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Can Early-Assignment Grades Predict Final Grades in IT Courses?

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Conference

2017 ASEE Annual Conference & Exposition

Location

Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

Emerging Computing and Information Technologies I

Tagged Division

Computing & Information Technology

Page Count

11

DOI

10.18260/1-2--28002

Permanent URL

https://peer.asee.org/28002

Download Count

452

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Paper Authors

biography

Parameswari Ramanathan Indiana University-Purdue University, Indianapolis

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Param Ramanathan works has a Senior Programmer Analyst for the Family and Social Services Administration (FSSA) IT division. She graduated from Pondicherry Engineering College, India with a Bachelors degree in Computer Science and Engineering. She then worked as a Software
Engineer for Larsen and Toubro Infotech limited (L&T), India for couple of years and then as a Senior Programmer Analyst for Indiana Support Enforcement Tracking System (ISETS), State of Indiana for few years. She then joined as a Senior IT Consultant at FedEx Corporation, Memphis, TN and worked in Accounts Receivables system for couple of years. At present, she is working for the Indiana Client Eligibility System (ICES), a FSSA IT division. She is currently attending Masters of Science degree in Computer and Information Technology at IUPUI University, IN. Her major concentration is Applied data analysis and management.

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Eugenia Fernandez Indiana University-Purdue University, Indianapolis

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Eugenia Fernandez is an Associate Professor of Computer and Information Technology and Chair of the Department of Computer Information and Graphics Technology in the Purdue School of Engineering and Technology at Indiana University-Purdue University, Indianapolis. She is a Fellow of the Mack Center at Indiana University for Inquiry on Teaching and Learning and an Editor of the Journal of Scholarship of Teaching and Learning. Her research focuses on the scholarship of teaching and learning related to learning with technology.

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Abstract

Numerous studies have been conducted to predict final grades of students in a course using test scores, such as SAT and ACT, and high school performance as predictors (Delong, 1986; Jensen & Barron, 2014; Roşeanu & Drugaş, 2011; Zwick, 2005). While helpful for looking at overall performance, this is not useful when trying to identify students at risk of failing a particular course so that an intervention may be attempted. Thus, the purpose of this research is to investigate student performance on early assignments in a course as a predictor of their final course grades. Specifically, this study will examine the prediction of students' final course grades based on the first two assignments in undergraduate Information Technology courses at Indiana University Purdue University Indianapolis (IUPUI).

Student work in courses taught in spring 2016 formed the sampling frame for this research. A sample of 110 students was selected using stratified cluster sampling with course levels (100, 200, 300, 400 level) as the strata and courses as clusters. Selection was carried out so as to result in a sample proportional to the percentage of students enrolled in each strata. The following data was collected for each student: points earned in the first two graded assignments, point value of the first two assignments, the type of the assignments, week in the semester the assignments were done, final grade, student class standing (freshman, sophomore, junior, senior) and student gender. Linear regression was used to predict the final course grade.

This study is currently ongoing. The study will be completed prior to the final submission date.

Works Cited

Delong, G. S. B. (1986). The predictive value of ACT scores in determining grades in selected business courses (Doctoral dissertation, Oklahoma State University).

Jensen, P. & Barron, J. (2014). Midterm and first-exam grades predict final grades in biology courses. Journal of College Science Teaching, 44(2), 82-89.

Roşeanu, G. & Drugaş, M. (2011). The admission criteria to the university as predictors for academic performance: A pilot study. Journal of Psychological and Educational Research, 19(2), 7-19.

Zwick, R. (2005). Predicting college grades and degree completion using high school grades and SAT scores: The role of student ethnicity and first language. American Educational Research Journal, 42, 439-464.

Ramanathan, P., & Fernandez, E. (2017, June), Can Early-Assignment Grades Predict Final Grades in IT Courses? Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28002

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2017 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015