Explicating the influences that explain intention to use technology among English teachers in China

Teo, Timothy; Huang, Fang; Hoi, Cathy Ka Weng

doi:10.1080/10494820.2017.1341940

Cited by 169 publications

(172 citation statements)

References 68 publications

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“…While this study adds to knowledge pertaining to the dynamic relationships between EFL motivational factors and students' feedback experience and preference, a number of limitations need to be acknowledged. First, this study relied on the use of self-reported data, which might have resulted in the common method variance, a situation that might have inflated the true associations between variables (Teo et al, 2017). Future observational qualitative classroom-based research is needed to complement the statistical evidence reported here so as to provide a more detailed understanding of the associations between motivational factors and students' feedback experience.…”

Section: What May Characterize Chinese University Efl Students' Feedbmentioning

confidence: 99%

How Learning Motivation Influences Feedback Experience and Preference in Chinese University EFL Students

Gan¹

2020

Front. Psychol.

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Drawing on the argument that students' different learning behaviors, including their perceptions of and engagement with feedback, could have roots in learners' fundamental motivational characteristics, this study examines how different second language learning motivational variables may predict university EFL (English as a foreign language) students' feedback experience and preference. Data were collected from EFL students from three universities in an Asian region (N = 409) through three self-report questionnaires. Results of structural equation modeling (SEM) revealed that different components of the second language learning motivational construct appear to display differential associations with EFL students' feedback experience and preference. In particular, this study brought to light the crucial role of attitudes to classroom English learning and intended learning effort as essential mediating motivational variables in predicting how EFL students conceive of and act on feedback. The findings of this study also provide significant insights into a complex and dynamic view of how student preference for different types of feedback actually works in the feedback process. The authors conclude by arguing that EFL teachers need to shoulder the burden of making the EFL classroom a supportive environment that promotes a positive self-concept and self-confidence as the first step toward stimulating students' active feedback use, and that conditions need to be created to allow for connection of students' preference for learning process-oriented feedback to action to maximize the pivotal role that students play in the classroom and learning process.

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Section: What May Characterize Chinese University Efl Students' Feedbmentioning

confidence: 99%

How Learning Motivation Influences Feedback Experience and Preference in Chinese University EFL Students

Gan¹

2020

Front. Psychol.

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“…Although the attitudes of teachers and pre-service teachers play an important role in the incorporation of ICT in their classes, few studies examine attitudes in affective, cognitive and behavioral dimensions. Different sub-dimensions of attitudes, such as attitudes towards the general use of ICT (Hernández-Ramos et al, 2014, Blackwell, Lauricella & Wartella, 2014, attitudes towards the educational use of ICT (Baş, Kubiatko & Sünbül, 2016) and attitudes towards the ease of use of ICT have been investigated (Scherer et al, 2018, Teo, Huang & Hoi, 2018.…”

Section: Attitudes In Pre-service Teachersmentioning

confidence: 99%

Diagnosis of the attitudes towards ICT of education students according to gender and educational modality

Guillén‐Gámez

Martínez

Camacho

2020

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“…As we have mentioned this construct was formulated as part of the TPB and it measures the perception of the individual of the social pressure towards the performance of a behavior. SN is a widely used construct in investigations on the technology acceptance process of teachers with good results [68][69][70] and it is included on both TAM2 and TAM3 as antecedent of PU and BI. Considering the current social debate on the use of AI, this construct will play an important role on the acceptance of these resources by the teachers.…”

Section: Subjective Normmentioning

confidence: 99%

How to Measure Teachers' Acceptance of AI-driven Assessment in eLearning

Prieto

Cruz-Benito

Therón

et al. 2019

Proceedings of the Seventh International Conference on Technological Ecosystems for Enhancing Multiculturality

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The use of AI is becoming a growing reality the educational field. One of the activities in which it is beginning to be implemented is the assessment of student achievement. This way, we can find in the literature an increasing number of investigations focused on the possibilities offered by the adoption of AI-driven assessment. However, the use of AI is also a source of concern that raises suspicions in some sectors of our society. In this context, knowing the position of the teachers towards this topic is critical to guarantee the successful development of the field. This paper intends to fill a research gap in the literature by offering a technology adoption model based on TAM to study the factors that condition the use of AI-driven assessment among teachers. To present this model we offer a background on the use of AI in education and the technology acceptance among teachers, as well as the definition of the eight constructs and the relational hypotheses included. Finally, the possibilities of the model and future lines of research are discussed.

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Explicating the influences that explain intention to use technology among English teachers in China

Cited by 169 publications

References 68 publications

How Learning Motivation Influences Feedback Experience and Preference in Chinese University EFL Students

How Learning Motivation Influences Feedback Experience and Preference in Chinese University EFL Students

Diagnosis of the attitudes towards ICT of education students according to gender and educational modality

How to Measure Teachers' Acceptance of AI-driven Assessment in eLearning

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