University students often experience hidden challenges in various courses across all levels of their academic careers. These difficulties often serve to deter student learning and academic progress which may end in high student failure rates. In some instances, this may be attributed to tacit assumptions that academic teachers make about their learners when preparing lesson plans, course content and learning assessments. It is often mistakenly assumed that students already possess the necessary information literacy ways of thinking to overcome bottlenecks within their respective disciplines. To this end, the Teaching and Learning Librarian at the University of the Western Cape (UWC) Library, collaborated with an academic teacher to decode specific disciplinary difficulties and to subsequently enhance the required information literacy knowledge practices in student learning. Using a qualitative research approach, this study reports on how an Economics and Management Science (EMS) lecturer and the librarian used the Decoding the Disciplines Paradigm (DtD) to identify and deconstruct troublesome concepts in the Business and Finance module. The DtD model provides a clearly delineated, seven-step process for identifying and analysing disciplinary challenges and provides guidelines for designing instructional, motivational and assessment strategies that support deep learning. Through the DtD Paradigm, the study identified specific information literacy proficiencies that should be developed or enhanced in student learning. Moreover, the article describes how, as one of the paradigm’s steps, pedagogic methods were transformed to develop information literacy ways of thinking.

中文翻译：

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解码学生学习中的信息素养思维方式：影响教学方法

大学生经常在其学术职业的各个级别的各种课程中遇到隐藏的挑战。这些困难通常会阻止学生的学习和学术进步，最终可能导致学生失败率高。在某些情况下，这可能归因于学术教师在准备课程计划，课程内容和学习评估时对学习者的默认假设。人们常常错误地认为学生已经具备了必要的信息素养思维方式，可以克服各自学科中的瓶颈。为此，西开普大学（UWC）图书馆的教与学馆员 与一位学术老师合作，​​解决了特定的学科困难，并随后增强了学生学习中所需的信息素养知识实践。本研究使用定性研究方法，报告了经济管理科学（EMS）讲师和图书馆员如何使用“解码学科范式（DtD）”来识别和解构“商业与金融”模块中的麻烦概念。DtD模型提供了清晰界定的七步过程，用于识别和分析学科挑战，并提供设计支持深度学习的教学，动机和评估策略的指南。通过DtD范例，该研究确定了应在学生学习中发展或增强的特定信息素养水平。此外，