education specific to UG programmes and NITs. However, many innovations are on the way to improvise the assessment and evaluation mechanisms in the engineering education especially in the context of Outcome Based Education OBE . J. P. Tegar | Shreya Gupta "Assessment and Evaluation System in Engineering Education of UG Programmes at Premier Institutes (NITs) in India - A Review of Literature" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30921.pdf Paper Url :https://www.ijtsrd.com/humanities-and-the-arts/education/30921/assessment-and-evaluation-system-in-engineering-education-of-ug-programmes-at-premier-institutes-nits-in-india--a-review-of-literature/j-p-tegar
A study model on the impact of various indicators in the performance of stude...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This document summarizes a research study that assessed key factors for establishing knowledge management in hospitals in Isfahan, Iran. The study examined the relationship between organizational culture, knowledge processes, information technology, and knowledge management establishment. A survey was administered to 300 hospital staff. The results showed that organizational culture, knowledge processes, and information technology all had a significant positive impact on knowledge management establishment. Organizational culture was found to promote participation and a sense of belonging, while knowledge processes and information technology facilitated knowledge sharing and management. The study concluded that considering these key factors can help to successfully establish knowledge management in organizations.
Ijdms050304A SURVEY ON EDUCATIONAL DATA MINING AND RESEARCH TRENDSijdms
Educational Data Mining (EDM) is an emerging field exploring data in educational context by applying
different Data Mining (DM) techniques/tools. It provides intrinsic knowledge of teaching and learning
process for effective education planning. In this survey work focuses on components, research trends (1998
to 2012) of EDM highlighting its related Tools, Techniques and educational Outcomes. It also highlights
the Challenges EDM.
This document summarizes a research paper that evaluates the performance of decision tree and clustering techniques using the WEKA data mining tool. The paper uses student academic and performance data to apply decision tree and clustering algorithms and compare the results of each technique. Specifically, it uses WEKA to classify and cluster a dataset containing the marks and percentages of students from educational institutions. The paper aims to determine which technique (decision tree or clustering) provides more accurate and useful results for predicting student performance.
Recommendation of Data Mining Technique in Higher Education Prof. Priya Thaka...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Educational Data Mining is used to find interesting patterns from the data taken from
educational settings to improve teaching and learning. Assessing student’s ability and performance with
EDM methods in e-learning environment for math education in school level in India has not been
identified in our literature review. Our method is a novel approach in providing quality math education
with assessments indicating the knowledge level of a student in each lesson. This paper illustrates how
Learning Curve – an EDM visualization method is used to compare rural and urban students’ progress
in learning mathematics in an e-learning environment. The experiment is conducted in two different
schools in Tamil Nadu, India. After practicing the problems the students attended the test and their
interaction data are collected and analyzed their performance in different aspects: Knowledge
component level, time taken to solve a problem, error rate. This work studies the student actions for
identifying learning progress. The results show that the learning curve method is much helpful to the
teachers to visualize the students’ performance in granular level which is not possible manually. Also it
helps the students in knowing about their skill level when they complete each unit.
The influence of information technology capability, organizational learning, ...Alexander Decker
This document reports on a study that examined the influence of information technology capability, organizational learning, and knowledge management capability on organizational performance in banking branches in Southern Kalimantan Province, Indonesia. The study hypothesized that information technology capability positively impacts organizational learning, knowledge management capability, and organizational performance. It also hypothesized that organizational learning positively impacts knowledge management capability and organizational performance. Survey data were collected from 69 banking branches and analyzed using partial least squares. The results supported most of the hypotheses, finding significant positive relationships between the variables except for the relationship between organizational learning and knowledge management capability.
Assessment and Evaluation System in Engineering Education of UG Programmes at...ijtsrd
Assessment is one of the most critical dimensions in engineering education process it focuses not only on identifying how many of the predefined education goals and objectives outcomes have been achieved but also works as a feedback component for educators to upgrade their teaching practices. The assessment can be seen as a link that it forms with other education processes. Lamprianou et al. 2009 point out that assessment is associated with the educational objectives of "evaluation, diagnosis, guidance, selection, placement, administration, prediction or grading. Assessment is one main factors that contribute to a high quality teaching and learning environment and student's performance as whole. It also makes clearer what teachers expect from students Biggs et al., 1999 . The perceived difficulty in this process is how assessment system, approaches and schemes can be standardized and adapted across the premier institutes NITs of in the country. Credit system has been used widely by many HEIs in India for over 20 years but no nationally agreed and rationalized framework of credit and Credit Transfer and Accumulation System is developed. The purpose of the literature review is to outline research studies in the assessment and evaluation systems being practicedand to highlight the studies that can be used in the research project undertaken. Specifically, the literature review attempts to address the following research questions What researches are undertaken nationally and internationally into the assessment system in higher education, especially engineering education What are the key findings from these researches What are the limits delimitations of these researches Are there research findings could be applied to engineering education at UG in NITs in India Are there any prime concern for future research in this area From this literature review, it is apparent that a very few number of studies have been conducted in higher education institutions but no research was found in the context of Engineering Education specific to UG programmes and NITs. However, many innovations are on the way to improvise the assessment and evaluation mechanisms in the engineering education especially in the context of Outcome Based Education OBE . J. P. Tegar | Shreya Gupta "Assessment and Evaluation System in Engineering Education of UG Programmes at Premier Institutes (NITs) in India - A Review of Literature" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30921.pdf Paper Url :https://www.ijtsrd.com/humanities-and-the-arts/education/30921/assessment-and-evaluation-system-in-engineering-education-of-ug-programmes-at-premier-institutes-nits-in-india--a-review-of-literature/j-p-tegar
A study model on the impact of various indicators in the performance of stude...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This document summarizes a research study that assessed key factors for establishing knowledge management in hospitals in Isfahan, Iran. The study examined the relationship between organizational culture, knowledge processes, information technology, and knowledge management establishment. A survey was administered to 300 hospital staff. The results showed that organizational culture, knowledge processes, and information technology all had a significant positive impact on knowledge management establishment. Organizational culture was found to promote participation and a sense of belonging, while knowledge processes and information technology facilitated knowledge sharing and management. The study concluded that considering these key factors can help to successfully establish knowledge management in organizations.
Ijdms050304A SURVEY ON EDUCATIONAL DATA MINING AND RESEARCH TRENDSijdms
Educational Data Mining (EDM) is an emerging field exploring data in educational context by applying
different Data Mining (DM) techniques/tools. It provides intrinsic knowledge of teaching and learning
process for effective education planning. In this survey work focuses on components, research trends (1998
to 2012) of EDM highlighting its related Tools, Techniques and educational Outcomes. It also highlights
the Challenges EDM.
This document summarizes a research paper that evaluates the performance of decision tree and clustering techniques using the WEKA data mining tool. The paper uses student academic and performance data to apply decision tree and clustering algorithms and compare the results of each technique. Specifically, it uses WEKA to classify and cluster a dataset containing the marks and percentages of students from educational institutions. The paper aims to determine which technique (decision tree or clustering) provides more accurate and useful results for predicting student performance.
Recommendation of Data Mining Technique in Higher Education Prof. Priya Thaka...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Educational Data Mining is used to find interesting patterns from the data taken from
educational settings to improve teaching and learning. Assessing student’s ability and performance with
EDM methods in e-learning environment for math education in school level in India has not been
identified in our literature review. Our method is a novel approach in providing quality math education
with assessments indicating the knowledge level of a student in each lesson. This paper illustrates how
Learning Curve – an EDM visualization method is used to compare rural and urban students’ progress
in learning mathematics in an e-learning environment. The experiment is conducted in two different
schools in Tamil Nadu, India. After practicing the problems the students attended the test and their
interaction data are collected and analyzed their performance in different aspects: Knowledge
component level, time taken to solve a problem, error rate. This work studies the student actions for
identifying learning progress. The results show that the learning curve method is much helpful to the
teachers to visualize the students’ performance in granular level which is not possible manually. Also it
helps the students in knowing about their skill level when they complete each unit.
CFA IN ORGANISATIONAL COMMITMENT WITH SPEACIAL REFERENCE TO WOMEN FACULTIES O...IAEME Publication
The survival in the present insecure and competitive environment has forced organizations to have specialized and committed employees which act beyond their duties, because the success of organizations depends on them. Committed human resources are organization’s greatest assets. This study aims to examine the confirmatory factor analysis (CFA) of organisational commitment among academicians. The research method, according to the purpose of applied research and the manner of data collection is a descriptive and the analyzing of the model specifically is based on structural equation modeling (SEM) via AMOS and SPSS softwares.
IRJET- Performance for Student Higher Education using Decision Tree to Predic...IRJET Journal
This document discusses using decision trees to predict career decisions for 12th grade students in India. It first provides background on the challenges in the Indian education system and how data mining can help improve decision making. It then reviews previous studies applying various data mining techniques like decision trees and random forests to predict student performance. The paper proposes using a decision tree approach on student data to distinguish slow and fast learners and help students make better career choices based on their interests and skills. The decision tree approach achieved 80% accuracy in predicting student career decisions, helping students choose appropriate paths.
Using Analytics to Transform the Library Agenda - Linda Corrin | Talis Insigh...Talis
1. The document discusses the use of learning analytics to understand student learning and optimize teaching practices. It describes how analytics can provide insights into student performance, engagement, and retention at various levels from the individual to the institution.
2. Interviews with teachers found they are interested in analytics about student engagement and performance but have concerns about interpreting data. Teachers want analytics to help understand ideal students and provide feedback to improve teaching.
3. A conceptual framework is presented that links learning analytics to learning design to provide context for analyzing educational activities and interactions with resources. Planning questions are also outlined to help educators implement learning analytics.
This document describes an academic performance analysis system that uses educational data mining techniques. It analyzes student and teacher performance data collected from an engineering college. The system applies the Apriori algorithm and decision tree algorithm to mine patterns in academic data. The Apriori algorithm is used to generate rules based on support, confidence and lift to analyze student performance in different courses. The decision tree algorithm is used to analyze and visualize results for individual students, student groups, and indirectly for teachers. The goal is to identify existing patterns in past student performance data and use it to improve future student and teacher performance.
This document provides a literature review on the use of grounded theory in management research. It discusses:
1) Grounded theory was introduced in the 1960s by Glaser and Strauss as a qualitative research method to develop theories grounded in empirical data. It aims to close the gap between theory and research.
2) Grounded theory involves collecting and analyzing qualitative data through open, axial, and selective coding to develop conceptual categories and explore their relationships. It produces explanatory theories rather than testing existing hypotheses.
3) Grounded theory has evolved over time, with Glaser developing an emerging design approach and Strauss a more structured systematic design approach. It remains a useful method for developing new concepts and theories in management and
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.
IRJET - Recommendation of Branch of Engineering using Machine LearningIRJET Journal
This document describes a machine learning system that recommends engineering branches to students based on their scores. It uses K-nearest neighbors and collaborative filtering techniques. The system aims to help students select an engineering branch that matches their abilities and reduces confusion. It analyzes student data like marks to make personalized recommendations. The document reviews similar existing recommendation systems and the techniques they use. The proposed system seeks to guide students towards suitable engineering fields and reduce the workload on counselors.
Due to the increasing interest in big data especially in the educational field and online education has led to a conflict in terms of performance indicators of the student. In this paper we discuss the methodology of assessing the student performance in terms of the success indicators revealing a number of indicators that is recommended to indicate success of the final academic achievement.
This document discusses the information needs and seeking behavior of educational administrators in Pakistan. It finds that administrators require information to manage their institutions effectively but face several issues. There is a lack of available data and inconsistent policies impact education. Administrators rarely use libraries and have no formal method to find needed information. A national information system is recommended to fill gaps and allow administrators easy access to reliable information needed for planning and decision making.
E-supporting Performance Styles based on Learning Analytics for Development o...IJITE
This study aims to identify the effectiveness of delivering electronic supporting performance styles that are
based on learning analytics for the development of teaching practices in teaching science, moreover, the
Electronic and face to face supporting performance styles will deliver according to the data analytics that
extracted from observations, (participating rate- page views) data from platform, therefore, to determine
the effectiveness, the researchers design observation rubric based on teaching practices standard that
extract from (ASTE/NSTA, AITSL) to observe teaching practices of student science teachers. Regarding the
participants they were science students who enrolled in educational diplomas, researchers use the mixed
method in collected data and quantitative data, furthermore, they will study a supportive program of
considering data analyses to develop their teaching practices in teaching science, the results exposed that
providing a supporting program that considers learning analytics, helps increase teaching practices in
teaching science for student's science teachers.
E-SUPPORTING PERFORMANCE STYLES BASED ON LEARNING ANALYTICS FOR DEVELOPMENT O...IJITE
This study aims to identify the effectiveness of delivering electronic supporting performance styles that are
based on learning analytics for the development of teaching practices in teaching science, moreover, the
Electronic and face to face supporting performance styles will deliver according to the data analytics that
extracted from observations, (participating rate- page views) data from platform, therefore, to determine
the effectiveness, the researchers design observation rubric based on teaching practices standard that
extract from (ASTE/NSTA, AITSL) to observe teaching practices of student science teachers. Regarding the
participants they were science students who enrolled in educational diplomas, researchers use the mixed
method in collected data and quantitative data, furthermore, they will study a supportive program of
considering data analyses to develop their teaching practices in teaching science, the results exposed that
providing a supporting program that considers learning analytics, helps increase teaching practices in
teaching science for student's science teachers.
Due to the increasing interest in big data especially in the educational field and online education has led to a conflict in terms of performance indicators of the student. In this paper we discuss the methodology of assessing the student performance in terms of the success indicators revealing a number of indicators that is recommended to indicate success of the final academic achievement
The document describes a case study that uses educational data mining techniques to analyze graduate student data from the College of Science and Technology in Khanyounis, Palestine from 1993-2007. The data includes 18 attributes for 3360 students. After preprocessing, association rules, classification, clustering, and outlier detection are applied. Association rules found relationships between attributes like poor grades and average performance. Classification rules predicted grade based on attributes like secondary school type and GPA. Clustering grouped students and outlier detection found anomalous cases. The results provide insights to improve student performance and academic decision making.
This document defines learning analytics as an emerging field that uses sophisticated analytic tools to improve learning and education. It draws from fields like business intelligence, web analytics, academic analytics, and educational data mining. Learning analytics seeks to analyze large amounts of online educational data in real-time to improve student outcomes, identify at-risk students, and enable timely interventions. The goal is to better understand how to optimize learning interactions and support student needs using insights from extensive data on student engagement and performance.
This study investigated factors that determine teacher job satisfaction in secondary schools in ABA Education Zone, South-East Nigeria. The researchers surveyed 512 teachers to identify factors related to school facilities, teacher characteristics, and human relations that influence job satisfaction. They found that teachers were less satisfied with advancement opportunities, compensation, supervision, human relations, and working conditions. Specifically, inadequate classroom environments and school facilities negatively impacted job satisfaction. The researchers recommended equipping school laboratories to improve science teaching and promote effective teacher job satisfaction.
This article summarizes a journal article that examines distributed leadership in higher education institutions. The authors interviewed 25 individuals from project teams to identify factors influencing distributed leadership at both the organizational and team levels. At the organizational level, they found leadership requires involvement with external stakeholders and alignment with the wider institution context. At the team level, critical internal conditions like autonomy and clear goals/responsibilities as well as processes like information sharing and coordination influence distributed leadership. The findings provide an integrated framework for understanding distributed leadership in higher education.
This study aimed to evaluate the effectiveness of institutional performance in public secondary schools in Al-Ahsa, Saudi Arabia from the perspective of school administrators. A questionnaire was administered to 90 randomly selected school principals. The findings showed no significant differences in institutional performance based on principal qualifications or experience. However, the study concluded that effective school administration requires strategic planning, organization, evaluation, development, and adaptation. It was also concluded that school effectiveness can be measured by positive culture, cooperation, feedback systems, and alignment with the five responsibilities of effective principals outlined by Orloski: strong leadership, appropriate atmosphere, skills learning, teacher expectations, and performance monitoring.
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.
This document discusses knowledge management in public and private higher education organizations in India. It aims to understand the dimensions of knowledge management and how they differ between public and private sectors. The document provides an extensive literature review on knowledge management, including definitions, types of knowledge, knowledge infrastructure capabilities like organizational culture, structure, and information technology. It also reviews past studies on knowledge management implementation in universities around the world.
This document summarizes a research paper about the moderating role of management leadership on the relationship between knowledge management implementation and organizational performance in a university context. The paper reviews literature on knowledge management processes in universities and indicators of organizational performance at universities. It discusses how leadership is important for knowledge management success and is both an enabler of knowledge management and a factor for performance. The purpose of the research is to analyze the moderating effect of management leadership on the relationship between knowledge management implementation and organizational performance, from the perspective of teacher-researchers at a university in Morocco.
A case study of an affiliated undergraduate engineering institution showing f...Premier Publishers
- The document presents a case study examining faculty perspectives on factors affecting education quality at an affiliated undergraduate engineering institution in Haryana, India.
- A questionnaire was administered to 110 faculty members with different qualifications to understand their views on parameters like selection process, academic excellence, infrastructure, personality development, and administration.
- Statistical analysis found no significant differences in faculty views based on their qualification level for any of the parameters studied. Specifically, ANOVA tests showed p-values above 0.05, indicating faculty qualification did not impact their assessment of factors influencing education quality.
Higher education institutions now a days are operating in an increasingly complex and
competitive environment. The application of innovation is a must for sustaining its competitive advantage.
Institution leaders are using data management and analytics to question the status quo and develop effective
solutions. Achieving these insights and information requires not a single report from a single system, but
rather the ability to access, share, and explore institution-wide data that can be transformed into meaningful
insights at every level of the institution. Consequently, institutions are facing problems in providing necessary
information technology support for fulfilling excellence in performance. More specifically, the best practices
of big data management and analytics need to be considered within higher education institutions. Therefore,
the study aimed at investigating big data and analytics, in terms of: (1) definition; (2) its most important
principles; (3) models; and (4) benefits of its use to fulfill performance excellence in higher education
institutions. This involves shedding light on big data and analytics models and the possibility of its use in
higher education institutions, and exploring the effect of using big data and analytics in achieving performance
excellence. To reach these objectives, the researcher employed a qualitative research methodology for
collecting and analyzing data. The study concluded the most important result, that there is a significant
relationship between big data and analytics and excellence of performance as big data management and
analytics mainly aims at achieving tasks quickly with the least effort and cost. These positive results support
the use of big data and analytics in institutions and improving knowledge in this field and providing a practical
guide adaptable to the institution structure. This paper also identifies the role of big data and analytics in
institutions of higher education worldwide and outlines the implementation challenges and opportunities in the
education industry.
CFA IN ORGANISATIONAL COMMITMENT WITH SPEACIAL REFERENCE TO WOMEN FACULTIES O...IAEME Publication
The survival in the present insecure and competitive environment has forced organizations to have specialized and committed employees which act beyond their duties, because the success of organizations depends on them. Committed human resources are organization’s greatest assets. This study aims to examine the confirmatory factor analysis (CFA) of organisational commitment among academicians. The research method, according to the purpose of applied research and the manner of data collection is a descriptive and the analyzing of the model specifically is based on structural equation modeling (SEM) via AMOS and SPSS softwares.
IRJET- Performance for Student Higher Education using Decision Tree to Predic...IRJET Journal
This document discusses using decision trees to predict career decisions for 12th grade students in India. It first provides background on the challenges in the Indian education system and how data mining can help improve decision making. It then reviews previous studies applying various data mining techniques like decision trees and random forests to predict student performance. The paper proposes using a decision tree approach on student data to distinguish slow and fast learners and help students make better career choices based on their interests and skills. The decision tree approach achieved 80% accuracy in predicting student career decisions, helping students choose appropriate paths.
Using Analytics to Transform the Library Agenda - Linda Corrin | Talis Insigh...Talis
1. The document discusses the use of learning analytics to understand student learning and optimize teaching practices. It describes how analytics can provide insights into student performance, engagement, and retention at various levels from the individual to the institution.
2. Interviews with teachers found they are interested in analytics about student engagement and performance but have concerns about interpreting data. Teachers want analytics to help understand ideal students and provide feedback to improve teaching.
3. A conceptual framework is presented that links learning analytics to learning design to provide context for analyzing educational activities and interactions with resources. Planning questions are also outlined to help educators implement learning analytics.
This document describes an academic performance analysis system that uses educational data mining techniques. It analyzes student and teacher performance data collected from an engineering college. The system applies the Apriori algorithm and decision tree algorithm to mine patterns in academic data. The Apriori algorithm is used to generate rules based on support, confidence and lift to analyze student performance in different courses. The decision tree algorithm is used to analyze and visualize results for individual students, student groups, and indirectly for teachers. The goal is to identify existing patterns in past student performance data and use it to improve future student and teacher performance.
This document provides a literature review on the use of grounded theory in management research. It discusses:
1) Grounded theory was introduced in the 1960s by Glaser and Strauss as a qualitative research method to develop theories grounded in empirical data. It aims to close the gap between theory and research.
2) Grounded theory involves collecting and analyzing qualitative data through open, axial, and selective coding to develop conceptual categories and explore their relationships. It produces explanatory theories rather than testing existing hypotheses.
3) Grounded theory has evolved over time, with Glaser developing an emerging design approach and Strauss a more structured systematic design approach. It remains a useful method for developing new concepts and theories in management and
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.
IRJET - Recommendation of Branch of Engineering using Machine LearningIRJET Journal
This document describes a machine learning system that recommends engineering branches to students based on their scores. It uses K-nearest neighbors and collaborative filtering techniques. The system aims to help students select an engineering branch that matches their abilities and reduces confusion. It analyzes student data like marks to make personalized recommendations. The document reviews similar existing recommendation systems and the techniques they use. The proposed system seeks to guide students towards suitable engineering fields and reduce the workload on counselors.
Due to the increasing interest in big data especially in the educational field and online education has led to a conflict in terms of performance indicators of the student. In this paper we discuss the methodology of assessing the student performance in terms of the success indicators revealing a number of indicators that is recommended to indicate success of the final academic achievement.
This document discusses the information needs and seeking behavior of educational administrators in Pakistan. It finds that administrators require information to manage their institutions effectively but face several issues. There is a lack of available data and inconsistent policies impact education. Administrators rarely use libraries and have no formal method to find needed information. A national information system is recommended to fill gaps and allow administrators easy access to reliable information needed for planning and decision making.
E-supporting Performance Styles based on Learning Analytics for Development o...IJITE
This study aims to identify the effectiveness of delivering electronic supporting performance styles that are
based on learning analytics for the development of teaching practices in teaching science, moreover, the
Electronic and face to face supporting performance styles will deliver according to the data analytics that
extracted from observations, (participating rate- page views) data from platform, therefore, to determine
the effectiveness, the researchers design observation rubric based on teaching practices standard that
extract from (ASTE/NSTA, AITSL) to observe teaching practices of student science teachers. Regarding the
participants they were science students who enrolled in educational diplomas, researchers use the mixed
method in collected data and quantitative data, furthermore, they will study a supportive program of
considering data analyses to develop their teaching practices in teaching science, the results exposed that
providing a supporting program that considers learning analytics, helps increase teaching practices in
teaching science for student's science teachers.
E-SUPPORTING PERFORMANCE STYLES BASED ON LEARNING ANALYTICS FOR DEVELOPMENT O...IJITE
This study aims to identify the effectiveness of delivering electronic supporting performance styles that are
based on learning analytics for the development of teaching practices in teaching science, moreover, the
Electronic and face to face supporting performance styles will deliver according to the data analytics that
extracted from observations, (participating rate- page views) data from platform, therefore, to determine
the effectiveness, the researchers design observation rubric based on teaching practices standard that
extract from (ASTE/NSTA, AITSL) to observe teaching practices of student science teachers. Regarding the
participants they were science students who enrolled in educational diplomas, researchers use the mixed
method in collected data and quantitative data, furthermore, they will study a supportive program of
considering data analyses to develop their teaching practices in teaching science, the results exposed that
providing a supporting program that considers learning analytics, helps increase teaching practices in
teaching science for student's science teachers.
Due to the increasing interest in big data especially in the educational field and online education has led to a conflict in terms of performance indicators of the student. In this paper we discuss the methodology of assessing the student performance in terms of the success indicators revealing a number of indicators that is recommended to indicate success of the final academic achievement
The document describes a case study that uses educational data mining techniques to analyze graduate student data from the College of Science and Technology in Khanyounis, Palestine from 1993-2007. The data includes 18 attributes for 3360 students. After preprocessing, association rules, classification, clustering, and outlier detection are applied. Association rules found relationships between attributes like poor grades and average performance. Classification rules predicted grade based on attributes like secondary school type and GPA. Clustering grouped students and outlier detection found anomalous cases. The results provide insights to improve student performance and academic decision making.
This document defines learning analytics as an emerging field that uses sophisticated analytic tools to improve learning and education. It draws from fields like business intelligence, web analytics, academic analytics, and educational data mining. Learning analytics seeks to analyze large amounts of online educational data in real-time to improve student outcomes, identify at-risk students, and enable timely interventions. The goal is to better understand how to optimize learning interactions and support student needs using insights from extensive data on student engagement and performance.
This study investigated factors that determine teacher job satisfaction in secondary schools in ABA Education Zone, South-East Nigeria. The researchers surveyed 512 teachers to identify factors related to school facilities, teacher characteristics, and human relations that influence job satisfaction. They found that teachers were less satisfied with advancement opportunities, compensation, supervision, human relations, and working conditions. Specifically, inadequate classroom environments and school facilities negatively impacted job satisfaction. The researchers recommended equipping school laboratories to improve science teaching and promote effective teacher job satisfaction.
This article summarizes a journal article that examines distributed leadership in higher education institutions. The authors interviewed 25 individuals from project teams to identify factors influencing distributed leadership at both the organizational and team levels. At the organizational level, they found leadership requires involvement with external stakeholders and alignment with the wider institution context. At the team level, critical internal conditions like autonomy and clear goals/responsibilities as well as processes like information sharing and coordination influence distributed leadership. The findings provide an integrated framework for understanding distributed leadership in higher education.
This study aimed to evaluate the effectiveness of institutional performance in public secondary schools in Al-Ahsa, Saudi Arabia from the perspective of school administrators. A questionnaire was administered to 90 randomly selected school principals. The findings showed no significant differences in institutional performance based on principal qualifications or experience. However, the study concluded that effective school administration requires strategic planning, organization, evaluation, development, and adaptation. It was also concluded that school effectiveness can be measured by positive culture, cooperation, feedback systems, and alignment with the five responsibilities of effective principals outlined by Orloski: strong leadership, appropriate atmosphere, skills learning, teacher expectations, and performance monitoring.
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.
This document discusses knowledge management in public and private higher education organizations in India. It aims to understand the dimensions of knowledge management and how they differ between public and private sectors. The document provides an extensive literature review on knowledge management, including definitions, types of knowledge, knowledge infrastructure capabilities like organizational culture, structure, and information technology. It also reviews past studies on knowledge management implementation in universities around the world.
This document summarizes a research paper about the moderating role of management leadership on the relationship between knowledge management implementation and organizational performance in a university context. The paper reviews literature on knowledge management processes in universities and indicators of organizational performance at universities. It discusses how leadership is important for knowledge management success and is both an enabler of knowledge management and a factor for performance. The purpose of the research is to analyze the moderating effect of management leadership on the relationship between knowledge management implementation and organizational performance, from the perspective of teacher-researchers at a university in Morocco.
A case study of an affiliated undergraduate engineering institution showing f...Premier Publishers
- The document presents a case study examining faculty perspectives on factors affecting education quality at an affiliated undergraduate engineering institution in Haryana, India.
- A questionnaire was administered to 110 faculty members with different qualifications to understand their views on parameters like selection process, academic excellence, infrastructure, personality development, and administration.
- Statistical analysis found no significant differences in faculty views based on their qualification level for any of the parameters studied. Specifically, ANOVA tests showed p-values above 0.05, indicating faculty qualification did not impact their assessment of factors influencing education quality.
Higher education institutions now a days are operating in an increasingly complex and
competitive environment. The application of innovation is a must for sustaining its competitive advantage.
Institution leaders are using data management and analytics to question the status quo and develop effective
solutions. Achieving these insights and information requires not a single report from a single system, but
rather the ability to access, share, and explore institution-wide data that can be transformed into meaningful
insights at every level of the institution. Consequently, institutions are facing problems in providing necessary
information technology support for fulfilling excellence in performance. More specifically, the best practices
of big data management and analytics need to be considered within higher education institutions. Therefore,
the study aimed at investigating big data and analytics, in terms of: (1) definition; (2) its most important
principles; (3) models; and (4) benefits of its use to fulfill performance excellence in higher education
institutions. This involves shedding light on big data and analytics models and the possibility of its use in
higher education institutions, and exploring the effect of using big data and analytics in achieving performance
excellence. To reach these objectives, the researcher employed a qualitative research methodology for
collecting and analyzing data. The study concluded the most important result, that there is a significant
relationship between big data and analytics and excellence of performance as big data management and
analytics mainly aims at achieving tasks quickly with the least effort and cost. These positive results support
the use of big data and analytics in institutions and improving knowledge in this field and providing a practical
guide adaptable to the institution structure. This paper also identifies the role of big data and analytics in
institutions of higher education worldwide and outlines the implementation challenges and opportunities in the
education industry.
A Proposed Theoretical Model For Evaluating E-LearningChristina Bauer
This document proposes a theoretical model for evaluating e-learning in higher education institutions. It begins by reviewing current models for e-learning evaluation and their limitations. It then presents a new proposed model that aims to address the shortcomings of existing approaches. The proposed model is intended to provide guidelines for comprehensively evaluating e-learning systems and determining their return on investment in higher education settings.
This document summarizes a journal article that proposes an e-Learning Maturity Model (eMM) as a framework to help institutions assess and improve their e-learning capabilities. The eMM is designed to assess an institution's ability to develop, deploy, and support e-learning. It draws from similar maturity models used in software engineering to benchmark processes. Implementing an eMM could provide institutions a roadmap to guide improvements and allow them to benchmark their e-learning capabilities against other institutions.
A Study on Data Mining Techniques, Concepts and its Application in Higher Edu...IRJET Journal
This document discusses how data mining techniques can be applied in higher education to analyze educational data and improve various aspects of the student experience and institutional effectiveness. It provides an overview of common data mining methods like classification, clustering, association rule mining and their uses in higher education for applications such as student performance analysis, course recommendation systems, dropout prediction, and curriculum improvement. It also addresses potential issues around privacy, data security and ethics when using data mining in education.
This document summarizes a systematic literature review of 40 empirical studies on learning analytics and educational data mining from 2008-2013. The review aimed to document applied research approaches, identify strengths and weaknesses, and suggest opportunities for future research. Four major directions of LA/EDM empirical research were identified: 1) predicting student performance, 2) understanding student behavior, 3) improving educational systems, and 4) developing analytic methods/tools. The results highlighted the added value of LA/EDM in improving learning and informed decision making, but also identified opportunities to explore new technologies and research questions.
This document outlines a research study exploring how LinkedIn Learning can be used by organizations to improve employee performance. The study will use a qualitative case study method with surveys to collect data from two groups of employees - one that chooses their own learning path and one assigned a path. The surveys will ask questions about skills improvement, impact on the organization, and learning effectiveness. Descriptive, inferential, causal, and predictive analyses will be used to analyze the data. The theoretical frameworks of connectivism, social exchange theory, and path-goal theory provide a lens for the study.
Role of Recruitment and Selection of Faculty in Technical Aducation in Rajast...professionalpanorama
The importance of Human Resource Development (HRD) practices is being increasingly
realised in education sector in Rajasthan. Technical Institutes in Rajasthan are facing
problem of getting the competent faculty, retaining them, keeping up their motivation
and morale and helping them to both continuously grow and contribute their best
to the Institute. Due to changes in values, norms, social climate, their expectations
are different, they become problem if the organisation is not able to manage human
resources properly. Organisations today realise that innovative and creative employees
who hold the key to organisational knowledge provide a sustainable competitive
advantage because unlike other resources, intellectual capital is difficult to imitate
by competitors. This becomes all the more important in terms of educational organisations.
Accordingly, the people management function has become strategic in its importance
and outlook and is geared to attract, retain, and engage talent. These developments
have led to the creation of the Human Resource (HR) workforce scorecard as well.
Role of recruitment and selection of faculty inTapasya123
The importance of Human Resource Development (HRD) practices is being increasingly
realised in education sector in Rajasthan. Technical Institutes in Rajasthan are facing
problem of getting the competent faculty, retaining them, keeping up their motivation
and morale and helping them to both continuously grow and contribute their best
to the Institute. Due to changes in values, norms, social climate, their expectations
are different, they become problem if the organisation is not able to manage human
resources properly. Organisations today realise that innovative and creative employees
who hold the key to organisational knowledge provide a sustainable competitive
advantage because unlike other resources, intellectual capital is difficult to imitate
by competitors. This becomes all the more important in terms of educational organisations.
Accordingly, the people management function has become strategic in its importance
and outlook and is geared to attract, retain, and engage talent. These developments
have led to the creation of the Human Resource (HR) workforce scorecard as well.
Organizational Effectiveness of Naval State University: Proposed Institutiona...Dr. Amarjeet Singh
This research sought to study the organizational
effectiveness of Naval State University (NSU), Biliran,
Philippines. It was intended to answer the organizational
effectiveness of the delivery of service by the present
academic organizational set-up in terms of: Instruction,
Research, and Community Extension. The study used the
descriptive survey method through the aid of focus group
discussion and researcher-made guided questions as the
main instrument for data collection. There were items in
the instrument that were patterned from the accreditation
activities by the Accrediting Agency of Chartered Colleges
and Universities in the Philippines (AACUP). The
researcher tapped a third party who was an expert in
conducting focus group discussions. The expert researcher
who conducted the FGD was not connected with the Naval
State University to avoid any biases. The activity of FGD
was recorded with the consent of the key informants. The
key informants were the key officials of the university. And
they come up with only one answer in each item or
indicator. The data were recorded according to the
frequencies and corresponding percentage. After analyzing
and interpreting the processed data, the Organizational
Effectiveness of NSU in the areas of: Instruction, Research
and Community Extension were rated as very effective. But
some indicators were identified for needed improvements.
And the institutional capacity building as designed in the
study should be implemented accordingly.
KNOWLEDGE SELF-EFFICACY AND RESEARCH COLLABORATION TOWARDS KNOWLEDGE SHARING:...IAEME Publication
Purpose: This research examines the impact of individual self-efficacy and research collaboration among college professors. Higher education institutions involve the dissemination of knowledge and learning, knowledge management is thus deemed as significant in this field. Knowledge management has dimensions like knowledge creation, acquisition, storing, and sharing. The research aims to determine the essence of knowledge-sharing practices. Methodology: The research sample includes 410 respondents in Tamil Nadu. Data collection is made through a structured measurement scale. The hypotheses were tested and data were analyzed by using statistical tools such as descriptive statistics, reliability tests, correlation analysis, and structural equation modeling. Findings: In higher education institutions, the faculty member is engage in knowledge-sharing aspects in recent days. It is very essential to retain the quality of knowledge among the faculty members. Conclusion: The education institution may facilitate the facilities to maintain and equip the knowledge of the professor. The institution must facilitate and support for proper implementation of the knowledge management strategy.
This document summarizes a project to design and implement a quality management framework for online learning environments using a distributed leadership approach. The framework includes six key elements: planning, technologies, organizational structure, evaluation, governance, and resourcing. It was developed and tested over four phases by a team from several Australian universities. The goals were to help conceptualize quality assurance and improvement for online learning and how distributed leadership can support institutional transformation.
This document presents a study that developed a conceptual model called the hexagonal e-learning assessment model (HELAM) to evaluate learning management systems (LMS) using a multi-dimensional approach across six dimensions: system quality, service quality, content quality, learner perspective, instructor attitudes, and supportive issues. The researchers designed a survey based on HELAM and administered it to 84 students to evaluate their university's LMS. Statistical analysis supported the model and found that each dimension significantly impacted student satisfaction with the LMS.
Automated Essay Score Predictions As A Formative Assessment ToolLisa Muthukumar
This document discusses an automated essay scoring feature added to ETIPS cases, which are online learning objects designed to develop teachers' instructional decision-making skills about technology integration. The summary evaluates students' initial responses to the automated essay scorer to understand their reactions, inform future implementation, and provide insight to improve the reliability of the scorer. Research suggests learning environments should provide formative assessment to give students feedback and opportunities to improve, and automated scoring holds promise as a formative assessment tool within online learning. Student perceptions of similar computer-based formative assessment have been generally positive.
E-SUPPORTING PERFORMANCE STYLES BASED ON LEARNING ANALYTICS FOR DEVELOPMENT O...IJITE
This study aims to identify the effectiveness of delivering electronic supporting performance styles that are
based on learning analytics for the development of teaching practices in teaching science, moreover, the
Electronic and face to face supporting performance styles will deliver according to the data analytics that
extracted from observations, (participating rate- page views) data from platform, therefore, to determine
the effectiveness, the researchers design observation rubric based on teaching practices standard that
extract from (ASTE/NSTA, AITSL) to observe teaching practices of student science teachers. Regarding the
participants they were science students who enrolled in educational diplomas, researchers use the mixed
method in collected data and quantitative data, furthermore, they will study a supportive program of
considering data analyses to develop their teaching practices in teaching science, the results exposed that
providing a supporting program that considers learning analytics, helps increase teaching practices in
teaching science for student's science teachers.
The Performative Production of Trace Data in Knowledge WorkAleksi Aaltonen
Invited talk at Bentley University on September 15, 2023. I talk about my recent paper co-authored with Marta Stelmaszak on trace data and how knowledge workers actively perform such data.
A Survey on Educational Data Mining TechniquesIIRindia
Educational data mining (EDM) creates high impact in the field of academic domain. The methods used in this topic are playing a major advanced key role in increasing knowledge among students. EDM explores and gives ideas in understanding behavioral patterns of students to choose a correct path for choosing their carrier. This survey focuses on such category and it discusses on various techniques involved in making educational data mining for their knowledge improvement. Also, it discusses about different types of EDM tools and techniques in this article. Among the different tools and techniques, best categories are suggested for real world usage.
The document summarizes a case study on using data analysis and learning analytics in higher education. It describes how data was collected through student surveys to understand attitudes towards university services quality. The data was analyzed using SPSS and most students had positive attitudes. Recommendations included using additional quality models and awareness campaigns for services. Data scientists can help universities make data-driven decisions to improve student outcomes and resource allocation.
Similar to IJCER (www.ijceronline.com) International Journal of computational Engineering research (20)
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BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
IJCER (www.ijceronline.com) International Journal of computational Engineering research
1. International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 5
Institutional Knowledge to Institutional Intelligence: A Data Mining
Enabled Knowledge Management Approach
Bhusry Mamta
Research Scholar
Singhania University Pacheri Bari, Jhunjhunu, Rajasthan, India
Abstract
Significant amount of knowledge is created in Higher Educational Institutions (HEIs) as a result of the academic, research
and administrative activities. Deployment of the knowledge generated towards performance enhancement, decision making
and process improvement will yield effective results such as enhanced planning and development, better administrative
services, improved teaching and learning processes, effective faculty and student performance evaluation, efficient research,
and better placements and recruitments. To generate the desired outcomes, the institutions need to better access, analyse and
utilize the institutional knowledge for extracting the existing relationships, associations, patterns and trends in knowledge.
The author proposes a tiered architecture for capture and storage of institutional knowledge and its transformation
into institutional intelligence. The research adopts a three phase approach, the first phase consisting of identification of the
functional domains and performance indicators that determine performance, the second phase being the proposed
architecture and the third phase consists of modeling the architecture using knowledge management and data mining
methods. This paper covers with the first two phases of the research and the third phase is proposed to be taken up as a
future work.
Keywords – Data Mining, Functional Domains, Higher Educational Institutions, Institutional Intelligence, Knowledge
Management, Knowledge Repository, Performance Indicators
1. Introduction
Higher educational institutions encounter many challenges that prevent them to achieve their quality objectives (Delavari,
Shirazi and Beikzadeh, 2004). Some of these problems stem from the lack of robust KM capabilities in HEIs. The increasing
competition for performance has forced the HEIs with the challenge of having more efficient, effective and accurate
educational processes. Knowledge evolves continuously in the functions and processes of HEIs but lack of proper
acquisition, storage, deductions, conclusions and analysis of the available knowledge prevents the institutions from utilizing
the institutional knowledge towards their educational objectives. Today HEIs face the important challenge of reaching a
stage to facilitate more efficient, effective and accurate educational processes (Delavari, 2005). Knowledge gaps exists in
HEIs due to lack of proper mechanisms for knowledge transformation into useful patterns, relationships and associations.
Knowledge management and data mining techniques in integration can help to bridge the knowledge gaps by providing
additional insight into the functions and processes of administration, teaching and learning and research and acting as tools
towards better decisions in the educational activities.
One important task for HEIs is to identify the existing knowledge and tailor its knowledge management interventions
in order to apply the institutional knowledge towards enhancement of performance rate. In order to capture and analyze the
institutional knowledge more effectively, it is important to develop a holistic and reliable system that attempts to examine,
assess and predict how multiple variables influence the performance of the institution while taking into account the
vagueness and fuzziness of the factors involved (Sahay and Mehta, 2010). A transformation process that converts the
knowledge chunks, explicit as well as implicit, into explicit and objective constructs has to be emphasized. The authors
propose a tiered architecture for creating and sustaining institutional intelligence from institutional knowledge through
knowledge management and data mining techniques. HEIs can apply the institutional intelligence towards fulfillment of KM
services of performance enhancement, decision making and process improvement. This will facilitate to bring advantages
such as enhanced planning and development, better administrative services, improved teaching and learning processes,
effective faculty and student performance evaluation, efficient research, and better placements and recruitments.
2. Knowledge Management and Data Mining Applications – Background and Research
Knowledge management and data mining have been interesting areas of research in the educational domain. Kidwell, et
al.(2000) discussed how an institution wide approach to KM can lead to exponential improvements in knowledge sharing in
educational institutions and the subsequent surge benefits. Ranjan and Khalil (2007,pp. 15-25) argued that in order to build
and develop a robust and thriving knowledge environment the institutions need to look beyond technology and develop the
overall culture of accessing, collaborating and managing knowledge. Huveida, Shams, and Hooshmand(2008, pp. 695-702)
demonstrated the relevance of problem solving and decision making theory in assessing the purpose of organizational KM
activities and suggested new ways to conceptualize KM practices. Nagad and Amin (2006, pp.60-65) concluded that
effective KM may require significant change in culture and value, organizational structures and reward systems.
Issn 2250-3005(online) September| 2012 Page 1356
2. International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 5
Rowley(2000, pp. 325-333)in the study on KM in higher education said that KM challenges lie in the creation of a
knowledge environment and the recognition of knowledge as intellectual capital and emphasized that effective KM in higher
education requires significant change in the culture and values, organizational structures and reward systems.
Researchers have explored various applications of data mining in context of education. Luan (2001) introduced a
decision support tool using data mining in the context of knowledge management. Shyamala and Rajagopalan(2006)
developed a model for prediction of student performance by finding similar patterns from data gathered. Ranjan and
Malik(2007) proposed a framework for effective student counseling process using data mining techniques. Ranjan and
Ranjan (2010) explored the application of data mining techniques in higher education from the Indian perspective. Sahay
and Mehta (2010) developed a software system to assist higher education in assessing and predicting key issues related to
student success using data mining algorithms. Ehlers, et al. (2009) reported on a decision support system for research
management for higher education using clustering technique of data mining to bridge the inherent ambiguity across different
academic disciplines. Delavari (2004) proposed a model for improving the efficiency and effectiveness of higher
educational processes using the capabilities of data mining technologies.
Though there are many established research activities available on KM intervention in higher education, few
studies have focused on data mining enabled knowledge management intervention. This is the motivation for this paper.
3. Research Methodology
The research adopted a three phase approach, the first phase consisting of an interview and questionnaire method for the
identification, verification and validation of the functional domains and performance indicators, the second phase being the
proposed tiered architecture for transforming institutional knowledge to institutional intelligence and the third phase
consisting of modeling the proposed architecture using knowledge management and data mining methods. This paper
covers the first two phases of the research and the third phase is proposed as a future work.
A Identification of the Functional Domains and Performance Indicators
Interviews with faculty members and other functionaries in engineering colleges and business schools, observation of
procedures and processes as well as study of work already done (Ashish and Arun, 2006, Ranjan and Khalil, 2007) were
used to identify the functional domains and performance indicators that determine the performance in HEIs. The outcomes
were analyzed using the content analysis technique. Content analysis consists of analyzing the contents of documentary
materials(books, magazines, newspapers) and verbal materials (interviews, group discussions) for the identification of
certain characteristics that can be measured or counted (Kothari, 2010). The list of performance indicators identified in the
functional domains was distributed to senior faculty members with experience more than 7 years, heads of departments and
deans for rating on a five point likert scale (1 for not important and 5 for most important). 160 faculty members participated
and only those performance indicators with standard deviation (SD) of 1.0 or less and average rating of 3.5 out of 5 and
above were considered and the rest were eliminated. This process eliminated about 32% of the initial list of performance
indicators. The criteria (SD < 1.0 and mean >= 3.5/5) offer a suitable definition of threshold for stability (Yeoh, Gao and
Koronios, 2009) and hence considered appropriate. This study facilitated to identify the generic performance indicators in
functional domains of HEIs. The research focusses on these performance indicators for the development of institutional
intelligence in HEIs.
B Transformation of Institutional Knowledge to Institutional Intelligence : A Knowledge Management and Data
Mining Approach
This section presents the proposed architecture based on the capture and storage of institutional knowledge and its
transformation into institutional intelligence using data mining methods (Figure 1). The institutional knowledge is
generated in the form of performance indicators as a result of interaction between processes, people and environment within
the HEI functional domains. Knowledge is captured and stored in a central knowledge base called the knowledge repository.
The knowledge repository is a structured collection of the institutional knowledge that ensures the availability of related
knowledge quickly and efficiently at the same place. Data mining techniques such as clustering, classification, prediction
and association are applied to the stored knowledge to create institutional intelligence in the form of patterns, trends, rules
and relationships. These outcomes from the data mining process are used as KM services to enhance the functions of
decision making, process improvement and institutional performance management in the HEIs.
Classification is a data mining function used to classify the data group into pre-defined classes based on certain criteria.
Classification assigns items in a collection to target categories or classes with the goal to accurately predict the target class
for each case in the data (Oracle® Data Mining Concepts, 2008). Clustering is used to segment a dataset into subsets or
clusters based on a set of attributes. It results into division of data into groups of similar objects where each cluster consists
of objects that are similar between themselves and dissimilar to other objects. Prediction focuses on predicting certain events
or behaviour based on historical information. Association consists in finding affinities among a collection of data objects.
Association rules help to detect relationships or associations between specific values of categorical variables in large data
sets.
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The performance indicators are illustrated in Table 1; only two functional domains have been considered due to lack of
space. The main objective of the proposed architecture is to identify how each performance indicator can be improved
through data mining techniques leading to the overall improvement of the functional domain. The data mining functions that
can be applied to the performance indicators in order to achieve useful outcomes in the form of institutional intelligence and
the benefits that the stakeholders can draw by deployment of the institutional intelligence to their decisions and actions are
illustrated in table 1.
Functional Domain Databases
Planning and Research and Projects & Placement Feedback Alliances and
Development AXN Based Consultancy Services Mechanism Collaborations
outcomes Assignments
Performance
indicators
Drivers
Knowledge
Knowledge Knowledge
Repository
Acquisition & (Knowledge Storage) Transformation
Capture
DATA CAPTURE AND TRANSFORMATION
TRANSFORMED DATA
Classification Association Prediction Clustering
KNOWLEDGE PROCESSING USING DM ENABLED KM
APPROACH
INSTITUTIONAL INTELLIGENCE
Rules Patterns Trends
Relaionships
KNOWLEDGE VISUALIZATION THROUGH INSTITUTIONAL INTELLIGENCE
AXN OUTPUTS AND OUTCOMES
Performance Process Improvement
Management Decision Making
KM SERVICES
Fig. 1: A Four Tiered Architecture for Developing Institutional Intelligence
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4. Conclusion and Future Work
Higher educational institutions today desire high levels of institutional intelligence in order to achieve their educational
goals and objectives. Till very recently technology was not amenable to the intelligence levels required. Recent years have
experienced information technology as a tool to capture, store, transform and distribute knowledge. However the utilization
of the institutional knowledge into actionable intelligence has not been exploited by HEIs to enhance and deliver their
services better. HEIs need to structure KM applications to facilitate capture the institutional knowledge and convert it into
institutional intelligence to be used for decision making, planning and implementing the institutional processes.
In order to establish the priority for constructing institutional intelligence from institutional knowledge, the author identified
the generic functional domains in HEIs and the performance indicators that determine the performance in the functional
domains and further proposed a tiered architecture to transform the knowledge into intelligence. As a future work, the author
proposes to implement the architecture by applying data mining methods to achieve outcomes illustrated in table 1. The
author concludes that the final outcome of such application is improvement in the overall quality management system in
HEIs.
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Appendix :
Table 1: Data Mining Outcomes for KM in Functional Domains
Input Knowledge Outcome of Data Mining Process / Benefits to the stakeholders Data Mining Function
(Performance Indicators in Institutional Intelligence
Functional Domains)
Institutional Teaching and Learning Process
Teaching material Clusters of teaching material in Easy and quick availability Clustering
prepared by the faculty accordance with topics / of teaching material
relevance
Course plans – Patterns in successful course Designing effective course Classification
proposed and actual plans plans
Curriculum Patterns in curriculum revisions Design of new curriculum Prediction
Patterns in factors that determine
curriculum revisions
Frequently asked Clusters of FAQs for various Efficient access to queries Clustering
Questions (FAQs) topics / subjects
Effective teaching methodologies Clusters of teaching Availability of efficient Clustering
used by faculty methodologies for various topics / teaching methodologies Classification
subjects Prediction of effective
Patterns of success of teaching teaching methodology for a
methodologies topic / subject
Faculty Performance
Courses taught by faculty Clusters of expertise of faculty Assignment of courses to Clustering
faculty
Results in courses taught by Patterns of results based on pre Evaluation of faculty Classification
faculty defined parameters Assignment of courses to Clustering
faculty
Design of strategies for
faculty improvement
Awards and recognition to
faculty
Research activity Patterns of research areas of Identification of research Classification
faculty areas Prediction
Clusters of related research areas Prediction of research
Clusters of related research trends
literature Research guidance
Clusters of available guidance Awards and recognition to
faculty
Student feedback Patterns in student feedback Faculty recognition Classification
based on pre-defined parameters Faculty counselling Clustering
Patterns in competencies / skills Designing strategies for
most sought for faculty improvement
Career development plans
Peer rating Patterns of peer rating based on Self improvement Clustering
pre defined parameters Team work Classification
Patterns in skills most sought for Counselling
Patterns in missing / deficient
skills
Administrative responsibilities Clusters of administrative Assignment of Clustering
carried out by the faculty responsibilities in functional responsibilities Classification
domains Faculty skill development
Patterns of administrative initiatives
responsibilities performed Team work
Initiatives for self Patterns of self improvement and Support for self Classification
improvement and career career development initiatives improvement
development Patterns of success rates of self Career Development plans
improvement and career
development initiatives
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