Lele Sha

• research fellow at Monash University (Australia)

Automated classification of learner-generated text to identify behavior, emotion, and cognition indicators, collectively known as Learning Engagement Classification (LEC), has received considerable attention in fields such as NLP, Learning Analytics, and Educational Data Mining. Recently, Large Language Models (LLMs), such as ChatGPT, which are con...

This study explores the challenge of sentence-level AI-generated text detection within human-AI collaborative hybrid texts (abbreviated as hybrid texts). Existing studies of AI-generated text detection for hybrid texts often rely on synthetic datasets. These typically involve hybrid texts with a limited number of boundaries, e.g., single-boundary h...

Various machine learning approaches have gained significant popularity for the automated classification of educational text to identify indicators of learning engagement -- i.e. learning engagement classification (LEC). LEC can offer comprehensive insights into human learning processes, attracting significant interest from diverse research communit...

Effective collaboration and teamwork skills are critical in high‐risk sectors, as deficiencies in these areas can result in injuries and risk of death. To foster the growth of these vital skills, immersive learning spaces have been created to simulate real‐world scenarios, enabling students to safely improve their teamwork abilities. In such learni...

The recent large language models (LLMs), e.g., ChatGPT, have been able to generate human-like and fluent responses when provided with specific instructions. While admitting the convenience brought by technological advancement, educators also have concerns that students might leverage LLMs to complete their writing assignments and pass them off as t...

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are concerns...

Human-AI collaborative writing has been greatly facilitated with the help of modern large language models (LLM), e.g., ChatGPT. While admitting the convenience brought by technology advancement, educators also have concerns that students might leverage LLM to partially complete their writing assignment and pass off the human-AI hybrid text as their...

Massive Open Online Courses (MOOCs) are often plagued by a low level of student engagement and retention, with many students dropping out before completing the course. In an effort to improve student retention, educational researchers are increasingly turning to the latest Machine Learning (ML) models to predict student learning outcomes, based on...

Generative Large Language Models (LLMs) demonstrate impressive results in different writing tasks and have already attracted much attention from researchers and practitioners. However, there is limited research to investigate the capability of generative LLMs for reflective writing. To this end, in the present study, we have extensively reviewed th...

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (e.g., question generation, feedback provision, and essay grading), there are concer...

Predictive modeling is a core technique used in tackling various tasks in learning analytics research, e.g., classifying educational forum posts, predicting learning performance, and identifying at-risk students. When applying a predictive model, it is often treated as the first priority to improve its prediction accuracy as much as possible. Class...

Providing educational feedback has been widely acknowledged as an effective method to assist student learning. To offer feedback for a large student cohort, educational researchers started developing artificial intelligence (AI) systems. Though the existing AI-driven feedback achieved certain success, many concerns still exist during the deployment...

In online courses, discussion forums play a key role in enhancing student interaction with peers and instructors. Due to large enrolment sizes, instructors often struggle to respond to students in a timely manner. To address this problem, both traditional Machine Learning (ML) (e.g., Random Forest) and Deep Learning (DL) approaches have been applie...

To construct dialogue-based Intelligent Tutoring Systems (ITS) with sufficient pedagogical expertise, a trendy research method is to mine large-scale data collected by existing dialogue-based ITS or generated between human tutors and students to discover effective tutoring strategies. However, most of the existing research has mainly focused on the...

Automatic classifiers of educational forum posts are essential in helping instructors effectively implement their teaching practices and thus have been widely investigated. However, existing studies mostly stressed the accuracy of a classifier, while the fairness of the classifier remains largely unexplored, i.e., whether the posts generated by a g...