TLCANZ18: Use of Learning and Academic Analytics to Support Improvements in Blended Learning Methodologies in Nursing Education

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Use of Learning and Academic Analytics to Support Improvements in Blended Learning Methodologies in Nursing Education

ANN BOLTON, KOBI SCHUTZ, MEAGAN GASKETT, ZACHARY WATT & NIJEL RATONEL | CHARLES DARWIN UNIVERSITY

 

Insights from learners’ participation in learning activities and interactions with their peers and the educator in a brick-and-mortar facility provide underlying information about the learning process. However, these observable patterns in a classroom setting become harder to see in an online learning environment.

 

Despite the challenges in combining conventional face-to-face teaching and online lesson delivery, blended learning methodologies offer the affordances of flexible learning for students with diverse background and learning needs. By flexibility, it means access to essential learning materials at learners’ convenient schedule and interaction with their instructor and peers for immediate feedback even in locations such as their workplaces, cafés or at the comfort of their homes. In view of flexible learning through blended learning approaches, the VET Nursing lecturers and VET Online Project team at Charles Darwin University (CDU) endeavoured to offer and deliver the VET Nursing diploma to remote, domestic, Indigenous and international students via a unique combination of theoretical components and assessments hosted via Blackboard Learn, face-to-face clinical teaching blocks (CTB) and a work-based project.

 

This presentation will explore the range of learning and academic analytics functions available to report on actionable insights about learners’ online behaviours and interactions with their peers, the instructor, the learning content and the LMS as a learning environment. Ultimately, these activities related to analytics aim to direct next steps in improving student performance in assessments, formulating effective teacher-student communication and intervention strategies, and identifying opportunities to enhance the design and structure of the VET Nursing units. These reports include but are not limited to the Blackboard Unit Analytics and Reports (Learn), VET Site at a Glance (Pyramid Analytics), and Unit Overview Video Reports (ShareStream). In addition to the available quantitative analysis and visualisation of data, this presentation aims to triangulate system-generated reports with students’ feedback gathered from VET MyView (eXplorance Survey) and course reviewers’ feedback on the Blackboard Exemplary Course Program (ECP) award-winning CDU VET Nursing unit, HLTENN001 - Practise nursing within the Australian health care system, for the validation of data. As a data gathering technique, triangulation provides the VET Nursing lecturers and the VET Online Project team with in-depth and contextual analysis of statistical data from a set of descriptive data (Harvey, 1998; Fretchling, 2010).  

 

The practical examples of learning and academic analytics, their impacts on teaching and learning, and recommendations in this action research will consult readings such as but not limited to Cook and Ellaway's (2015) comprehensive framework for evaluating technology-enhanced learning (TEL), a case study on virtual learning environment with learning analytics capabilities (Agudo-Peregrina et. al, 2014), a case study on data visualisation (Olmos and Corrin, 2012), and comparative study on learning analytics (West et al., 2018).

 

At the end of this session, participants will be able to:

  • Identify learning and academic analytics functions available on Blackboard Learn and other partner solution(s) and services.
  • List best practices in data gathering techniques.
  • Analyse data from learning and academic analytics reports.
  • Formulate pedagogical, technical and learning design strategies for the next iteration of the VET Nursing units.

Outcomes