Abstract:
Scientific Research proposal writing skill is an important part for novice researchers, including
postgraduate students. However, writing a clear, concise, readable, and understandable proposal
has been identified as a great challenge for novice Researcher to convince proposal evaluator. This
means then that novice researcher starts proposal work without adequately prepared and gets the
necessary skill to review literature, define statement of the problem and formulate research
methodology, among others. This is because some of the common mistakes and difficulties novice
researchers faced and encounters need deep understanding, expertise and support. This finally
leads some students’ proposal have taken long to be approved because they have been found to be
problematic and also, despite the standard completion time for Master students, majority of
students goes beyond the stipulated standard minimum completion time. Even worse, seriously
compromising the standards expected of a Postgraduate Student thesis.
This study therefore investigates common mistakes and difficulties that novice researcher’s faced
and the associated solution to assist them in writing acceptable proposal. To this end, the study
develops a knowledge based system to assist novice researchers to enhance their proposal writing
skill by mitigating the common mistakes and difficulties they commit or encountered. In this study,
Design Science Research Methodology (DSRM) has been followed to assess and find solution for
the problem. To design and develop the artifact, a Knowledge engineering process has been used
for knowledge acquisition, modeling, representation and prototyping the knowledge based system.
The performance of the proposed system was evaluated with 50 test cases. The results of the
validation test indicate that the prototype registers on the average 85.0% accuracy. In addition, the
prototype registers 84.6% user’s acceptance with all the novice researchers proved the usefulness
of the prototype. The prototype achieves a promising result and meets the objective of the study.
However, in this study an attempt is made to apply rule based systems. Rule based systems solve
problems from scratch, while case based systems use pre-stored situations to deal with similar new
instances. Therefore, the integration of rule based and case based reasoning with intelligent User
interface is left for further research.
