Connecting the dots between rigor and learning

What do we mean when we say “rigor,” and how can we ensure classroom lessons have the kind of rigor that promotes learning?

At a Glance

The word rigor is used in different ways, and people’s meaning isn’t always clear.
Cognitive rigor refers to the type of thinking required to complete a task.
Activities at higher levels of rigor require students to go beyond memorization to apply their knowledge to new situations.
Project-based learning is one teaching method that increases cognitive rigor.
Teachers can adapt current lessons to increase cognitive rigor by asking students to discuss and debate the facts they’re learning.

The concept of rigor has a long history in educational research and practice. Unfortunately, how the term “rigor” is used has not always been consistent, leading to confusion about what rigor really means and whether it makes a difference for student learning.

When we describe a teacher or course as “rigorous,” we’re most likely using one of these three definitions:

The most common understanding is how hard it is from a quantitative standpoint: how much homework the teacher gives or how much reading the course requires.
Another common definition is the developmental level of the material learned: Shakespeare is more rigorous than a picture book; calculus is more rigorous than addition.
A less common way to talk about rigor is to describe the type of thinking required for students to complete a learning task. This type, called “cognitive rigor,” can be applied to almost any learning situation and has a strong connection to learning outcomes in research.

Shifting the focus from teaching to learning

Cognitive rigor is a thread that runs through educational research in many frameworks: Benjamin Bloom’s taxonomy, Art Costa’s levels of questioning (Costa & Kallick, 2015), and Norman Webb’s depth of knowledge (1997). What these have in common is a shift in focus from teaching to learning. In other words, the best way to know if students are learning in the classroom is to analyze what students are doing.

This understanding has informed many protocols for evaluating teaching and learning, from Richard Elmore’s instructional rounds (City et al., 2009) to John Hattie’s (2008) focus on the effect size of student tasks. Research for each framework finds a positive association between the level of cognitive rigor in student tasks and learning outcomes on standardized assessments (Antonetti & Garver, 2015; Fisher, Frey, & Hattie, 2016; Fortsch et al., 2018; Tarr et al., 2008). Cognitive rigor has also been associated with higher levels of student engagement (Paige, Sizemore, & Neace, 2013).

The best way to know if students are learning in the classroom is to analyze what students are doing.

One of the seminal studies in the field was the Trends in International Mathematics and Science Study (TIMSS) of international mathematics achievement that found the most important predictor for a country’s mathematics achievement was the level of cognitive rigor of student tasks. Compared to lower-performing countries, countries with the highest levels of mathematics achievement taught the same mathematics concepts as other industrialized countries, but they asked students to apply mathematical concepts to novel situations more often than memorizing processes and applying algorithms out of context (Office of Educational Research and Improvement, 1997).

Similarly, studies show that student tasks at higher levels of rigor, such as project-based learning, lead to better long-term memory retrieval than tasks on the same concepts at lower levels of rigor (Saavedra, Morgan, & Haderlein, 2022). This is, in part, because transfer of learning from short- to long-term memory requires experiences that make the information meaningful. While rote memorization can work in the short-term, new information needs to connect to existing memories and emotional experiences and be applied in new contexts to remain salient enough over time to successfully transfer to long-term memory (Willis & Willis, 2020).

Measuring cognitive rigor

Some researchers have created systems to measure the cognitive rigor of student tasks, most notably Norman Webb (1997) in his description of depths of knowledge, and John Antonetti and James Garver (2015) in their work with teachers and administrators in schools that were changing their instructional practices to improve student learning outcomes.

Both systems use a four-point scale to describe the levels of cognitive rigor in student tasks:

Level 1: Rote memorization
Level 2: Conceptual understanding
Level 3: Strategic thinking
Level 4: Creativity and extended thinking

Educators can use these levels to analyze their own instruction and to plan units and lessons that provide a range of learning experiences for students that improve engagement and long-term retention of learning.

The AVID model to increase rigor

So how does an educator begin the work of increasing rigor in student tasks? One place to start is using AVID (www.avid.org) strategies as a foundation for lesson design. The AVID model’s emphasis on student-centered instruction puts the student in the driver’s seat of learning. Instead of being a “sage on the stage,” the teacher facilitates student learning by creating engaging learning experiences that lean on hands-on application, critical thinking, creativity, and collaboration.

The instructional core of AVID’s strategies derive from research on the impact of elevating cognitive rigor to improve student learning. Effectively adopting strategies such as Socratic seminar, philosophical chairs, and collaborative study groups, as well as implementing project-based learning, will support increasing rigor in the classroom.

Lesson planning with rigor in mind

Implementing project-based learning at the highest levels of rigor may require extensive planning, especially for a teacher who is used to traditional methods. But any teacher can tweak their current lessons to increase rigor — along with student engagement and learning — without substantially increasing time in lesson planning.

Cognitive rigor, or the level of thinking required by a student task, is a useful concept for designing units and lessons to improve student learning outcomes.

One approach is to use evaluation and argumentation to review material that has already been covered. You’re a history teacher and need students to remember the three amendments passed after the Civil War that expanded rights for the previously enslaved population. You might ask students to list these amendments and summarize each one as a bell-ringer — a Level 1 activity. An easy way to move this task to a higher level of rigor is to rephrase it in a way that engages the student’s critical thinking and own perspectives: Ask which of the three amendments was most important and why. Then ask students to discuss their answers with classmates. Asking students to discuss opinions or feelings about facts will increase rigor without extensive additional lesson planning.

One question that may arise is how to make sure all students can access a more rigorous task. For example, if a student does not remember the three amendments, how can they weigh in on which one was most important? Providing scaffolding, such as a picture to represent each amendment, ensures students get the benefit of the cognitive rigor while not feeling overwhelmed and left behind. Other options are to encourage students to review notes and help one another remember the amendments in a group discussion. Providing sentence stems may support English learners and others who need language support to share their ideas.

When planning lessons, teachers can scan existing curricula for opportunities to engage students in discussions. Math teachers may ask students to debate the best strategy for solving a problem. Science teachers can relate facts to decisions that businesses or governments make and ask students to provide their opinions. A health teacher may ask students what one new behavior they would incorporate to improve their own health based on the previous unit. These tasks can be as quick as five or 10 minutes and can come at the beginning of a lesson as a bell-ringer, as the main course of a lesson for deeper analysis, or at the end of a lesson as a quick reflection activity.

Making the connection

Cognitive rigor, or the level of thinking required by a student task, is a useful concept for designing units and lessons to improve student learning outcomes. While working toward project-based learning and the highest levels of cognitive rigor are important long-term goals, this can take significant time. In the meantime, even slight shifts in the rigor level of routine activities can make a difference for student learning.

References

Antonetti, J. & Garver, J. (2015). 17,000 classroom visits can’t be wrong: Strategies that engage students, promote active learning, and boost achievement. ASCD.

City, E.A., Elmore, R., Fiarman, S., & Teitel, L. (2009). Instructional rounds in education. Harvard Educational Publishing Group.

Costa, A. & Kallick, B. (2015). Five strategies for questioning with intention. Educational Leadership, 73 (1), 66-69.

Hattie, J. (2008). Visible learning. Routledge.

Office of Educational Research and Improvement. (1997). Introduction to TIMSS: The Third International Mathematics and Science Study: TIMSS as a starting point to examine U.S. education. U.S. Dept. of Education.

Fisher, D., Frey, N., & Hattie, J. (2016). Visible learning for literacy: Implementing the practices that work best to accelerate student learning. Corwin.

Fortsch, C., Werner, S., Kotzebue, L., & Neuhaus, B. (2018). Effects of high-complexity and high cognitive level instructional tasks in biology lessons on students’ factual and conceptual knowledge. Research in Science & Technological Education, 36 (3), 353-374.

Paige, D., Sizemore, J., Neace, W. (2013). Working inside the box: Exploring the relationship between student engagement and cognitive rigor. NASSP Bulletin, 97 (2), 105-123.

Saavedra, A., Morgan, K., & Haderlein, S. (2022). The impact of project-based learning on AP exam performance. Educational Evaluation and Policy Analysis, 44 (4).

Tarr, J., Reys, R., Reys, B., & Chavez, O. (2008) The impact of middle-grades mathematics curricula and the classroom learning environment on student achievement. Journal for Research in Mathematics Education, 39 (3), 247-280.

Webb, N. (1997). Criteria for alignment of expectations and assessments on mathematics and science education (Research Monograph Number 6). Council of Chief State School Officers.

Willis, J. & Willis, M. (2020). Research-based strategies to ignite student learning: Insights from a neurologist and classroom teacher. ASCD.

This article appears in the Winter 2025 issue of Kappan, Vol. 107, No. 3-4.