On the Development of a Computer-Assisted Testing System With Genetic Test Sheet-Generating Approach

Hwang, Gwo‐Jen; Lin, Bertrand M.T.; Tseng, Hsien-Hao; Lin, Tsung-Liang

doi:10.1109/tsmcc.2004.843184

Cited by 46 publications

(35 citation statements)

References 14 publications

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“…Constraint (4) indicates that the selected test items in each parallel test sheet must have a relevance degree no less than the expected relevance degree to each specified concept. Equations (5) and (6) emphasis that total expected test time of each generated parallel test sheet must be in its specified range.…”

Section: Problem Modelmentioning

confidence: 99%

“…In order to solve the PTSG problem effectively, evolutionary algorithms are attractive option for their simplicity and computational efficiency. Previous investigations have shown that most of the existing test item selection approaches focus on the composition of a single test sheet, such as genetic algorithm [4], particle swarm optimization algorithm [5], and Tabu algorithm [6]. However, little research has been reported about parallel test sheet generation algorithm.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Discrete Fruit Fly Optimization Algorithm for Intelligent Parallel Test sheets Generation

Wang

Dong

et al. 2015

MATEC Web of Conferences

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Section: Problem Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Discrete Fruit Fly Optimization Algorithm for Intelligent Parallel Test sheets Generation

Wang

Dong

et al. 2015

MATEC Web of Conferences

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“…Overall, assessment of UNIX Application Development would have 25 simple, 17 medium and 8 complex questions from various subtopics. One can use genetic algorithms for creating more efficient test sheet generating approaches for large question bank [8]. Scheduling module is responsible for scheduling exam for specific or group of participants.…”

Section: Mitigating Systems and Process Centric Challengesmentioning

confidence: 99%

Developing Effective Online Assessment System for anEnterprise – Multidimensional Strategies for Success

Ghosh¹

2011

IJEEEE

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Abstract-Online assessments are rapidly creating a market space for measuring competency of employees in an enterprise. This unanimously blends with competency development programs. Such programs offer various certifications to assess multi facet skills of an employee. In a flat world, employee workforce is geographically spread in multiple development centers across the world. Designing a common online assessment platform for this workforce makes any competency development program very perplexing. This paper highlights potential adaptability, acquiescence related, location specific, systems and process centric challenges an enterprise can face while creating and running an online assessment system to measure the competency of employees. Anticipated modules and their features imperative to any enterprise online competency assessment system are proposed. Multidimensional strategies to mitigate various challenges are discussed. It also highlights the best practices that an enterprise should follow in order to have a balanced assessment platform. Adoption of recommended mitigation strategies lead to tangible measurable business benefits and had positive impact on customer satisfaction, issue resolution time, number of reported issues and escalations.Index Terms-online assessment, competency development, question bank, authoring manager, assessment rule

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“…Some test assembling systems use random or manual strategy [5,6]. Some experts use methods in machine learning to solve the test sheet generation problem: Tabu search [7], genetic algorithm (GA) [8], particle swarm optimization [9,10], etc.…”

Section: Introductionmentioning

confidence: 99%

An Improved Personalized Genetic Algorithm Incorporated Item Distribution for Test Sheet Assembling

Gu¹,

Niu²,

Chen³

et al. 2014

Appl. Math. Inf. Sci.

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Abstract:In recent years, computer-based testing has become an effective approach to evaluate students' learning level. In our previous work, a personalized genetic algorithm (PGA) for test sheet assembling was proposed. In this paper, an improved personalized genetic algorithm named PGAC which makes an improvement in the crossover process of PGA is presented. Considering item distribution, an improved algorithm incorporated item distribution (IGAID) based on PGAC is presented to assemble simulation test sheets which have good item distribution in knowledge hierarchy for each student. Experiments and comparison with random assembling algorithm and GA are conducted. The results show that PGAC supports effectively assembling a test sheet with more non-mastered items for different students, and IGAID is capable of effectively constructing simulation test sheets with good item distribution in knowledge hierarchy for each student.

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On the Development of a Computer-Assisted Testing System With Genetic Test Sheet-Generating Approach

Cited by 46 publications

References 14 publications

A Novel Discrete Fruit Fly Optimization Algorithm for Intelligent Parallel Test sheets Generation

A Novel Discrete Fruit Fly Optimization Algorithm for Intelligent Parallel Test sheets Generation

Developing Effective Online Assessment System for anEnterprise – Multidimensional Strategies for Success

An Improved Personalized Genetic Algorithm Incorporated Item Distribution for Test Sheet Assembling

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