Optimizing testing feedback in introductory chemistry: a multi-treatment study exploring varying levels of assessment feedback and subsequent performance

计算机科学 化学
作者
Kristen L. Murphy,David G. Schreurs,Melonie A. Teichert,Cynthia J. Luxford,Jaclyn M. Trate,Jordan T. Harshmann,Jamie L. Schneider
出处
期刊:Chemistry Education. Research and Practice [The Royal Society of Chemistry]
标识
DOI:10.1039/d4rp00077c
摘要

Providing students with feedback on their performance is a critical part of enhancing student learning in chemistry and is often integrated into homework assignments, quizzes, and exams. However, not all feedback is created equal, and the type of feedback the student receives can dramatically alter the utility of the feedback to reinforce correct processes and assist in correcting incorrect processes. This work seeks to establish a ranking of how eleven different types of testing feedback affected student retention or growth in performance on multiple-choice general chemistry questions. These feedback methods ranged from simple noncorrective feedback to more complex and engaging elaborative feedback. A test-retest model was used with a one-week gap between the initial test and following test in general chemistry I. Data collection took place at multiple institutions over multiple years. Data analysis used four distinct grading schemes to estimate student performance. These grading schemes included dichotomous scoring, two polytomous scoring techniques, and the use of item response theory to estimate students’ true score. Data were modeled using hierarchical linear modeling which was set up to control for any differences in initial abilities and to determine the growth in performance associated with each treatment. Results indicated that when delayed elaborative feedback was paired with students being asked to recall/rework the problem, the largest student growth was observed. To dive deeper into student growth, both the differences in specific content-area improvement and the ability levels of students who improved the most were analyzed.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
felix发布了新的文献求助10
刚刚
菜菜发布了新的文献求助10
刚刚
1秒前
1秒前
1秒前
1秒前
1秒前
1秒前
胡图图发布了新的文献求助10
1秒前
完美的听芹完成签到,获得积分10
1秒前
种地一代完成签到,获得积分10
1秒前
大个应助haowang1135采纳,获得10
1秒前
2秒前
3秒前
3秒前
科研通AI6应助hjhhjh采纳,获得10
3秒前
Tmac发布了新的文献求助10
3秒前
米米发布了新的文献求助10
3秒前
Alicia完成签到,获得积分10
3秒前
smottom应助lucky燕子采纳,获得10
4秒前
4秒前
宇宙拿铁发布了新的文献求助10
4秒前
4秒前
4秒前
百事可乐发布了新的文献求助10
5秒前
5秒前
5秒前
我是小张发布了新的文献求助10
5秒前
Something发布了新的文献求助10
5秒前
陶醉凝丝发布了新的文献求助10
5秒前
fighting完成签到,获得积分10
6秒前
刘璇发布了新的文献求助10
6秒前
kangkang发布了新的文献求助30
6秒前
悠悠发布了新的文献求助10
7秒前
suodeheng完成签到,获得积分20
7秒前
7秒前
量子星尘发布了新的文献求助10
7秒前
7秒前
WANGYUANLE发布了新的文献求助10
8秒前
生动秋蝶发布了新的文献求助10
8秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Binary Alloy Phase Diagrams, 2nd Edition 8000
Encyclopedia of Reproduction Third Edition 3000
Comprehensive Methanol Science Production, Applications, and Emerging Technologies 2000
From Victimization to Aggression 1000
Exosomes Pipeline Insight, 2025 500
Red Book: 2024–2027 Report of the Committee on Infectious Diseases 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5648073
求助须知:如何正确求助?哪些是违规求助? 4774828
关于积分的说明 15042676
捐赠科研通 4807153
什么是DOI,文献DOI怎么找? 2570560
邀请新用户注册赠送积分活动 1527333
关于科研通互助平台的介绍 1486398