Xiao Chang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Xiao Chang has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Fengxia Wang2 shared publications
- Cassandra Thomas
Tuskegee University, Tuskegee, AL, USA
1 shared publication - Huixia Jin
Hunan City University
1 shared publication - Jung Won Hur
Auburn University, Auburn, AL, USA
1 shared publication - Li Huang
Department of Psychology & Sociology, Tuskegee University, Tuskegee, AL 36088, USA
1 shared publication
Latest Publications
- Open Access
- 3 November 2024
- Published by MDPI AG in Trends in Higher Education
- Vol. 3 (4) , 912-927
Improving Retention and Success of African American Students in Computer Science: A Mixed-Method Case Study at an HBCU
This case study introduces the STARS (Supporting Talented African American Undergraduates for Retention and Success) project, designed to foster the retention and success of academically talented African American computer science students from low-income backgrounds at Historically Black Colleges and Universities (HBCUs) in the U.S. The STARS program employs a holistic approach, integrating four primary pillars of support: academic, social, career, and financial. Specific support provided includes near-peer mentoring, technical skill development seminars, undergraduate research, and high school outreach activities. To explore the program’s effectiveness and areas of improvement, a mixed-method evaluation study was conducted, collecting data through surveys, observations, individual interviews, and focus group interviews. The findings revealed that the STARS program contributed to high levels of retention among its scholars, and the mentoring program provided valuable networking opportunities. The study suggests that the program’s comprehensive approach, tailored to scholars’ needs, and combined with a culturally affirming learning environment, facilitates the retention and success of talented African American students in computer science.
- 3 November 2024
- Published by MDPI AG in Trends in Higher Education
- Vol. 3 (4) , 912-927
Open AccessImproving Retention and Success of African American Students in Computer Science: A Mixed-Method Case Study at an HBCU
This case study introduces the STARS (Supporting Talented African American Undergraduates for Retention and Success) project, designed to foster the retention and success of academically talented African American computer science students from low-income backgrounds at Historically Black Colleges and Universities (HBCUs) in the U.S. The STARS program employs a holistic approach, integrating four primary pillars of support: academic, social, career, and financial. Specific support provided includes near-peer mentoring, technical skill development seminars, undergraduate research, and high school outreach activities. To explore the program’s effectiveness and areas of improvement, a mixed-method evaluation study was conducted, collecting data through surveys, observations, individual interviews, and focus group interviews. The findings revealed that the STARS program contributed to high levels of retention among its scholars, and the mentoring program provided valuable networking opportunities. The study suggests that the program’s comprehensive approach, tailored to scholars’ needs, and combined with a culturally affirming learning environment, facilitates the retention and success of talented African American students in computer science.
- 31 December 2010
- Published by AICIT in Journal of Convergence Information Technology
- Vol. 5 (10) , 109-116
Cost-Sensitive Support Vector Ranking for Information Retrieval
- 31 December 2010
- Published by AICIT in Journal of Convergence Information Technology
- Vol. 5 (10) , 109-116
Cost-Sensitive Support Vector Ranking for Information Retrieval
- 30 November 2010
- Published by AICIT in Journal of Convergence Information Technology
- Vol. 5 (9) , 118-125
Relevance Vector Ranking for Information Retrieval
- 30 November 2010
- Published by AICIT in Journal of Convergence Information Technology
- Vol. 5 (9) , 118-125
Relevance Vector Ranking for Information Retrieval