Innovative Item Types for Computerized Testing

Parshall, Cynthia G.; Davey, Tim; Pashley, Peter J.

doi:10.1007/0-306-47531-6_7

Cited by 73 publications

(53 citation statements)

References 20 publications

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“…Items and tasks like those highlighted above have become the subject of considerable research as testing on computer has become increasingly practical and popular (Clauser, 1995;Haladyna, 1996;Huff & Sireci, 2001;Parshall et al, 2010). A wide assortment of options are therefore now available for using a computer to present information, facilitate interaction, and collect responses in ways not possible with traditional textbased items.…”

Section: As With All Trips We Need To Start By Deciding Whether the mentioning

confidence: 99%

Practical Considerations in Computer-Based Testing

Parshall¹,

Spray²,

Kalohn³

et al. 2002

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167

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Section: As With All Trips We Need To Start By Deciding Whether the mentioning

confidence: 99%

Practical Considerations in Computer-Based Testing

Parshall¹,

Spray²,

Kalohn³

et al. 2002

Self Cite

167

View full text Add to dashboard Cite

“…Research showed that in videoconference interviews candidate ratings and applicant reactions are therefore lower (Chapman,Uggerslev,& 4 These categories represent broad categories and finer distinctions are possible. One such distinction pertains to the medium for conveying the stimuli (Parshall et al, 2000;Potosky, 2008). For instance, textual and pictorial stimuli might be presented via a paper-and-pencil or computerized medium (PC, tablet, smartphone, etc.).…”

Section: Stimulus Formatmentioning

confidence: 99%

“…Here no interpretative leaps are required because an a priori scoring key (determined via empirical keying, theoretical keying, expert keying or a combination of those) is applied for evaluating candidates. Automated scoring is typically done via computer algorithms, which might vary from simple (dichotomous) to complex (e.g., polytomous or partial credit scoring systems where answers are scored on a number of weighted criteria, Parshall et al, 2000). Automated scoring applies not only to ability tests, biodata, personality scales or SJTs, but also to essays and simulations (see Clauser, Kane, & Swanson, 2002).…”

Section: Response Evaluation Consistencymentioning

confidence: 99%

The effects of predictor method factors on selection outcomes: A modular approach to personnel selection procedures.

Lievens¹,

Sackett²

2017

Journal of Applied Psychology

110

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Past reviews and meta-analyses typically conceptualized and examined selection procedures as holistic entities. We draw on the product design literature to propose a modular approach as a complementary perspective to conceptualizing selection procedures. A modular approach means that a product is broken down into its key underlying components. Therefore, we start by presenting a modular framework that identifies the important measurement components of selection procedures. Next, we adopt this modular lens for reviewing the available evidence regarding each of these components in terms of affecting validity, subgroup differences, and applicant perceptions, as well as for identifying new research directions. As a complement to the historical focus on holistic selection procedures, we posit that the theoretical contributions of a modular approach include improved insight into the isolated workings of the different components underlying selection procedures and greater theoretical connectivity among different selection procedures and their literatures. We also outline how organizations can put a modular approach into operation to increase the variety in selection procedures and to enhance the flexibility in designing them. Overall, we believe that a modular perspective on selection procedures will provide the impetus for programmatic and theory-driven research on the different measurement components of selection procedures.

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“…The use of technological enhancements of sound, graphics, animation, video or t h e i n c o r p o r a t i o n o f media can be utilized also for e-learning assessment designs [6]. Figure 1 below shows the summary of the 13 questions types collected from 15 various sources of scientific research and publications and used as guiding tool in designing questionnaires.…”

Section: E-learning Assessment Questionsmentioning

confidence: 99%

Improving Learning Throughput in E-Learning Using Interactive-Cognitive Based Assessment

Ballera¹,

Lukandu

Radwan³

2015

IJEETDM

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An e-learning website is not sufficient to fully attain the results of online education. There also is a need to align the educational objectives into the design of the assessment to improve and develop cognition, critical thinking and problem-solving skills. Previous studies have explored the potentials of the assessment models but few ventured into their implementation. Others only proposed and introduced conceptual frameworks. The implementation of these proposals, however, revealed that the question type in the assessment phase neglected to align their questionnaire formats into a cognitive schema. At present, the standard multiple-choice question is the most frequently used of the question type of e-learning assessments. However, if this type is the only format adopted by e-learning developers, then the potentially rich and embedded assessment of the computer platform will be given up. This paper focuses on the design of assessment questions, which is created and guided by the hierarchical Bloom cognitive taxonomy and by utilizing rich media formats. Results conducted for eighteen weeks show a dramatic increase in the academic performance of the students. Likewise, digital transcripts converted from the collected perceptions after training undergoes sentiment analysis have correlated with the student improved academic throughput.

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Innovative Item Types for Computerized Testing

Cited by 73 publications

References 20 publications

Practical Considerations in Computer-Based Testing

Practical Considerations in Computer-Based Testing

The effects of predictor method factors on selection outcomes: A modular approach to personnel selection procedures.

Improving Learning Throughput in E-Learning Using Interactive-Cognitive Based Assessment

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