Development Of Elearning Software System

Published Date: 02 Nov 2017

To analyze the applicability of such systems in full time education, the project of "Virtual Classroom" was uploaded on Intranet for use by B. Tech third year students of the sixth semester. This project aims at implementing above mentioned activities (except few ones like Video Conferencing etc) in Hyper Text Pre-processor (PHP), Hyper Text Markup language (HTML), Javascript and MySQL technologies. These students were taught "Software Engineering (SE)" without any virtual classroom tool in previous fifth semester. At the end of the sixth semester, total 35 students studying "Multimedia Technologies (MT)" were given questionnaire using GoogleDocs. The scale of 1 to 5 is used where 5 means higher value and 1 means lower value to question asked. Following were questions asked in the questionnaire:

Out of "SE" and "MT", which subject do you find interesting?

Out of the two subjects, which one you consider best for your future research?

Out of the two subjects, which one really transformed the hidden ideas of mind into practice?

Out of the two subjects, which one was the highest scoring for you?

When compared the teaching strategy for the two subjects, how much you rate these components:

Easiness.

Problem solution oriented.

Collaborative.

Work Originality due to plagiarism.

Practice oriented.

Transparency.

Students allotted values for each question asked for two courses are given by following figures.

Figure 6.9. Number of students interested in "MT" course.

Figure 6.10. Number of student’s interest as research area.

Figure 6.11. Number of students who transformed ideas into practice.

Figure 6.12. Number of students who find the subject as highest scoring.

Figure 6.13. Ratings of individual components of effective teaching strategy

In figure 6.13, the ratings of each student for each strategy for two courses are added and presented in the form of graphical representation. In Figure 6.9 to 6.12, only the number of students who rated using values of 5, 4, 3, 2 and 1 are presented graphically. Thus it shows the number of students categorized in accordance with the value supplied while figure 6.13 presents aggregated allotted values.

Result Analysis

Figure 6.9 shows that students found the course of MT very interesting. When asked the reason behind such results, the majority of students reported that due to virtual classroom they got enough time in classrooms focusing on what is being taught without any stress of documentation of classroom notes since they are available of the intranet. Thus the whole effort is just to listen, comprehend, understand and documenting important points. Deadline for assignment submission, plagiarism detection, and support for collaboration among students and teachers due to chat and posting about problems and solutions made everyone come forward and perform required activities within deadline. Since software does not accept any assignments after deadline and due to plagiarism detection capability students were forced to write after a full understanding of the application based assignments questions, this allowed them to solve their doubts within reasonable time rather than during exam times. This all enhanced their interest, due to which they started implementing the knowledge into practical by implementation of projects. Maximum students found interesting problems in which they started taking interest as their future research work. The subject of MT becomes very high scoring subject for them which they passed with very good percentage. Students found that it is very easy to share problems, find solutions by working collaboratively, carry out original work that earlier happens to be copy-paste work. Students also reported that use of such tools provides transparency in grades allotment, and is overall learning of new subject becomes an easy activity.

In case of the Software Engineering course, since some of the students had applied software engineering knowledge in implementation of projects, thus some of these students were also interested in this course. Thus some values were assigned to this course also in above given figures. But allotted values are far lesser than allotted to "MT" course.

Teaching should be dynamic means teaching contents must be current research trends. Students should be able to understand the recent research trends which are only possible if they had complete basic knowledge and interest in the subject. Use of e-learning tools like virtual classroom made it possible to encourage students to learn while doing the things. Such web 2.0 tools provide 24x7 access worldwide and hence irrespective of location of tutor or learner, collaboration could be promoted to solve problems emerged.

From the presented data, it could be easily concluded that effective teaching and hence a revolution in the area of education sector could be attributable not only to the quality of teachers, quality of notes etc but also to quality of software employed for the purpose of e-learning. Quality of e-learning software is the main factor in determining the effectiveness of teaching strategy since quality software will bring revolution in the education sector. This will enhance the quality of learning and knowledge among students and teachers thereby influencing learners and educators of the next generation.

Proposed Prioritization Model: Development of E-learning software system

As discussed in previous sections that for making teaching very effective, e-learning software system should be employed that could either be uploaded on the Internet or on the Intranet. Such e-learning systems are mostly web 2.0 applications that are read/write and execute web applications. The poor quality of such applications would mean complete rejection in the education sector. Thus to deliver software implementing highest priority requirements to reduce changes off delays and satisfying each and every stakeholder, effective requirement prioritization technique must be employed.

In order to support incremental delivery, paper proposes a new requirement prioritization method that selects those requirements for implementation that are required at most by stakeholders and has a lower regression count associated with them thereby reducing regression testing effort. The priority of a requirement is determined by "Customer Satisfaction" and Regression Count Value such that the cost of implementation of the selected requirement set is approximately within the allotted budgets. Figure 6.14 gives the proposed technique for requirement prioritization.

Identification of Stakeholders

Calculation of relative importance of stakeholders for "customer satisfaction" aspect using AHP.

Allot values for each requirement against "customer satisfaction" aspect.

Compute prioritization value.

Compute Implementation costs and Regression count for each requirement.

Negotiation?

Compute Final Priority (FP) and select requirements with High FP value.

Figure 6.14. Proposed requirement prioritization Model.

The working of this proposed prioritization technique is given in form of algorithm in Table 6.11.

Table 6.11. Algorithm: Requirement Prioritization of E-Learning software system.

Input: Set of gathered requirements.

Output: Prioritized set of requirements.

Identify influential stakeholders for prioritizing requirements. As a customers or users, a good combination of experienced teachers, research scholars, students, project staff etc should be identified. Teachers could better identify those requirements that are very important for them and without which their work will suffer.

Compute the relative importance of each stakeholder against "customer satisfaction" aspect using Analytical Hierarchical Process (AHP). AHP is a decision making process that allows stakeholders to fill prioritization matrix using a scale of 1-9. The relative prioritization value is then computed and the results are analyzed for accuracy purpose by calculating a consistency index (CI). A result of execution of this step is the computation of the importance of one stakeholder with respect to another. Execution of this step is necessary since experienced teachers should be given higher importance as compared to other stakeholders and voice of students or other project staff with huge development experiences could not be bypassed.

For each requirement against customer satisfaction aspect

Each stakeholder allots value using a scale of 1-9 as proposed in (Satty, 1980).

Compute the priority using equation 6.9:

Priority = (Wa*Va)+(Wb*Vb)+............+ (Wb*Vb) (6.9)

Wi denotes the relative importance of stakeholder "i" and Vi is the value assigned by stakeholder "i". Computation of this step is similar to that in (Gupta and Srivastav, 2011a).

Compute Implementation costs and Regression count for each requirement. This step requires the involvement of software engineers rather than involving customers and users. The implementation of each requirement would be dependent on the implementation of another requirement. Such dependency implies that changes in particular requirement would create ripple effects in other parts of source code i.e. in the source code of dependent requirement. This thesis terms number of such dependencies between code parts of one requirement and parts of another one as regression count. To compute regression count, developers use AHP technique, where each requirement is Pairwise compared with another. If there is very strong dependency between the two requirements say Ri and Rj, prioritization matrix cell (i, j) is given a value of 9 (scale of 1-9) and for no dependency, it is given a value of 1. Finally the relative regression count value is computed. A similar scale is used to represent the implementation cost of each requirement.

Select the highest priority requirement. Such requirements are those that have the highest value of Customers Satisfaction. Denote this set by R’. It varies from organization to organization to have threshold value of the selection. An optimal value could be at least 65%. Requirements with highest regression count and lower development costs are highly desirable. Let R be the set of gathered requirements. Let R’’ = R – R’. Each requirement of R" is represented by three tuples i.e. (P, C, R) where P represents assigned priority, C is development cost and R is regression count.

Compute cost associated with the set R’. If it exceeds the allotted budget, perform negotiation by holding talks with stakeholders and a re allotment of values and thus repeating step 3 and onwards.

Sort the requirements in decreasing order of their priorities. Find the set R’’’ where, R’’’ = R’’ – R(i). The set R(i) denotes the set of those requirements of set R’’ which are having the highest value of R and lowest value of P.

For remaining requirements belonging to set R’’’, compute the final value of priority using equation 6.10:

FP = (P * R) / C (6.10)

In this equation, value is "C" is not in monetary terms but in terms of scale of 1-9. Thus the highest cost value 9 represents a high cost requirement.

Implement the set R’ and select requirements of set R’’’ with the highest value of FP until resources permits.

This algorithm generates the implementation set of requirements. Selected requirements are such that they provide maximum customer satisfaction to its indeed users (one of the important criteria for educational sector software success) and lowest cost and highest regression count value. Requirements that provide less value to its customers and have the highest value of regression count are simple ignored since these requirements could never alter project success chances. The proposed prioritization technique could be named as "CCR" technique where First C stands for Customer satisfaction, second C stands for cost and R stand for Regression count.

Conclusion and Future Work

This chapter proposed requirement prioritization techniques that involve decision makings in such a manner that the impact of requirement (currently under consideration) on regression testing is considered as one of the main parameters. The proposals deal with three different set classes of the software i.e. Mobile applications, Web applications and Desktop Applications. These proposals are equally valid for desktop applications.

The first technique of the requirement prioritization process of web 2.0 applications is a hybrid approach i.e. based on combination of negotiations and methods to prioritize both decision aspects and software requirements. This technique reduces regression testing effort by taking an impact on regression testing as one of the parameters during prioritization and overcomes various problems related to prioritization of web 2.0 applications. This technique is applied on live web application of "Virtual Classroom". Some of the project success critical aspects like risks and development complexity were identified for this project that was not used in the previous project of Tour "N" travel. Identification of these aspects might not have been possible if prioritization technique uses predefined aspects. Negotiations during prioritization made it possible to delay requirements related to web cam face to face chat and voice chat. These requirements were given high priority by customer groups but categorized by high implementation complexity and not possible to be implemented in short delivery time. Negotiations also made each group aware of the views of other groups. Implementation of security requirement ay highest hierarchical level leads to the delivery of a secured web application under resource constrained environment. This technique is suitable for application with thousands of requirements and suitable for geographically distributed environments. The main advantages of this technique are that it allows stakeholders to be distributed across cultural or organizational boundaries, overcomes problems related to involvement of diverse stakeholders, do not suffer from scalability problem, applicable for both web 2.0 and desktop applications, provides a method for decision aspect selection and is automated to maximum extend.

As a future work, it is expected that this technique be applied in software development industries on complex software’s and some manual activities like categorization of decision aspects, populating of buckets being done automatically. Case based reasoning can be employed to identify and categorize aspects, populating of buckets etc.

The second requirement prioritization method aims to prioritize requirements of mobile applications in such a manner that it lowers regression testing effort and simultaneously satisfied diverse stakeholders. The proposed technique is basically a framework where various proven techniques for decision aspect prioritization, requirement prioritization and regression test suite minimization are used along with new methods of requirement prioritization based on analysis of effects on regression testing. The aim is to implement almost all dependent highest priority requirements in current release so that implementation of new requirements is unlikely to have ripple effects. Changes in requirements might not be related to variable usage and definition and might not involve a change in functionality. In such cases there is no need to select already executed test cases of previous versions. Module dependencies can lead to test case selections of previous versions if changes of requirement lead to ripple effects. This paper aims to implement highest priority requirements such that regression testing is performed to minimum thereby improving development process of mobile applications. Effects on regression testing are analyzed by computation of the dependency value by the use of trust worthy multi objective decision making method called AHP. The proposed technique had been successfully evaluated on Android based notification software application that meets the specification of Aakash tablets. In order to analyze its effectiveness on desktop applications, it had been applied on the "Software for ABC Organization" developed in Computer Programming Laboratory of NIT Hamirpur. The Results proved that there is a better reduction of test cases and hence regression testing effort since it leads to neglection of those parts of code that are not actually affected by the changes but seems to be affected. In future we hope that proposed technique will be extended to overcome the scalability problem that lies with AHP. It is also expected that in the near future the identification of regression test cases as a result of software evolution be automated and it could be expected that it will be tested on various web applications including social networking sites.

The objectives of the third paper, were twofold i.e. first, accessing the applicability of E-learning software system in the education sector and second to propose a method to incrementally develop high quality E-learning system such that it could be an asset to education organization. Such a system will be delivered without any delay with almost all preferences of diverse stakeholders implemented in a resource constrained environment.

To achieve the first objective, paper "Virtual Classroom" E-learning software was employed for teaching a course of "Multimedia Technologies" to B. Tech students of the sixth semester. As compared to courses taught in the fifth semester, students found that they were very comfortable with the course taught using e-learning software system. Such E-learning system provides the necessary virtual classroom environment that strengthens classroom face to face in person teaching. Results indicate that students found the use of such e-learning software system as a good database of lecture notes documentation, forces them to collaboratively focus on problems identified by classmates, report unique and original contents, work or findings in assignments. Students also reported that use of such tools provides transparency in grades allotment, and is overall learning of new subject becomes an easy activity. This all enlightened them with the necessary knowledge of the subject which they transformed into practical and thus lightened the way for their future research.

Total 50 students enrolled under both distance education and full time education (25 in each category) were asked some questions and results indicate that E-learning system would bring revolution in the field of education whether study programme is full time, part time or distance education programme.

Educational institutes demands complex E-learning software system timely delivery of which happens to be a very difficult task. To have timely delivery, paper proposed requirement prioritization technique that prioritizes software requirements that provide maximum satisfaction to its customers and lessen regression testing effort. To achieve more optimizations in regression testing effort, as a heuristic, requirements with highest regression count and lesser customer satisfaction value could be ignored.

Quality of developed E-learning system would influence the quality of teaching in educational sectors and thereby enlighten the glow of knowledge among both educators and learners. The country will be benefitted since economic development depends heavily on education and quality of researchers involved in research projects in the country. E-learning systems overcome the global distances that exist between experts and learners and thereby making the whole world as an education hub.

Thus it is expected that good quality of E-learning software systems would be developed using the proposed prioritization technique. It is also expected that Mobile compatible E-learning systems would be launched soon so that "any time and any place" access could be provided (M-Learning). Advancement in the area of Software engineering, Mobile Communications and Web Technologies would improve quality of E-learning and hence teaching quality.

In near future it is expected that the regression testing techniques based requirement prioritization techniques will be evaluated on different softwares of varying complexities and domains. The applicability of the proposal is yet to be verified on different complexities softwares. Complexity of the software might possess a threat to the validity of the proposals.