Evaluating the effectiveness of a writing intervention for first-year, ‘at-risk’ students

2016 ◽  
Vol 47 (1) ◽  
pp. 22-44
Author(s):  
Avasha Rambiritch
2020 ◽  
Vol 44 (3) ◽  
pp. 334-343
Author(s):  
Miriam Leary ◽  
Aimee Morewood ◽  
Randy Bryner

Using a Scholarship of Teaching and Learning lens, this study systematically examined if a targeted intervention in at-risk students within a science, technology, engineering, and mathematics (STEM)-based physiology program would elicit positive student perceptions and higher retention rates into the second year. Those students who were considered at risk for attrition (retention; n = 82) were compared against a control group (non-retention; n = 165), and outcomes were evaluated with an End-of-Semester Survey and university enrollment data. Students in the retention group reported more favorable responses to questions pertaining to a first-year seminar course and academic advising. By the start of the following (spring 2019) semester, 48 students transferred out of the program (20%) with little difference between groups (non-retention 19%; retention 22%). At the start of fall 2019 term, 55% of the 2018 freshman class were retained within the program (non-retention 66%; retention 39%), and 85% were retained within the university (non-retention 91%, retention 74%). The intervention was successful in eliciting positive student perceptions of the major, but did not improve retention of at-risk students within the physiology major.


2017 ◽  
Vol 17 (2) ◽  
pp. 45-52
Author(s):  
Jason Siefken

Tracking the difference between the time a first-year student is allowed to register for a course and the time he or she does register for a course (a student’s registration delay), we notice a negative correlation between registration delay and final grade in a course. The difference between a student who registers within the first two minutes they are allowed to and one who waits three weeks to register is approximately a full GPA point (on a 9 point scale). Registration delay may be a useful factor in helping to identify at-risk students, and should be taken into account as a confounding variable when doing educational studies on multi-section courses.


2021 ◽  
Vol 48 (6) ◽  
pp. 720-728
Author(s):  
Wenting Weng ◽  
Nicola L. Ritter ◽  
Karen Cornell ◽  
Molly Gonzales

Over the past decade, the field of education has seen stark changes in the way that data are collected and leveraged to support high-stakes decision-making. Utilizing big data as a meaningful lens to inform teaching and learning can increase academic success. Data-driven research has been conducted to understand student learning performance, such as predicting at-risk students at an early stage and recommending tailored interventions to support services. However, few studies in veterinary education have adopted Learning Analytics. This article examines the adoption of Learning Analytics by using the retrospective data from the first-year professional Doctor of Veterinary Medicine program. The article gives detailed examples of predicting six courses from week 0 (i.e., before the classes started) to week 14 in the semester of Spring 2018. The weekly models for each course showed the change of prediction results as well as the comparison between the prediction results and students’ actual performance. From the prediction models, at-risk students were successfully identified at the early stage, which would help inform instructors to pay more attention to them at this point.


2014 ◽  
Vol 38 (3) ◽  
pp. 229-234 ◽  
Author(s):  
Cynthia J. Miller

While the first year of medical school is challenging for all students, there may be specific issues for students from rural areas, economically disadvantaged backgrounds, ethnic minorities, or nontraditional age groups. A Summer Prematriculation Program (SPP) was created to prepare entering at-risk students for the demands of medical school. For the past 2 yr, an emphasis was placed on the development of appropriate study plans and skills. On presurveys, students predicted an increase in their number of study hours per lecture hour, from 7.6 h in undergraduate coursework to 9.1 h in medical school coursework ( n = 35). These study plans were infeasible given the rigorous didactic lecture schedule in medical school. Interventions were made through lectures on study plans and modeling of appropriate study habits using engaging lectures in the SPP physiology course. At the end of the program, a postsurvey was given, and students reported a reduction in the planned hours of study to a more realistic 3.9 h of study time per hour of lecture. Furthermore, students planned to decrease their use of textbooks while increasing their use of concept mapping, videos, and peer teaching. The majority of students completing the SPP program with a study skills emphasis performed well in the Medical Physiology course, with 4 students honoring in the course, 27 students passing, and 2 students remediating the course after an initial failure. These results indicate that at-risk medical students may have inappropriate study plans that can be improved through participation in a program that emphasizes study skills development.


2014 ◽  
Vol 38 (2) ◽  
pp. 161-169 ◽  
Author(s):  
Susan B. Higgins-Opitz ◽  
Mark Tufts

Health Science students at the University of KwaZulu-Natal perform better in their professional modules compared with their physiology modules. The pass rates of physiology service modules have steadily declined over the years. While a system is in place to identify “at-risk” students, it is only activated after the first semester. As a result, it is only from the second semester of their first year studies onward that at-risk students can be formally assisted. The challenge is thus to devise an appropriate strategy to identify struggling students earlier in the semester. Using questionnaires, students were asked about attendance, financing of their studies, and relevance of physiology. After the first class test, failing students were invited to complete a second questionnaire. In addition, demographic data were also collected and analyzed. Correlation analyses were undertaken of performance indicators based on the demographical data collected. The 2011 class comprised mainly sport science students (57%). The pass rate of sport science students was lower than the pass rates of other students (42% vs. 70%, P < 0.001). Most students were positive about physiology and recognized its relevance. Key issues identified were problems understanding concepts and terminology, poor study environment and skills, and lack of matriculation biology. The results of the first class test and final module marks correlated well. It is clear from this study that student performance in the first class test is a valuable tool to identify struggling students and that appropriate testing should be held as early as possible.


2018 ◽  
Vol 8 (2) ◽  
pp. 10
Author(s):  
Greet Langie ◽  
Maarten Pinxten

For Europe to remain at the forefront of scientific and technological devel-opment, the current shortage of persons trained in these fields at secondary and higher education has to be overcome. The readySTEMgo project aims to improve the retention rates of higher education STEM programmes by the identification of at-risk students in an early stage. We successfully identified a number of key skills that are essential for first-year achievement in a STEM programme. Additionally, we investigated which intervention tools can support at-risk students and evaluated their effectiveness. Based on the output of this research project four policy recommendations are formulated.


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