Teaching Computer Programming for Undergraduate Engineering Students using Outcome Based Education Paradigm Padmashree D.Desai, Gopalkrishna Joshi Department of Computer Science & Engineering B.V.Bhoomaraddi College of Engineering & Technology Hubli, India -580031
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Abstract-- A course on programming language for the students of undergraduate programme in Engineering is expected to equip the student with the knowledge of algorithmic problem solving skills and expose them to the basics of a chosen programming language. Besides, it also serves him the information about the basics of information technology and acts as a prerequisite course for some courses later in the program. It is observed that even after completing the course on programming, students fail to meet the stated objectives of the course. There are a number of reasons for these lacunae. An attempt is made to redesign the course on programming, integrating it with implementation and assessment. This includes a few strategic changes in the design and assessment in addition to teaching – learning innovations. The results of this experiment are encouraging both in terms of improved results and meeting the stated course objectives. This paper narrates the experience of the authors in curriculum design, implementation and assessment methodology. Keywords: Blooms Taxonomy, Course Learning Objectives (CLO), Outcome Based Education(OBE)
I. INTRODUCTION The first course on Programming language in undergraduate program of Engineering is perceived to be a challenge because of a number of reasons: a. Students have varied backgrounds with some having exposure to computers and some having the experience for the first time. b. The approach to teaching the course has continued to be the same since decades failing to adapt to the changed requirements of the industry in terms of maintenance of code taking a major role. Our observations in teaching the course on Computer Programming indicated that, after completing the course on programming, students failed to meet the basic expectations of the course viz.
An ability for algorithmic problem solving.
An ability to write modular programs.
An ability to document and indent program.
Reasons for the lacunae are that, gap between Course contents, Delivery and Assessment. We can list the reasons like this:
Expectations were not explicitly communicated to students
Syllabus was not focused.
Poor correlation between theory and laboratory in both curriculum design and implementation.
Assessment criteria not in line with stated objectives of the course both in theory and laboratory.
In addition, the syllabus content did not orient itself towards the changed needs of the industry like maintenance of code. In order to meet the objectives of the course, we followed the following steps: 1. Redesigning of Curriculum. Course syllabus is Redesigned ( Limiting the syllabus to modular programming skills i.e. upto functions )
Laboratory course is redesigned.
2. Curriculum Implementation. Lesson plan is written using Blooms Taxonomy.
Chapter wise objectives are written which addresses different levels of Blooms Taxonomy.
Correlated Theory and laboratory activities.
3. Redesigning of Assessment.
Assessment methodology for the theory course is redesigned.
Assessment methodology for the lab course is redesigned.
II.
CURRICULUM DESIGN AND IMPLEMENTATION
For designing the curriculum we selected an Outcome Based Education Paradigm which states that “starting with a clear picture of what is important for students to be able to do, then organizing the curriculum, instruction, and assessment to make sure that this learning ultimately happens.” (Spady, 1994) Our curriculum makes shift from Traditional approach to Content Driven approach. Our curriculum design depicts innovations done as per the following table I. TABLE I. DIFFERENCE BETWEEN TRADITIONAL APPROACH AND OUTCOME BASED APPROACH Traditional Approach
Outcome based approach
Content Driven –
Outcome Driven –
Inputs are important
Results are important
Focus is on
Focus is on
Subject Matter
Covering Curriculum
Tests Designed to assess student Mastery over Content
Content as a vehicle to attain Outcomes
Outcomes dictate Teaching / learning and assessment strategies
Figure 1. OBE Frame work
In OBE approach Curriculum reforms is a Continuous process as shown in figure 2.
In outcome based education, what matters ultimately is not what is taught, but what is learned. Therefore for the course we formulated intended learning outcomes. What we teach and how we teach, and how we assess, ought to be aligned with the intended learning outcomes[2]. The quality of teaching is judged by the quality of learning that takes place. At the course level, objectives need be defined. Then mapping outcomes to curriculum requires following things need to define:
Scope and structure of the content: through which students will develop knowledge, skill and attitudes
Instructional methods: each learning activity has a specific purpose.
Assessment methods: linked to outcomes that are learners to achieve
We followed the above approach for designing the Course content, implementation through different activities and an assessment methodology to ensure learnability. Current curriculum design focus on Problem solving skills and programming skills. Bloom’s Taxonomy is used for writing the course objectives and Topic objectives. The learning process itself has been well defined through the Bloom’s Taxonomy of educational goals [3]. It is some thing that all teachers should be aware of as well as practice. Bloom has defined six question categories, namely: knowledge, comprehension, application, analysis, synthesis and evaluation, this helped us to write the course objectives and course outcomes. OBE approach for our course design and implementation takes the model shown in figure 1.
Figure 2. OBE Frame work for curricular design.
Theory Course Learning objectives are written as follows: On Completion of the course, the student will be able to: i.
Explain the process of problem solving using computer. ii. Design an algorithmic solution for a given problem. iii. Write a maintainable C program for a given algorithm and implement the same. iv. Interpret a given C program. v. Debug a given C program.
Chapter wise learning objectives are written using blooms taxonomy. The table II shown below provides an e.g. of chapter wise learning objectives written in a Lesson plan. TABLE II.
LEARNING OBJECTIVES & L ESSON SCHDULE FOR A CHAPTER
Subject Title: Programming Fundamentals with C Chapter Title: Introduction to Computer Problem Solving and Fundamental Algorithms
Planned Hours: 07
Our observations indicated that earlier,
Students are tested only for algorithmic problem solving skills (Writing a program for given problem)
Apart from algorithmic problem solving skills, our approach also developed following abilities in the student
An ability to code reading (Student is able to read, understand and analyze the code)
Modular programming skills (Converting a monolithic code to modular program)
Lesson Schedule
IV. ASSESSMENT We designed a new assessment methodology to meet the objectives of the course. As an Examination system is proved to be a better assessment methodology, we changed the Theory examination question paper pattern and Semester end practical examination pattern. Following tables III & IV shows the difference in earlier and present methodology used in Theory assessment and Laboratory assessment.
Class No. Portion covered per hour 1.
Introduction to problem-solving Aspect
2.
Algorithm Notations, Flowcharts, Top-down Design
3.
Implementation of Algorithms
4.
Exchanging the Values of Two Variables, Counting,
5.
Summation of a Set of Numbers, Factorial Computation
6.
Sine Function Computation
7
Generation of the Digits of an Integer
Fibonacci
TABLE III. sequence,
Reversing
the
Sl No
List the symbols used to draw flowchart. (L1)
Test whether an algorithm/flowchart gives the required output for all cases of legitimate inputs. (L5)
III. ACADEMIC DELIVERY Academic Delivery plays an important role in achieving the objectives. We followed following pedagogical tools in the Class room and Laboratory.
On line teaching (Demos) in the Laboratory (e.g. Formatted Inputs and Outputs and execution of sample programs to describe the syntax of different statements)
Methodology to teach students needing special attention.
Wake up activity in the classroom.
Feedback after a chapter.
One minute paper.
Mock tests.
Online quizzes.
Present assessment
A student answer any 5 questions out of 8 questions. Does not ensure the completion of the course study.
2
Many questions were theory Focused questions relative to course oriented. objectives.
TABLE IV.
Design algorithms/flowcharts for fundamental operations viz. counting, summation, factorial computation, sine function, Fibonacci sequence and reversing the digits of an integer. (L6) (L1 to L6 shows different levels of blooms taxonomy)
Earlier assessment
1
Learning Objectives (LO): At the end of the chapter the student should be able to List the characteristics of an algorithm. (L1)
ASSESSMENT METHODOLOGY USED IN EARLIER AND PRESENT THEORY COURSE.
A student studying 85% of syllabus only can answer 5 full questions.
ASSESSMENT METHODOLOGY USED IN EARLIER AND PRESENT LABORATORY COURSE.
Sl No Earlier assessment
Present assessment
1
Student used to pick a question from fixed set.
Consists of two sections Part A and Part B. Part A tests the students memorizing capability and Part B tests their logical thinking ability, modular programming skills.
2
Algorithmic problem solving Modular programming skill and Code skill is tested. reading ability is tested.
V. RESULTS To understand the performance of our methodology, we conducted the tests among three different colleges. The colleges are selected such that one college is affiliated to University which follows syllabus prescribed by university, another one is autonomous college which has flexibility in designing the curriculum and our college which is autonomous and adopted the Outcome come Based Education paradigm for designing the course, implementation ,delivery and assessment. Mainly a Test was conducted for second year BE Computer Science & Engineering students to check their entry level programming skills. We designed a test paper to focus on
different aspects of programming. It consists of five sections and details are shown in table V below: TABLE V.
SECTION WISE DETAILS OF QUESTION PAPER.
Section 1
Variables, constants and expressions.
Section 2
Conditional statements. (if to switch)
Section 3 Section 4
Looping constructs . Basics of functions.
Section 5
Problem solving skills and modular programming.
who enter second year Computer Science Engineering which helps to improve their programming ability in Data structure course. The Bar graph showed in the figure 3 shows the great improvement in this area as compared to other colleges. VI. CONCLUSION Outcome Based Education paradigm helped us to achieve the stated objectives of the course and also to ensure learnability. Students who have entered Second year exhibited good problem solving skills as compared to previous semester students. At the end of the first year course students have an ability of algorithmic problem solving, programming skills, analyzing the given code and performing proper documentation and indentation of the written code.
Performance Comparison across three colleges is shown below in table VI. Each column gives information of average number of correct answers obtained by three different colleges. Highlighted row for section five in the table VI indicates that there is improvement in our students in the area problem solving and modular programming skills. A bar graph has been plotted shown in figure 3 to determine the performance of different colleges.
ACKNOWLEDGEMENT The authors thank Principal Dr. Ashok Shettar for motivating us in adopting Outcome Based Education model in teaching and learning process.
REFERENCES TABLE VI. Sections
SECTION-WISE PERFORMANCE COMPARISON ACROSS COLLEGES College-1
College-2
BVBCET
1
0.7
1.03
1.6
2
1.52
1.45
1.71
3
1.83
1.76
1.785
4
0.88
0.97
1.02
5
1.12
0.79
1.55
Total
6.044
6.00
7.51
Performance Comparision Chart for different sections 2
1.5 college-1 1
college-2 BVBCET
0.5
0
S1
S2
S3
S4
S5
college-1
0.7
1.52
1.83
0.88
1.12
college-2
1.03
1.45
1.76
0.97
0.79
BVBCET
1.6
1.71
1.785
1.02
1.55
Figure 3. Bar Graph of Performance Comparison.
Our curriculum was focused on improving the problem solving skills and modular programming skills of the students
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