The Effects of Personalized Nudges on Cognitively Disengaged Student Behavior in Low-Stakes Assessments

Author:

Arslan Burcu1,Finn Bridgid2

Affiliation:

1. Educational Testing Service Global, Strawinskylaan 929, 1077 XX Amsterdam, The Netherlands

2. Educational Testing Service, Princeton, NJ 08544, USA

Abstract

In educational settings, students rely on metacognitive processes to determine whether or not to exert effort. We investigated ways to minimize cognitively disengaged responses (i.e., not-fully-effortful responses) during a low-stakes mathematics assessment. Initially, we established theory-driven time thresholds for each item to detect such responses. We then administered the test to 800 eighth-graders across three conditions: (a) control (n = 271); (b) instruction (n = 267); and (c) nudge (n = 262). In the instruction condition, students were told to exert their best effort before starting the assessment. In the nudge condition, students were prompted to give their best effort following each first-attempt response that was both incorrect and not-fully-effortful. Therefore, students had multiple opportunities to adjust their level of effort. Nudges, but not effort instruction, significantly reduced students’ not-fully-effortful responses. Neither the nudges nor the effort instruction significantly impacted performance. In a post-test survey, most students reported that they received nudges whenever they did not know the answer (55%). Overall, these findings suggest that while nudges reduce cognitively disengaged responses, most students appear to strategically modulate their level of effort based on self-monitoring their knowledge and response effort.

Funder

Educational Testing Service

Publisher

MDPI AG

Subject

Cognitive Neuroscience,Developmental and Educational Psychology,Education,Experimental and Cognitive Psychology

Reference68 articles.

1. Extending problem-solving procedures through reflection;Anderson;Cognitive Psychology,2014

2. Anderson, John R. (2007). How Can the Human Mind Occur in the Physical Universe?, Oxford University Press.

3. Arslan, Burcu, Lehman, Blair, Sparks, Jesse R., and Steinberg, Jonathan (2021). Application of a theory-driven approach to detect cognitively disengaged test-taker behavior. NERA Conference Proceedings, 3.

4. Fitting linear mixed-effects models using lme4;Bates;Journal of Statistical Software,2015

5. Formative assessment: A critical review;Bennett;Assessment in Education: Principles, Policy & Practice,2011

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3