scholarly journals CENTRALIZED OUTCOME-BASED ASSESSMENT PROCESS AT MCGILL UNIVERSITY

2018 ◽  
Author(s):  
Nasim Razavinia ◽  
Laurent Mydlarski
Keyword(s):  
Data Analysis ◽  
Organizational Structure ◽  
Management System ◽  
Learning Management System ◽  
Assessment Process ◽  
Engineering Programs ◽  
Continual Improvement ◽  
Graduate Attributes ◽  
Essential Component ◽  
Mcgill University

Abstract - Compliance with the Graduate Attributes and Continual Improvement criteria is an essential component of the accreditation of engineering programs in Canada. In response to this requirement, McGill University’s Faculty of Engineering established a centralized process in which 1) a uniform organizational structure was established, 2) a set of common graduate attribute indicators was developed, 3) the current Learning Management System (D2L) was integrated into the assessment of the graduate attributes, 4) universal indirect assessments for all programs were designed, 5) consistent data analysis and interpretation processes were implemented, and 6) standardized guidelines for continual improvement were created. The implementation of this process, its strengths, and recommendations to increase its efficiency and sustainability are discussed in this paper.  

scholarly journals DEVELOPMENT OF PROCESSES AND CRITERIA FOR CEAB GRADUATE ATTRIBUTE ASSESSMENT

2011 ◽  
Author(s):  
Brian Frank
Keyword(s):  
Management System ◽  
Outcomes Assessment ◽  
Learning Management System ◽  
Assessment Criteria ◽  
System Software ◽  
Engineering Programs ◽  
Graduate Attributes ◽  
Working Groups ◽  
Assessment Measures ◽  
Degree Level

The Canadian Engineering Accreditation Board (CEAB) is following the lead of other accreditation bodies in requiring engineering programs to measure graduate attributes, also known as outcomes. Canadian ministers of education have also established undergraduate degree-level expectations that will imact engineering programs. This paper will review the evolution of outcomes assessment as it pertains to engineering accreditation and compare the new CEAB graduate attribute requirements to those of engineering accreditation bodies in countries including the U.S.A, U.K., and Australia. The process of implementing outcomes assessment at Queen's University will be described, including development of measurable assessment criteria from faculty working groups. Finally, the paper will provide an overview of learning management system software that can manage and report on assessment measures.

Selecting and Evaluating a Learning Management System

2011 ◽  
Vol 9 (3) ◽  
pp. 13-30 ◽  
Author(s):  
Andreas Konstantinidis ◽  
Pantelis M. Papadopoulos ◽  
Thrasyvoulos Tsiatsos ◽  
Stavros Demetriadis
Keyword(s):  
Blended Learning ◽  
Organizational Structure ◽  
Management System ◽  
Learning Management System ◽  
Learning Approach ◽  
Single System ◽  
Student Needs ◽  
Evaluation Data ◽  
Learning Management ◽  
New System

This paper presents the rationale behind the utilization of a Moodle Learning Management System for the facilitation of a blended learning approach in the Informatics department. The authors present and analyze the steps followed in order to replace the prior decentralized organizational structure of the courses, which consisted of a multitude of different and incompatible systems. The main goal was to implement a single system, which would be easy to operate, maintain, and update, and would cater to the variety of instructor and student needs. Furthermore, evaluation data of the new system is presented in detail. The analysis of the results serves to confirm the success of this department-wide migration.

Data Mining and Explorative Multivariate Data Analysis for Customer Satisfaction Study

2011 ◽  
pp. 243-266 ◽  
Author(s):  
Rosaria Lombardo
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Customer Satisfaction ◽  
Management System ◽  
Multivariate Data Analysis ◽  
Learning Management System ◽  
Multivariate Data ◽  
Data Sets ◽  
System Data ◽  
Learning Management

By the early 1990s, the term “data mining” had come to mean the process of finding information in large data sets. In the framework of the Total Quality Management, earlier studies have suggested that enterprises could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk customers/consumers and allow for more timely interventions (Macfadyen & Dawson, 2009). The Learning Management System data and the subsequent Customer Interaction System data can help to provide “early warning system data” for risk detection in enterprises. This chapter confirms and extends this proposition by providing data from an international research project investigating on customer satisfaction in services to persons of public utility, like education, training services and health care services, by means of explorative multivariate data analysis tools as Ordered Multiple Correspondence Analysis, Boosting regression, Partial Least Squares regression and its generalizations.

scholarly journals Intersecting Roadmaps: Resolving Tension Between Profession-Specific and University-Wide Graduate Attributes

2021 ◽  
pp. 71-98
Author(s):  
Samira ElAtia ◽  
Jason P. Carey ◽  
Marnie Jamieson ◽  
Bashair Alibrahim ◽  
Marcus Ivey
Keyword(s):  
Social Sciences ◽  
Management Strategies ◽  
Assessment Process ◽  
Continual Improvement ◽  
Graduate Attributes ◽  
Research Institution ◽  
Mapping Process ◽  
Backward Mapping ◽  
Program Graduate ◽  
Canadian Research

Can we map university-wide graduate attributes to specific program requirements? Can we develop and manage an integrated assessment process? In this article, we present a seven-month long project where we attempted to map generic university graduate attributes (UGAs) to required engineering program graduate attributes in a large Canadian research institution. The purpose of the project was to explore the intersection of the UGAs with engineering graduate attributes, evaluate the accreditation process, develop a mapping process, and examine management strategies for assessing both sets of graduate attributes, all the while keeping the continual improvement process attractive to students, instructors, and administrators. Using a modified dialectical inquiry, two groups worked on the mapping process: one from engineering, the other from social sciences (Education and Arts), to ensure objectivity of comparison. Both forward and backward mapping took place. Results demonstrated that, although generic, UGAs may not necessarily capture specific professional program graduate attributes. The study also highlighted the need for more revisions and updates of UGAs by including various stakeholders who can substantially contribute to the implementation and assessment of UGAs.

Selecting and Evaluating a Learning Management System

2014 ◽  
pp. 189-205
Author(s):  
Andreas Konstantinidis ◽  
Pantelis M. Papadopoulos ◽  
Thrasyvoulos Tsiatsos ◽  
Stavros Demetriadis
Keyword(s):  
Blended Learning ◽  
Organizational Structure ◽  
Management System ◽  
Learning Management System ◽  
Learning Approach ◽  
Single System ◽  
Student Needs ◽  
Evaluation Data ◽  
Learning Management ◽  
New System

This paper presents the rationale behind the utilization of a Moodle Learning Management System for the facilitation of a blended learning approach in the Informatics department. The authors present and analyze the steps followed in order to replace the prior decentralized organizational structure of the courses, which consisted of a multitude of different and incompatible systems. The main goal was to implement a single system, which would be easy to operate, maintain, and update, and would cater to the variety of instructor and student needs. Furthermore, evaluation data of the new system is presented in detail. The analysis of the results serves to confirm the success of this department-wide migration.

scholarly journals Factors Affecting Students' Acceptance of SMART2 Learning Management System

2017 ◽  
pp. 154-171 ◽  
Author(s):  
Liew Kian Loon ◽  
Chin Chen Mun ◽  
Teow Yong Kang ◽  
Sherah Chong Seh Rui ◽  
Lau Wei Ping ◽  
...  
Keyword(s):  
Data Analysis ◽  
Management System ◽  
Learning Management System ◽  
Factors Affecting ◽  
Multiple Regressions ◽  
Research Outcomes ◽  
Learning Management ◽  
State Of Affairs ◽  
Study Offer ◽  
Front Movement

The aims of this study is to inspect the factors affecting students' acceptance of SMART2 Learning Management System. This study applied a multiple regression for data analysis covering a sample of 218 respondents. Results revealed that the proposed hypothesis via multiple regressions validated that the acceptance and usage of SMART2 UMS was effected positively by the use behaviour. Research outcomes may benefit the learning management system market involving SMART2 UMS in developing constructive strategies to evaluate the usage behaviour of students in UMSLIC in using the SMART2 UMS learning management system and assess the acceptance level of students of SMART2 UMS towards the use behaviour. The consequences of this research study offer a new towards the front movement to the discoveries of advanced studies on acceptance and use behaviour, which is not revealed much in the literature in the state of affairs of UMSLIC by providing extra details in tapering the research space with considerations to comprehend the acceptance and usage of the SMART2 UMS.

scholarly journals A SHORT ONLINE COURSE TARGETING PROFESSIONALISM, THE IMPACT OF ENGINEERING ON SOCIETY AND THE ENVIRONMENT, AND ETHICS AND EQUITY

2020 ◽  
Author(s):  
Nasim Razavinia ◽  
Laurent Mydlarski
Keyword(s):  
Engineering Students ◽  
Online Course ◽  
Continual Improvement ◽  
Additional Training ◽  
Graduate Attributes ◽  
Improvement Process ◽  
Mcgill University ◽  
Curriculum Map ◽  
The Creation ◽  
The Impact

Understanding the role and responsibilities of Professional Engineers is of immediate relevance to those who aspire to enter the profession. These obligations most prominently manifest themselves in three of the twelve graduate attributes: Professionalism; the Impact of engineering on society and the environment; and Ethics and equity. Following an analysis of the curriculum map of programs that was performed as part of the CEAB-mandated Continual Improvement process at McGill University, it was concluded that our students could benefit from additional training in the aforementioned three graduate attributes. To this end, a required, 0-credit, online course was created to further expose and train Engineering students in all programs on these three important topics. The present paper will i) review the motivation behind the creation of this new course, ii) describe the evolution of its format and design, and iii) discuss the course’s contents and implementation.

Data Mining and Explorative Multivariate Data Analysis for Customer Satisfaction Study

Data Mining ◽  
2013 ◽  
pp. 1472-1495
Author(s):  
Rosaria Lombardo
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Customer Satisfaction ◽  
Management System ◽  
Multivariate Data Analysis ◽  
Learning Management System ◽  
Multivariate Data ◽  
Data Sets ◽  
System Data ◽  
Learning Management

By the early 1990s, the term “data mining” had come to mean the process of finding information in large data sets. In the framework of the Total Quality Management, earlier studies have suggested that enterprises could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk customers/consumers and allow for more timely interventions (Macfadyen & Dawson, 2009). The Learning Management System data and the subsequent Customer Interaction System data can help to provide “early warning system data” for risk detection in enterprises. This chapter confirms and extends this proposition by providing data from an international research project investigating on customer satisfaction in services to persons of public utility, like education, training services and health care services, by means of explorative multivariate data analysis tools as Ordered Multiple Correspondence Analysis, Boosting regression, Partial Least Squares regression and its generalizations.

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