Innovative massive open online course for young researchers: impact of implementation in Kazakhstani universities

Abstract

This study determined the effectiveness of a developed MOOC ‘Statistical Analysis and Information Processing for Research’ in enhancing Kazakhstan’s young researchers’ research skills. This study employed pedagogical experience generalization, pedagogical observation, discussion, questioning, and mathematical statistics to process experimental results. Criteria were selected to assess MOOCs’ impact on participants’ skills. Pearson’s goodness-of-fit criterion was utilized as the experimental results were categorized into high, sufficient, and low levels. Following the MOOC’s implementation, the experimental testing results showed a significant improvement compared to the control group. This comparison was valid for a random selection of students with a probability of 0.99, with a correlation coefficient of 0.9. Our study encompassed 340 participants. The MOOC’s implementation led to a 12.1% increase in the number of experimental group students receiving high assessments for their scientific work, a 14.1% increase in the number of experimental group students obtaining average scores, and a 26.2% increase in the number of control group students who did not partake in the MOOC and obtained low grades. An experimental evaluation of the effectiveness of implementing the MOOC in three languages confirmed the hypothesis that MOOC-based learning technology is more effective than traditional methods in enhancing Kazakhstan’s young researchers’ research skills.

Keywords

• Massive open online course
• higher education
• online learning
• research skill
• statistical analysis
• Stephen Darwin, Universidad Alberto Hurtado, Chile