Can Self-Assessment Play a Greater Role in Advanced Chinese Learning in the Digital Era?

Can Self-Assessment Play a Greater Role in Advanced Chinese Learning in the Digital Era?

Professor Jianling Liao from Arizona State University is a member of Cheng & Tsui's Higher Education Advisory Council.

In an era where technology reshapes education, a critical question arises: Are our traditional assessment methods keeping pace? As Chinese educators, we often pour our hearts into feedback, yet wonder how effectively it translates into student growth. Let's explore how we can shift from teacher-centered evaluation to empowering students through innovative self-assessment, particularly with the aid of AI.

Is Our Assessment Practice Too Teacher-Centered?

As language educators, we understand the importance of integrating assessment activities into second language (L2) learning. Current advanced college Chinese courses often emphasize formal presentational speaking and writing skills, which require mastering complex, multi-dimensional subskills. These advanced skills can pose significant challenges for learners. When evaluating advanced students’ language production, we tend to provide detailed,  comprehensive feedback in our eagerness to help them enhance their language skills. We genuinely hope that students will carefully process our feedback, learn from it, and ultimately improve their language proficiency.

Nevertheless, in reality, it is not often clear to us whether or how students actually use the feedback we worked hard to provide. Also, we are not able to assume that students will love or feel motivated by our feedback. Assessment without student involvement becomes a passive process—one that may reassure teachers but does little to enhance student learning. So, how can we better engage students in our assessment practice?

Empowering Students’ Self-Assessment

Student-oriented self-assessment can be an integral part of our assessment practice, facilitating learner engagement in the learning process. AI and related technological tools offer great potential for fostering self-regulated learning. With the support of generative AI, learners can unpack their learning processes more easily, making language learning a more interactive and iterative experience. Students can use AI to self-check their language production and receive personalized feedback on language, content, and discourse. They can also interact with AI forsupport, such as refining their language and writing strategies during the writing process. Thus with AI, we can empower students to take greater ownership of their learning journey.

Nevertheless, since using AI for self-assessment is still relatively new, we as teachers must first expand our own knowledge and understanding. We also need to keep in mind that generative AI is not specifically designed to produce input or output tailored for L2 learners. Additionally, self-assessment is an academic skill that requires ongoing guidance and development. 

Here are some steps to integrate AI into effective self-assessment: 

1. Educate Students on the Value of Self-Assessment:

   • Help them understand how it benefits their learning journey.

2. Provide Concrete Guidance on AI Integration:

   • Explain how to use AI for different essay types.

   • Share different types of prompts for obtaining relevant feedback.

3. Teach Students to Process AI Feedback:

   • Guide them in creating meaningful "can-do" statements.

4. Acknowledge Student Achievements:

   • Showcase their final work, highlighting AI-supported self-assessment.

Including AI-supported self-assessment as a regular part of our language curriculum can truly provide sustainable, long-term benefits to Chinese learning.

Cheng & Tsui Higher Education Advisory Council

To stay at the forefront of language education as part of our shared mission of ‘bringing Asia to the world,’ Cheng & Tsui has established the Higher Education Advisory Council—an expert group of educators dedicated to working with us to help shape the future of our Asian-language and culture publishing projects. By collaborating with leading instructors and program directors, we seek to ensure that our resources reflect the real needs of the classroom, meet evolving curriculum standards, and respond to emerging trends in language teaching and learning.

The Council provides ongoing insight into pedagogy and the evolving landscape to guide  Cheng & Tsui’s innovative, culturally authentic programs that support both students and instructors.

Members of the Chinese Language Advisory Council

• Jianling Liao, Arizona State University
• Yi-Hsien Liu, University of Southern California
• Ke Peng, Western Kentucky University
• Zhongqi Shi, Columbia University
• Feng Xiao, Pomona College