Massive Development of E-Testing Questions

Ristov, Sasko; Gušev, Marjan; Armenski, Goce

doi:10.3991/ijet.v10i4.4688

Cited by 5 publications

(4 citation statements)

References 14 publications

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“…Seixas et al (2015) and Smith (2017) short answer and multiple-choice exams lacked instruments that evaluated students' skills at a low level. These tests helped students to memorize factual knowledge and not deeper reasoning (Gusev et al, 2017;Leber et al, 2018;Mingo et al, 2018;Ristov et al, 2015). Historical thinking skills helped students to reason profoundly about historical events in establishing a full historical narrative.…”

Section: Discussionmentioning

confidence: 99%

The Development of Historical Thinking Assessment to Examine Students’ Skills in Analyzing the Causality of Historical Events

Aman¹,

Aman²,

Zahra³

et al. 2022

EUROPEAN J ED RES

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<p style="text-align: justify;">This research aimed to develop a historical thinking assessment for students' skills in analyzing the causality of historical events. The development process of Gall and colleagues and Rasch analysis models were used to develop an assessment instrument consisting of two processes, including the analysis of the framework of cause and consequence, the validity, reliability, and difficultness test. This research involved 150 senior high school students, with data collected using the validation sheet, tests, and scoring rubric. The results were in the form of an essay test consisting of six indicators of analyzing cause and consequence. The instruments were valid, reliable, and suitable for assessing students’ skills in analyzing the causality of historical events. The developed instruments were paired with a historical thinking skills assessment to improve the accuracy of the information about students' level of historical thinking skills in the learning history.</p>

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Section: Discussionmentioning

confidence: 99%

The Development of Historical Thinking Assessment to Examine Students’ Skills in Analyzing the Causality of Historical Events

Aman¹,

Aman²,

Zahra³

et al. 2022

EUROPEAN J ED RES

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“…The preparation of the database is a tough and a time-consuming task. [25] Afterwards, the structure of the test is defined and stored in the database (Activity B). The prepared test structure is used for the generation of different versions of tests for each student in the next step (Activity C).…”

Section: Software Solution Architecturementioning

confidence: 99%

“…Preparation of knowledge base that can be used to assess the students' outcomes properly is a tough and time-consuming task that requires an extensive amount of resources [25]. E-assessment with automated scoring, in comparison to traditional assessment with written tests, enables to move the teacher's attention to assessment preparation and the evaluation of results.…”

Section: Introductionmentioning

confidence: 99%

Software Solution Improving Productivity and Quality for Big Volume Students' Group Assessment Process

Mišút

Mišútová

2017

Int. J. Emerg. Technol. Learn.

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The key difference between testing a small and a larger group of students is typically the impossibility to use an e-assessment interface for a very large group of students in one room, especially in mathematics courses. Traditional testing causes overloading of the teacher when evaluating students´ results, and delay in releasing of the results. Moreover, the detailed results and test content are not directly stored in the database for further evaluation, which is a condition for optimization of learning environment. To overcome these problems, new teaching model along with method of assessment with enhanced software support was designed. Experimental data collected during three experimental academic years were compared to traditional assessment data to evaluate the efficiency of the proposed solutions. Results have proved that the overall productivity was significantly increased – more than eleven times without compromising quality. Internal dependencies among parameters of the automated assessment procedure were identified, analyzed and used to maximizing the impact of automation, as well.

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“…In this case, a typical AQG system would struggle to generate a comprehensive QA dataset by ignoring tabular data. AQG also offers great value in computer-aided assessments [37,38], allowing the instructors to generator a plethora of questions from existing materials such as presentations and documents.…”

Section: Introductionmentioning

confidence: 99%

Answer-Aware Question Generation from Tabular and Textual Data using T5

Pandraju¹,

Mahalingam

2021

Int. J. Emerg. Technol. Learn.

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Automatic Question Generation (AQG) systems are applied in a myriad of domains to generate questions from sources such as documents, images, knowledge graphs to name a few. With the rising interest in such AQG systems, it is equally important to recognize structured data like tables while generating questions from documents. In this paper, we propose a single model architecture for question generation from tables along with text using “Text-to-Text Transfer Transformer” (T5) - a fully end-to-end model which does not rely on any intermediate planning steps, delexicalization, or copy mechanisms. We also present our systematic approach in modifying the ToTTo dataset, release the augmented dataset as TabQGen along with the scores achieved using T5 as a baseline to aid further research.

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Massive Development of E-Testing Questions

Cited by 5 publications

References 14 publications

The Development of Historical Thinking Assessment to Examine Students’ Skills in Analyzing the Causality of Historical Events

The Development of Historical Thinking Assessment to Examine Students’ Skills in Analyzing the Causality of Historical Events

Software Solution Improving Productivity and Quality for Big Volume Students' Group Assessment Process

Answer-Aware Question Generation from Tabular and Textual Data using T5

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