1. COURSE FILE SEMINAR NCAAA & ABET SSR PREPARATION (2014-15) QAU, College of CS & IS

2. Compliment for CCs “Due to huge technical and laborious efforts of CCs COURSE FILES has served the faculty in teaching & learning & NCAAA distinctive position in the whole University”

3. Why Course Coordinators Should Perform this job?  Internal Satisfaction  No Change in Salary but a distinctive Position  Prove that You deserve the post  Learning every day

4. Agenda  Course Assessment (CC Presentation)  Findings (Year 2013-14) (Year 2013-14)  Preparation (Year 2014-15) (Year 2014-15)  Course File Assessment  Analysis (CFR Proforma) (CFR Proforma)  Follow-Up (One to One Meeting)  Course File Update  Course Specs & Reports (NCAAA-New Templates)  ABET Course Binder

5. NCAAA National Quality Framework (NQF)  Provides FIVE learning domains  Recommends that Normally CLOs should not exceed more than EIGHT  CLOs should be aligned with PLOs  One course may or may not have CLOs from all five learning domains  One course may Satisfy more than one PLO

6. Guidelines to write CLOs  CLOs should be derived from Course Objectives  CLOs are intended not actual  Should not be complex and ambiguous  Should be measureable and specific

7. Difference between Subject & Course  Subject (like Database,……………….)  a particular area of study that is offered in a study program.  Course (DB-1, DB-2, OODB, DW&DM, DB-Admin,….)  study of particular topics within a subject. (subset) (bounded with in a fix time and offered at certain level of degree program)  Depth / Breadth topics distribution in courses depends on curriculum design  A course may cover all cognitive domains of Bloom’s Taxonomy (Normally series of courses from same subject are offered from junior to senior levels and cover topics on the basis of Low-to-High difficulty hence cover Blooms Domain gradually.)

8. Algorithms & Data Structures -1 (COMP-221) CLOs derived from Course Objectives On Completion of This Course students will be able to: 1.Describe the properties of various data structures 2.List the strengths and weaknesses of different data structures 3.Describe the role of algorithms as basic operations of data structures 4.Develop linear data structures using C++ according to ADT Rules. 5.Predict and use appropriate data structures for given problems 6.Demonstrate the appropriateness of Algorithm Design Architecture (Recursive/Iterative) for certain computing problems. 7.Calculate the efficiency of algorithms (computational complexity) on asymptotic ranges [O, ϴ, Ω](T(n)) for boundary value analysis.

9. CLOs of Algorithms & Data Structures -1 (COMP-221) & Framing of CLOs into NCAAA-NQF NCAAA-NQF Learning Domains And Course Learning Outcomes Course Teaching Strategies Course Assessment Methods 1.0Knowledge 1.1Describe the properties of various data structures Visual & Verbal [Lectures / Presentations] with deductive organization. Written Exams (Quiz/Mid/Final) 1.2List the strengths and weaknesses of different data structures Visual & Verbal [Lectures / Presentations] with inductive organization. Written Exams (Quiz/Mid/Final) 1.3 Describe the role of algorithms as basic operations of data structures Visual & Verbal [Lectures / Presentations] with deductive organization. Assignments Written Exams (Quiz/Mid/Final) 2.0Cognitive Skills 2.1Develop linear data structures using C++ according to ADT Rules. Visual & Verbal Class Participation in the Labs with deductive organization. Assignments Lab Exams 2.2Predict and use appropriate data structures for given problems Visual & Verbal [Lectures / Presentations] with inductive organization Assignments Written Exams (Quiz/Mid/Final) Mini Projects 3.0Interpersonal Skills & Responsibility 3.1 Demonstrate the appropriateness of Algorithm Design Architecture (Recursive/Iterative) for certain computing problems. Active Class participation as Group Activity with inductive organization Presentations by Student Groups 4.0Communication, Information Technology, Numerical 4.1 Calculate the efficiency of algorithms (computational complexity) on asymptotic ranges [O, ϴ, Ω](T(n)) for boundary value analysis. Visual & Verbal Class Lecturing to invoke student’s previously learned mathematical abilities. Assignment Written Exams (Quiz/Mid/Final) 5.0Psychomotor 5.1

10. Teaching Strategies

11. TLCourses Course Coordinator Status Department of Computer Sciences GOOD AVERAGE GOOD AVERAGE GOOD AVERAGE GOOD AVERAGE GOOD NEED IMPROVMENTS GOOD AVERAGE GOOD Course Code Course Name Level Course Coordinator Department Prerequi site Offered as Track Leader Track Name Last Course File Updated Text Book / Lecture Notes / Slides (from text book) / Slides from Internet Learning Material is % Course Contents & Provided Learning Material Meet the Course Objectives Yes / No Satisfaction of course team with the text book (If not then a new is proposed or not) % Differences in the results of all groups within the course Yes / No SWOT Analysis or Deficiency Analysis performed by Course Team Ever Yes / No Improvements mentioned by Course Coordinator are valuable and doable Excellent / Good / Average / Need Improvements / Not required in next curriculum Overall Assessment Back Course Status (CC Presentation Fall 13-14)

12. Course Title Course Code Course Coordinator LevelVersion # Status of Course File According to Check List / Last Update Complete / IncompleteDate: Course Description & Course Specification: Course Description is latest (Edition -II) Yes / No (If not emergency action is required) Text Book and Grading Scheme in Course Des. & Course Specs Same / Mismatch All students assessments are available according to grading policy Course Report: (Section B & C) Course delivery depicts real picture or just copy-paste from course specs. Real / Copy-Paste Total Groups Students Entered in All Groups PassFailDropped Course Reading Material & Lab Material Reading Material is: 1.Text Book 2.Slides / Lecture Notes by Text Book Author 3.Slides / Lecture Notes from Text Book prepared by CC. 4.Mixed (Not Acceptable) Lab Material is Excellent / Good / Good but Insufficient / Poor Lab Material is Aligned with Theory Material 100-80 % / 80-60% / 60-50 % / Below (Not Acceptable) Course Coordination Meeting Meetings depicts Original Discussions / Non Issues / Not available Course File Presentation Look & Feel Excellent / Good / Average / Poor Course Files Assessment Summative Assessment Activity of Teaching Material (2014-15) NCAAA: Std. 4, 6 – ABET: Cri. 4, 5

13. Course Name Percentage(%) Course File Status Course Description Status Text Book & Grading Scheme Student Assessments Course Delivery Report Marks Sheets Study Material (Theory) Lab Material Meetings Look & Feel Points 10555 5302055 68002355301544 831055454301244 67055554201634 78055555301544 821005545301643 841055535301533 52000200301433 77055455301544 911055565301645 811002465301545 911055575301644 861055555301434 901055565301743 71055355301044 881055555301544 811002465301644 Course Files Assessment Summary for One Department Back