Multimedia Adaptive Computer based Testing: An Overview

Basu, Anup; Cheng, Irene; Prasad, Manoj; Rao, G. Madhukar

doi:10.1109/icme.2007.4285034

Cited by 12 publications

(9 citation statements)

References 22 publications

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“…ISSN 1822-7864 Adaptability is the ability to "tailor the difficulty level of each question based on the correctness of the previously answered question" (Basu, �heng, Prasad, & Rao, 2007). Adaptive techniques were developed for local systems before the advent of WWW (Barra, Iannaccone, Palmieri, & Scarano, 2002).…”

Section: Computer Based Testing and Computer Adaptive Testsmentioning

confidence: 99%

“…• �an significantly reduce the number of questions (even for 50%) (�heng, Rodrigez, & Basu, 2009), • Are student friendly, and • Not less precise than non-adaptive tests (Basu, �heng, Prasad, & Rao, 2007) (�hua Abdullah & �ooley, 2002). Their main disadvantage is that questions paths are modeled with probabilistic functions (Guzmán & �onejo, 2005).…”

Section: Computer Based Testing and Computer Adaptive Testsmentioning

confidence: 99%

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Smart E-Testing: Future Trend of E-Learning or Gentle Deviation

Krašna

Bratina

Kaučič

2012

PEC

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A decade of experience with e-learning material production gives significant trends overview. From the perspective of ICT evolution this means very long time. E-learning is always closely coupled to ICT but with the distinction - it always lags behind the advancement in ICT. Among many unknown issues one thing is certain – e-learning permanently changes. From the past experiences prediction of immediate future e-learning is possible but the prediction for longer time is less accurate. In the article chronological e-learning achievements and their connections are presented in order to give an overview of trends in e-learning in Slovenia. But despite of the detailed past knowledge fundamental prediction error of e-learning future developments was made. Today's hot topics are not better e-learning materials, not even broad application of interactive boards but e-testing. Possible immediate future of e-learning is therefore application of intelligent e-testing systems. Intelligent computer assisted testing (CAT) is not the new topic in e-learning. It is object of many researches but it is not suitable for teachers. It is way too complicated for teachers to apply it successfully in their work. E-learning development process for intelligent computer assisted test production that suits teachers' competences is prepared and explained in the article. Key words: distance education, electronic testing, learning management system, knowledge assessment.

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Section: Computer Based Testing and Computer Adaptive Testsmentioning

confidence: 99%

Section: Computer Based Testing and Computer Adaptive Testsmentioning

confidence: 99%

Smart E-Testing: Future Trend of E-Learning or Gentle Deviation

Krašna

Bratina

Kaučič

2012

PEC

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show abstract

“…The increasing use of computers for both formative and summative testing has many advantages. Computers provide for example an excellent medium to include different representations (e.g., videos, text, and pictures) and response formats (e.g., drag-and-drop questions, interactive questions) in tests (see Basu et al, 2007 for an overview ;Mayer, 2014aMayer, , 2019. This makes computer-based tests (CBT) more engaging, effective, and entertaining as compared to paper-based tests (Azabdaftari & Mozaheb, 2012;Başoğlu & Akdemir, 2010;Basu et al, 2007;Chua & Don, 2013;Kaplan-Rakowski, & Loranc-Paszylk, 2017) and increases student motivation (Lin & Yu, 2017).…”

Section: Introductionmentioning

confidence: 99%

Designing computer-based tests: design guidelines from multimedia learning studied with eye tracking

Dirkx

Skuballa

Manastirean-Zijlstra³

et al. 2021

Instr Sci

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The use of computer-based tests (CBTs), for both formative and summative purposes, has greatly increased over the past years. One major advantage of CBTs is the easy integration of multimedia. It is unclear, though, how to design such CBT environments with multimedia. The purpose of the current study was to examine whether guidelines for designing multimedia instruction based on the Cognitive Load Theory (CLT) and Cognitive Theory of Multimedia Learning (CTML) will yield similar effects in CBT. In a within-subject design, thirty-three vocational students completed a computer-based arithmetic exam, in which half of the items were presented in an original design format, and the other half was redesigned based on the CTML principles for instructional design (i.e., adapted format). Results showed that applying CTML principles to a CBT decreased the difficulty of the test items, i.e., students scored significantly higher on the adapted test items. Moreover, eye-tracking data showed that the adapted items required less visual search and increased attention for the question and answer. Finally, cognitive load, measured as silent pauses during a secondary think-aloud task, decreased. Mean fixation duration (a different indicator of cognitive load), however, did not significantly differ between adapted and original items. These results indicate that applying multimedia principles to CBTs can be beneficial. It seems to prevent cognitive overload and helps students to focus on important parts of the test items (e.g., the question), leading to better test results.

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“…Takođe, adaptivni testovi daju bolji kvalitet merenja u odnosu na klasične testove za željeni nivo sposobnosti [165]. U radu [13] takođe se analiziraju prednosti računarskih adaptivnih testova.…”

Section: Računarski Adaptivni Testoviunclassified

“…Za svaki odgovor koji ispitanik da, matematička funkcija koju predstavlja jednačina koristi se za procenjivanje nivoa znanja ispitanika. Kako 3PL model zahteva poznavanje parametara a, b i c, podaci o vrednostima ovih parematara čuvaju se u bazi pitanja zajedno sa samim pitanjem [13]. Za pitanja bez istorijskih podataka, inicijalna vrednost parametra težine pitanja b, definisana je na osnovu procene stručnjaka i kretala se od -3 (najmanja vrednost) do +3 (najveda vrednost).…”

Section: Primer Testaunclassified

Computer Adaptive Tests in Evaluation of Knowledge of C++ and Java Programming Languages

Maravić-Čisar¹

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Multimedia Adaptive Computer based Testing: An Overview

Cited by 12 publications

References 22 publications

Smart E-Testing: Future Trend of E-Learning or Gentle Deviation

Smart E-Testing: Future Trend of E-Learning or Gentle Deviation

Designing computer-based tests: design guidelines from multimedia learning studied with eye tracking

Computer Adaptive Tests in Evaluation of Knowledge of C++ and Java Programming Languages

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