This document provides the syllabus for a Knowledge Management course offered by Occidental Mindoro State College. The syllabus outlines the course description, objectives, topics, activities, assessments and policies. The course aims to equip students with an understanding of knowledge management principles and strategies, and their application to development programs. Over 18 weeks, students will learn about knowledge management theories, tools, processes and challenges. Assessments include quizzes, activities, presentations, exams and a final knowledge management plan project. The syllabus adheres to the college's vision of developing globally competitive and lifelong learners.
Human-Centered Learning Analytics and Artificial Intelligence in Education: H...Yannis
Although Artificial Intelligence (AI) and Learning Analytics (LA) have shown their potential in Education, stakeholders’ agency seems to be threatened. On the other hand, multiple issues regarding FATE (Fairness, Accountability, Transparency and Ethics) have been raised when AI or LA-based solutions are designed and implemented. These issues have been especially acute since the emergence of Large Language Models and Generative AI.
This talk discusses the quest for an optimal balance between human and computational agents, when LA tools and services are employed in a Technology Enhanced Learning (TEL) ecosystem. Through the discussion of relevant conceptual models and examples, it argues for Human-Centered Learning Analytics (HCLA) and Human-Centered Artificial Intelligence (HCAI) approaches, where agency and FATE principles are essential design parameters.
The talk focuses especially on LA/AI solutions that may position teachers as designers of effective interventions and orchestration actions. Selected Human-Centered Design (HCD) principles are discussed and illustrated, and directions for future research and development are formulated to overcome the main obstacles for adoption of human-centered approaches for LA and AI in education.
Computers in Human Behavior xxx (2012) xxx–xxxContents lists.docxpatricke8
Computers in Human Behavior xxx (2012) xxx–xxx
Contents lists available at SciVerse ScienceDirect
Computers in Human Behavior
j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p h u m b e h
Critical thinking in E-learning environments
Raafat George Saadé a,⇑, Danielle Morin a,1, Jennifer D.E. Thomas b,2
a Concordia University, John Molson School of Business, Montreal, Quebec, Canada
b Pace University, Ivan Seidenberg School of CSIS, New York, NY, USA
a r t i c l e i n f o
Article history:
Available online xxxx
Keywords:
E-learning
Critical thinking
Assessment
Information technology
0747-5632/$ - see front matter � 2012 Elsevier Ltd. A
http://dx.doi.org/10.1016/j.chb.2012.03.025
⇑ Corresponding author. Tel.: +1 514 848 2424; fax
E-mail address: [email protected] (R.G. Sa
1 Tel.: +1 514 848 2424; fax: +1 514 848 2824.
2 Tel.: +1 212 346 1569; fax: +1 212 346 1863.
Please cite this article in press as: Saadé, R. G., e
10.1016/j.chb.2012.03.025
a b s t r a c t
One of the primary aims of higher education in today’s information technology enabled classroom is to
make students more active in the learning process. The intended outcome of this increased IT-facilitated
student engagement is to foster important skills such as critical thinking used in both academia and
workplace environments. Critical thinking (CT) skills entails the ability(ies) of mental processes of discern-
ment, analysis and evaluation to achieve a logical understanding. Critical thinking in the classroom as well
as in the workplace is a central theme; however, with the dramatic increase of IT usage the mechanisms by
which critical thinking is fostered and used has changed. This article presents the work and results of
critical thinking in a virtual learning environment. We therefore present a web-based course and we
assess in which parts of the course, and to what extent, critical thinking was perceived to occur. The course
contained two categories of learning modules namely resources and interactive components. Critical
thinking was measured subjectively using the ART scale. Results indicate the significance of ‘‘interactivity’’
in what students perceived to be critical-thinking-oriented versus online material as a resource. Results
and opportunities that virtual environments present to foster critical thinking are discussed.
� 2012 Elsevier Ltd. All rights reserved.
1. Introduction
One of the primary aims of higher education in today’s informa-
tion technology (IT) enabled classroom, is to make students more
active in the learning process (Ibrahim & Samsa, 2009). The in-
tended outcome of this increased IT-facilitated student engage-
ment is to foster important skills such as critical thinking. Given
the importance of information technology for critical thinking in
learning, it is vital that we understand better the associated key
factors related to: background of students, beliefs, perceptions
and attitudes and associated anteceden.
Assessing The Tangible And Intangible Impacts Of The Convergence Of E-Learnin...ijistjournal
Learning comes through creating and applying knowledge, whilst learning increases an individual's and organization's knowledge asset. Both e-learning and knowledge management feed off the same root: learning, improved capacity to perform work tasks, ability to make effective decisions, and positively impact the world around us. The difference between KM and e-learning is a function of time; knowledge management is dynamic, e-learning is static. As a medium, e-learning allows for the sharing of knowledge that has been tested, researched and organized. Knowledge management is much livelier. Conversations and sharing understanding happens in real time. Through KM, tacit understanding can be communicated, problems can be jointly solved, and serendipitous connections are formed. KM is chaotic, current. KM is ecology; e-learning is the architecture. E-learning courses become outdated, while KM environments are continually fresh and reflective of current activity in a field. Anyway, the strengths of the two fields need to be brought together. KM should feed into e-learning in order for the content of the "course" to remain fresh and to tap learners into a sustained knowledge environment after the course is done and e-learning should feed into the KM environment to provide easy mechanisms for organizing information in the manner that most of the people function. There‟s no doubt that converging this two technology creates bigger impact in the learning process, but our discussion is focused to justify whether the convergence creates better value or not. In the light of the discussion, the conceptual link between these two key technologies has been drawn and several related issues are discussed.
Human-Centered Learning Analytics and Artificial Intelligence in Education: H...Yannis
Although Artificial Intelligence (AI) and Learning Analytics (LA) have shown their potential in Education, stakeholders’ agency seems to be threatened. On the other hand, multiple issues regarding FATE (Fairness, Accountability, Transparency and Ethics) have been raised when AI or LA-based solutions are designed and implemented. These issues have been especially acute since the emergence of Large Language Models and Generative AI.
This talk discusses the quest for an optimal balance between human and computational agents, when LA tools and services are employed in a Technology Enhanced Learning (TEL) ecosystem. Through the discussion of relevant conceptual models and examples, it argues for Human-Centered Learning Analytics (HCLA) and Human-Centered Artificial Intelligence (HCAI) approaches, where agency and FATE principles are essential design parameters.
The talk focuses especially on LA/AI solutions that may position teachers as designers of effective interventions and orchestration actions. Selected Human-Centered Design (HCD) principles are discussed and illustrated, and directions for future research and development are formulated to overcome the main obstacles for adoption of human-centered approaches for LA and AI in education.
Computers in Human Behavior xxx (2012) xxx–xxxContents lists.docxpatricke8
Computers in Human Behavior xxx (2012) xxx–xxx
Contents lists available at SciVerse ScienceDirect
Computers in Human Behavior
j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p h u m b e h
Critical thinking in E-learning environments
Raafat George Saadé a,⇑, Danielle Morin a,1, Jennifer D.E. Thomas b,2
a Concordia University, John Molson School of Business, Montreal, Quebec, Canada
b Pace University, Ivan Seidenberg School of CSIS, New York, NY, USA
a r t i c l e i n f o
Article history:
Available online xxxx
Keywords:
E-learning
Critical thinking
Assessment
Information technology
0747-5632/$ - see front matter � 2012 Elsevier Ltd. A
http://dx.doi.org/10.1016/j.chb.2012.03.025
⇑ Corresponding author. Tel.: +1 514 848 2424; fax
E-mail address: [email protected] (R.G. Sa
1 Tel.: +1 514 848 2424; fax: +1 514 848 2824.
2 Tel.: +1 212 346 1569; fax: +1 212 346 1863.
Please cite this article in press as: Saadé, R. G., e
10.1016/j.chb.2012.03.025
a b s t r a c t
One of the primary aims of higher education in today’s information technology enabled classroom is to
make students more active in the learning process. The intended outcome of this increased IT-facilitated
student engagement is to foster important skills such as critical thinking used in both academia and
workplace environments. Critical thinking (CT) skills entails the ability(ies) of mental processes of discern-
ment, analysis and evaluation to achieve a logical understanding. Critical thinking in the classroom as well
as in the workplace is a central theme; however, with the dramatic increase of IT usage the mechanisms by
which critical thinking is fostered and used has changed. This article presents the work and results of
critical thinking in a virtual learning environment. We therefore present a web-based course and we
assess in which parts of the course, and to what extent, critical thinking was perceived to occur. The course
contained two categories of learning modules namely resources and interactive components. Critical
thinking was measured subjectively using the ART scale. Results indicate the significance of ‘‘interactivity’’
in what students perceived to be critical-thinking-oriented versus online material as a resource. Results
and opportunities that virtual environments present to foster critical thinking are discussed.
� 2012 Elsevier Ltd. All rights reserved.
1. Introduction
One of the primary aims of higher education in today’s informa-
tion technology (IT) enabled classroom, is to make students more
active in the learning process (Ibrahim & Samsa, 2009). The in-
tended outcome of this increased IT-facilitated student engage-
ment is to foster important skills such as critical thinking. Given
the importance of information technology for critical thinking in
learning, it is vital that we understand better the associated key
factors related to: background of students, beliefs, perceptions
and attitudes and associated anteceden.
Assessing The Tangible And Intangible Impacts Of The Convergence Of E-Learnin...ijistjournal
Learning comes through creating and applying knowledge, whilst learning increases an individual's and organization's knowledge asset. Both e-learning and knowledge management feed off the same root: learning, improved capacity to perform work tasks, ability to make effective decisions, and positively impact the world around us. The difference between KM and e-learning is a function of time; knowledge management is dynamic, e-learning is static. As a medium, e-learning allows for the sharing of knowledge that has been tested, researched and organized. Knowledge management is much livelier. Conversations and sharing understanding happens in real time. Through KM, tacit understanding can be communicated, problems can be jointly solved, and serendipitous connections are formed. KM is chaotic, current. KM is ecology; e-learning is the architecture. E-learning courses become outdated, while KM environments are continually fresh and reflective of current activity in a field. Anyway, the strengths of the two fields need to be brought together. KM should feed into e-learning in order for the content of the "course" to remain fresh and to tap learners into a sustained knowledge environment after the course is done and e-learning should feed into the KM environment to provide easy mechanisms for organizing information in the manner that most of the people function. There‟s no doubt that converging this two technology creates bigger impact in the learning process, but our discussion is focused to justify whether the convergence creates better value or not. In the light of the discussion, the conceptual link between these two key technologies has been drawn and several related issues are discussed.
Assessing The Tangible And Intangible Impacts Of The Convergence Of E-Learnin...ijistjournal
Learning comes through creating and applying knowledge, whilst learning increases an individual's and organization's knowledge asset. Both e-learning and knowledge management feed off the same root: learning, improved capacity to perform work tasks, ability to make effective decisions, and positively impact the world around us. The difference between KM and e-learning is a function of time; knowledge management is dynamic, e-learning is static. As a medium, e-learning allows for the sharing of knowledge that has been tested, researched and organized. Knowledge management is much livelier. Conversations and sharing understanding happens in real time. Through KM, tacit understanding can be communicated,problems can be jointly solved, and serendipitous connections are formed. KM is chaotic, current. KM is ecology; e-learning is the architecture. E-learning courses become outdated, while KM environments are continually fresh and reflective of current activity in a field. Anyway, the strengths of the two fields need to be brought together. KM should feed into e-learning in order for the content of the "course" to remain fresh and to tap learners into a sustained knowledge environment after the course is done and e-learning should feed into the KM environment to provide easy mechanisms for organizing information in the manner that most of the people function. Thereis no doubt that converging this two technology creates bigger impact in the learning process, but our discussion is focused to justify whether the convergence creates better value or not. In the light of the discussion, the conceptual link between these two key technologies has been drawn and several related issues are discussed.3.
Presentation by Mr. Adam Rahman from KNUST Dept. of Communication Design on instructional design models and principles for OER.
Given in February 2011 at University of Michigan and August 2011 in Kumasi.
CC BY NC SA Adam Rahman
Webinar: Learning Informatics Lab, University of Minnesota
Replay the talk: https://youtu.be/dcJZeDIMr2I
Learning Informatics
AI • Analytics • Accountability • Agency
Simon Buckingham Shum
Professor of Learning Informatics
Director, Connected Intelligence Centre
University of Technology Sydney
Abstract:
“Health Informatics”. “Urban Informatics”. “Social Informatics”. Informatics offers systemic ways of analyzing and designing the interaction of natural and artificial information processing systems. In the context of education, I will describe some Learning Informatics lenses and practices which we have developed for co-designing analytics and AI with educators and students. We have a particular focus on closing the feedback loop to equip learners with competencies to navigate a complex, uncertain future, such as critical thinking, professional reflection and teamwork. En route, we will touch on how we build educators’ trust in novel tools, our design philosophy of “embracing imperfection” in machine intelligence, and the ways that these infrastructures embody values. Speaking from the perspective of leading an institutional innovation centre in learning analytics, I hope that our experiences spark productive reflection around as the UMN Learning Informatics Lab builds its program.
Biography:
Simon Buckingham Shum is Professor of Learning Informatics at the University of Technology Sydney, where he serves as inaugural director of the Connected Intelligence Centre. CIC is a transdisciplinary innovation centre, using analytics to provide new insights for university teams, with particular expertise in educational data science. Simon’s career-long fascination with software’s ability to make thinking visible has seen him active in communities including Computer-Supported Cooperative Work, Hypertext, Design Rationale, Scholarly Publishing, Semantic Web, Computational Argumentation, Educational Technology and Learning Analytics. The challenge of visualizing contested knowledge has produced several books: Visualizing Argumentation, Knowledge Cartography, and Constructing Knowledge Art. He has been active over the last decade in shaping the field of Learning Analytics, co-founding the Society for Learning Analytics Research, and catalyzing several strands: Social Learning Analytics, Discourse Analytics, Dispositional Analytics and Writing Analytics. http://Simon.BuckinghamShum.net
Can Technological, Organizational and Individual Antecedents Together Optimiz...Dr. Amarjeet Singh
Faculty members’ are the intellectual leader for
developing societies. It is believed that the new knowledge
is created and transferred to the people in the Universities.
Although, relatively still an infancy field of research,
studies in Knowledge Management (KM) and Knowledge
Sharing (KS) continue to be on the boost. Knowledge
Sharing and Innovation are also whispered to be interrelated and could influence organizational performance.
Studies show that individual’s knowledge does not renovate
simply into institutional knowledge even with the use of
knowledge depository. Furthermore, it is also believed that
Information and Communication Technology (ICT) can
enhance knowledge sharing with the integration of
individual behaviour and diverse organizational factors. As
a comparatively new field of research, studies on
knowledge sharing based on Information Systems (IS) in
developed countries is also on the increase. Unfortunately,
knowledge sharing research in the higher academic
institutions in developing countries were mostly found to be
given trivial considerations. Therefore, the aim of this
study is to investigate whether the technological,
organizational and individual factors together can help
increase Knowledge Sharing in HEIs and contribute it in
augmenting organizational performance in developing
countries. The methodology of this study was
subjective/argumentative i.e., idea generation in
Information Systems (IS). The findings of the study reveal
that utilizing the technological, organizational and
individual antecedents together for organizational
knowledge sharing can augment overall organizational
performance. The study explored the antecedents that
increased innovation in organizations. These were the
individual intention, attitude, self-efficacy for training and
development, subjective norm, organizational trust,
leadership, organizational rewards, organizational culture,
social network, and use of ICT. It also reveals that KS
could be increased in the organizations utilizing selecting
and initiating proper antecedents for practicing KS. We
desire to extend this study to further an empirical
investigation on the same issue to validate the research
results.
Assessing The Tangible And Intangible Impacts Of The Convergence Of E-Learnin...ijistjournal
Learning comes through creating and applying knowledge, whilst learning increases an individual's and organization's knowledge asset. Both e-learning and knowledge management feed off the same root: learning, improved capacity to perform work tasks, ability to make effective decisions, and positively impact the world around us. The difference between KM and e-learning is a function of time; knowledge management is dynamic, e-learning is static. As a medium, e-learning allows for the sharing of knowledge that has been tested, researched and organized. Knowledge management is much livelier. Conversations and sharing understanding happens in real time. Through KM, tacit understanding can be communicated,problems can be jointly solved, and serendipitous connections are formed. KM is chaotic, current. KM is ecology; e-learning is the architecture. E-learning courses become outdated, while KM environments are continually fresh and reflective of current activity in a field. Anyway, the strengths of the two fields need to be brought together. KM should feed into e-learning in order for the content of the "course" to remain fresh and to tap learners into a sustained knowledge environment after the course is done and e-learning should feed into the KM environment to provide easy mechanisms for organizing information in the manner that most of the people function. Thereis no doubt that converging this two technology creates bigger impact in the learning process, but our discussion is focused to justify whether the convergence creates better value or not. In the light of the discussion, the conceptual link between these two key technologies has been drawn and several related issues are discussed.3.
Presentation by Mr. Adam Rahman from KNUST Dept. of Communication Design on instructional design models and principles for OER.
Given in February 2011 at University of Michigan and August 2011 in Kumasi.
CC BY NC SA Adam Rahman
Webinar: Learning Informatics Lab, University of Minnesota
Replay the talk: https://youtu.be/dcJZeDIMr2I
Learning Informatics
AI • Analytics • Accountability • Agency
Simon Buckingham Shum
Professor of Learning Informatics
Director, Connected Intelligence Centre
University of Technology Sydney
Abstract:
“Health Informatics”. “Urban Informatics”. “Social Informatics”. Informatics offers systemic ways of analyzing and designing the interaction of natural and artificial information processing systems. In the context of education, I will describe some Learning Informatics lenses and practices which we have developed for co-designing analytics and AI with educators and students. We have a particular focus on closing the feedback loop to equip learners with competencies to navigate a complex, uncertain future, such as critical thinking, professional reflection and teamwork. En route, we will touch on how we build educators’ trust in novel tools, our design philosophy of “embracing imperfection” in machine intelligence, and the ways that these infrastructures embody values. Speaking from the perspective of leading an institutional innovation centre in learning analytics, I hope that our experiences spark productive reflection around as the UMN Learning Informatics Lab builds its program.
Biography:
Simon Buckingham Shum is Professor of Learning Informatics at the University of Technology Sydney, where he serves as inaugural director of the Connected Intelligence Centre. CIC is a transdisciplinary innovation centre, using analytics to provide new insights for university teams, with particular expertise in educational data science. Simon’s career-long fascination with software’s ability to make thinking visible has seen him active in communities including Computer-Supported Cooperative Work, Hypertext, Design Rationale, Scholarly Publishing, Semantic Web, Computational Argumentation, Educational Technology and Learning Analytics. The challenge of visualizing contested knowledge has produced several books: Visualizing Argumentation, Knowledge Cartography, and Constructing Knowledge Art. He has been active over the last decade in shaping the field of Learning Analytics, co-founding the Society for Learning Analytics Research, and catalyzing several strands: Social Learning Analytics, Discourse Analytics, Dispositional Analytics and Writing Analytics. http://Simon.BuckinghamShum.net
Can Technological, Organizational and Individual Antecedents Together Optimiz...Dr. Amarjeet Singh
Faculty members’ are the intellectual leader for
developing societies. It is believed that the new knowledge
is created and transferred to the people in the Universities.
Although, relatively still an infancy field of research,
studies in Knowledge Management (KM) and Knowledge
Sharing (KS) continue to be on the boost. Knowledge
Sharing and Innovation are also whispered to be interrelated and could influence organizational performance.
Studies show that individual’s knowledge does not renovate
simply into institutional knowledge even with the use of
knowledge depository. Furthermore, it is also believed that
Information and Communication Technology (ICT) can
enhance knowledge sharing with the integration of
individual behaviour and diverse organizational factors. As
a comparatively new field of research, studies on
knowledge sharing based on Information Systems (IS) in
developed countries is also on the increase. Unfortunately,
knowledge sharing research in the higher academic
institutions in developing countries were mostly found to be
given trivial considerations. Therefore, the aim of this
study is to investigate whether the technological,
organizational and individual factors together can help
increase Knowledge Sharing in HEIs and contribute it in
augmenting organizational performance in developing
countries. The methodology of this study was
subjective/argumentative i.e., idea generation in
Information Systems (IS). The findings of the study reveal
that utilizing the technological, organizational and
individual antecedents together for organizational
knowledge sharing can augment overall organizational
performance. The study explored the antecedents that
increased innovation in organizations. These were the
individual intention, attitude, self-efficacy for training and
development, subjective norm, organizational trust,
leadership, organizational rewards, organizational culture,
social network, and use of ICT. It also reveals that KS
could be increased in the organizations utilizing selecting
and initiating proper antecedents for practicing KS. We
desire to extend this study to further an empirical
investigation on the same issue to validate the research
results.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
The French Revolution Class 9 Study Material pdf free download
Syllabus_Knowledge Management_OBE_2022-2023.pdf
1. Reference No.: OMSC-Form-COL-13 Effectivity Date: January 07, 2022 Revision No.02
Republic of the Philippines
OCCIDENTAL MINDORO STATE COLLEGE
San Jose, Occidental Mindoro
Website: www.omsc.edu.ph Email address: omsc_9747@yahoo.com
Tele/Fax: (043) 491-1460
College of Arts, Sciences & Technology
BACHELOR OF SCIENCE IN DEVELOPMENT COMMUNICATION
OBE COURSE SYLLABUS
OMSC VISION
A premier higher education institution that develops globally competitive, locally responsive, innovative professional and lifelong learners.
OMSC MISSION
OMSC is committed to produce intellectual and human capital by developing excellent graduates through outcomes-based instruction, relevant research ,responsive
technical advisory services ,community engagement, and sustainable production
COLLEGE OF ARTS, SCIENCES, AND TECHNOLOGY GOAL
The College of Arts, Sciences, and Technology aims to provide excellent education to students equipped with the necessary knowledge and skills in their specialized
profession.
COURSE TITLE: Knowledge Management
COURSE DESCRIPTION: Principles, processes and strategies of identifying, capturing, analyzing, storing, and sharing knowledge within an organization.
These elements are facilitated by the use of ICT (CMO No. 36, s. 2017).
COURSE CODE: RC2202
CREDIT UNITS: 3
PREREQUISITES: None
PROGRAM GOAL:
This program aims to equip students with the knowledge and skills needed in teaching, managing, and implementing communication programs for development.
PROGRAM OUTCOMES:
Graduates of BS Development Communication are able to
Develop a critical understanding of development perspective;
2. Reference No.: OMSC-Form-COL-13 Effectivity Date: January 07, 2022 Revision No.02
Define and access information needs; assess and organize information and knowledge; produce, share, and utilize information and knowledge
Apply communication theories /models, principles, practices and tools in development work.
Develop a communication program/plan
Demonstrate effective interpersonal skills as a linker, networker and mediator.
Communicate in different formats and plat forms (print, broadcast and online)
Develop and produce multi-media materials
Demonstrate program management and leadership skills;
Develop entrepreneurial capabilities;
Adhere to ethical standards and practices;
Know and practice rights and responsibilities and accountabilities in the communication process profession; and
Integrate technical knowledge (eg. Biological Science, Physical Science, Health Science, and Applied Science
COURSE OUTCOMES:
At the end of the course, the students should :
1. Understand the importance of knowledge management in development.
2. Apply knowledge management theories in developmental programs.
3. Distinguish the different knowledge management tools and strategies for development.
4. Propose a KM development effort in organizations.
COURSE OUTLINE
Week Desired Learning
Outcomes
Course Content Textbooks/
References
Teaching/Learning
Activities
Resource Materials Assessment
1 Familiarize the
students with the
OMSC VMGO,
Quality Policy and
College’s goals.
VMGO of OMSC
GAD Topic on Republic Act No.
9344, as amended by RA 10630,
defines the “Juvenile Justice and
Welfare Act
Quality Policy Manual
Student Handbook
PCW Reading on RA
10630 Materials
Discussion Student Handbook
Official
Website/Page of
the Institution
Creative
representation of
the student’s
understanding of
the VMGO &
RA 10630
2-4
Understand the
importance of
knowledge
management in
development.
I. Introduction to Knowledge
Management (KM)
-Understanding Knowledge
-Definition of KM
-Importance of KM
-Nature of KM
Alavi, M. & Leidner, D.E.
(2001). Knowledge
Management and
Knowledge Management
Systems: Conceptual
Foundations and
Research Issues. MIS
Lecture
Discussion
Research
Online Videos
Group Work
Games
Online Platforms
Journal Articles
E-Learning Sites
FB Group Chat
Google Drive
Videos/AVP
1st Case Study
Nonaka, I., & Takeuchi,
H. (1995). The
knowledge creating
company: How
Japanese companies
create the dynamics of
innovation.
3. Reference No.: OMSC-Form-COL-13 Effectivity Date: January 07, 2022 Revision No.02
- Elements of KM: People; Process;
and – Technology
- KM for Individuals,
Communities, and Organizations
Quarterly, 25(1):107-
136.
Dalkir, K. (2011).
Knowledge Management
in Theory and Practice
(2nd edition).
Cambridge,
Massachusetts: The MIT
Press
Danijela J. D. (2011). The
importance of knowledge
management in
organizations – with
emphasis on the balanced
scorecard learning and
growth perspective.
Management, knowledge
and learning international
conference.
https://ideas.repec.org/h/i
sv/mklp11/33-43.html
Quiz
Activity
5-6
Apply KM theories
and practice in
developmental
programs
II. Theoretical Foundation and
Models of Knowledge
Management (KM)
- Major Theoretical KM Models
-Von Krogh and Roos Model of
Organizational Epistemology
- Nonaka & Takeuchi Knowledge
Spiral Model
- Choo Sense-Making KM Model
- ISO/DIS 30401
Baskerville, R. &
Dulipovici, A. (2006).
The Theoretical
Foundations of
Knowledge
Management.
Knowledge
Management Research
and Practice. 4.
10.1057/palgrave.kmrp.
8500090.
ISO DIS 30401, 2017
Edition, November 23,
2017- KNOWLEDGE
MANAGEMENT
SYSTEMS
Lecture
Discussion
Research
Online Videos
Group Work
Online course
Journal Articles
E-Learning Sites
FB Group Chat
Google Drive
Videos/AVP
Quiz
Activity on
compilation of
KM Theories
4. Reference No.: OMSC-Form-COL-13 Effectivity Date: January 07, 2022 Revision No.02
7-8
Determine the
different KM tools
used.
III. Knowledge Management
Tools
- Knowledge Capture and Creation
Tools
-Knowledge Sharing and
Dissemination Tools
Dalkir, K. (2011).
Knowledge
Management in Theory
and Practice (2nd
edition). Cambridge,
Massachusetts: The
MIT Press
Lecture
Discussion
Research
Online Videos
Group Work
Games
Journal Articles
E-Learning Sites
FB Group Chat
Google Drive
Videos/AVP
Quiz
Activity
9th week-Midterm Examination
10-13
Distinguish the
different knowledge
management tools
and strategies for
development
III. Knowledge Management
(KM) Process, Strategy & Systems
- Knowledge Capture
-KM Process
-KM Systems
-KM Strategy
Dalkir, K. (2011).
Knowledge Management
in Theory and Practice
(2nd edition).
Cambridge,
Massachusetts: The MIT
Press
Mcinerney, C. & Koenig,
M. (2011). Knowledge
Management (KM)
Processes in
Organizations:
Theoretical Foundations
and Practice.
10.2200/S00323ED1V01
Y201012ICR018.
Lecture
Discussion
Research
Online Videos
Group Work
Games
Journal Articles
E-Learning Sites
FB Group Chat
Google Drive
Videos/AVP
2nd Case Study:
Watson, I.
(2003). Applying
Knowledge
Management.
Techniques for
Building
Corporate
Memories. San
Francisco:
Morgan
Kaufmann
Publisher.
Chapter 3
14-17
Discuss the
challenges and
issues of concern in
implementing KM
IV. Knowledge Management
(KM) Challenges, Solutions and
Technologies
-Barriers to KM
- Future Challenges for KM
-Technologies used in KM
De Long, D.W. and Fahey,
L. (2000) Diagnosing
cultural barriers to
knowledge management.
Academy of
Management Executive
14(4),113–127.
Lecture
Discussion
Research
Online Videos
Group Work
Games
Journal Articles
E-Learning Sites
FB Group Chat
Google Drive
Videos/AVP
Quiz
Activity- Craft
a KM Plan
18th week- Final Examination
5. Reference No.: OMSC-Form-COL-13 Effectivity Date: January 07, 2022 Revision No.02
SUGGESTED LEARNING RESOURCES:
Alavi, M. & Leidner, D.E. (2001). Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. MIS Quarterly,
25(1):107-136.
Baskerville, R. & Dulipovici, A. (2006). The Theoretical Foundations of Knowledge Management. Knowledge Management Research and Practice. 4.
10.1057/palgrave.kmrp.8500090.
Dalkir, K. (2011). Knowledge Management in Theory and Practice (2nd edition). Cambridge, Massachusetts: The MIT Press
Danijela J. D. (2011). The importance of knowledge management in organizations – with emphasis on the balanced scorecard learning and growth perspective.
Management, knowledge and learning international conference. https://ideas.repec.org/h/isv/mklp11/33-43.html
Desouza, K. C. (2011). An introduction to knowledge management. In: K. C. Desouza and S.Paquette (Eds.), Knowledge Management: An Introduction (pp. 3-34).
New York: NY: Neal-Schuman Publishers, Inc
De Long, D.W. and Fahey, L. (2000) Diagnosing cultural barriers to knowledge management. Academy of Management Executive 14(4),113–127.
Frappaolo, C. (1998) Defining knowledge management: four basic functions. Computerworld 32(8), 80.
Grossman, M, (2007). The emerging academic discipline of knowledge management. Journal of information systems education.
Mcinerney, C. & Koenig, M. (2011). Knowledge Management (KM) Processes in Organizations: Theoretical Foundations and Practice.
10.2200/S00323ED1V01Y201012ICR018.
Ramadan, B. M., Dahiyat, S. E., Bontis, N., & Al-Dalahmeh, M. A. (2017). Intellectual capital, knowledge management and social capital within the ICT sector in
Jordan. Journal of Intellectual Capital, 18(2), 437-462.
Sharabati, A. A. A., Naji Jawad, S., & Bontis, N. (2010). Intellectual Capital and Business Performance in the pharmaceutical sector of Jordan. Management
Decision, 48(1), 105-131.
Tan, M. , Chaudhry, A. S. & Lee, C. (2009). Establishing the taxonomy of knowledge management: An analysis of the structural components of the discipline.
International Journal of Knowledge, Culture and Change Management, 9(3), 177-196.
6. Reference No.: OMSC-Form-COL-13 Effectivity Date: January 07, 2022 Revision No.02
Wang, Wang, & Liang (2014). Knowledge sharing, intellectual capital and firm performance, Management Decision, 52(2), 230-258.
Zack, M., McKeen, J. & Singh, S. (2009). Knowledge management and organizational performance: an exploratory analysis. Journal of knowledge management,
13(6)
COURSE
REQUIREMENTS
Class standing/ Lecture
Attendance
Quizzes
Activities (including Attendance to webinar and E-course)
Research work
Midterm/Final Examination
Project
Creative Presentation of KM (Mideterm)
Knowledge Management Plan (Final Term)
GRADING SYSTEM
Mid-Term/Final Examination =40%
Class Standing =50%
Project =10%
100%
*Final Rating = Midterm (40%) + Final Term (60%)
COURSE POLICIES
Expectations from student:
The student’s responsibility is to come to each class prepared. S/he is also expected to take all examinations on the date
scheduled. S/he should read the assigned problems prior to class. S/he is expected to attend each class and participate
actively in the discussions.
Submission of requirements:
Submitted requirements will be evaluated as follows: Submission, Cleanliness, orderliness, format is 20%; Content or
accuracy of output including attitude towards work is 80%. Failure to submit required output will be given a grade of
65%.
Incomplete Grades
No final examination or its equivalent (conduct of extension) will be automatically given incomplete grade. Incomplete
grade should be complied within one year.
7. Reference No.: OMSC-Form-COL-13 Effectivity Date: January 07, 2022 Revision No.02
Academic Dishonesty
All students are expected to be academically honest. Cheating, lying and other forms of unethical behavior will not be
tolerated. Any student found guilty of cheating in examinations or plagiarism in submitted course requirements will
receive a failing grade in the course requirement or in the course.
Policy on absences
The allowed number of absences is 10% of the total class hours. It is the responsibility of the student to monitor her/his
own tardy incidents and absences that might accumulate leading to a grade of “Dropped.” It is also his/her responsibility
to consult with the instructor, program head or dean should her/his case be of special nature.
Policies stipulated in Colleges manuals will be strictly followed.
Prepared by:
MARY YOLE APPLE
DECLARO- RUEDAS
Associate Professor V
Consultation Hours:
M 1:00-4:00 pm
Noted:
LEOMAR CHRISTIAN NIELO
Program Head, BS DevCom
Recommending Approval:
MARICRIS M. USITA, EdD
Dean, College of Arts, Sciences and Technology
Approved:
NORMA B. MUYOT, ChE, EdD
Vice President for Academic Affairs