Week 12

Decision tree: is also a knowledge codification technique. A decision tree is usually a hierarchically arranged semantic network.

Frame: A frame is a codification scheme used for organizing knowledge through previous experience. It deals with a combination of declarative and operational knowledge. Key elements of frames:

      Slot: A specific object being described/an attribute of an entity.

     Facet: The value of an object/slot.

Production Rule: They are conditional statements specifying an action to be taken in case a certain condition is true. They codify knowledge in the form of premise-action pairs.

Syntax: IF (premise) THEN (action)

Rules can incorporate certain levels of uncertainty. A certainty factor is synonymous with a confidence level, which is a subjective quantification of an expert's judgment. The premise is a Boolean expression that should evaluate to be true for the rule to be applied. The action part of the rule is separated from the premise by the keyword THEN. The action clause consists of a statement or a series of statements separated by AND's or comma's and is executed if the premise is true.

In case of knowledge-based systems, planning involves:

• Breaking the entire system into manageable modules.
• Considering partial solutions and liking them through rules and procedures to arrive at a final solution.
• Deciding on the programming languages.
• Deciding on the software packages.
• Testing and validating the system.
• Developing the user interface.
• Promoting clarity, flexibility; making rules clear.
• Reducing unnecessary risk.

Role of inference:

• Inference implies the process of deriving a conclusion based on statements that only imply that conclusion.
• An inference engine is a program that manages the inference strategies.
• Reasoning is the process of applying knowledge to arrive at the conclusion.

Case-Based Reasoning: Case-based reasoning is a technique that records and documents cases and then searches the appropriate cases to determine their usefulness in solving new cases presented to the expert. The aim is to bring up the most similar historical case that matches the present case. Adding new cases and reclassifying the case library usually expands knowledge. A case library may require considerable database storage as well as an efficient retrieval system.

Knowledge-Based Agents: An intelligent agent is a program code which is able to perform independent action in a appropriate manner. They can exhibit goal directed behavior by taking initiative. They can be programmed to interact with other agents or humans by using some agent communication language. In terms of knowledge-based systems, an agent can be programmed to learn from the user behavior and deduce future behavior for assisting the user.

Kulsum Raza

Week 11

Other Knowledge Capture techniques

On Site Observation: Process which involves knowledge developer observing the expert while solving the specific problem.
Brainstorming: Unstructured approach of creating ideas about solution of a problem. Questions can be raised for clarification.

Role of Knowledge Developer in Brainstorming:

General procedure for the session of brainstorming are as follows:

• Introduce and coordinate the brainstorming session
• Presenting the problem to the expert
• Prompt experts to generate ideas
• Watch for signs of possible convergence 

Electronic Brainstorming: Promotes instant exchange of ideas b/w experts that identifies objectives and structures the agenda. Through brainstorming effective communication can be made about the sensitive issues.

Protocol Analysis: Scenarios are collected by asking experts to solve the problem.

Consensus: Process of group decision making. Inputs gather from all experts and make final and better decision/solution.

Consensus Procedure:

• A proposal for resolution is put forward
• Amend and modify proposal through discussion
• Those participants who disagree with the proposal have the responsibility to put forward alternative proposals
• The one who put forward the proposal, with help of facilitator, can choose to withdraw proposal if seems to be dead end.
• When a proposal seems to be well understood and no new changes asked for, the facilitator confirm any objections
• If no objections, the facilitator can call for consensus
• If there are still no objections, then after a moment of silence, you have the decision
• If consensus appears to have reached, the facilitator repeats the decision so everyone is clear

Maheen Asif

Week 10

KM Architecture:

We classify fundamentals for KM systems in Layers that represents internal technologies of company which are as follows:

The User Interface: Interface b/w user and KM system like a web browser which should be consistent and easy to use.
Authorized Access Control: This layer ensures the unauthorized access to the info stored in company repositories. It maintains security.
Knowledge-Enabling Application: It provides knowledge Bases(i.e how performance can improve?), dbms information and aurtomation tools.

Transport Layer: Ensures that company will become a network of relationships such as LANs. WANs. intranets, extranets, and the internet.

Middleware: It makes possible to connect old and new data formats.

Physical Repositories: Most bottom layer of KM architecture where all repositories are installed.

KM System Development Life Cycle:

~Evaluate existing infrastructure~Form the KM team~Knowledge capture~Design KM blueprint (master plan)~Test the KM system~Implement the KM system~Manage change and reward structure~Post-system evaluation

Chapter 5

Capturing Tacit Knowledge

Knowledge Capturing: The process of gathering information about the expert's experience and thinking.

3 Important Steps:

• Use appropriate technique to gather info
• Interpret the info
• Build rules with the interpretations.

Level of Experts:

• Highly expert persons. 
• Moderately expert problem solvers. 
• New experts.

Individual Expert: Ideal when building simple KM system, easily conflicts can be resolved.

Multiple Experts: It can benefit complex problem domain and allow alternative way of representing knowledge.

Types of Interview:

Structured: Questions and responses are definitive.

Unstructured: Neither the questions nor their responses specified in advance.

Semi Structured: Predefined questions are asked.

Maheen Asif

Week 9

"MIDS EXAMS"

Week 8

FYP Mid year Evaluation Presentation

&

Revision for MIDS Exam

Week 7

EID MUBARAK

Week 6

Seminar Presentation

Technology Enhanced Learning

It is the improvement of learning support with the help of information and communication technologies.

TEL aims to design, develop and test socio-technical innovations than can improve learning of both individuals and organizations, especially using digital technologies

Formal Settings

Learners are involved in a learning process which is pre-defined by teachers within a specific curriculum for achieving a particular accreditation from educational institutions like University, College or School.

Informal Settings

Learners are participated in daily life activities related to work, family or leisure, and are responsible for their own learning pace and path, it dose not lead to a specific accreditation.

Other Learning Technologies

Mobile Leaning: Mobile helps in learning when learners are waiting for public transport or in airport lounges, in free time between lectures, and travelling to and from school on the bus.

Context aware Ubiquitous: A system is context-aware if it uses context to provide relevant information and/or services to the user, where relevancy depends on the user’s task.

A context aware ubiquitous learning (U-Learning) environment provides such a learning scenario that individual students are guided to learn in a real-world situation with supports or instructions from a computer system, using a mobile device to access the digital content via wireless communications; in the meantime, the learning system is able to detect and record the learning behaviors of the students in the real-world and virtual world with the help of the sensor technology 

Virtual Reality: Virtual learning Environments (VLE) are computer-based environments that are relatively open systems, enabling interactions, and encounters with other learners and providing access to a wide range of resources

VLEs can supplement face-to-face teaching methods, or totally replace these teaching methods in the case of distance learning