Work

Exploring the determinants of the global massive open online courses for diminishing diversified gender discrimination

Year: 2025

Type: article

Abstract: This research investigates the effectiveness of Massive Open Online Courses (MOOCs) in addressing diversified gender discrimination in the post-sexism era. A mixed-methods approach is employed to explore gender education within global MOOCs, drawing from theoretical perspectives such as feminist pedagogy, intersectionality theory, social constructivism, and post-structuralist gender theory. Hence, the quantitative data, including MOOC enrollment, completion rates, participant demographics, and survey responses, will be analyzed using descriptive and inferential statistics. Qualitative data will be collected through content analysis, interviews, and focus groups, and analyzed using thematic analysis, critical discourse analysis, and comparative analysis. Ethical considerations, such as informed consent and cultural sensitivity, will be prioritized. Finally, the potential limitations include language barriers, self-selection bias, and researcher bias. By combining quantitative and qualitative methods, this research aims to provide a nuanced understanding of the effectiveness, challenges, and opportunities of using MOOCs for gender education, contributing to the ongoing efforts to address gender discrimination.

Source: Educational Innovations and Emerging Technologies

DOI: 10.35745/eiet2025v05.01.0002

Authors: Ai-Chieh Chang, Chien-Hui Lee, Jiin-Chyuan Mark Lai, Chun-Ming Shih, Ming-Yuan Hsieh

Institutions: Shu-Te University, Southern Taiwan University of Science and Technology, TransWorld University, National Taichung University of Education

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDGs: Gender equality, Quality education, Reduced inequalities

Open Access status: diamond

Funder: National Science and Technology Council