A person-centred approach to L2 learners’ informal mobile language learning

Peng, Hongying; Jager, Sake; Lowie, Wander

doi:10.1080/09588221.2020.1868532

Cited by 25 publications

(21 citation statements)

References 31 publications

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“…The measure of the items was scored on a six-point Likert scale, with 1 indicating strongly disagree or not at all and 6 referring to strongly agree or very much. The questionnaire had been piloted and successfully applied in Peng et al (2020). It consisted of two parts: Part I collected participants' background information such as gender, educational level, and language proficiency (NCEE score).…”

Section: Methodsmentioning

confidence: 99%

Dynamics of Language Learning Motivation and Emotions: A Parallel-Process Growth Mixture Modeling Approach

Peng²,

Lowie³

2022

Front. Psychol.

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The present study adopted a novel parallel-process growth mixture modeling (GMM) technique to research the adaptive interaction between foreign language learners’ learning motivation and emotions, with a view to advancing our understanding of how language learning motivation and emotions (enjoyment and anxiety) adaptively interact with each other over time. The present study, situated in the Chinese English as a foreign language (EFL) learning context, collected learning motivation and emotion data from 176 Chinese EFL learners over a period of two semesters (12 months). The GMM technique adopted in the study identified three developmental profiles of motivation and two of emotions, respectively. The study further distilled salient patterns of motivation–emotion interaction over time, patterns significant for designing and implementing pedagogical interventions for motivation enhancement. The parallel-process GMM technique was also proven to be a useful approach to parsing learner variety and learning heterogeneity, efficiently summarizing the complex, dynamic processes of motivation and emotion development.

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Section: Methodsmentioning

confidence: 99%

Dynamics of Language Learning Motivation and Emotions: A Parallel-Process Growth Mixture Modeling Approach

Peng²,

Lowie³

2022

Front. Psychol.

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“…Bernardo and Santos (2021) further emphasized the importance of guiding students to acquire mobile technology-supported up-to-date knowledge for promoting students' learning outcomes. Additionally, Peng et al (2020) pointed out the need to engage students in making reflections via interacting in social contexts during the exercising process, which echoes the social constructivism theory (Bozkurt, 2017).…”

Section: Mobile Technology-facilitated Higher Order Thinkingmentioning

confidence: 90%

“…Additionally, Peng et al. ( 2020 ) pointed out the need to engage students in making reflections via interacting in social contexts during the exercising process, which echoes the social constructivism theory (Bozkurt, 2017 ).…”

Section: Literature Reviewmentioning

confidence: 99%

An MDRE approach to promoting students' learning performances in the era of the pandemic: A quasi‐experimental design

Hwang

Yang

Chou

et al. 2022

Brit J Educational Tech

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Educators have indicated the need to foster students' ability to solve problems by acquiring up‐to‐date knowledge as well as promoting their competences for making decisions from diverse perspectives based on the acquired knowledge. Traditional courses mainly use lecture‐based instruction without providing sufficient opportunities for students to practice and interact with the teacher; therefore, it is difficult to deliver such up‐to‐date knowledge via traditional instruction, not to mention fostering students' critical thinking. In this study, the Mobile technology–supported Decision, Reflection and Exercise (MDRE) model is proposed to address this problem. Moreover, a learning system is developed based on the proposed approach. To evaluate the effectiveness of the proposed approach, a quasi‐experiment was conducted in a university with a two‐group pretest posttest design to assess participants' learning achievement, critical thinking and learning satisfaction. The participants were two classes of undergraduate students. One class with 37 students was the experimental group learning with the MDRE learning approach, whereas the other class with 37 students was the control group learning with the conventional technology‐based learning approach. Analysis of covariance was performed to evaluate the effect of the intervention on the target outcomes. It was found that the experimental group showed better learning achievement, critical thinking and learning satisfaction than the control group. This implies that the MDRE approach has good potential in helping learners think from diverse perspectives and promoting their learning performance and engagement, which is important in higher education aimed at fostering students' competence of acquiring up‐to‐date knowledge for solving problems. Practitioner notes What is already known about this topic Fostering students' problem‐solving competence is an important educational objective. The advancement of mobile and wireless communication technologies provides opportunities for students to acquire up‐to‐date information for solving problems. In the conventional technology‐enhanced professional learning mode, instructors generally use computers to present learning content and exemplary cases. In such a learning mode, learners have few opportunities to think in depth. What this paper adds A Mobile technology–supported Decision, Reflection and Exercise (MDRE) approach is proposed to guide students to make decisions and think from diverse perspectives via acquiring up‐to‐date information using a mobile application. An experiment was conducted to show the effectiveness of the proposed approach. The experimental results showed that the MDRE approach is able to boost students' creative thinking tendency and learning satisfaction as well as promoting their lear...

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“…Burstein et al [14]; Ortega [15]; Bridgeman and Ramineni [16]; Ranalli et al [17]; Godwin-Jones [18]; Hibert [19] Hussein et al [20]; Warschauer et al [21]; Saricaoglu [22]; Link et al [23]; Peng et al [24]; Palermo and Wilson [25] Nunes et al [26]; Camacho et al [27]; Godwin-Jones [28]; Huang and Wilson [29]; Ranalli [30] Automated writing corrective feedback (AWCF) tools (text editors supplying synchronous feedback)…”

Section: Automated Writing Evaluationmentioning

confidence: 99%

AI in the Foreign Language Classroom: A Pedagogical Overview of Automated Writing Assistance Tools

Alharbi

2023

Education Research International

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Recent technological advances in artificial intelligence (AI) have paved the way for improved and in many cases the creation of entirely new and innovative, electronic writing tools. These writing support systems assist during and after the writing process making them indispensable to many writers in general and to students in particular who can get human-like sentence completion suggestions and text generation. Although the wide adoption of these tools by students has been faced with a steady growth of scientific publications in the field, the results of these studies are often contradictory and their validity may be questioned. To gain a deeper understanding of the validity of AI-powered writing assistance tools, we conducted a systematic review of the recent empirical AI-powered writing assistance studies. The purpose of this review is twofold. First, we wanted to explore the recent scholarly publications that evaluated the use of AI-powered writing assistance tools in the classroom in terms of their types, uses, limits, and potential for improving students’ writing skills. Second, the review also sought to explore the perceptions of educators and researchers about learners’ use of AI-powered writing tools and review their recommendations on how to best ingrate these tools into the contemporary and future classroom. Using the Scopus research database, a total of 104 peer-reviewed papers were identified and analyzed. The findings indicate that students are increasingly using a variety of AI-powered writing assistance tools for improving their writing. The tools they are using can be categorized into four main groups: (1) automated writing evaluation tools, (2) tools that provide automated writing corrective feedback, (3) AI-powered machine translators, and (4) GPT-3 automatic text generators. The analysis also highlighted the scholars’ recommendations regarding dealing with learners’ use of AI-powered writing assistance tools and grouped the recommendations into two groups for researchers and educators.

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A person-centred approach to L2 learners’ informal mobile language learning

Cited by 25 publications

References 31 publications

Dynamics of Language Learning Motivation and Emotions: A Parallel-Process Growth Mixture Modeling Approach

Dynamics of Language Learning Motivation and Emotions: A Parallel-Process Growth Mixture Modeling Approach

An MDRE approach to promoting students' learning performances in the era of the pandemic: A quasi‐experimental design

AI in the Foreign Language Classroom: A Pedagogical Overview of Automated Writing Assistance Tools

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