A learning progression should address regression: Insights from developing non‐linear reasoning in ecology

Abstract

Although ecological systems at varying scales involve non‐linear interactions, learners insist thinking in a linear fashion when they deal with ecological phenomena. The overall objective of the present contribution was to propose a hypothetical learning progression for developing non‐linear reasoning in prey–predator systems and to provide empirical evidence for one part of this progression. Pre‐service teachers followed three teaching units that involved a game simulation of the prey–predator system. Participants predicted how wolf and deer populations would evolve in a hypothetical forest, and then they used the simulation to generate data, construct a graph, describe their graph, and compare their predictions with graph description. A new learning context was introduced and new predictions were requested to investigate whether participants would transfer former learning experiences in the new setting. Analysis of learning products revealed the “messy” character of learners' intermediate steps. Some participants succeeded in identifying aspects of metamodeling knowledge, but this was not used in their new predictions. Graph description could either perpetuate or challenge linear heuristics depending on the strategy participants followed. There were a number of participants who misrepresented prey and predator population trends as “inversely proportional,” which indicated that there is a possibility of regression to the lower anchor. Linearity and proportionality might have re‐surfaced during the learning activity sequence and linear heuristics could have been so powerful as to distract learners' attention from axes labels. Learning products constructed by learners during learning activities included crucial benchmarks to diagnose learner performance and indicated proper timing for feedback provision. Overall, the implications of the study highlight the importance of using learning products to enact formative assessment. Directions for future research are discussed. © 2016 Wiley Periodicals, Inc. J Res Sci Teach 53: 1447–1470, 2016

Toward coherence in curriculum, instruction, and assessment: A review of learning progression literature

“…">6.Understanding simple food chains (Allen, ) 7.Developing nonlinear reasoning in ecology (Hovardas, ) 8.Complex reasoning about biodiversity (Gotwals & Songer, , ; Songer et al, )…”

Qualitative graphing in an authentic inquiry context: How construction and critique help middle school students to reason about cancer

“…Because they make such misunderstandings visible within an inquiry context, graph construction and critique activities can be opportunities for formative assessment, as teachers may use these to diagnose and guide students' thinking about the relationship between the graph and its conceptual meaning (cf. Hovardas, ). In further work, we might explore how misunderstandings apparent in students' graphing artifacts might relate to their conceptual understanding of the science.…”

Model-Based Inquiry in Computer-Supported Learning Environments: The Case of Go-Lab

“…Models and model-based inquiry have been a primary teaching and research focus in science education during the last three decades (Clement 2000;Gobert and Buckley 2000;Louca and Zacharia, 2008, 2015Hovardas 2016). Models are understood as scientific representations of systems or phenomena, which allow for tracing and monitoring the interrelations and interactions among the structural components that compose the system or the phenomenon at hand (e.g., McComas 2002;Matthews 2005).…”

“…Although a substantial number of formative assessment formats have been using a wide array of instruments to diagnose student performance, such as multiple-choice items, data collection by means of these instruments would necessitate allocation of additional time for data analysis, and this would endanger the proper timing of teacher feedback. Using learning products for the purpose of enacting formative assessment would shorten considerably the time frame from diagnosis of student performance to provision of teacher feedback (for more details, in this direction, see Hovardas 2016). Future research might shed more light on how much and what kind of feedback provision might be undertaken by computer-supported learning environments without the direct involvement of the teacher.…”