Using computer-based technology to improve feedback to staff and students on MCQ assessments

Malau‐Aduli, Bunmi S.; Assenheimer, Dwight; Choi-Lundberg, DL; Zimitat, Craig

doi:10.1080/14703297.2013.796711

Cited by 17 publications

(6 citation statements)

References 18 publications

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“…Evaluating the quality of questions has attracted significant interest in educational research. Standard metrics from classical test theory and item response theory, such as discrimination indices, have been used for decades to aid instructors in identifying poor quality questions (Brown et al 2021;Malau-Aduli et al 2014). However, computing such quantitative measures requires large quantities of data on student responses to items.…”

Section: Related Workmentioning

confidence: 99%

DeepQR: Neural-Based Quality Ratings for Learnersourced Multiple-Choice Questions

Qiming

et al. 2022

AAAI

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Automated question quality rating (AQQR) aims to evaluate question quality through computational means, thereby addressing emerging challenges in online learnersourced question repositories. Existing methods for AQQR rely solely on explicitly-defined criteria such as readability and word count, while not fully utilising the power of state-of-the-art deep-learning techniques. We propose DeepQR, a novel neural-network model for AQQR that is trained using multiple-choice-question (MCQ) datasets collected from PeerWise, a widely-used learnersourcing platform. Along with designing DeepQR, we investigate models based on explicitly-defined features, or semantic features, or both. We also introduce a self-attention mechanism to capture semantic correlations between MCQ components, and a contrastive-learning approach to acquire question representations using quality ratings. Extensive experiments on datasets collected from eight university-level courses illustrate that DeepQR has superior performance over six comparative models.

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Section: Related Workmentioning

confidence: 99%

DeepQR: Neural-Based Quality Ratings for Learnersourced Multiple-Choice Questions

Qiming

et al. 2022

AAAI

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“…Butcher and Hoosen (2014) stated, "fundamental judgments about quality should not depend on whether education is provided in a traditional or post-traditional manner" He pointed that quality assurance of distance education should be similar to general education assurance in higher education. Bunmi S. et al (2014) indicated in their study entitled, Using Computer-based technology to improve feedback to staff and students on MCQ that students' responses, showed satisfaction of MCQ in terms of time comprehension revision, while teaching staff is satisfied with the efficient provision of automatic feedback about students' learning progress, which leads to quality assurance and support students learning.…”

Section: Literature Reviewmentioning

confidence: 99%

The Challenges of Online English Language Teaching From EFL Instructors’ Point of View in KKU, Tehama Campus During COVID 19 Period

Hamad

Dafaallah

Alhaj

2021

jltr

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Spreading of COVID 19 in the whole world affected all fields of life in general and education in specific; this study aims at finding out the challenges of online teaching from EFL instructors' point of view at KKU/ Tehama campus during the COVID 19 period in the field of 1- Quality of teaching.2 Students' interaction. 3- Results of Authentic learning outcome. 4- Instructors’ planning and correction load 5- Macro and Micro skills. A questionnaire is used to collect the data from instructors who work in Tehama. The researchers used the descriptive-analytical approach. Data were analyzed using SPSS. The finding of this study reflected many challenges of online teaching from Instructors perspectives, such as the difficulty of reflecting desired learning outcomes due to multiple attempts and students cheating, which results in high marks in grading, interaction problems between instructors and students, multi-tasks that are added to instructors burden beside many other challenges that affect EFL teaching.

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“…Teaching, research, and administrative workloads put pressure on the time available for course improvement . Many staff who are involved in designing, running, and administering laboratory teaching practicals have numerous demands on their time as they may also be active researchers and have additional school‐level and university‐level administrative duties.…”

Section: Presentation Of Datamentioning

confidence: 99%

Grade distribution digests: A novel tool to enhance teaching and student learning in laboratory practicals

Arthur

Zareie

Kirkwood

et al. 2017

Biochem Molecular Bio Educ

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Assessment is a central component of course curriculums and is used to certify student learning, but it can also be used as a tool to improve teaching and learning. Many laboratory courses are structured such that there is only a grade for a particular laboratory, which limits the insights that can be gained in student learning. We developed a laboratory program that incorporates assessments designed to probe student understanding of different components of the individual modules making up the program. The challenge was to analyze and present grades from these assessment tasks in a format that was readily interpretable by academics. We show that a simplified synthesis of grade distributions (grade distribution digests) provides sufficient information to make decisions about changes in course components. The main feature of the digests is its data visualization approach, where student grades for individual laboratory practicals, individual assessment tasks or individual assessment items are graphically presented as an overall average grade, an average top quartile grade and an average bottom quartile grade, and relative averages across all assessments. This ability to visualize student grades in variety of contexts enables academics with many other demands on their time (e.g. research and administration) to more efficiently identify ways to improve teaching delivery and learning outcomes. Examples are presented of the use of such data to identify and improve deficiencies in both student skills and teaching practice, resulting in improved learning outcomes. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(2):130-140, 2018.

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Using computer-based technology to improve feedback to staff and students on MCQ assessments

Cited by 17 publications

References 18 publications

DeepQR: Neural-Based Quality Ratings for Learnersourced Multiple-Choice Questions

DeepQR: Neural-Based Quality Ratings for Learnersourced Multiple-Choice Questions

The Challenges of Online English Language Teaching From EFL Instructors’ Point of View in KKU, Tehama Campus During COVID 19 Period

Grade distribution digests: A novel tool to enhance teaching and student learning in laboratory practicals

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