<![CDATA[This study examines how Indonesia’s Minister of Primary and Secondary Education (Mendikdasmen), Abdul Mu’ti, employs persuasive pragmatic strategies when conveying education policies related to addressing learning loss after the Covid-19 pandemic. Through discourse analysis of his statements in press conferences and seminars on the implementation of deep learning, this research traces the forms of speech acts such as directives, representatives, and implicatures used to build support and influence how the public understands the policy. The findings show that Abdul Mu’ti underscores the seriousness of the learning-loss problem by referring to concrete data, including the decline in students’ cognitive abilities and the results of the 2022 Programme for International Student Assessment (PISA). Presenting these data serves to strengthen his arguments and enhance their persuasive force. In addition, his critique of surface-level learning practices generates an implicature that a shift in instructional approaches is an urgent necessity. His emphasis on the central role of teachers and assurances that the existing curriculum will not be replaced also function as strategies to reduce potential public resistance. This study demonstrates that Abdul Mu’ti’s use of language in policy communication plays a crucial role in framing deep learning as a solution for restoring the quality of national education.]]>
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