Web Participative Knowledge Based Crediting System

Ma. Lorelyn  D. Santos,

Web Participative Knowledge Based Crediting System

Abstract:

Motivated by the desire for instantaneous, accurate and relevant academic records of transferee students, the researcher explored solutions using three concepts: user web participation; knowledge-based resource; and, evaluation and crediting of expert system. All were made possible through the combination of the instructions of PHP: Hypertext Processor, Apache HTTP server, and Microsoft SQL Server 2008 R2. The credit engine as the prime mover of the system note rules and frames on crediting as its major standpoint: curriculum year, subject, unit requirement, and passing grade. Subject content is visited in cases where related but not perfectly matched subject is encountered. Discrimination is applied using words identification in three algorithms--tokenize module, SQL Like operator, and Levenshtein distance. Analysis for merging and storage uses three knowledge resources each with corresponding function: KR1 for cached invalid words; KR2 for permanent invalid words; and, KR3 for permanent valid words. The evaluators noted the utilization value of the system during the try-out with suggestions to improve on the integration of the human computer interaction (HCI); hence, a more friendly interaction is recommended.