Teacherbot Model based-on Automatic Question Generation for Cyber Education

This study is focused on addressing the tasks of developing learning objects and media delivery using digital education technology. 

The proliferated digital transformation in education domain has caused some disrupted changes in higher education system. This study is focused on addressing the tasks of developing learning objects and media delivery using digital education technology. The purposes of this research are two folds. First, developing a question generation-based TeacherBot for constructing questions that require in-depth answers to leverage teacher and student engagement productivity in a pedagogical context when they seek to explore broader and deeper knowledge. Second, evaluating acceptance of the generated questions produced by the Teacherbot moodel using BLEU and Cohen’s Kappa score measurements. In addition, measuring the impact of the generated questions adption on learning using the Kirkpatrick evaluatin framework which includes: Student Reaction Evaluation, Learning Transfer Evaluation, Student Behavior Change, Performance Impact Evaluation. Some experimentation results showed some evidences that the question generation-based TeacherBot which was implemented using Text-to-Text Transfer Transformer (T5) approach achieved good results. Using 100 questions as samples, the measurement results achieved BLEU score = 0.92 and a Cohen’s Kappa coefficient = 0.60 which means that the questions generated by Question Generation can be understood by readers or users. Meanwhile, the results of the evaluation using the Kirkpatrick framework showed a score of 4.111, which means that Teacherbot built based on the

Question Generation model can be recommended for learning in various fields of science and knowledge.

Keywords—Artificial Intelligence; Question Generator; Teacherbot; Transformer; T5.

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Teacherbot Model based-on Automatic Question Generation for Cyber Education

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