Academic Rigor White Paper 2: Contextualizing Academic Rigor

Authored by Andria F. Schwegler, Associate Professor of Psychology in the Counseling and Psychology Department at Texas A&M University - Central Texas

Andria teaches a range of fully online courses at the graduate and undergraduate levels, including statistics, research methods, history of psychology, and social psychology in addition to courses in the psychology of learning and educational technology. She is the Graduate Coordinator for the Master of Science in Educational Psychology program.

Locating academic rigor in the higher education landscape requires an explicit consideration and detangling of the constructs that are commonly conflated with it. Many definitions of academic rigor confound it with other variables such as curriculum and/or student learning (e.g., see the variety of definitions in Hechinger Institute, 2009). In the second of three white papers on this topic, learn how various elements affect and support academic rigor. Refer to the first paper in the series for a comprehensive definition of academic rigor.


To clarify the location of academic rigor as it relates to student learning, the learning context needs to be distinguished from related contexts (see Figure 1).
figure showing location of academic rigor within context of student's life

Figure 1. Location of academic rigor in the context of students’ personal and professional lives in the real world and within the institutional context of programs, learning context, student support for learning, and assessments of student learning. Student learning assessments can be used internally to the institution for revisions to the program curriculum, the learning context, and support services provided for learning.

The Real World

The real world each student occupies enables a host of choices including decisions regarding contributing as a citizen and obtaining education and employment. Part of this context includes perceptions of the purpose of a higher education and beliefs regarding its value, which shape the higher education options students pursue. The learning students obtain via higher education is then brought to bear on this context, and a meaningful education helps students navigate the challenges they encounter.


Program Context

The educational programs that students select are influenced by their experiences in the real world, and programs are shaped by this broader context. Articulating the curriculum and its sequence within a program are essential prerequisites to creating an academically rigorous learning context, but specifying curriculum is not synonymous with setting the conditions for rigor.

 

Course Design

Broadly, the learning context can be distinguished into static features that can be planned in advance and recreated across iterations (i.e., course design) and dynamic features that may be unique to each iteration as it unfolds (i.e., course delivery). The design of the materials, resources, activities, and assessments that are implemented to support student learning have been clearly articulated and recognized as influential for student learning (Quality Matters, 2019).


Course Delivery

Course delivery includes the manner in which the course is carried out and the expectations and requirements the teacher enforces. Course delivery that does not include an explicit consideration of the evidence to support rigor may fall short of conveying the goals of the stated curriculum and design of the course. Though program faculty may have specified curriculum, learning activities, and embedded assessments across courses in a program, these requirements do not imply that they will be taught by individual faculty members to the level intended. 


Mode of Delivery

The medium through which the learning context is delivered (i.e., online, blended, face-to-face) does not indicate the rigor of a course; instead, the decisions the teacher makes in delivering the content in the learning context (e.g., selection of materials, time spent on learning tasks) reflects the level of academic rigor of the course and the subsequent learning students obtain from it.  


Responsibilities of Teachers and Students

Defining academic rigor in a way that it can be evaluated and revised through a continuous improvement process requires that the teacher’s choices and actions in crafting the learning context can be assessed separately of the students’ choices and actions.


Support for Learning

When the learning context incorporates elements that promote and protect student learning, students will be hard pressed to succeed without engaging with the content in ways that help them learn it. Though some students will be prepared for the workload, some students will need assistance with learning how to learn, with prerequisite information and skills, and/or with creating their own understanding or interpretation of the content. The need for assistance is so essential that some argue academic rigor cannot be achieved without it (Graham & Essex, 2001; Schnee, 2008; Whitaker, 2016). Beyond facilitation provided by faculty members in the learning context, students may need additional supports for learning.


Remedial Coursework

One way to support student learning is to provide remedial courses to address gaps in students’ academic preparation, but the efficacy of such coursework on students’ outcomes is mixed, and the effectiveness with which it is carried out lacks systematic investigation..


Academic Support Services

An alternative to remedial coursework is academic support services provided to students outside of their courses; however, most students do not utilize these services. Defining academic rigor as research-based characteristics of the learning context instead of as elite qualities of students (e.g., admitting only the best prepared) demands that these services be destigmatized and aligned with the curriculum and learning contexts so all students utilize the resources they need.


Student Learning 

Because the cognitive processes underlying learning cannot be directly observed, student learning must be inferred based on assessment information. Indirect measures cannot substitute for direct measures, which are subject to the same validity and reliability concerns as other types of assessment. Faculty-designed assessment artifacts can be leveraged beyond grades to inform revisions to the curriculum, learning context, and academic support services.


Conclusion

Considering the broader context in which rigor is situated, this perspective distinguishes academic rigor from other related constructs and allows documentation and assessment of academic rigor that is independent from decisions that are outside of a faculty member’s control. 


References

About NSSE. (2019, March 15). Retrieved from http://nsse.indiana.edu/html/about.cfm

American Association of University Professors. (2009). Statement on professional ethics. Retrieved from the American Association of University Professors website: https://www.aaup.org/report/statement-professional-ethics

American Association of University Professors, American Council on Education, & Association of Governing Boards of Universities and Colleges. (1990). Statement of government of colleges and universities. Retrieved from the American Association of University Professors website: https://www.aaup.org/report/statement-government-colleges-and-universit…

American Association of University Professors, & Association of American Colleges and Universities. (1970). 1940 statement of principles on academic freedom and tenure with 1970 interpretive comments. Retrieved from the American Association of University Professors website: https://www.aaup.org/report/1940-statement-principles-academic-freedom-…

Arum, R., & Roksa, J. (2011). Academically adrift: Limited learning on college campuses. Chicago, IL: University of Chicago Press.

Association of American Colleges & Universities. (n.d.). High-impact educational practices: A brief overview. Retrieved September 12, 2019, from aacu.org/leap/hips

Bachman, R. M. (2013). Shifts in attitudes: A qualitative exploration of student attitudes towards efforts of remediation. Research & Teaching in Developmental Education, 29(2), 14-29.

Billing, D. (2007). Teaching for transfer of core/key skills in higher education: Cognitive skills. Higher Education, 53, 483-516. doi 10.1007/s10734-005-5628-5

Bjork, E. L., & Bjork, R. A. (2011). Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. In M. A. Gernsbacher, R. W. Pew, L. M. Hough, & J. R. Pomerantz (Eds.) Psychology and the real world: Essays illustrating fundamental contributions to society (pp. 56-64). New York, NY: Worth.

Cain, T. R. (2014, November). Assessment and academic freedom: In concert, not conflict. (Occasional Paper #22). Urbana, IL: University of Illinois and Indiana University, National Institute for Learning Outcomes Assessment. Retrieved from http://www.learningoutcomesassessment.org/documents/OP2211-17-14.pdf

Cerasoli, C. P., Nicklin, J. M., & Ford, M. T. (2014). Intrinsic motivation and extrinsic incentives jointly predict performance: A 40-year meta-analysis. Psychological Bulletin, 140(4), 980-1008.

Cheatle, J., & Bullerjahn, M. (2015). Undergraduate student perceptions and the writing center. Writing Lab Newsletter, 40, 19-26.

Chen, X. (2016). Remedial coursetaking at U.S. public 2- and 4-year institutions: Scope, experiences, and outcomes. Statistical Analysis Report (Report No. NCES 2016-405). Washington, DC: the National Center for Education Statistics. Retrieved from https://files.eric.ed.gov/fulltext/ED568682.pdf

Choy, S. P. (2002). Nontraditional undergraduates (Report No. NCES 2002-012). Washington, DC: the National Center for Education Statistics. Retrieved from https://nces.ed.gov/pubs2002/2002012.pdf

Crede, M., & Kuncel, N. R. (2008). Study habits, skills, and attitudes: The third pillar supporting collegiate academic performance. Perspectives on Psychological Science, 3(6), 425-453.

DePaoli, J. L., Balfanz, R., Atwell, M. N., & Bridgeland, J. (2018). Building a grad nation: Progress and challenges in raising high school graduation rates. Retrieved from https://files.eric.ed.gov/fulltext/ED585524.pdf

Duncan, H. E., Range, B., & Hvidston, D. (2013). Exploring student perceptions of rigor online: Toward a definition of rigorous learning. Journal on Excellence in College Teaching, 24(4), 5-28.

Fong, C. J., Davis, C. W., Kim, Y., Kim, Y. W., Marriott, L., & Kim, S. Y. (2017). Psychosocial factors and community college student success: A meta-analytic investigation. Review of Educational Research, 87(2), 388-424. doi: 10.3102/0034654316653479

Graham, C., & Essex, C. (2001). Defining and ensuring academic rigor in online and on-campus courses: Instructor perspectives. Annual Proceedings National Convention of the Association for Educational Communications and Technology, 1-2, 330-337.

Hechinger Institute. (2009). Understanding and reporting on academic rigor. Retrieved from http://hechinger.tc.columbia.edu/primers/Hechinger_Institute_Rigor_Prim…

Honicke, T., & Broadbent, J. (2016). The influence of academic self-efficacy on academic performance: A systematic review. Educational Research Review, 17, 63-84.

Hutchings, P., Huber, M. T., & Ciccone, A. (2011). The scholarship of teaching and learning reconsidered: Institutional integration and impact. San Francisco, CA: Jossey-Bass.

Jaschik, S., & Lederman, D. (2016). The 2016 Inside Higher Ed survey of faculty attitudes on technology: A study by Gallup and Inside Higher Ed. Retrieved from https://www.insidehighered.com/booklet/2016-survey-faculty-attitudes-te…

Keller, C. M. (2018). Reframing rigor: Implication for institutional practice and policy. New Directions for Higher Education, 181, 89-96. Retrieved from https://onlinelibrary.wiley.com/doi/full/10.1002/he.20273

Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: How difficulties recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121-1134.

Kuh, G. D., Ikenberry, S. O., Jankowski, N. A., Cain, T. R., Ewell, P. T., Hutchings, P., & Kinzie, J. (2015). Using evidence of student learning to improve higher education. San Francisco, CA: Jossey-Bass.

Labaree, D. F. (1997). Public goods, private goods: The American struggle over educational goals. American Educational Research Journal, 34(1), 39-81.

Mathers, C. E., Finney, S. J., & Hathcoat, J. D. (2018). Student learning in higher education: A longitudinal analysis and faculty discussion. Assessment & Evaluation in Higher Education, 43(8), 1211-1227.

Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2010). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. Retrieved from the U.S. Department of Education Office of Planning, Evaluation, and Policy Development https://www2.ed.gov/rschstat/eval/tech/evidence-based-practices/finalre…

Moon, A., Gere, A. R., & Shultz, G. V. (2018). Writing in the STEM classroom: Faculty conceptions of writing and its role in the undergraduate classroom. Science Studies and Science Education, 102, 1007-1028. doi: 10.1002/sce.21454

Multon, K. D., Brown, S. D., & Lent, R. W. (1991). Relation of self-efficacy beliefs to academic outcomes: A meta-analytic investigation. Journal of Counseling Psychology, 39(1), 30-38.

No significant difference. (2010). Retrieved from http://www.nosignificantdifference.org/

Pan, S. C., & Rickard, T. C. (2018). Transfer of test-enhanced learning: Meta-analytic review and synthesis. Psychological Bulletin, 144(7), 710-756. doi: 10.1037/bul0000151

Quality Matters (2019). QM Rubrics & Standards. Retrieved from the Quality Matters website: https://www.qualitymatters.org/qa-resources/rubric-standards

Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130(2), 261-288.

Schnee, E. (2008). “In the real world no one drops their standards for you”: Academic rigor in a college worker education program. Equity & Excellence in Education, 41(1), 62-80. doi: 10.1080/10665680701764502

Schwinger, M., Wirthwein, L., Lemmer, G., & Steinmayr, R. (2014). Academic self-handicapping and achievement: A meta-analysis. Journal of Educational Psychology, 106(3), 744-761.

Shields, K. A., & O’Dwyer, L. M. (2017). Remedial education and completing college: Exploring differences by credential and institutional level. Journal of Higher Education, 88(1), 85-109. http://dx.doi.org/10.1080/00221546.2016.1243943

Sitzmann, T., Ely, K., Brown, K. G., & Bauer, K. N. (2010). Self-assessment of knowledge: A cognitive learning or affective measure? Academy of Management Learning & Education, 9(2), 169-191.

Sparks, D., & Malkus, N. (2013). First-year undergraduate remedial coursetaking: 1999-2000, 2003-2004, 2007-2008 (Report No. NCES 2013-013). Washington, DC: the National Center for Educational Statistics. Retrieved from https://files.eric.ed.gov/fulltext/ED538339.pdf

Truschel, J., & Reedy, D. L. (2009). National survey - What is a learning center in the 21st century? Learning Assistance Review, 14(1), 9-22. Retrieved from http://eric.ed.gov/?id=EJ839147

Whitaker, M. (2016). (Re)defining academic rigor: From theory to praxis in college classrooms. Currents in Teaching & Learning, 8(1), 4-17.

Wiggins, G. (1990). The case for authentic assessment (ERIC Digests ED328611). ERIC Clearinghouse on Tests Measurement and Evaluation. Washington, DC: American Institutes for Research.

Wyatt, J. N., Wiley, A., Camara, W. J., & Proestler, N. (2012). The development of an index of academic rigor for college readiness (Report No. 2011-11). New York, NY: the College Board. Retrieved from https://eric.ed.gov/?id=ED561023