Sitting arrangement and malpractice behaviours among higher education test-takers: On educational assessment in Africa

doi:10.37074/jalt.2023.6.1.5

Cited by 3 publications

(4 citation statements)

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“…The examiners must also assure the examinees that the test conditions will be satisfactory. There is also a need to minimize cheating using diverse approaches, such as adjusting the sitting arrangements for physically taken tests (Owan et al, 2023) and proctoring electronically taken tests (Owan, 2020;Owan et al, 2019). LLMs can be useful in various ways during test administration to ensure that all students have a fair chance to manifest the desired behavior being measured and to minimize cheating.…”

Section: Test Administrationmentioning

confidence: 99%

Exploring the potential of artificial intelligence tools in educational measurement and assessment

Owan,

Abang,

Idika

et al. 2023

EURASIA J Math Sci Tech Ed

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Artificial intelligence (AI) is transforming various industries, and education is no exception. Rapid advancements in AI technology have become essential for educators and educational assessment professionals to enhance teaching and learning experiences. AI-powered educational assessment tools provide numerous benefits, including improving the accuracy and efficiency of assessments, generating personalized feedback for students, and enabling teachers to adapt their teaching strategies to meet the unique needs of each student. Therefore, AI has the potential to revolutionize the way education is delivered and assessed, ultimately leading to better educational outcomes for students. This paper explores the various applications of AI tools in educational measurement and assessment. Specifically, it discusses the integration of large language AI models in classroom assessment, in specific areas such as test purpose determination and specification, developing, test blueprint, test item generation/development, preparation of test instructions, item assembly/selection, test administration, test scoring, interpretation of test results, test analysis/appraisal, and reporting. It analyses the role of teachers in AI-based assessment and the challenges of using AI-powered tools in educational assessment. Finally, the paper presents strategies to address these challenges and enhance the effectiveness of AI in educational assessment. In conclusion, using AI in educational assessment has benefits and limitations. As such, educators, policymakers, and stakeholders must work together to develop strategies that maximize the benefits of AI in educational assessment while mitigating the associated risks. The application of AI in educational assessment can ultimately transform education, improve learning outcomes, and equip students with the skills needed to succeed in the 21st century.

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Section: Test Administrationmentioning

confidence: 99%

Exploring the potential of artificial intelligence tools in educational measurement and assessment

Owan,

Abang,

Idika

et al. 2023

EURASIA J Math Sci Tech Ed

View full text Add to dashboard Cite

show abstract

“…Students' participation in sharp practices has eaten deeply into the credibility of higher and distance education institutions, contributing to the swelling of their error scores (Owan et al, 2023). According to the Classical Test Theory (CTT), a student's true score can be determined using their observed score (actual score) plus or minus an error score.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, students' indulgence in sharp practices increases the error score while decreasing or skewing the true score (Ekechukwu & Nwamadi, 2017;Joshua, 2019). Thus, misleading judgments can be made on the trait measured Memory & Abosede, 2021;Owan et al, 2023;Owan, 2020) if the error score is not minimized.…”

Section: Introductionmentioning

confidence: 99%

“…Quality assurance committees are now overseeing and enforcing distance institutions' examination policies, as have campaigns to welcome new students and educate them on the importance of avoiding sharp examination practices (Bassey et al, 2019). Additionally, some distance education institutions have banned the idea of having class representatives and adopted the two-week result submission policy (Owan et al, 2023). Furthermore, conference marking strategies have also been used in crossing out and stamping all empty spaces in students' answer booklets before handing them to instructors for scoring (Arop et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distance Education Students’ Indulgence in Six Sharp Practices: General Linear Modelling of Predictive Parameters

OWAN,

CHUKTU,

DIJEH

et al. 2023

TOJDE

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This study examined the degree to which students indulge in six prominent misconducts in Distance Education Institutions (DEIs). The study also quantified how class size, instructional delivery and institutional policies predict students’ indulgence in sharp practices using a general linear modelling approach. A sample of 871 participants was drawn from 1,742 final-year students across two DEIs in Nigeria. A structured questionnaire was used for data collection. The questionnaire had acceptable psychometric estimates of dimensionality, content and construct validity, as well as reliability. Sharp practices such as cheating, plagiarism, falsification, impersonation, and arm-twisting were more prevalent in large classes, whereas only inducement was higher in small classes. Class size influenced students’ indulgence in sharp practices in DEIs. Instructional delivery and institutional policies negatively predicted students’ indulgence in the six sharp practices. Almost all the six sharp practices correlated positively and significantly, except for impersonation and inducement. Therefore, distance education students who cheat, plagiarize, arm-twist, falsify records, induce lecturers, and promote impersonation are more likely to indulge in other forms of sharp practices. It was concluded that large class sizes, poor instructional delivery, and poorly implemented institutional policies promote sharp practices among distance education students. Based on this conclusion, key policy and research implications are discussed.

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Students’ perceptions, attitudes and utilisation of ChatGPT for academic dishonesty: Multigroup analyses via PLS‒SEM

Ofem,

Owan,

Iyam

et al. 2024

Educ Inf Technol

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Sitting arrangement and malpractice behaviours among higher education test-takers: On educational assessment in Africa

Abstract: Jo u r n a l o f A p p l ie d Lea r n in g & T e a c h in g JALT http://journals.sfu.ca/jalt/index.php/jalt/index

Cited by 3 publications

References 51 publications

Exploring the potential of artificial intelligence tools in educational measurement and assessment

Exploring the potential of artificial intelligence tools in educational measurement and assessment

Distance Education Students’ Indulgence in Six Sharp Practices: General Linear Modelling of Predictive Parameters

Students’ perceptions, attitudes and utilisation of ChatGPT for academic dishonesty: Multigroup analyses via PLS‒SEM

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