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PREDICTING AND SUPPORTING STUDENT PERFORMANCE IN A HIGH FAIL AND HIGH INCOMPLETION COURSE: AN EXPLORATORY STUDY OF INTRODUCTION TO GENERAL CHEMISTRY.

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Title: PREDICTING AND SUPPORTING STUDENT PERFORMANCE IN A HIGH FAIL AND HIGH INCOMPLETION COURSE: AN EXPLORATORY STUDY OF INTRODUCTION TO GENERAL CHEMISTRY.
Authors: VAN DUSER, KYLE E., XIAOFEI YAN, LUCAS, CHRIS M., COHEN, SHOSHANA K.
Source: College Student Journal. Jun2021, Vol. 55 Issue 2, p135-144. 10p.
Subjects: Academic ability, Logistic regression analysis, ACT Assessment, Achievement tests, College entrance examinations
Abstract: This quantitative exploratory study investigated factors related to the fail rate of first-year students in Introduction to General Chemistry courses (CHEM 1xx) at a mid-sized public research university. This course represents a gateway course for many scientific, medical, and healthcare majors. The sample consisted of 595 undergraduate students and used binary logistic regression to analyze the data. We found individual instructors were a significant predictor of students' grade in the Introduction to General Chemistry course. The students' American College Testing (ACT) math scores, SAT, or originally the Scholastic Aptitude Test, math scores, and high school grade point average (GPA) were also significant predictors. Interestingly, receipt of a Pell Grant was not a significant predictor of academic performance. Implications include course design, academic advising, tutoring and peer support, institutional research office reporting, as well as considerations for faculty course loads and emphasizing student success in the tenure and promotion process. [ABSTRACT FROM AUTHOR]
Copyright of College Student Journal is the property of Project Innovation Austin LLC and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: <searchLink fieldCode="DE" term="%22Academic+ability%22">Academic ability</searchLink><br /><searchLink fieldCode="DE" term="%22Logistic+regression+analysis%22">Logistic regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22ACT+Assessment%22">ACT Assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Achievement+tests%22">Achievement tests</searchLink><br /><searchLink fieldCode="DE" term="%22College+entrance+examinations%22">College entrance examinations</searchLink>
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  Data: This quantitative exploratory study investigated factors related to the fail rate of first-year students in Introduction to General Chemistry courses (CHEM 1xx) at a mid-sized public research university. This course represents a gateway course for many scientific, medical, and healthcare majors. The sample consisted of 595 undergraduate students and used binary logistic regression to analyze the data. We found individual instructors were a significant predictor of students' grade in the Introduction to General Chemistry course. The students' American College Testing (ACT) math scores, SAT, or originally the Scholastic Aptitude Test, math scores, and high school grade point average (GPA) were also significant predictors. Interestingly, receipt of a Pell Grant was not a significant predictor of academic performance. Implications include course design, academic advising, tutoring and peer support, institutional research office reporting, as well as considerations for faculty course loads and emphasizing student success in the tenure and promotion process. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of College Student Journal is the property of Project Innovation Austin LLC and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: ACT Assessment
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              Text: Jun2021
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