Erosion in a River

Nicole LaDue, Northern Illinois University
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Formative assessment questions using a classroom response system ("clickers") can be used to reveal students' spatial understanding.

Students are shown this diagram and instructed to "Click in the river where you expect to find the greatest rate of erosion along the river bed."

A follow-up question asks students to "Click in the river where you expect to find the fastest moving water."

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Students in an introductory-level geoscience course

Skills and concepts that students must have mastered

Students need to know where the fastest current will be in a river

How the activity is situated in the course

This activity is used as a formative assessment following a lecture or activity about sediment transport in rivers. Displaying the results after administering the question provides students and instructor immediate feedback about how well students understand velocity and erosion in a river.


Content/concepts goals for this activity

The goals of this activity are:

  1. to evaluate how well students recognize the relationship between velocity and erosion patterns in a meandering river (conceptual goal)
  2. to engage students in predicting where erosion will occur to test their mental models of fluid dynamics (spatial skill)

Higher order thinking skills goals for this activity

Students will make a spatial prediction, receive feedback, and modify their prediction based on the feedback.

Other skills goals for this activity

Not applicable

Description and Teaching Materials

Several student response systems (clickers) offer a response option where you can upload an image and students can respond by clicking directly on the image. The system will generate a heat map of the responses. After teaching students about flow velocity and erosion in meandering rivers through lecture, videos, or an activity, use this question as a low stakes (low/no point-value) evaluation of their understanding. Revealing the results to students will show whether there is general consensus on one answer or more than one answer. For example, in the heat map of students' responses shown here, students' answers are split between the inside of the curve and the outside of the curve, both for the location of fastest water flow and for the location of greatest erosion.

Using a technology-enhanced formative assessment (TEFA) approach, if the pattern of responses lacks consensus, engage the students in peer discussion about the answer (Beatty and Gerace, 2009). Allow students to "revote" for their answer after a brief discussion. If there is not convergence on the scientifically accurate answer, then engage in re-teaching the concept.

Science of Learning: Why It Works

There is accumulating evidence that engaging in spatial prediction and receiving feedback about the nature of one's errors leads to improved spatial reasoning (Gagnier et al. 2017; Resnick et al., 2017). Making a prediction, receiving feedback, and learning from the mismatch between the expected and actual outcomes is a process studied in cognitive science called the delta-rule model of learning (Rescorla and Wagner, 1972). Modern models of learning from the education research literature focuses on Piaget's concept of accommodation, where people will adjust their mental models as a consequence of the the feedback (Dole and Sinatra, 1998). Examples from research on geology concepts show us that students' build more scientifically accurate mental models after engaging in prediction and feedback. Gagnier et al. (2017) engaged students in making predictions about the interior of a geologic structure using block diagrams. The cycle of prediction and feedback facilitated students improved performance on a test of penetrative thinking. Resnick et al. (2017) engaged students in making predictions about the geologic time scale using a classroom response system (clickers). Students answered multiple-choice questions about the position of geologic events on a typical diagram of the geologic time scale. The spatial prediction clicker questions were as effective as, and more efficient than a hands-on meter stick activity at building a scientifically accurate linear conception of geologic time. Building on this research, we propose that the technique described below is a useful approach to identify students' spatial conceptions associated with various geologic phenomena (LaDue and Shipley, 2018).

Teaching Notes and Tips

I use this activity to assess student understanding immediately after lecturing about fluid dynamics and sediment transport in meandering river systems.


This question is useful for students to self-assess where their answer fits relative to other students in the class. Top Hat displays student responses in a heat map image that highlights the most common answers. In most systems it is possible to designate a region for the correct answer, but receiving a right-wrong answer is likely less useful than engaging students in peer discussion if the students' responses do not converge on one region.

References and Resources

Resources: There are several systems that offer click-on-diagram questions. The one we use is:


Beatty, I. D., & Gerace, W. J. (2009). Technology-enhanced formative assessment: A research-based pedagogy for teaching science with classroom response technology. Journal of Science Education and Technology, 18(2), 146-162.

Dole, J. A., & Sinatra, G. M. (1998). Reconceptalizing change in the cognitive construction of knowledge. Educational psychologist, 33(2-3), 109-128.

Gagnier, K. M., Atit, K., Ormand, C. J., & Shipley, T. F. (2017). Comprehending 3D diagrams: Sketching to support spatial reasoning. Topics in cognitive science, 9(4), 883-901.

LaDue, N.D. and Shipley, T.F. (2018). Click-on-Diagram Questions: A New Tool to Study Conceptions using Classroom Response Systems. Journal of Science Education and Technology, 27(6), 492-507.

Rescorla, R. A., & Wagner, A. R. (1972). A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. Classical conditioning II: Current research and theory, 2, 64-99.

Resnick, I., Newcombe, N. S., & Shipley, T. F. (2017). Dealing with big numbers: Representation and understanding of magnitudes outside of human experience. Cognitive science, 41(4), 1020-1041.