Paul J. Moore (University of Queensland), Jo Mynard, Isra Wongsarnpigoon, and Kie Yamamoto (Kanda University of International Studies)
Moore, P. J., Mynard, J., Wongsarnpigoon, I., & Yamamoto, K. (2019). Autonomy and interdependence in a self-directed learning course. Relay Journal, 2(1), 218-227. https://doi.org/10.37237/relay/020126
*This page reflects the original version of this document. Please see PDF for most recent and updated version.
This paper provides the background to an ongoing study which aims to investigate ways in which Japanese learners of foreign languages make use of online and offline resources during a period of self-directed study. The researchers are currently collecting data from interviews, learning journals, and other documentation produced by ten EFL learners as part of a self-directed learning course at a university in Japan. This paper will give insights into the rationale and researchers’ motivations for the study, some background on the course, the learners, and the institution; a brief review of the relevant literature; and details of the research methods. Findings will be presented in subsequent publications.
Keywords: self-directed learning, social media, EFL, Japanese university
This study investigates the affordances of a self-directed language learning module, including online and offline instructional and interactional resources and spaces, for learners of English-as-a-foreign-language in an international university in Japan. From an ecological perspective, which privileges emic perspectives on the role of learner engagement as mediated by peers and resources in a learning community, we explore the tasks and (physical, human and technological) resources learners choose to focus on, their perspectives on the effectiveness of these tasks and resources in developing language learner autonomy, and their perceptions of the mediating roles of these resources in their learning experience.
Language learner autonomy and interdependence
Autonomy in the context of second and foreign language learning has been defined as “a capacity to take charge of one’s own learning. An autonomous learner can make informed choices which requires a level of awareness and control of learning processes which is achieved through reflection” (SALC Handbook, 2016; cf. Mynard & Stevenson, 2017, p. 171).
Given that language learning and use involve contextualised communication, it is increasingly recognised (e.g., Little & Thorne, 2017) that the development of learner autonomy is not simply an individualistic, but a sociocognitive pursuit, relying on the support of an interdependent community (Benson, 2017; Rourke et al., 2001). Such a perspective has led to calls for holistic ecological approaches to understanding the contextualised affordances of (material and interpersonal) resources for the development of autonomy for language learning (e.g., Palfreyman, 2014; van Lier 2004), particularly recognising the fact that such resources are increasingly mediated by and through technologies, including social media (Cappellini, Lewis, & Mompean, 2017; Levy & Moore, 2018).
Space, time and social presence
Information and communication technologies, including social media, are increasingly influencing language education both inside and outside the classroom, to the extent that definitions of ‘classroom’ itself are blurred between physically and technologically mediated ‘spaces’ (Gruba, Hinkelman, & Cardenos-Claros, 2016). With a strong focus on technologically mediated language learning, Chun, Kern, & Smith (2016) argue that space, time and social presence are qualitatively different in online and face-to-face interactions, and that, as a result, new technologies require community members to negotiate interactional conventions in ways which may be seen as accepted, or static, in face-to-face interactions. Actions and interaction in physical spaces are less likely to be open to interpretation, or requiring negotiation, than those in so-called ‘interface spaces’ – such as text-based chat, email, or Skype. With regard to the notion of time, they argue that speed and delay (of responses, for example) are also negotiated by individuals interacting in online communities.
Finally, social presence has been defined as follows:
The ability of learners to project themselves socially and emotionally in a community of inquiry. The function of this element is to support the cognitive and affective objectives of learning. Social presence supports cognitive objectives through its ability to instigate, sustain and support critical thinking in a community of learners.
(Rourke et al. 2001, p. 51, cited in Mynard, 2017, p. 276).
Social presence in online communication involves both projection of the self, and subjective evaluation of others, each of which is open to negotiation (Kehrwald, 2010).
The complex negotiation of space, time and presence in online interactions, which have become commonplace in language learning both in and out of the classroom, led Chun, Kern and Smith (2016) to propose a research agenda with a major focus on the language learning goals which are set for (and by) learners, the linguistic, cultural and instructional resources available in language learning spaces, and the evaluation of such resources in attaining language learning goals. The current study draws on the perspectives outlined above to explore, from the emic perspective of a community of language learners engaged in a course in learner autonomy, how their face-to-face and online interactions support their autonomous language learning goals, in both ‘real world’ and online spaces, using physical, interpersonal and virtual resources.
RQ1. How do learners choose areas of focus?
RQ2. What resources do they select?
RQ3. With whom do they interact in their learning activities and for what purposes?
RQ4. What evidence is there in their course-based interaction and reflections of a role for social presence/community building in supporting autonomous language learning?
Context of the Study
The study is being conducted in a self-access centre in a small private university in Japan, where students major in languages as well as related programs in international studies. Learning advisors in the self-access centre work alongside staff from languages programs to provide all students with support for developing autonomous learning skills and strategies, including planning and directing their own language learning.
The Effective Language Learning Module (ELM) comprises two 15-week elective credit-bearing self-directed courses, with the following objectives (cf. Curry et al., 2017, p. 22):
- knowing about support and learning opportunities outside class;
- setting and reviewing goals;
- selecting, using, and evaluating resources;
- identifying, using, and evaluating strategies;
- making, implementing, and evaluating a learning plan; and
- evaluating linguistic and learning gains.
The first course involves learner training (‘structured awareness raising’, Kato & Mynard, 2016), which focuses on the following language learning skills and strategies: goal setting and reflection (week 1); learning strategies (week 2); learning resource identification and evaluation (week 3); and development of a formal learning plan, using a ‘study, use, reflect, evaluate (SURE)’ cycle (weeks 4-6). Weeks 7-14 involve students enacting and revising their learning plan, supported by weekly evaluation meetings with their Learning Advisor, and online interaction with their learning advisor and peers, using the collaborative social media tool Moxtra (http://www.moxtra.com). Week 15 culminates in the submission of a final reflective report on the process, including a portfolio of learning plans and activities conducted throughout the semester.
In the second course, learners begin by developing an independent learning plan from the start of the semester, using the skills and strategies learned in the training units of the first module course. This plan is discussed and finalised in a face-to-face meeting with their Learning Advisor—usually the same advisor they worked with in the first course. They then implement their plan for 14 weeks. The longer implementation period provides more opportunities for students to reflect on their learning processes and progress and make more careful revisions to their learning activities based on such reflection. Another major difference is that along with focusing on a language target, in each week of enacting their plan, learners also choose a learning process target (e.g., focusing on time management, motivation, or learning balance). In addition to their weekly online interaction, the learners receive support from their advisors in monthly individual meetings, in which the advisors promote reflection on the previous month’s learning and goal-setting for the upcoming month. Similar to the previous course, the learners complete the module by submitting a final reflective report.
Implementation of an Online Module
Recent research has investigated the enhancement of self-directed learning beyond the physical boundary using technology (e.g., Mynard & Yamamoto, 2018). In the current research context, each student has an iPad and a smartphone and is familiar with mobile apps. Thus, the researchers investigated various social apps, including Facebook, Google Classroom and Moxtra (see Davies, 2015). Moxtra was found to be most suitable for the module for three reasons. First, Moxtra allows both a learner and his/her learning advisor to have an individual virtual space (called a “binder”) where they can upload files, add and share comments on the files, and send instant messages. Second, the multimodal functionality enables a more personalised level of interaction than that afforded by paper-based submission of independent learning plans and journals. Third, like other social apps, Moxtra can be used across devices, enabling learners and advisors to contribute or interact anywhere or at any time. The use of Moxtra thus helps advisors avoid some of the drawbacks of written advising (Kato & Mynard, 2016), such as the inherent delay between when learners submit work and when they receive feedback from their advisor. Through Moxtra, advisors can comment on reflections while they are still fresh in the students’ minds or answer short questions quickly.
Overview of the Methodology
The research follows a qualitative design with a focus on the roles and affordances of a learning community (face-to-face and online) in supporting the decisions and choices learners make in choosing and using language learning resources as part of a course in language learner autonomy. Data from four sources will be triangulated to answer the four research questions in a process which, following Creswell and Plano-Clark (2011), can be termed a qualitative convergent parallel design. Such a design involves concurrent data collection, along with triangulated data analysis. In addition to allowing for data collection over a short period of time, such a design also allows for validation of findings from a range of perspectives (Ivankova & Creswell, 2009).
Data are being collected from ten first and second year students of English as a foreign language (aged 18-21), enrolled in ELM 2 Modules, and their language advisors (LAs). Student participants’ language proficiency will be at the intermediate level (A2 or B1 on the internationally recognised Common European Framework for Languages CEFR).
Recruitment. The population for this study comprises the students studying the Effective Learning Module 2. Approximately 80 students undertake the course per semester, of which ten were invited to participate in the study. These students were selected as they were among the many students using Moxtra for multiple purposes, and agreed to participate. Students were informed of the study, provided with information sheets and the opportunity to ask questions about the study. Principles of informed consent were followed, as per the ethics process approved by the institution.
This study will draw upon five major data sources which are collected as a part of the students’ coursework:
- Weekly learning plans and reflections;
- Audio-recorded reflection meetings between students and learning advisors (all three LAs are co-investigators on the project);
- Final reflective report;
- Transcripts of interaction amongst participants on Moxtra;
- Students’ written evaluations of the affordances of the instructional materials and activities in developing their language learning and autonomous learning skills
In addition, semi-structured interviews will be conducted with student participants throughout the semester.
Document analysis. The use of existing documents reduces the level of obtrusiveness normally associated with data collection. In this study, course documents (learning plans and reflections) will be analysed for evidence of the choices learners make in their learning focus, resources and activities, and the spaces where they conduct their learning activities. They will also be analysed for preliminary data as to the bases of their decisions, and who or what may have influenced their choices.
Analysis of interview data. Interview data will be coded and analysed collaboratively in an iterative process, using NVivo10. Transcripts will be read and re-read independently by two of the researchers before meeting to compare, reach agreement, and develop categories which represent both expected themes and those arising from the data.
Social presence analysis. Conversation threads from participants in the closed Moxtra collaborative network platform will be analysed for social presence, following Mynard’s (2017) analysis (cf. also Rourke et al. 2001). This includes descriptive quantitative and qualitative analyses of posts which display emotion (affective responses), cohesion (cohesive responses) and an interactive stance (interactive responses).
Observations so Far
Data analysis will commence after the completion of data collection in January, 2019. The preliminary insights provided below are based on Learning Advisors’ insights into their experience of the transition from paper-based submission of learning plans to submission and interaction via Moxtra.
We expect that the answers to RQs 1-3 will confirm the findings of previous research, but will also provide a more nuanced understanding of the choices learners make, with regard to selection of learning foci (RQ1), resources, and interactants (RQ2 and RQ3). It is expected that the use of Moxtra will provide interesting findings regarding learners’ perspectives on the increased opportunity for interaction with their learning advisors, the multimodal resources available to them for both submitting their ongoing learning plans, and interacting with their learning advisors. We are particularly interested in learners’ perspectives on whether interaction via Moxtra provides a level of connectedness with their learning advisors (and others), and if so, whether they agree with the research literature that increased connectedness affords more effective language learning experiences.
A logical avenue for further research into the role of social media in language learning advising in this context is to create more opportunities for learners to develop connections with other learners in the program. This study is expected to provide insights into who learners choose to collaborate with, and for what purposes. We envisage drawing on these findings to investigate whether a more systematic approach to fostering the development of social networks among learners can lead learners to develop a more interdependent approach to the development of language learner autonomy.
Notes on the Contributors
Paul J. Moore lectures in and coordinates the Master of Applied Linguistics program in The School of Languages and Cultures, University of Queensland. His research interests include task-based interaction in face-to-face and technologically mediated contexts, intercultural discourse, and the dynamic roles of the L1 in L2 interaction. His research interests include sociocognitive perspectives on task-based interaction in classroom and online contexts, intercultural communication, and the dynamic roles of the L1 in L2 interaction. firstname.lastname@example.org
Jo Mynard is a professor in the English department, Director of the Self-Access learning Center, and Director of the Research Institute of Learner Autonomy Education at Kanda University of International Studies in Japan. Her research interests are advising in language learning and the psychology of language learning.
Isra Wongsarnpigoon is a learning advisor at Kanda University of International Studies. He holds an M.S.Ed from Temple University, Japan Campus. His research interests include learner autonomy, language learner motivation, and L2 vocabulary learning.
Kie Yamamoto is a learning advisor at Kanda University of International Studies. She holds an M.S.Ed from Temple University Japan, and is currently pursuing an Ed.D at the University of Bath in the UK. Her research interests are language learner identity, social learning theory, student engagement, and narrative analysis
Benson, P. (2017). Ways of seeing: The individual and the social in applied linguistics research methodologies. Language Teaching, 1-11. doi: 10.1017/S0261444817000234
Cappellini, M., Lewis, T., & Mompean A. R. (2017)(Eds.), Learner autonomy and web 2.0.. Sheffield: Equinox.
Chun, D., Kern, R., & Smith, B. (2016). Technology in language use, language teaching, and language learning. Modern Language Journal, 100(Supplement 2016), 64–80.
Creswell, J. W., & Plano Clark, V. L. (2011). Designing and conducting mixed methods research (2nd ed.). Thousand Oaks, CA: Sage.
Curry, N., Mynard, J., Noguchi, J., & Watkins, S. (2017). Evaluating a self-directed learning course in a Japanese university. International Journal of Self-Directed Learning, 14(1), 17-36.
Davies, R. (2015, November 22). One app to rule them all: Going paperless with Moxtra [Video file]. Retrieved from https://www.youtube.com/watch?v=yXP-BOrmNSw
Ivankova, N. V., & Creswell, J. W. (2009). Mixed methods. In J. Heigham & R. A. Croker (Eds.), Qualitative research in applied linguistics: A practical introduction. Hampshire: Palgrave Macmillan.
Kato, S., & Mynard, J. (2016). Reflective dialogue: Advising in language learning. New York, NY: Routledge.
Kehrwald, B. (2010). Being online: Social presence and subjectivity in online learning. London Review of Education 8(1), 39–50.
Levy, M. & Moore, P. J. (2018). Qualitative Research in CALL. Language Learning and Technology 22(2), 1-8.
Mynard, J. (2017). Investigating social presence in a social networking environment. In K. Van de Poel & C. Ludwig (Eds.). Collaborative language learning and new media: Insights into an evolving field (pp. 276-293). Frankfurt am Main: Peter Lang.
Mynard, J., & Stevenson, R. (2017). Promoting learner autonomy and self-directed learning: The evolution of a SALC curriculum. Studies in Self-Access Learning, 8(2), 169-182.
Palfreyman,D. (2014). The ecology of learner autonomy. In G. Murray (Ed.), Social dimensions of autonomy in language learning (pp. 175-191). Basingstoke: Palgrave Macmillan.
Rourke, L., Anderson, T., Garrison, R. D., & Archer, W. (2001). Assessing social presence in asynchronous text-based computer conferencing. Journal of Distance Education, 14(3), 51–70.
van Lier, L. (2004). The ecology and semiotics of language learning. A sociocultural perspective. Dordrecht: Klewer.