26 citations · 112 across the 21 of their papers we have counts for
8 papers · 1 filter
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…