paper-with-me

Papers

Towards a Recommender System for Undergraduate Research

2017-06-20 · del-Rio Felipe, Parra Denis, Kuzmicic Jovan, Svec Erick

Several studies indicate that attracting students to research careers requires to engage them from early undergraduate years. Following this paradigm, our Engineering School has developed an undergraduate research program that allows students to enroll in research in exchange for course credits. Moreover, we developed a web portal to inform students about the program and the opportunities, but participation remains lower than expected. In order to promote student engagement, we attempt to build a personalized recommender system of research opportunities to undergraduates. With this goal in mind we investigate two tasks. First, one that identifies students that are more willing to participate on this kind of program. A second task is generating a personalized list of recommendations of research opportunities for each student. To evaluate our approach, we perform a simulated prediction experiment with data from our School, which has more than 4,000 active undergraduate students nowadays. Our results indicate that there is a big potential to create a personalized recommender system for this purpose. Our results can be used as a baseline for colleges seeking strategies to encourage research activities within undergraduate students.

📄 PDF Abstract BibTeX arXiv:1706.06701

Code (0)

등록된 구현이 없습니다.

Tasks

Recommendation Systems

Similar Papers 제목 키워드 기반

Trends in Machine Learning and Electroencephalogram (EEG): A Review for Undergraduate Researchers

2023-07-06 · Nathan Koome Murungi, Michael Vinh Pham, Xufeng Dai, Xiaodong Qu

This paper presents a systematic literature review on Brain-Computer Interfaces (BCIs) in the context of Machine Learning. Our focus is on Electroencephalography (EEG) research, highlighting the latest trends as of 2023.…

EEGElectroencephalogram (EEG)Systematic Literature Review

"Which LLM should I use?": Evaluating LLMs for tasks performed by Undergraduate Computer Science Students

2024-01-22 · Vibhor Agarwal, Madhav Krishan Garg, Sahiti Dharmavaram, Dhruv Kumar

This study evaluates the effectiveness of various large language models (LLMs) in performing tasks common among undergraduate computer science students. Although a number of research studies in the computing education co…

Code Generation

A Framework for Undergraduate Data Collection Strategies for Student Support Recommendation Systems in Higher Education

2022-10-16 · Herkulaas MvE Combrink, Vukosi Marivate, Benjamin Rosman

Understanding which student support strategies mitigate dropout and improve student retention is an important part of modern higher educational research. One of the largest challenges institutions of higher learning curr…

Decision MakingRecommendation Systems

Learning About Learning: A Path from Spin Glasses to Artificial Intelligence

2026-01-12 · Denis D. Caprioti, Matheus Haas, Constantino F. Vasconcelos, Mauricio Girardi-Schappo arxiv

The Hopfield model, originally inspired by spin glasses, occupies a central place at the intersection of statistical mechanics, neural networks, and artificial intelligence. Despite its conceptual simplicity and broad ap…

The Use of Machine Learning Algorithms in Recommender Systems: A Systematic Review

2015-11-17 · Ivens Portugal, Paulo Alencar, Donald Cowan

Recommender systems use algorithms to provide users with product or service recommendations. Recently, these systems have been using machine learning algorithms from the field of artificial intelligence. However, choosin…

BIG-bench Machine LearningRecommendation Systems