scholarly journals Increasing Retention in Engineering and Computer Science with a Focus on Academically At-Risk First-Year and Sophomore Students

2020 ◽  
Author(s):  
Sharon Jones ◽  
Zulema Naegele ◽  
Tammy VanDeGrift
2021 ◽  
pp. 009155212110476
Author(s):  
Jessica Williams ◽  
Thomastine Sarchet ◽  
Dawn Walton

Objective/Research Question: Students with disabilities, including deaf and hard of hearing (DHH) students, are enrolling in college at rates higher than in the past with most of them pursuing an associate’s degree. For DHH students, their reading ability is a predictor of their academic achievement in college. However, more than half of DHH students enroll in remedial reading and writing college courses indicating they are not reading and writing at a college level and putting them at-risk for non-completion. In addition, remedial reading and writing courses often do not count for credit toward graduation and may hinder rather than support student progress. One way to mitigate the need for remedial coursework during college is to provide the remedial instruction in a low-stakes manner through summer bridge to college programs. The purpose of the present study was to measure the effects of remedial reading and writing instruction provided through a summer bridge program on first-year, academically at-risk DHH college students’ ( N = 20) reading and writing abilities. Methods: Using a pretest/posttest design, we implemented remedial reading and writing instruction for 2 hours a day, 5 days a week for 5 weeks. Results: Upon the completion of instruction, the student participants’ reading and writing skills improved. Conclusions/Contributions: Our findings may encourage researchers to attempt remedial instruction through summer bridge programs with other populations with disabilities or English language learners.


2021 ◽  
Vol 11 (3) ◽  
pp. 297-310
Author(s):  
Erika B. Varga ◽  
Ádám Sátán

AbstractThe purpose of this paper is to investigate the pre-enrollment attributes of first-year students at Computer Science BSc programs of the University of Miskolc, Hungary in order to find those that mostly contribute to failure on the Programming Basics first-semester course and, consequently to dropout. Our aim is to detect at-risk students early, so that we can offer appropriate mentorship program to them. The study is based on secondary school performance and first-semester Programming Basics course results from the last decade of over 500 students. Secondary school performance is characterized by the rank of the school, admission point score, and foreign language knowledge. The correlation of these data with the Programming Basics course result is measured. We have tested three hypotheses, and found that admission point score and school rank together have significant impact on the first-semester Programming Basics course results. The findings also support our assumption that students having weaknesses in all examined pre-enrollment attributes are subject to dropout. This paper presents our analysis on students' data and the method we used to determine the attributes that mostly affect dropout.


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