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Tired of Failing Students? Improving Student Learning Using Detailed and Automated Individualized Feedback in a Large Introductory Science Course

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Abstract

Providing students with timely, targeted, and useful feedback regarding their understanding of course topics is generally accepted as a good educational practice. However, when classes are very large there are challenges that prevent many instructors from accomplishing this goal. This study explores the perceived helpfulness to students and the instructor of implementing a relatively new method of automated scoring and feedback in a large section of an organic chemistry course. Prior research has shown this method to be helpful in other STEM classes. In the current study, students in two different offerings of a stand-alone organic chemistry course completed an anonymous survey in which they were asked to provide feedback about their perceptions of the new methodology. The faculty member who taught the course was also asked to respond to a series of questions regarding the feedback system. Both students and the instructor provided favorable comments about the helpfulness of the methodology and the feedback provided by it. The instructor found it helpful for providing individual feedback to students, which had previously not been possible due to the number of students enrolled in the course. Students reported that the feedback helped them to identify course topic strengths and challenge areas and that they planned to study the material differently going forward. The results indicate that this intervention can help improve student understanding of course topics and necessary actions for improving future performance in the course.

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Availability of Data and Material

The survey instrument used and the confidential survey data collected in support of this project are available upon request. Our current IRB approval does not include permission to publish all data obtained in the study. We would need to submit a revised IRB proposal if the journal wanted us to publish the data in their entirety.

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Acknowledgements

The authors wish to thank the anonymous reviewers for their valuable feedback on an earlier draft of this manuscript.

Funding

No funding was received in support of this research.

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Authors and Affiliations

  1. Dean’s Office – College of Humanities and Social Sciences, North Carolina State University, Campus Box 8101, Raleigh, NC, 27695-8101, USA

    Karen R. Young

  2. Office of Information Technology, North Carolina State University, Campus Box 7109, Raleigh, NC, 27695-7109, USA

    Henry E. Schaffer

  3. Department of Psychology, North Carolina State University, Raleigh, NC, 27695-7650, USA

    Jasmine B. James

  4. Department of Chemistry, North Carolina State University, Campus Box 8204, Raleigh, NC, 27695-8204, USA

    Maria T. Gallardo-Williams

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  1. Karen R. Young
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  2. Henry E. Schaffer
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  3. Jasmine B. James
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  4. Maria T. Gallardo-Williams
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Corresponding author

Correspondence to Karen R. Young.

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Conflicts of Interest/Competing Interests

One of the authors was the faculty instructor for the course described in the study, but we do not believe that had an inappropriate influence on the research. This research was not supported by any funding agency and the authors do not have any financial or non-financial interests that might be perceived as influencing the research.

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All computer code used in this project is available in GitHub for anyone to freely use, per the reference section of the paper.

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Young, K.R., Schaffer, H.E., James, J.B. et al. Tired of Failing Students? Improving Student Learning Using Detailed and Automated Individualized Feedback in a Large Introductory Science Course. Innov High Educ 46, 133–151 (2021). https://doi.org/10.1007/s10755-020-09527-5

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