skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Attention:

The NSF Public Access Repository (PAR) system and access will be unavailable from 10:00 PM ET on Friday, February 6 until 10:00 AM ET on Saturday, February 7 due to maintenance. We apologize for the inconvenience.


Title: When and why framing effects are neither errors nor mistakes
Abstract Framing effects play a central role in the debate regarding human rationality. They violate the normative principle ofdescription invariance, which states that merely redescribing options or outcomes in equivalent ways should not affect judgments or decisions. Description invariance is considered by many decision researchers to be “normatively unassailable”, and violations are widely regarded as demonstrations of systematic irrationality. This article develops an alternative perspective on invariance violations, applying Funder’s (1987) distinction between “errors” and “mistakes”. Description invariance implicitly assumes that (1) rational preferences must be complete and (2) frames do not convey choice-relevant information. We argue that both assumptions often do not hold. When they fail, framing effects in the laboratory are not “errors”, and they do not provide evidence for “mistakes” in natural environments. Furthermore, recent findings suggest that participants often do not regard different responses to different frames as unreasonable, and presenting them with arguments for and against description invariance has little effect on their views. Finally, we argue that similar lessons generalize to other coherence norms, such as procedure invariance and independence of irrelevant alternatives.  more » « less
Award ID(s):
2049935
PAR ID:
10656992
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Springer
Date Published:
Journal Name:
Mind & Society
Volume:
24
Issue:
2
ISSN:
1593-7879
Page Range / eLocation ID:
209 to 229
Subject(s) / Keyword(s):
Framing effects Description invariance Rationality Incomplete preferences Information leakage
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract BackgroundIn college science laboratory and discussion sections, student-centered active learning strategies have been implemented to improve student learning outcomes and experiences. Research has shown that active learning activities can increase student anxiety if students fear that they could be negatively evaluated by their peers. Error framing (i.e., to frame errors as natural and beneficial to learning) is proposed in the literature as a pedagogical tool to reduce student anxiety. However, little research empirically explores how an instructor can operationalize error framing and how error framing is perceived by undergraduate students. To bridge the gap in the literature, we conducted a two-stage study that involved science graduate teaching assistants (GTAs) and undergraduate students. In stage one, we introduced cold calling (i.e., calling on non-volunteering students) and error framing to 12 chemistry and 11 physics GTAs. Cold calling can increase student participation but may increase student anxiety. Error framing has the potential to mitigate student anxiety when paired with cold calling. GTAs were then tasked to rehearse cold calling paired with error framing in a mixed-reality classroom simulator. We identified GTA statements that aligned with the definition of error framing. In stage two, we selected a few example GTA error framing statements and interviewed 13 undergraduate students about their perception of those statements. ResultsIn the simulator, all the GTAs rehearsed cold calling multiple times while only a few GTAs made error framing statements. A thematic analysis of GTAs’ error framing statements identified ways of error indication (i.e., explicit and implicit) and framing (i.e., natural, beneficial, and positive acknowledgement). Undergraduate student interviews revealed specific framing and tone that are perceived as increasing or decreasing student comfort in participating in classroom discourse. Both undergraduate students and some GTAs expressed negative opinions toward responses that explicitly indicate student mistakes. Undergraduate students’ perspectives also suggest that error framing should be implemented differently depending on whether errors have already occurred. ConclusionError framing is challenging for science GTAs to implement. GTAs’ operationalizations of error framing in the simulator and undergraduate students’ perceptions contribute to defining and operationalizing error framing for instructional practice. To increase undergraduate student comfort in science classroom discourse, GTAs can use implicit error indication. In response to students’ incorrect answers, GTAs can positively frame students’ specific ideas rather than discussing broadly how errors are natural or beneficial. 
    more » « less
  2. The normative principle of description invariance presupposes that rational preferences must be complete. The completeness axiom is normatively dubious, however, and its rejection opens the door to rational framing effects. In this commentary, we suggest that Bermúdez’s insightful challenge to the standard normative view of framing can be clarified and extended by situating it within a broader critique of completeness. 
    more » « less
  3. Abstract Overparenting—taking over and completing developmentally appropriate tasks for children—is pervasive and hurts children's motivation. Can overparenting in early childhood be reduced by simply framing tasks as learning opportunities? In Study 1 (N = 77; 62% female; 74% White; collected 4/2022), US parents of 4‐to‐5‐year‐olds reported taking over less on tasks they perceived as greater learning opportunities, which was most often the case on academic tasks. Studies 2 and 3 (N = 140; 67% female; 52% White; collected 7/2022–9/2023) showed that framing the everyday, non‐academic task of getting dressed as a learning opportunity—whether big or small—reduced parents' taking over by nearly half (r = −.39). These findings suggest that highlighting learning opportunities helps parents give children more autonomy. 
    more » « less
  4. Image classifiers have become an important component of today’s software, from consumer and business applications to safety-critical domains. The advent of Deep Neural Networks (DNNs) is the key catalyst behind such wide-spread success. However, wide adoption comes with serious concerns about the robustness of software systems dependent on image classification DNNs, as several severe erroneous behaviors have been reported under sensitive and critical circumstances. We argue that developers need to rigorously test their software’s image classifiers and delay deployment until acceptable. We present an approach to testing image classifier robustness based on class property violations. We have found that many of the reported erroneous cases in popular DNN image classifiers occur because the trained models confuse one class with another or show biases towards some classes over others. These bugs usually violate some class properties of one or more of those classes. Most DNN testing techniques focus on per-image violations and thus fail to detect such class-level confusions or biases. We developed a testing approach to automatically detect class-based confusion and bias errors in DNN-driven image classification software. We evaluated our implementation, DeepInspect, on several popular image classifiers with precision up to 100% (avg. 72.6%) for confusion errors, and up to 84.3% (avg. 66.8%) for bias errors. DeepInspect found hundreds of classification mistakes in widely-used models, many of which expose errors indicating confusion or bias. 
    more » « less
  5. Abstract BackgroundMetacognitive processes have been linked to the development of conceptual knowledge in STEM courses, but previous work has centered on the regulatory aspects of metacognition. PurposeWe interrogated the relationship between epistemic metacognition and conceptual knowledge in engineering statics courses across six universities by asking students a difficult concept question with concurrent reflection prompts that elicited their metacognitive thinking. MethodWe used a mixed‐methods design containing an embedded phase followed by an explanatory phase. This design allowed us to both prompt and measure student epistemic metacognition within the learning context. The embedded phase consisted of quantitative and qualitative analyses of student responses. The explanatory phase consisted of an analysis of six instructor interviews. ResultsAnalysis of 267 student responses showed greater variation in students' epistemic metacognition than in their ability to answer correctly. Students used different kinds of epistemic metacognitive resources about the nature and origin of knowledge, epistemological forms, epistemological activities, and stances toward knowledge. These resources generally assembled into one of two frames: aconstructed knowledge framingvaluing conceptual knowledge and sense‐making, and anauthoritative knowledge framingforegrounding numerical, algorithmic problem‐solving. All six instructors interviewed described resources that align with both frames, and none explicitly considered student epistemic metacognition. ConclusionsInstructors' explicit attention to epistemic metacognition can potentially shift students to more productive frames for engineering learning. Findings here also inform two broader issues in STEM instruction: student resistance to active learning, and the direct instruction versus inquiry‐based learning debate. 
    more » « less