Artificial Intelligence Promotes the Evolution of English Writing Evaluation Model

Su, Zheqian; Liu, Miao; Jiang, Man

doi:10.1088/1757-899x/646/1/012029

Cited by 7 publications

(5 citation statements)

References 6 publications

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“…The results showed that AI was an effective intervention for improving positive and decreasing negative emotions in L2 students (Su et al, 2019). AIs provide in-depth analytical assessments and immediate feedback, which can induce a series of emotions in academic settings.…”

Section: Discussionmentioning

confidence: 94%

Application of Artificial Intelligence powered digital writing assistant in higher education: randomized controlled trial

Nazari

Shabbir

Setiawan

2021

Heliyon

163

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A major challenge in educational technology integration is to engage students with different affective characteristics. Also, how technology shapes attitude and learning behavior is still lacking. Findings from educational psychology and learning sciences have gained less traction in research. The present study was conducted to examine the efficacy of a group format of an Artificial Intelligence (AI) powered writing tool for English second postgraduate students in the English academic writing context. In the present study, (N ¼ 120) students were randomly allocated to either the equipped AI (n ¼ 60) or non-equipped AI (NEAI). The results of the parametric test of analyzing of covariance revealed that at post-intervention, students who participated in the AI intervention group demonstrated statistically significant improvement in the scores, of the behavioral engagement (Cohen's d ¼ .75, 95% CI [0.38, 1.12]), of the emotional engagement Cohen's d ¼ .82, 95% CI [0.45, 1.25], of the cognitive engagement, Cohen's d ¼ .39,95% CI [0.04, .76], of the self-efficacy for writing, Cohen's d ¼ .54, 95% CI [0.18, 0.91], of the positive emotions Cohen's d ¼ . 44, 95% CI [0.08, 0.80], and of the negative emotions, Cohen's d ¼ À.98, 95% CI [À1.36, À0.60], compared with NEAI. The results suggest that AI-powered writing tools could be an efficient tool to promote learning behavior and attitudinal technology acceptance through formative feedback and assessment for non-native postgraduate students in English academic writing.

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Section: Discussionmentioning

confidence: 94%

Application of Artificial Intelligence powered digital writing assistant in higher education: randomized controlled trial

Nazari

Shabbir

Setiawan

2021

Heliyon

163

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“…In addition, AI can also take the form of chatbots that facilitate communication, to improve one's language skills [22]. Then, in other studies, the use of AI was shown to improve writing skills and lower the fear of writing [23]. Fear in the use of foreign languages, especially speaking to students can cause student achievement scores in learning to decrease.…”

Section: Discussionmentioning

confidence: 99%

The Use of Ai (Artificial Intelligence) in English Learning Among University Student: Case Study in English Department, Universitas Airlangga

Dewi¹,

Putri²,

Rahim³

et al. 2021

Preprint

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Aim: This research aim is to analyze an artificial intelligence platform that can be used in imparting education as well as evaluating student performance. Method: This research was conducted with a qualitative method by conducting in-depth interviews and a literature study. Results: The findings of this study shows that Artificial Intelligence technology can be used as a means of developing English learning for students. Discussion: There have been several studies that support research results, that AI can be used to improve students' English skills through applications, websites, Virtual Reality technology, and other AI-based learning and teaching systems. Limitation: The limitation of this research is that it does not examine how far the role of AI in students' English learning is. Suggestion: For further research, it is expected to test how far the role of AI is to improve students' English skills, especially Universitas Airlangga students.

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“…Individualized and oral English learning stimulates students' interest in English learning as well as improves the learning atmosphere in English classrooms. This is not only a significant reflection of the value of English teaching and learning in the education industry, but also an in-depth exploration of the value of modern information technology [Su et al 2019].…”

Section: Figure 1: Typical Nlp For Education Research Lifecyclementioning

confidence: 98%

Natural Language Enhancement for English Teaching Using Character-Level Recurrent Neural Network with Back Propagation Neural Network based Classification by Deep Learning Architectures

Yang¹

2022

jucs

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Natural Language Processing (NLP) is an efficient method for enhancing educational outcomes. In educational settings, implementing NLP entails starting the learning process through natural acquisition. English teaching and learning have received increased attention from the relevant education departments as an integral aspect of the new curriculum reform. The environment of English teaching and learning is undergoing extraordinary changes as a result of the constant improvement and extension of teaching level and scale, as well as the growth of Internet information technology. As a result, the current research aims to look into techniques for efficiently using AI (artificial intelligence) apps to teach and learn English from the perspective of university students. This research can measure the levels as well as effectiveness of the employment of AI applications for teaching English based on deep learning techniques. There, the NLP based language enhancement has been carried out using Character-level recurrent neural network with back Propagation neural network (Cha_RNN_BPNN) based classification. With the help of this DL (deep learning) technique, it is possible to use AI methods to assist teachers in analysing and diagnosing students' English learning behaviour, replacing teachers in part to answer students' questions in a timely manner, and automatically grading assignments during the English teaching process. Experimental analysis shows Word Perplexity, Flesch-Kincaid (F-K) Grade Level for Readability, Cosine Similarity for Semantic Coherence, gradient change of NN, validation accuracy, and training accuracy of the proposed technique.

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Artificial Intelligence Promotes the Evolution of English Writing Evaluation Model

Cited by 7 publications

References 6 publications

Application of Artificial Intelligence powered digital writing assistant in higher education: randomized controlled trial

Application of Artificial Intelligence powered digital writing assistant in higher education: randomized controlled trial

The Use of Ai (Artificial Intelligence) in English Learning Among University Student: Case Study in English Department, Universitas Airlangga

Natural Language Enhancement for English Teaching Using Character-Level Recurrent Neural Network with Back Propagation Neural Network based Classification by Deep Learning Architectures

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Artificial Intelligence Promotes the Evolution of English Writing Evaluation Model

Cited by 7 publications

References 6 publications

Application of Artificial Intelligence powered digital writing assistant in higher education: randomized controlled trial

Application of Artificial Intelligence powered digital writing assistant in higher education: randomized controlled trial

The Use of Ai (Artificial Intelligence) in English Learning Among University Student: Case Study in English Department, Universitas Airlangga

Natural Language Enhancement for English Teaching&nbsp;Using Character-Level Recurrent Neural Network with&nbsp;Back Propagation Neural Network based Classification&nbsp;by Deep Learning Architectures

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Natural Language Enhancement for English Teaching Using Character-Level Recurrent Neural Network with Back Propagation Neural Network based Classification by Deep Learning Architectures