Course Descriptions

To enhance students’ information literacy, the library offers a variety of courses and lectures tailored for undergraduate and graduate students. Courses are available at both campuses.

Class Locations: Room B201, 2^nd Floor, Putuo Campus Library; Room B107, 1^st Floor, Podium Building, Minhang Campus Library

I. Undergraduate Courses/Lectures

1. Information Literacy Series (1-hour lectures)

Offered as part of extracurricular activities, the lectures cover essential information literacy topics and are announced in advance on the library’s WeChat account. Students are welcome to register. Customized lectures can also be arranged upon request.

Key Topics: AI literacy and tools for literature search and management; Ethics and norms of AI-assisted academic writing; Library catalog system and electronic resources; Common academic software

Learning Objectives: Understand the fundamentals of information literacy in the AI context; Use tools such as DeepSeek and Scopus AI for literature retrieval and academic writing; Comprehend the ethical and proper use of AI in academic writing; Master methods to search and access academic literature, including papers, books, and patents; Gain proficiency in reference management software and related tools

2. Academic Writing and Technical Reporting: Information Retrieval and Utilization (Putuo Campus)

Mandatory course for School of Software

Duration: 10 class hours

Credits: 1

Key Topics: Fundamentals of literature search; Library catalog system, e-books, Chinese and international electronic journals, specialized literature, index databases, and open-access resources; Practical search techniques and strategies

Learning Objectives: Understand basic concepts of information literacy and principles of literature search; Comprehend the framework and functions of search tools; Learn to select appropriate databases for targeted searches in computer science; Formulate and adjust search strategies to retrieve comprehensive and relevant information; Evaluate and filter retrieved literature effectively; Understand academic ethics and develop awareness of proper use of information resources.

II. Graduate Courses

1. Strategies and Methods for Literature Review (Humanities Track, Both Campuses)

(Optional for Master’s and PhD students; 36 class hours, 2 credits)

Key Topics: Overview of literature review methods; Library resources orientation; Searching free online resources; Retrieval methods for Chinese and international electronic journals; Formulating and adjusting search strategies; Searching Chinese and international thesis/dissertation databases and e-books; Comprehensive use of information resources and essential student information literacy; Academic writing and standards

Learning Objectives: Combine knowledge of free online resources and databases to develop and refine search strategies; Align search results with research topics and identify novel insights; Improve graduate students’ information retrieval and utilization skills to support research and learning

2. Strategies and Methods for Literature Review (Science Track, Minhang Campus)

(Optional for Master’s and PhD students; 36 class hours, 2 credits)

Key Topics: Overview of literature review methods; Library catalog system; Retrieval techniques for electronic journals, e-books, and theses/dissertations; Use of indexed databases; Reference management software; Academic norms and scientific paper writing and submission

Learning Objectives: Master fundamental information literacy knowledge; Learn how to access diverse academic resources (books, journals, theses); Develop optimized search queries to ensure comprehensive and accurate literature review; Build a solid foundation for graduate research and study

3. Educational Literature Retrieval and Data Analysis (Minhang Campus)

(Optional course; 36 class hours, 2 credits)

Key Topics: Literature search and data analysis methods in biology education research; Systematic retrieval of information through databases, Internet, and AI; Use of R or SPSS for basic data analysis and visualization; Writing literature reviews and research proposals with emphasis on innovation

Learning Objectives: Develop preliminary information and data literacy for digital-era research; Learn human–AI collaboration techniques for knowledge acquisition and data analysis