26 citations · 112 across the 21 of their papers we have counts for
22 papers
SketchMind: A Multi-Agent Cognitive Framework for Assessing Student-Drawn Scientific Sketches
Ehsan Latif, Zirak Khan, Xiaoming Zhai
Scientific sketches (e.g., models) offer a powerful lens into students' conceptual understanding, yet AI-powered automated assessment of such free-form, visually diverse artifacts…
Artificial Intelligence Bias on English Language Learners in Automatic Scoring
Shuchen Guo, Yun Wang, Jichao Yu +7
This study investigated potential scoring biases and disparities toward English Language Learners (ELLs) when using automatic scoring systems for middle school students' written re…
Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions
Luyang Fang, Xiaowei Yu, Jiazhang Cai +23
The exponential growth of Large Language Models (LLMs) continues to highlight the need for efficient strategies to meet ever-expanding computational and data demands. This survey p…
Efficient Multi-Task Inferencing: Model Merging with Gromov-Wasserstein Feature Alignment
Luyang Fang, Ehsan Latif, Haoran Lu +3
Automatic scoring of student responses enhances efficiency in education, but deploying a separate neural network for each task increases storage demands, maintenance efforts, and r…
Advancing Education through Tutoring Systems: A Systematic Literature Review
Vincent Liu, Ehsan Latif, Xiaoming Zhai
This study systematically reviews the transformative role of Tutoring Systems, encompassing Intelligent Tutoring Systems (ITS) and Robot Tutoring Systems (RTS), in addressing globa…
Privacy-Preserved Automated Scoring using Federated Learning for Educational Research
Ehsan Latif, Xiaoming Zhai
Data privacy remains a critical concern in educational research, requiring strict adherence to ethical standards and regulatory protocols. While traditional approaches rely on anon…
Fine-tuning ChatGPT for Automatic Scoring of Written Scientific Explanations in Chinese
Jie Yang, Ehsan Latif, Yuze He +1
The development of explanations for scientific phenomena is essential in science assessment, but scoring student-written explanations remains challenging and resource-intensive. La…
Human-Centered Design for AI-based Automatically Generated Assessment Reports: A Systematic Review
Ehsan Latif, Ying Chen, Xiaoming Zhai +1
This paper provides a comprehensive review of the design and implementation of automatically generated assessment reports (AutoRs) for formative use in K-12 Science, Technology, En…
Can OpenAI o1 outperform humans in higher-order cognitive thinking?
Ehsan Latif, Yifan Zhou, Shuchen Guo +6
This study evaluates the performance of OpenAI's o1-preview model in higher-order cognitive domains, including critical thinking, systematic thinking, computational thinking, data…
Efficient Multi-Task Inferencing with a Shared Backbone and Lightweight Task-Specific Adapters for Automatic Scoring
Ehsan Latif, Xiaoming Zhai
The integration of Artificial Intelligence (AI) in education requires scalable and efficient frameworks that balance performance, adaptability, and cost. This paper addresses these…
Using Generative AI and Multi-Agents to Provide Automatic Feedback
Shuchen Guo, Ehsan Latif, Yifan Zhou +2
This study investigates the use of generative AI and multi-agent systems to provide automatic feedback in educational contexts, particularly for student constructed responses in sc…
A Systematic Assessment of OpenAI o1-Preview for Higher Order Thinking in Education
Ehsan Latif, Yifan Zhou, Shuchen Guo +24
As artificial intelligence (AI) continues to advance, it demonstrates capabilities comparable to human intelligence, with significant potential to transform education and workforce…
Unveiling Scoring Processes: Dissecting the Differences between LLMs and Human Graders in Automatic Scoring
Xuansheng Wu, Padmaja Pravin Saraf, Gyeonggeon Lee +3
Large language models (LLMs) have demonstrated strong potential in performing automatic scoring for constructed response assessments. While constructed responses graded by humans a…
3P-LLM: Probabilistic Path Planning using Large Language Model for Autonomous Robot Navigation
Ehsan Latif
Much worldly semantic knowledge can be encoded in large language models (LLMs). Such information could be of great use to robots that want to carry out high-level, temporally exten…
G-SciEdBERT: A Contextualized LLM for Science Assessment Tasks in German
Ehsan Latif, Gyeong-Geon Lee, Knut Neumann +2
The advancement of natural language processing has paved the way for automated scoring systems in various languages, such as German (e.g., German BERT [G-BERT]). Automatically scor…
Gemini Pro Defeated by GPT-4V: Evidence from Education
Gyeong-Geon Lee, Ehsan Latif, Lehong Shi +1
This study compared the classification performance of Gemini Pro and GPT-4V in educational settings. Employing visual question answering (VQA) techniques, the study examined both m…
Automatic Scoring of Students' Science Writing Using Hybrid Neural Network
Ehsan Latif, Xiaoming Zhai
This study explores the efficacy of a multi-perspective hybrid neural network (HNN) for scoring student responses in science education with an analytic rubric. We compared the accu…
Multimodality of AI for Education: Towards Artificial General Intelligence
Gyeong-Geon Lee, Lehong Shi, Ehsan Latif +10
This paper presents a comprehensive examination of how multimodal artificial intelligence (AI) approaches are paving the way towards the realization of Artificial General Intellige…
Knowledge Distillation of LLM for Automatic Scoring of Science Education Assessments
Ehsan Latif, Luyang Fang, Ping Ma +1
This study proposes a method for knowledge distillation (KD) of fine-tuned Large Language Models (LLMs) into smaller, more efficient, and accurate neural networks. We specifically…
AI Gender Bias, Disparities, and Fairness: Does Training Data Matter?
Ehsan Latif, Xiaoming Zhai, Lei Liu
This study delves into the pervasive issue of gender issues in artificial intelligence (AI), specifically within automatic scoring systems for student-written responses. The primar…
Applying Large Language Models and Chain-of-Thought for Automatic Scoring
Gyeong-Geon Lee, Ehsan Latif, Xuansheng Wu +2
This study investigates the application of large language models (LLMs), specifically GPT-3.5 and GPT-4, with Chain-of-Though (CoT) in the automatic scoring of student-written resp…
Fine-tuning ChatGPT for Automatic Scoring
Ehsan Latif, Xiaoming Zhai
This study highlights the potential of fine-tuned ChatGPT (GPT-3.5) for automatically scoring student written constructed responses using example assessment tasks in science educat…