| 英文摘要 |
“What Do We Know about Migrant Workers in 2030?” is an interdisciplinary competence-driven course in which several Chinese, EFL, and math teachers collaborated to design, even though such subject areas as Chinese, EFL, and math exhibit different disciplinary qualities. After constant collaboration and brainstorming, these teachers developed an 18-week elective course founded on the phenomenon and the issue of migrant workers. Furthermore, they intended to utilize this interdisciplinary course to cultivate their students’ core competence, which correspond to these listed in the 2019 12-year Curriculum for Basic Education. In this interdisciplinary course design, these teachers guided the students to engage in multiple learning tasks: the students employed Focused Discussion to make an inquiry into the phenomenon of migrant workers; they differentiated facts from opinions by virtue of systems thinking; they were equipped with the competence to tell definitions from evidence so that they could be a better researcher conducting a study on a certain issue; they were assigned the job to read Chinese and English texts so as to analyze cross-cultural migrant worker issues and compare different migrant workers’ mentalities; they learned how to take advantage of data and charts to predict future migrant worker trends at home and abroad. This interdisciplinary course aims to create a ripple effect. In terms of teachers from different disciplines, they can come to realize that mutual trust and communication play a dominant role in an interdisciplinary course design. Concerning students’ learning objectives, they are supposed to base their course on their students’ key competence instead of combining respective disciplinary practices for no reason. With regard to the significance of subject areas, no discipline outweighs one another, as they are expected to be mutually complimentary. In brief, a well-rounded interdisciplinary competence-based course should be more learnercentered, future-oriented, and cross-departmental. |