What and when: the role of course type and timing in students' academic performance

In this paper we discuss the results of a study of students' academic performance in first year general education courses. Using data from 566 students who received intensive academic advising as part of their enrollment in the institution's pre-major/general education program, we investigate individual student, organizational, and disciplinary factors that might predict a students' potential classification in an Early Warning System as well as factors that predict improvement and decline in their academic performance. Disciplinary course type (based on Biglan's [7] typology) was significantly related to a student's likelihood to enter below average performance classifications. Students were the most likely to enter a classification in fields like the natural science, mathematics, and engineering in comparison to humanities courses. We attribute these disparities in academic performance to disciplinary norms around teaching and assessment. In particular, the timing of assessments played a major role in students' ability to exit a classification. Implications for the design of Early Warning analytics systems as well as academic course planning in higher education are offered.

[1]  Lisa R. Lattuca,et al.  Shaping the College Curriculum: Academic Plans in Context , 2009 .

[2]  Jennifer Docktor,et al.  Synthesis of Discipline-Based Education Research in Physics. , 2014 .

[3]  Steven Lonn,et al.  Issues, challenges, and lessons learned when scaling up a learning analytics intervention , 2013, LAK '13.

[4]  Matthew M. Chingos,et al.  Improving Educational Attainment: Recent Trends and Challenges. , 2011 .

[5]  Peter J. Collier,et al.  “Is that paper really due today?”: differences in first-generation and traditional college students’ understandings of faculty expectations , 2008 .

[6]  Jan Nespor,et al.  Knowledge In Motion : Space, Time And Curriculum In Undergraduate Physics And Management , 2014 .

[7]  Vincent Tinto,et al.  Research and Practice of Student Retention: What Next? , 2006 .

[8]  Tony Becher,et al.  Academic Tribes and Territories: Intellectual Enquiry and the Cultures of Disciplines , 2001 .

[9]  A. Biglan.  Relationships between subject matter characteristics and the structure and output of university departments. , 1973 .

[10]  L. Schauble,et al.  Design Experiments in Educational Research , 2003 .

[11]  Ernest T. Pascarella,et al.  How College Affects Students: A Third Decade of Research. Volume 2. , 2005 .

[12]  Vincent Tinto.  Dropout from Higher Education: A Theoretical Synthesis of Recent Research , 1975 .

[13]  Phil Parette,et al.  Advising At-Risk Students in College and University Settings , 2002 .

[14]  Tony Becher,et al.  Academic Tribes and Territories: Intellectual Enquiry and the Cultures of Disciplines , 1991 .

[15]  E. Duval.  Attention please!: learning analytics for visualization and recommendation , 2011, LAK.

[16]  Andrew J. Elliot,et al.  Achievement Goals and Intrinsic Motivation: A Meta-Analytic Review , 1999, Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc.

[17]  Steven Lonn,et al.  Customized course advising: investigating engineering student success with incoming profiles and patterns of concurrent course enrollment , 2014, LAK.

[18]  Catherine L. Finnegan,et al.  Differences by Course Discipline on Student Behavior, Persistence, and Achievement in Online Courses of Undergraduate General Education , 2008 .

[19]  Thomas F. Nelson Laird,et al.  The Effect of Teaching General Education Courses on Deep Approaches to Learning: How Disciplinary Context Matters , 2010 .

[20]  David Allen.  DESIRE TO FINISH COLLEGE: An Empirical Link Between Motivation and Persistence , 1999 .

[21]  Robert M. Gonyea,et al.  Unmasking the Effects of Student Engagement on First-Year College Grades and Persistence , 2008 .

[22]  Tak-Shing Harry So,et al.  The Use and Interpretation of Logistic Regression in Higher Education Journals: 1988–1999 , 2002 .

[23]  Paul Trowler,et al.  Teaching and Learning Regimes: Implicit theories and recurrent practices in the enhancement of teaching and learning through educational development programmes , 2002 .

[24]  George D. Kuh,et al.  The Development of Process Indicators to Estimate Student Gains Associated with Good Practices in Undergraduate Education , 1997 .

[25]  Steven Lonn,et al.  A Learning Management System-Based Early Warning System for Academic Advising in Undergraduate Engineering , 2014 .

[26]  D. Murphey,et al.  Academically Adrift: Limited Learning on College Campuses , 2011 .

[27]  Laura T. Hamilton,et al.  Paying for the Party: How College Maintains Inequality , 2013 .

[28]  K. Squire,et al.  Design-Based Research: Putting a Stake in the Ground , 2004 .

[29]  Ruth Neumann,et al.  A Disciplinary perspective on university teaching and learning , 2003 .

[30]  W. Wiegand.  : The System of Professions: An Essay on the Division of Expert Labor , 1990 .

[31]  Ernest T. Pascarella,et al.  How college affects students , 1991 .

[32]  John M. Braxton.  Disciplines with an Affinity for the Improvement of Undergraduate Education. , 1995 .

[33]  C. Nelson,et al.  Student Diversity Requires Different Approaches To College Teaching, Even in Math and Science , 1996 .

[34]  Sébastien George,et al.  TrAVis to Enhance Students’ Self-Monitoring in Online Learning Supported by Computer-Mediated Communication Tools , 2011, CISIM 2011.