Lecturers' perspectives on the use of a mathematics-based computer-aided assessment system

Broughton, Stephen; Robinson, Carol; Hernandez‐Martinez, Paul

doi:10.1093/teamat/hrt008

Cited by 14 publications

(9 citation statements)

References 8 publications

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“…E-assessment is a crucial aspect of online education. Some of its benefits include its fast scoring and cheap administration (Broughton et al, 2013;Rupp & Leighton, 2016;Smith, 2019). There is a bank of questions that instructors can utilize to compile their assessment, therefore saving them time.…”

Section: Benefits Of E-assessmentmentioning

confidence: 99%

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The COVID-19 Pandemic and the Challenges of E-Assessment of Calculus Courses in Higher Education: A Case Study in Saudi Arabia

Azmi

Khoshaim

2021

IJLTER

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The COVID-19 pandemic has affected many aspects of our lives, including education. Due to this unexpected catastrophe, education has shifted to virtual-learning and auto-grading models in most parts of the world. This study explores the validity and appropriateness of auto-grading-assessment for online exams by comparing students’ online exam scores where they are first auto-graded and then manually graded. Furthermore, it investigates whether the mean differences in their scores are statistically significant. The study included two calculus courses taught by the authors, during the spring semester 2019-2020 at a private university in Saudi Arabia. The online exam was performed on the WebAssign platform, which has built-in calculus questions. The sample consisted of fifty-five students who were registered on those calculus courses. The quantitative data was analysed using the SPSS statistical tool. A paired t-test at an alpha level of 0.05 was performed on differences in mean exam scores between auto-graded and manually-graded scores. The statistical analysis results revealed a statistically significant difference in students' mean scores. Our findings illustrate the importance of human intelligence, its role in assessing students' achievements and understanding of mathematical concepts, and the extent to which instructors can currently rely on auto-grading. A careful manual investigation of auto-graded exams revealed different types of mistakes committed by students. Those mistakes were characterized into two categories: non-mathematical mistakes (related to Platform Design) and minor mathematical mistakes, which might deserve partial credit. The study indicated a need to reform the auto-grading system and provided some suggestions to overcome its setbacks.

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Section: Benefits Of E-assessmentmentioning

confidence: 99%

“…Technology undoubtedly brings innovative tools and opportunities to the education field (Broughton et al, 2013;Parshall & Guille, 2015). It can support educators to teach and help students to learn (Raja & Nagasubramani, 2018).…”

Section: Introductionmentioning

confidence: 99%

The COVID-19 Pandemic and the Challenges of E-Assessment of Calculus Courses in Higher Education: A Case Study in Saudi Arabia

Azmi

Khoshaim

2021

IJLTER

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“…Although e-assessment with individualisation may act to reduce academic misconduct, it carries with it certain limitations. Random selection may offer limited range of questions (Broughton, Robinson and Hernandez-Martinez, 2013) and writing questions using random generation is difficult, requiring expertise unlike the setting of paper tests (Greenhow, 2015;Sangwin, 2015). The challenge is technical, because of the need to understand the minutiae of how an automated marking system will handle a response (Sangwin, 2007), and pedagogic, because this requires much clearer specification of what is assumed and tested along with knowledge of typical student mistakes (Greenhow, 2015).…”

Section: Summative Assessment: Validity Reliability and Efficiencymentioning

confidence: 99%

Partially-automated individualized assessment of higher education mathematics

Rowlett

2020

International Journal of Mathematical Education in Science and

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A partially-automated method of assessment is proposed, in which automated question setting is used to generate individualised versions of a coursework assignment, which is completed by students and marked by hand. This is designed to be (a) comparable to a traditional written coursework assignment in validity, in that complex and open-ended tasks can be set with diverse submission formats that would not be suitable for written examination or automated marking; and, (b) comparable to e-assessment in terms of reduction of academic misconduct, with individualisation acting as a barrier to copying and collusion.This method of assessment is implemented in practice. Evaluation focuses on expert second-marking, student feedback and analysis of marks, and aims to establish that the partially-automated method can be useful in practice. The partially-automated method proposed appears to be capable of adapting a coursework assignment to make it less sensitive to copying and collusion (and therefore more reliable) while maintaining its validity, though leading to reduced efficiency for the marker. This paper therefore contributes the introduction of a novel approach to assessment which offers a way to bring automated individualisation to the assessment of higher order skills in higher education mathematics.

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“…Table 2 shows the ten settings along with those articles that were selected for further investigation. [66], [67] 9 assessment AND feedback AND mathematic* 180 results -3 selected [68], [69], [70] 10 assessment AND feedback AND audio 26 results -5 selected [71], [72], [73], [74], [75] 3…”

Section: Taxonomy Evaluation: Selecting Settingsmentioning

confidence: 99%

Classifying and Evaluating Assessment Feedback Practices

Palmer-Brown¹,

Cai²,

Patel³

2016

ICERI2016 Proceedings

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The provision of assessment feedback to students is an area which has received much interest in modern education, particularly in the Higher Education context. As current pedagogic practices strongly encourage the provision of feedback and given also the advances in digital technology, feedback mechanisms are becoming ever more sophisticated. However, considering that a great deal of effort is expended on timely, actionable and constructive feedback by tutors, the student perception of the value of the feedback given to them is not as positive as it could be. Currently a multitude of feedback practices have been developed and utilised, though with varying degrees of productiveness. Research in this area is understandably extremely broad as subject disciplines, use of technology, assessment types, methods and tools, educator preferences, student audience and peer and self-assessment capability all have a significant part to play. Given that the approaches to providing feedback are myriad, it is desirable to advance a systematic method of understanding the most constructive feedback types. This paper describes the development of a taxonomical classification which provides structure, order and frame to current popular practices that have evolved during the last decade. The taxonomy is then evaluated with the use of dimensions such as effectiveness/impact, satisfaction, adoption/engagement and quantity of feedback. The main finding of the taxonomical evaluation is the significance of developmental feed-forward guidance with which students are able to self-regulate and evaluate themselves. The paper concludes that this powerful combination should underpin further investigations into how assessment and feedback provision can be optimised for the experiential learning domain in general and to the work-based learning area in particular.

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Lecturers' perspectives on the use of a mathematics-based computer-aided assessment system

Cited by 14 publications

References 8 publications

The COVID-19 Pandemic and the Challenges of E-Assessment of Calculus Courses in Higher Education: A Case Study in Saudi Arabia

The COVID-19 Pandemic and the Challenges of E-Assessment of Calculus Courses in Higher Education: A Case Study in Saudi Arabia

Partially-automated individualized assessment of higher education mathematics

Classifying and Evaluating Assessment Feedback Practices

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