At the nexus of learning and innovation

Making sense of Learning Analytics in English as a Second Language

Here is a short offering on my endeavours in the recent past...PhD wise that is.

Under the supervision of Prof. Peter Reimann, my research is investigating current practices and sense making of student data presented as Learning Analytics Visualisations (LAV) in the teaching of English as a Second Language (ESL). Existing knowledge of data use in this context will be advanced by examining and tracking teacher learning. This will be achieved by observing teachers’ ability to interpret, engage with and make sense of student data via the concept of expansive learning trajectories (Barab, Hay & Yamagata-Lynch, 1999; Cobb, 1996) in correlation with descriptive frameworks measuring the interplay of ESL pedagogy, technology, and the sense making process.

Widely discussed in the literature is the current and potential influence of digital technology in mainstream education. Opportunities now exist to enhance the teaching and learning experience through an expansive data trail generated by digital device users. In language instruction, the development of Computer Assisted Language Learning (CALL) as a field of research is indicative of this. At an institutional level, the collection and analysis of data is referred to as Academic Analytics, and through learning and teaching spaces, Learning Analytics. There has been however, recognition of inefficiencies within educational institutions to capitalize on such opportunities due to delays in executive action, intransigent institutional processes or an absence of proficiency in practical analytics applications (Siemens & Long, 2011).

Teachers are increasingly required to be capable of bridging the gap between traditional pedagogical approaches and the multimodality of the contemporary classroom, and pressure is increasing in pre-service teacher education to respond to this demand. There is an emergent need to prepare forthcoming generations of teachers who are able to deliver a more diverse and engaging teaching experience through new pedagogical practice, using student data to evaluate, differentiate and plan (Jacobs  2009). What then may we ask of those teachers currently engaged in the education of the masses?

A lack of research exists at the practitioner level into practical analytics applications. Through Design Based Research, the study will assist in addressing this paucity by investigating current data practices, and how teachers make sense of Learning Analytics in ESL. Teachers will engage with and make sense of student learning data in a collaborative workshop environment.  Using both quantitative and qualitative methods, this study will characterise the current use of student data, examine and gauge the emergent collaborative sense making process, observe the effect on pedagogical decisions, and measure the data-use learning trajectories of these in-service ESL practitioners. The objective is to obtain data which will assist in informing professional development in Learning Analytics literacy for ESL; elaborating the way in which levels of proficiency may be identified, measured and developed to increase student learning outcomes in digitally integrated teaching and learning spaces.


Barab, S., Hay, K., & Yamagata-Lynch, L. (1999). Constructing Networks of Activity: An In-Situ Research Methodology. Paper presented at the Annual Meeting of the American Educational Research Association (Montreal, Quebec, Canada, April 19-23).

Cobb, P. (1996). Justification and Reform: Research Advisory Committee of the National Council of Teachers of Mathematics. Journal for Research in Mathematics Education. 27(5)

Long, P.  & Siemens, G. (2011) Penetrating the Fog: Analytics in Learning and Education. EDUCAUSE Review. 46, Retrieved from:

Jacobs, J., Gregory, J., Hoppey, D., & Yendol-Hoppey, D. (2009). Data Literacy: Understanding Teachers' Data Use in a Context of Accountability and Response to Intervention. Action in Teacher Education. 31(3), 41-55