Course Outcomes Presentation

SHAH & ANCHOR KUTCHHI ENGINEERING COLLEGE

Course outcomes or learning outcomes are statements of what a learner is expected to know, understand and/or be able to demonstrate after completion of a process of learning.

Bloom’s taxonomy is frequently used for writing learning outcomes, since it provides a ready-made structure and list of verbs.

1.Knowledge

2. Comprehension

3. Application

4. Analysis

5. Synthesis

6. Evaluation

Bloom’s taxonomy

Verbs Arrange Define Describe Duplicate Identify Label List Match Memorize

Name Order Outline Recognize Relate Recall Repeat Reproduce Select State

VerbsClassify Convert Defend Describe Discuss Distinguish Estimate Explain Express Extend Generalized Give example(s)

Identify Indicate Infer Locate Paraphrase Predict Recognize Rewrite Review Select Summarize Translate

Verbs

Apply • Change • Choose • Compute • Demonstrate • Discover • Dramatize • Employ • Illustrate • Interpret • Manipulate

• Modify • Operate • Practice • Predict • Prepare • Produce • Relate • Schedule • Show • Sketch • Solve • Use • Write

VerbsAnalyze • Appraise • Breakdown • Calculate • Categorize • Compare • Contrast • Criticize • Diagram • Differentiate • Discriminate • Distinguish

• Examine • Experiment • Identify • Illustrate • Infer • Model • Outline • Point out • Question • Relate • Select • Separate • Subdivide • Test

Verbs •Arrange • Assemble • Categorize • Collect • Combine • Comply • Compose • Construct • Create • Design • Develop • Devise • Explain • Formulate • Generate

• Plan • Prepare • Rearrange • Reconstruct • Relate • Reorganize • Revise • Rewrite • Set up • Summarize • Synthesize • Tell • Write

Verbs•Appraise • Argue • Assess • Attach • Choose • Compare • Conclude • Contrast • Defend • Describe • Discriminate • Estimate • Evaluate

• Explain • Judge • Justify • Interpret • Relate • Predict • Rate • Select • Summarize • Support • Value

- At the end of the course, students will be able to

1. Describe different data structures. (Knowledge)

2. Identify various applications of data structures. (Comprehension)

3. Select a particular data structure and algorithm to solve a problem. (Application)

4. Develop programs to perform various operations on data structures like searching, sorting, insertion, deletion, traversing mechanism etc. (Application)

Begin each learning outcome with an action verb, followed by the object of the verb followed by a phrase that gives the context.

Use only one verb per learning outcome.

Avoid vague terms like know, understand, learn, be familiar with, be exposed to, be acquainted with, and be aware of. These terms are associated with teaching objectives rather than learning outcomes.

Avoid complicated sentences. If necessary use more one than one sentence to ensure clarity.

Ensure that the learning outcomes of the module relate to the overall outcomes of the programme.

The learning outcomes must be observable and measurable.

Ensure that the earning outcomes are capable of being assessed.

When writing learning outcomes, bear in mind the timescale within which the outcomes are to be achieved.

As you work on writing the learning outcomes, bear the mind how these outcomes will be assessed, i.e. how will you know if the student has achieved these learning outcomes? If the learning outcomes are very broad, they may be difficult to assess effectively. If the learning outcomes are very narrow, the list of learning outcomes may be too long and detailed.

Before finalising the learning outcomes, ask your colleagues and possibly former students if the learning outcomes make sense to them.

When writing learning outcomes, for students at levels beyond first year, try to avoid overloading the list with learning outcomes which are drawn from the bottom of Bloom’s taxonomy ( e.g. Knowledge and Comprehension) .Try to challenge the students to use what they have learned by including some learning outcomes drawn from the higher categories (e.g. Application, Analysis, Synthesis and Evaluation)

1)Direct method Tests, lab experiments, assignments,

project work, tutorials. 2)Indirect method Course exit survey at the end of the course.

Course Outcomes

Experiments Assignments Tests

CO1 1, 2 1, 2

CO2 1 2 1

CO3 1, 7 1 2

CO4 2, 3, 4, 5, 6,8,9, 10,11, 12

2 1, 2

1. Implementations of Infix to Postfix Transformation and its evaluation program. 2. Implementations of double ended queue menu driven program 3. Implementations of circular queue menu driven program 4. Implementation of different operations on linked list – copy, concatenate, split,

reverse, count no. of nodes.

5. Implementations of Linked Lists menu driven program (stack and queue) 6. Implementations of Binary Tree menu driven program 7. Implementation of construction of expression tree using postfix expression. 8. Implementations of BST program 9. Implementations of Shell sort, Radix sort and Insertion sort menu driven program 10. Implementations of Quick Sort, Merge sort and Heap Sort menu driven program11. Implementations of searching methods (Index Sequential, Interpolation Search)

menu driven program. 12. Implementations of Graph menu driven program (DFS & BSF)

1. What is Data Structure? Explain different types of Data Structures with suitable examples and Applications.

2. What is Recursion? Compare Iteration and Recursion. Write a program to implement Tower of Hanoi.

3. Implementation of polynomials operations ( addition, subtraction) using Linked List.

4. Implementation of multistack in one array.

5. Write detailed note on Johnsons algorithm with example.

Semester VII Information Technology

2014-2015

◦ At the end of the course, students will be able to1.Identify different building blocks of AI. (Knowledge)2.Apply the fundamentals of heuristic search, game

search, decision theory, planning and NLP. (Application)

3.Experiment various AI algorithms. (Application)4.Recognize and solve problems using AI. (Synthesis)

PI1 PI2 PI3CO1 Assignment 1 Test1CO2 Assignment 1, 2 Test1, 2CO3 Experiment No

4 to 10CO4 Assignment 2 Experiment No

1,2,3Test2

 1. What is AI? Explain PEAS descriptor with example.2. Measure 1 litre water if available jug sizes are 7 litres and 5 litres.3. Solve 8 Puzzle problem using Best First Search.4. What is Alpha and Beta pruning? Give one example.5. Evaluate the following problems using Constraint Satisfaction Problem a) S E N D E A T + M O R E + T H AT M O N E Y A P P L E   b) N O c ) ( B E ) ( B E ) = M O B G U N* N O H U N T

1. Explain formal requirements for agent communication. Show the structure of grammar used for it.

2. Write a short note on Uncertainty.3. Write a short note on Role of NLP in AI.4. Explain with a suitable example the inferencing process in Baye’s Belief

network.5. Draw and explain Single layer Feed Forward network? Explain

reinforcement learning.6. How can you define learning? Explain Inductive learning and learning with

Decision trees.7. Draw and explain block diagram of General Learning model and explain

various factors affecting learning performance in details.

http://sss.dcu.ie/afi/docs/bologna/writing_and_using_learning_outcomes.pdf

http://teaching.uncc.edu/learning-resources/articles-books/best-practice/goals-objectives/writing-objectives