20–22 Nov 2026
The WINC Aichi
Asia/Tokyo timezone

From Pride to Sadness: Emotions in Extensive Reading

21 Nov 2026, 18:45
30m
The WINC Aichi

The WINC Aichi

Research-oriented Presentation (30-minutes) ER: Extensive Reading Room 1103

Speaker

Haruka Ubukata (Kanda University of International Studies)

Description

This study explored Japanese EFL university students’ emotional experiences in Extensive Reading (ER). Their reading logs, recorded for two semesters, evidenced a wide range of emotions such as pride, desire, surprise, frustration, and sadness, and indicated positive effects of extensive reading beyond language skill development. This presentation introduces primary findings and practical implications for ER implementation in classrooms and beyond.

Abstract section 1: Relevance

While existing literature provides an extensive body of research on ER, its affective dimension remains less investigated (Tanemura, 2020). As emotions play a critical role in language learning (Lou et al., 2025), understanding what emotions students may experience in ER and why can provide valuable insights. Given its dual purpose of developing L2 proficiency and providing authentic reading experience in the target language, ER provides a unique context where learners may navigate a complex spectrum of emotions. The present study aims to contribute to this underexplored area by analyzing Japanese EFL university students’ ER experiences.

Abstract section 3: Content/method

Participants were 16 first-year EFL Japanese university students. I analyzed 192 ER log entries collected over two semesters, in which they described their reading experiences using emojis to represent their emotions. I labeled each entry with specific emotions based on the GoEmotions taxonomy (Demszky et al., 2020), and identified the underlying sources using Pekrun’s (2014) framework of academic emotions. I then conducted a thematic analysis to further explore the data.

Abstract section 5: References

Demszky, D., Movshovitz-Attias, D., Ko, J., Cowen, A., Nemade, G., & Ravi, S. (2020). GoEmotions: A dataset of fine-grained emotions. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 4040–4054. https://doi.org/10.18653/v1/2020.acl-main.372
Lou, N. M., Chaffee, K. E., & Noels, K. A. (2025). Beyond aptitudes and experiences: The unique role of mindsets in emotions in language classrooms. Learning and Individual Differences, 120, 102688. https://doi.org/10.1016/j.lindif.2025.102688
Pekrun, R. (2014). Emotions and learning. International Academy of Education (IAE).
Tanemura, S. (2020). Reading attitude and L2 extensive reading. JACET Journal, 64, 149-169. https://doi.org/10.32234/jacetjournal.64.0_149
Yamashita, H. (2015). Affect and the development of learner autonomy through advising. Studies in Self-Access Learning Journal, 6(1), 62-85.

Abstract section 2: Contribution/research questions

The study investigated the following three research questions.
RQ1: What emotions do students experience in ER?
RQ2: What is the distribution in terms of the four types of academic emotions?
RQ3: What are the sources of those emotions identified in each type?

Abstract section 4: Outcomes/results

Students reported 26 types of emotions, and three of the four types of academic emotions (achievement, topic, and epistemic emotions) emerged. A thematic analysis revealed that those emotions were triggered by various sources associated with the ER practice. Particularly noteworthy was the predominance of positive emotions and their range beyond pleasure, the emotion typically emphasized as the defining emotional characteristic of ER, indicating ER potentially enriching students’ learning experience in ways not commonly highlighted in the literature. Overall, findings provided evidence for the positive effects of ER beyond language skill development.

Title From Pride to Sadness: Emotions in Extensive Reading
Teaching Context College and university education

Author

Haruka Ubukata (Kanda University of International Studies)

Presentation materials

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