Kadota (2007) highlights shadowing’s efficacy in enhancing listening skills and aiding in memorization. Although previous studies have explored the impact of material difficulty on the memorization of multiword units (strings of words indicated by prosodic boundaries in the form of intonation and pauses in natural speech), the overall research is still limited. Variability in results suggests material difficulty’s effect depends on learner proficiency. It is necessary to explore the interaction of material difficulty and learner proficiency on the memorization of multiword units by shadowing. Studies have also explored how item length impacts task difficulty, but this effect has not been analyzed in shadowing tasks. Thus, the present study investigated these interactions. Thirty-five Chinese EFL learners conducted shadowing using materials on a nine-level difficulty scale based on Macmillan Graded Readers. The results of the generalized linear mixed model (GLMM) showed that high-level learners showed significant improvements in memorization of multiword units when using more difficult shadowing materials. In contrast, the memorization of multiword units for low-level learners increased at a slower pace as the material difficulty increased. In sum, the disparity between low and high-level learners widened as material difficulty increased. Additionally, it was difficult for learners to memorize long items.

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Since the influence of audiovisual materials on shadowing performance has not yet been studied well, this study compared the effects of two types of materials—auditory texts presented together with either a still or moving image of a face of a speaker who was reading the text aloud—on shadowing reproduction rates and loci of eye-gaze of learners. Twenty-four L1-Japanese learners of English (13 upper-level and 11 lower-level learners) participated in an eye-tracking experiment. In the results, the participants shadowed more accurately for moving images of a speaker’s face than for still images; when the moving images were presented, the lower-proficiency level group gazed at the speaker’s mouth longer than any other region, but the upper-proficiency level group gazed at the eyes and mouth equally longer than the other facial regions. The reproduction rates did not statistically differ between the eyes and mouth in the lower-proficiency group, but the upper-proficiency group exhibited better reproduction rates for the eyes compared to the mouth. On the one hand visual cues, such as movements of mouth and chin of a speaker’s face, help some learners perceive auditorily presented texts, and on the other hand some learners may have difficulty in linking speech sounds and mouth movements during shadowing.

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Laufer and Hulstijn (2001) proposed the involvement load hypothesis (ILH). The ILH assumes that incidental vocabulary learning activities are more effective when the combined involvement load index—need, search, and evaluation—is higher. According to the ILH, activities with identical involvement load indices should yield similar results in learning. The current study investigated this prediction using three activities: composition-level gap filling (CGF), sentence-level gap filling (SGF), and multiplechoice gloss (MCG). As these activities had equivalent involvement load indices, their effects were predicted to be the same. The null hypothesis significance testing merely confirms the absence of differences among the effects of the activities, rather than their equivalence. To address this limitation, this study employed Bayesian estimation. Fiftynine university students were randomly assigned to one of the CGF, SGF, and MCG tasks to learn five low-frequency nouns. Results revealed neither practical differences nor equivalence between the three tasks, showing that other variables, not included in the involvement load index, is influencing incidental vocabulary acquisition.

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With the development and prevalence of machine translators, concerns among English teachers have surfaced regarding their roles and the necessity of English education itself. By examining three prominent communication models by Widowson (1978), Canale (1983) and Bachman (1990), the study seeks to clarify the tendencies seen in machine translators’ translations. It becomes apparent that while certain competencies can indeed be automated, others necessitate human interventions. Consequently, this paper advocates for a strategic shift in English education, emphasizing the indispensable aspects that machine translators cannot replace. More precisely, the result indicates that future English education should focus on nurturing English skills necessary for personal interactions and reinforcing Japanese language abilities, knowledge on conventions of coherence, culture, and the world. Along with these language abilities and knowledge, sensitivity toward the context and language should also be emphasized. This reorientation is crucial for the future of English education to coexist with machine translators.

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In the Courses of Study revised in 1998 and 1999, it was stipulated in junior high schools that "in principle, students should take English as a compulsory subject in foreign languages" (hereinafter referred to as the "English Principle"). In addition, the subjects "German" and "French" were deleted and integrated into "other foreign languages" and "foreign languages other than English" in junior high schools and senior high schools, respectively. This shift, which seemingly prioritized English, faced criticism mainly from advocates of multilingual education. However, the origins of this decision-making process remain unclear. Therefore, this paper clarifies why (1) the English Principle was established in junior high schools and (2) German and French subjects were deleted from junior high and senior high schools, based on the minutes of the Curriculum Council held prior to the revision of the curriculum. We found that (1) the English Principle was adopted as a compromise between those who were in favor of making English compulsory and those who were against it, and (2) the deletion of German and French was made in consideration of the fact that many students study Chinese and the philosophy of familiarizing students with more languages than just German and French.

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Some researchers have demonstrated that retrieval practices can facilitate foreign vocabulary learning. Several have suggested that using example sentences is important for learning vocabulary, and that using various sentences may be particularly useful. However, the effects of sentential contexts on retrieval practice, regarding example sentence availability and quantity, remain unexplored. Therefore, the author investigated how sentential contexts affect intentional vocabulary learning through retrieval practice, specifically focusing on three test formats: form recall, meaning recall, and meaning recognition. For this study, 37 participants undertook a retrieval practice to recall the meanings of target English words. They learned these words under three learning conditions: no context, the same repeated context (1-context), and varied contexts (4- context). They completed three tests for each learning condition. The results revealed that the effects of the sentential contexts varied according to the vocabulary test formats. No differences were observed between the conditions for the form and meaning recall tests; however, there were differences in the meaning recognition test—scores for the 1-context were significantly higher than for the no-context condition. These findings suggest that sentential contexts are more related to vocabulary test formats than the number of example sentences in intentional vocabulary learning.

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Recent advancements in AI, and generative AI in particular, have boosted chatbots’ ability to maintain a conversation. This is especially critical for the field of English language education where chatbots can serve as conversation partners. However, how well can modern chatbots sustain a conversation with learners of English, as compared to the chatbots studied a decade ago? This research focuses on evaluating the linguistic ability of AI chatbots in text-based interactions with 64 Japanese undergraduate students who are non-native English speakers. In particular, the study examines three AI chatbots with different algorithms to find out how effectively these three chatbots can deliver errorfree, contextually appropriate responses even despite errors in users’ messages, and what linguistic challenges English language learners encounter when engaging with chatbots. The study revealed a relatively high response accuracy of AI chatbots towards non-native English speech. However, there was a significant difference in response accuracy among the three AI chatbots due to the nuances in their algorithms, with generative AI chatbot showing the highest response quality among the three. Despite the significant improvement of chatbots’ linguistic ability, the participants still reported instances of confusion and frustration due to occasional inappropriate responses.

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