Alpine Glaciers

Nicole LaDue, Northern Illinois University

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Summary

Formative assessment questions using a classroom response system ("clickers") can be used to reveal students' spatial understanding. Students are shown this diagram and told to "If more melting occurs than snowfall, click where you expect to find the front of the glacier next year."

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Learning Goals

Content/concepts goals for this activity

The goals of this activity are:

  • to engage students in predicting how far an alpine glacier will recede based on the diagram (spatial skill)
  • to evaluate whether students understand how alpine glaciers recede (content 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.

Context for Use

Audience

Students in an introductory-level geoscience course.

Skills and concepts that students must have mastered

Students should know how alpine glaciers recede based on the given diagram information.

How the activity is situated in the course

This activity is used as a formative assessment question following a lecture or activity about alpine glaciers. Displaying the results after administering the question provides students and instructor immediate feedback about how well students can visualize how changes in snowfall would effect glacier extent.

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 alpine glaciers through lecture, videos, or an activity, use this question as a low stakes (low/no point-value) evaluation of their understanding of glacial extent. 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 generally in an acceptable location below the snow line, but above the melt line.

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 here is a useful approach to identify students' spatial conceptions associated with various geologic phenomena (LaDue et al., 2021; LaDue and Shipley, 2018).

Teaching Notes and Tips

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 & 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.

Assessment

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 used is: https://tophat.com

References

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., Ackerman, J. R., Blaum, D., & Shipley, T. F. (2021). Assessing Water Literacy: Undergraduate Student Conceptions of Groundwater and Surface Water Flow. Water, 13(5), 622.

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.