2 research outputs found
A Machine Learning Prediction of Automatic Text Based Assessment for Open and Distance Learning: A Review
In this systematic literature review, automatic text-based and easy type assessment
grading system using Machine Learning and Natural Language Processing (NLP)
techniques was investigated. The major focus is on text-based and essay type
assessment in ODL courses. Text-based and essay type questions is an important tool
for performing quality examination and assessment to help the students gain mastery
over the task and widen their horizon of knowledge and increase the learner’s
development and learning than, for instance subjective question type, single choice
question (SCQ), multiple choice question (MCQ) and true/false question type.
Automatic text-based and essay type assessment grading system can be used as an
important tool in ODL institutions, where assessment and examination can be quickly
and easily evaluated for the purpose of efficient feedback. We carried out this study
using quality, exclusion and inclusion criteria by selecting only studies that focuses on
NLP and Machine Learning techniques for automatic text-based and essay type
assessment grading task. Searches in ACM Digital Library, Semantic Scholar, Scopus,
IEEE Xplore, Google Scholar, Microsoft Academic, Learn Tech Library and Springer is
performed in order to retrieve important and relevant literature in this research
domain. Conference papers, journals and articles between the year 2011 and 2019 were
considered in this study. This study found 34 published articles describing automatic
text-based and essay type assessment and examination grading task out of a total of
1260 articles that met our search criteria