Exploring Students' Views in the Use of Quizizz as an Assessment Tool in English as a Foreign Language (EFL) Class

Zuhriyah, Siti; Pratolo, Bambang Widi

doi:10.13189/ujer.2020.081132

Cited by 52 publications

(66 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Following closely was another online quiz, Quizizz (62.5%). This is in line with recent studies, in which Quizizz were used for assessment in education (Zuhriyah & Pratolo, 2020;Rahayu & Purnawarman, 2019;Darmawan, Daeni & Listiaji, 2020;Junior, 2020;Amalia, 2020). YouTube (62.5%) was also equally preferred because teachers could assign YouTube videos as learning materials that can be assessed any time as long as the students were given the links.…”

Section: Preferred Online Toolssupporting

confidence: 85%

TESL Teachers’ Online Teaching during COVID-19: Preferences of Online Tools and Factors Affecting Behavioural Intention

Ting

Aziz

2021

MJSSH

View full text Add to dashboard Cite

The use of online tools has become more prominent as the global lockdown of education institutions in order to slow the spread of the novel coronavirus pandemic (COVID-19). Teachers all over the world resorted to continue the teaching and learning process online using different online tools. In this study, the preferred online tools, and the relationship between the factors of TESL teachers’ use of online tools and their behavioural intention are investigated. A survey was conducted on 56 Malaysian TESL teachers using purposive sampling technique. The data were collected through online survey questionnaires assigned using Google Forms. The findings showed the top 3 major online tools used by TESL teachers were WhatsApp (80.4%), Google Form (71.4%), while Quizizz and YouTube both achieved a 62.5% among the 56 respondents. Regression analysis showed that Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Condition were positive predictors of teachers’ Behavioural Intention to use online tools, with Effort Expectancy being the factor that affects Behavioural Intention the most. Since the findings pointed out that Effort Expectancy was the main factor that influences teachers’ online teaching and learning experience, the ministry of education and online tools developers should ensure the online tools are user friendly to reduce teachers’ burden and hence, encouraging the use of online tools.

show abstract

Section: Preferred Online Toolssupporting

confidence: 85%

TESL Teachers’ Online Teaching during COVID-19: Preferences of Online Tools and Factors Affecting Behavioural Intention

Ting

Aziz

2021

MJSSH

View full text Add to dashboard Cite

show abstract

“…There is another similar study conducted by (Zuhriyah & Pratolo, 2020). The study was about "Exploring Students' Views on the Use of Quizizz as an Assessment Tool in English as a Foreign Language."…”

Section: Introductionmentioning

confidence: 82%

Quizizz as Distance Learning Tool: Effects and Students' Opinion

2021

View full text Add to dashboard Cite

The purposes of this study are: (1) To determine the effect of using Quizizz as a distance learning tool, and (2) To determine students' opinions of Quizizz as a distance learning tool. The participants of this study consisted of an English teacher and thirty-one eleventh-grade students. The data used in this study are in the form of interview results, description of students’ final grades, and the result of questionnaire. The method used is a mixed-method – qualitative and quantitative, with three instruments: Likert Scale questionnaire, interview, and students’ final score. The main findings of this study are: (1) Positive effects in increasing students’ learning motivation, competitiveness, and academic achievement in grammar and reading when using Quizizz as a distance learning tool, and (2) Students’ positive opinions towards Quizizz’s interesting appearance, challenging features, and their enjoy feelings while using Quizizz as distance learning tool.

show abstract

“…As shown in Figure 4, the model introduces an attention mechanism in each convolutional block in addition to the stacking method of convolution in VGG networks; the idea is to make the model pay more attention to the important information while ignoring the unimportant information. The attention mechanism is added because, in convolutional networks, image information is often compressed by pooling to reduce the number of operations and improve the accuracy, but such a direct way of merging information can easily lead to key information not being recognized [20]. Since the subjective judgment of the results is mainly based on the observation of image details and image quality and its standard is greatly affected by the observer's state, it is not used.…”

Section: Advances In Mathematical Physicsmentioning

confidence: 99%

A Three-Dimensional Anisotropic Diffusion Equation-Based Video Recognition Model for Classroom Concentration Evaluation in English Language Teaching

Liu

2021

Advances in Mathematical Physics

View full text Add to dashboard Cite

In this paper, a three-dimensional anisotropic diffusion equation is used to conduct an in-depth study and analysis of students’ concentration in video recognition in English teaching classrooms. A multifeature fusion face live detection method based on diffusion model extracts Diffusion Kernel (DK) features and depth features from diffusion-processed face images, respectively. DK features provide a nonlinear description of the correlation between successive face images and express face image sequences in the temporal dimension; depth features are extracted by a pretrained depth neural network model that can express the complex nonlinear mapping relationships of images and reflect the more abstract implicit information inside face images. To improve the effectiveness of the face image features, the extracted DK features and depth features are fused using a multicore learning method to obtain the best combination and the corresponding weights. The two features complement each other, and the fused features are more discriminative, which provides a strong basis for the live determination of face images. Experiments show that the method has excellent performance and can effectively discriminate the live nature of faces in images and resist forged face attacks. Based on the above face detection and expression recognition algorithms, the classroom concentration analysis system based on expression recognition is designed to achieve real-time acquisition and processing of classroom images, complete student classroom attendance records using face detection and face recognition methods, and analyze students’ concentration from the face integrity and facial expression of students facing the blackboard by combining face detection and expression recognition to visualize and display students’ classroom data for teachers, students, and parents with more data support and help.

show abstract

Exploring Students' Views in the Use of Quizizz as an Assessment Tool in English as a Foreign Language (EFL) Class

Cited by 52 publications

References 19 publications

TESL Teachers’ Online Teaching during COVID-19: Preferences of Online Tools and Factors Affecting Behavioural Intention

TESL Teachers’ Online Teaching during COVID-19: Preferences of Online Tools and Factors Affecting Behavioural Intention

Quizizz as Distance Learning Tool: Effects and Students' Opinion

A Three-Dimensional Anisotropic Diffusion Equation-Based Video Recognition Model for Classroom Concentration Evaluation in English Language Teaching

Contact Info

Product

Resources

About