Call for Papers

Introduction

The Workshop on Educational Data Mining in Writing and Literacy Instruction offers a unique platform for educators, researchers, and practitioners to delve into the transformative potential of data-driven approaches in enhancing writing and literacy education. As AI and technology continue to reshape the landscape of teaching and learning, this workshop aims to explore how educational data mining techniques can revolutionize writing instruction, foster literacy development, and empower educators with actionable insights.

Among the evolving educational landscape, this workshop seeks to address critical questions such as:

• How can data mining methodologies deepen our understanding of the writing process and literacy acquisition?

• What innovative approaches can be employed to assess writing proficiency and provide personalized feedback to students?

• In what ways can data analytics inform the design of adaptive learning systems tailored to individual learners’ needs in writing and literacy?

• How can ethical considerations surrounding data collection, privacy, and security be navigated in educational data mining research within the context of writing instruction?

• Through collaborative discussions, paper presentations, and hands-on activities, this workshop aims to foster a vibrant exchange of ideas and insights that will shape the future of writing and literacy instruction. Join us in exploring the cutting-edge intersections of education, data science, and language pedagogy, and contribute to the advancement of teaching practices that empower students to become proficient and confident communicators.

Topics of Interest:

We invite submissions of original research papers, work-in-progress reports, and position papers on topics including but not limited to:

• Advancements in NLP for writing assessment

• Automatic essay scoring and feedback generation

• Interactive writing environments and Intelligent Tutoring System(ITS)

• Writing Dataset across disciplines

• Large Language Model(LLM) application in writing analytic or classroom practice

• Policy, privacy, and ethical concerns with writing data

• Psychometrics and measurement

• Writing behavior analysis

• K-12 writing and literacy education

• Quantitive analysis and case studies for writing education practice

• Collaborate Writing and peer review

• Data-driven support for special education in literacy

• Writing styles and quality

• Plagiarism detection

Submission Guidelines:

We invite you to submit your original work for presentation and discussion. All papers should be formatted according to the EDM template(Word , Latex), and also should be carefully blinded for review. There will be two types of submissions:

• Research Papers (up to 6 pages): Original, substantive, mature, and unpublished research work addressing any of the above topics.

• Work-in-progress Report (up to 6 pages): Original, unpublished work-in-progress (incomplete or ongoing work, ready for feedback, but not yet fully developed).

Note: references do not count towards the page limit. Authors can also include appendices to more clearly describe datasets and tools if necessary, and these do not count toward the page limit.

The paper should be submitted through EasyChair.