Haiwei Sang
Biographic Data
| ID | 10394683 |
|---|---|
| NAME | Haiwei Sang |
| GIVEN NAMES | Haiwei |
| FAMILY NAME | Sang |
| SIGNATURE | SANG H |
| AFFILIATIONS | Guizhou University |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2026 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Races
With the rapid advancement of large language models, the demand for intelligent and fine-grained automated essay scoring in educational assessment has increased significantly. However, existing methods still face challenges in maintaining scoring alignment and output consistency, making it difficult to consistently approximate human scoring standards. To address these issues, this paper proposes a unified framework named RACES (Reward-Aligned Con…
LLM-Cr
Recommender systems have become increasingly important in online learning platforms, where learners face a growing number of available courses and substantial variation in course quality and relevance. However, many existing course recommendation methods primarily rely on user–course interaction sequences and therefore often underutilize rich course semantic information, such as descriptions of learning objectives, covered concepts, and prerequis…
Knowledge-augmented form-filling agent for higher education services
Online academic and administrative services in higher education increasingly require students, faculty, and staff to complete structured forms across heterogeneous institutional platforms. These tasks are complicated by variations in field naming, page layout, validation rules, and dynamic interaction logic, which limits the reliability of rule-based form-filling tools. To address these challenges, this study proposes KAFA, a knowledge-augmented …
Arpg
Despite widespread adoption of large language models (LLMs), most students cannot effectively prompt them. The core challenge is teaching students how to ask: transforming prompting from trial-and-error guessing into a systematic, transferable skill. Existing solutions, such as static templates, rule-based hints, and automated rewriting, either ignore individual learning needs or optimize outputs without building competence, leaving students depe…
No prominent works on this page.
Races
With the rapid advancement of large language models, the demand for intelligent and fine-grained automated essay scoring in educational assessment has increased significantly. However, existing methods still face challenges in maintaining scoring alignment and output consistency, making it difficult to consistently approximate human scoring standards. To address these issues, this paper proposes a unified framework named RACES (Reward-Aligned Con…
LLM-Cr
Recommender systems have become increasingly important in online learning platforms, where learners face a growing number of available courses and substantial variation in course quality and relevance. However, many existing course recommendation methods primarily rely on user–course interaction sequences and therefore often underutilize rich course semantic information, such as descriptions of learning objectives, covered concepts, and prerequis…
Knowledge-augmented form-filling agent for higher education services
Online academic and administrative services in higher education increasingly require students, faculty, and staff to complete structured forms across heterogeneous institutional platforms. These tasks are complicated by variations in field naming, page layout, validation rules, and dynamic interaction logic, which limits the reliability of rule-based form-filling tools. To address these challenges, this study proposes KAFA, a knowledge-augmented …
Arpg
Despite widespread adoption of large language models (LLMs), most students cannot effectively prompt them. The core challenge is teaching students how to ask: transforming prompting from trial-and-error guessing into a systematic, transferable skill. Existing solutions, such as static templates, rule-based hints, and automated rewriting, either ignore individual learning needs or optimize outputs without building competence, leaving students depe…
Intelligent Tutoring Systems and Adaptive Learning (3 works) · Recommender Systems and Techniques (2 works) · Coaching (1 work) · Cognition (1 work) · Cognitive Load (1 work) · Higher education (1 work) · Innovative Teaching and Learning Methods (1 work) · Language model (1 work) · Massive open online course (1 work) · Metadata (1 work)