If at first you do not succeed: student behavior when provided feedforward with multiple trials for online summative assessments

Faulconer, Emily K.; Griffith, John C.; Frank, Hayden

doi:10.1080/13562517.2019.1664454

Cited by 25 publications

(15 citation statements)

References 20 publications

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“…However, they describe mastering “quantitative disciplines” by way of “massive practice” (p. 1), which seems to focus on the how (to solve a specific type of problem) more so than the what/why (relationships between variables and what-if-something-changes type of question) and does not seem to fit what I am doing with my online tests. Faulconer, Griffith, and Frank (2018) also point to the virtues of multiple attempts (although their study used LMS tests that were configured quite differently than mine). They found that second attempts score higher than first attempts (for a given individual student), which I observed with my data as well and is not surprising (what I found that was surprising was that those that attempt twice do not achieve better results than those that attempt once).…”

Section: Discussionmentioning

confidence: 99%

Experiences from a Data-informed Approach to Configuring Online Assignments

Orchard

2019

Journal of Educational Technology Systems

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Learning management systems (LMS) allow for a variety of ways in which online multiple-choice assessments (“tests”) can be configured, including the ability to allow for multiple attempts and options for which of and how the attempts will count. These options are usually chosen according to the instinct of the instructor; however, LMS also provide an opportunity to make data-informed decisions based on data captured by the LMS itself. This article describes an experience with extracting and analyzing LMS data for determining online test option settings that encourage behaviors that promote learning (or discourage behaviors that do not). The data extraction and cleaning process was relatively straightforward, but not without some challenges, and required beyond-novice spreadsheet skills. It seems to have been worth the effort, though, as the insights gained led directly to a change in online test administration, and current option settings seem more appropriate and are supported by data.

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Section: Discussionmentioning

confidence: 99%

Experiences from a Data-informed Approach to Configuring Online Assignments

Orchard

2019

Journal of Educational Technology Systems

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“…Very few of the works focused on the student experience, instead emphasizing learning experiences. They primarily highlighted students' positive reception of features such as immediate grading with the allowance of multiple submissions [55]. Together with this, several works focused on the ability to create custom learnings paths based on student performance [56,26,54,55,56,57,58,59], and the ability to flag students at high risk of not succeeding [51,60,61,62,63,64,62].…”

Section: F Rq3 What Are the Positive Effects On The Student Experience Of Using Automatic Feedback And Automatic Scoring?mentioning

confidence: 99%

A Systematic Review of the Effects of Automatic Scoring and Automatic Feedback in Educational Settings

Hahn

Navarro

de-la-Fuente-Valentín

et al. 2021

IEEE Access

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Automatic scoring and feedback tools have become critical components of online learning proliferation. These tools range from multiple-choice questions to grading essays using machine learning (ML). Learning environments such as massive open online courses (MOOCs) would not be possible without them. The usage of this mechanism has brought many exciting areas of study, from the design of questions to the ML grading tools' precision and accuracy. This paper analyzes the findings of 125 studies published in journals and proceedings between 2016 and 2020 on the usages of automatic scoring and feedback as a learning tool. This analysis gives an overview of the trends, challenges, and open questions in this research area. The results indicate that automatic scoring and feedback have many advantages. The most important benefits include enabling scaling the number of students without adding a proportional number of instructors, improving the student experience by reducing the time between submission grading and feedback, and removing bias in scoring.On the other hand, these technologies have some drawbacks. The main problem is creating a disincentive to develop innovative answers that do not match the expected one or have not been considered when preparing the problem. Another drawback is potentially training the student to answer the question instead of learning the concepts. With this, given the exitance of a correct answer, such an answer could be leaked to the internet, making it easier for students to avoid solving the problem. Overall, each of these drawbacks presents an opportunity to look at ways to improve technologies to use these tools to provide a better learning experience to students.

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“…Recent empirical studies are inconclusive as to the value of multiple attempts, although the tactic is generally viewed as useful. Reasons for lukewarm empirical support of multiple attempts have included students using throwaway attempts or preparing more carefully for one or two attempt assessments (Orchard, 2016;Faulconer et al, 2019). One recent empirical study assesses the ideas that students learn well what they practice, consistent feedback aids their learning, and they value what is assessed (Robbins, 2020).…”

Section: Assessment Of Student Learningmentioning

confidence: 99%

Learning management system‐integrated spreadsheet exercises for facility location modeling

Strakos

Brazhkin

2021

Decision Sci J Innov Edu

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Supply chain management students are introduced to a variety of modeling concepts. Yet learning facility location and capacity allocation modeling to the level of application and mastery proves difficult for the typical undergraduate business student. Spreadsheets facilitate the teaching of optimization modeling; however, providing feedback to students on spreadsheet assignments is an onerous and time-consuming task for instructors. In this teaching brief, a set of learning management system (LMS)-integrated spreadsheet exercises is presented which helps students learn spreadsheet modeling for the capacitated plant location problem. These exercises are also designed to reduce the instructor's grading burden while providing timely feedback and assessment of student performance. The effectiveness of the exercises is demonstrated by assessment data gathered from the LMS as well as postmodule student survey results.

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If at first you do not succeed: student behavior when provided feedforward with multiple trials for online summative assessments

Cited by 25 publications

References 20 publications

Experiences from a Data-informed Approach to Configuring Online Assignments

Experiences from a Data-informed Approach to Configuring Online Assignments

A Systematic Review of the Effects of Automatic Scoring and Automatic Feedback in Educational Settings

Learning management system‐integrated spreadsheet exercises for facility location modeling

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