Abstract:

English learning motivation has traditionally been categorized into intrinsic versus extrinsic motivation (Deci & Ryan, 1985, 2000, 2012, 2014) and integrative versus instrumental motivation (Gardner & Lambert, 1972). While these classifications have provided a foundational framework, recent research suggests that motivation exists on a continuum rather than within rigid categories. This study examines the interplay of these motivational constructs among adult learners at a national open university in Korea, using data visualization techniques to reveal complex interconnections.

A total of 336 undergraduate students from the English Language and Literature department participated in the study. Enrolled in the Spring 2023 "English Conversation II" course, they responded to structured academic assignments reflecting on their English learning motivation (Dörnyei & Ushioda, 2021).

The assignment included three open-ended questions:
(1) “Tell me what’s on your mind about learning English at this Open University,”
(2) “What did you learn through your studies at this Open University?” and
(3) “Is there any special reason for studying English literature?”

Their responses highlighted diverse motivational factors, including obtaining a degree for career advancement, transitioning into English teaching post-retirement, serving the community, and gaining confidence for global travel. These findings suggest that motivations often overlap, challenging traditional binary classifications.

The study combined qualitative content analysis with quantitative network analysis using a mixed-methods approach (Creswell & Plano Clark, 2022). Text preprocessing was conducted using Python (Bird et al., 2022; Kumar & Bhattacharyya, 2023), involved tokenization, stopword removal, and text cleaning. Word frequency counts and co-occurrence relationships were extracted to construct a network model of motivational themes, providing a structured view of how students conceptualize their reasons for learning English.

Gephi was employed as a powerful data visualization tool to explore and interpret motivational patterns in educational research (Bastian et al., 2023; Cherven, 2023). By leveraging Gephi’s interactive and graphical capabilities, this study visually represents the interconnected nature of English learning motivation. Nodes represent word frequencies, while edges capture word-pair relationships, allowing for an intuitive understanding of motivational trends. The network analysis approach demonstrates how motivation extends beyond individual responses, forming a dynamic system of interrelated factors. This approach highlights the potential of Gephi as a valuable tool for educational researchers and instructional technologists, particularly in analyzing complex qualitative data for pedagogical insights.

This study contributes to the evolving discourse on English learning motivation by illustrating its fluid nature. It provides empirical evidence that motivation should not be treated as a fixed dichotomy but as an evolving construct influenced by various personal and professional aspirations. Additionally, it underscores the applicability of Gephi as an innovative instructional technology tool, offering a model for integrating network analysis into educational research to enhance teaching and learning strategies.

Keywords:

English, Motivation, Gephi, Data visualization.