Open AccessSimplified Reliable Online Essay Test Marking for Massive Open Online Course (MOOC) using Rasch Model Analysis
Author(s) -
Mohd Noor Mamat,
Zawawi Temyati,
Siti Fatahiyah Mahamood,
Hanifah Musa
Publication year - 2018
Publication title -
social and management research journal/social and management research journal
Language(s) - English
Resource type - Journals
eISSN - 0128-1089
pISSN - 1675-7017
DOI - 10.24191/smrj.v15i2.4968
Subject(s) - rasch model , raw score , test (biology) , reliability (semiconductor) , massive open online course , mathematics education , computer science , test score , multiple choice , item response theory , logit , scale (ratio) , measure (data warehouse) , psychology , raw data , statistics , machine learning , psychometrics , data mining , significant difference , standardized test , mathematics , paleontology , power (physics) , physics , quantum mechanics , biology , programming language
Manual practice in formal examination does not assess accurate measureof a student’s ability, as it merely counts the score of every question to beconsidered for the student’s grade. There are many educators who haveused raw score as a form of measurement for a student’s ability, but it nevertruly measures the right measurement. The raw score should be convertedinto the right linear metrics for ability measurement. This procedurecontains measuring score of accurate student’s ability in LOGIT unit,providing of student’s result profile, and measuring reliability of the testset and the student’s answers. The procedure is designed for massive openonline learning and paperless essay-based test which is more difficult tobe analysed. This procedure converts the student’s answer into rubricalratio-based scale to be more accurately measured. It is definitely better thanthe common practice of merely analysis on raw marks for each question.It would show true student’s performance of cognitive performance (test)which represents the true student’s ability (in LOGIT unit), in order toaccurately measure the right outcome. This new paradigm of assessmentis fit to be applied for massive numbers on online students. It uses Raschmodel which offers reliable solution in producing accurate ability marksfor students, together with scientific reliability score for student’s answer.