Danny Liu

The changing landscape of higher education is putting increasing strain on educators, leading to a diminishing ability to provide pedagogical and pastoral support to ballooning and diversifying cohorts. Learning analytics promises solutions to these challenges for educators, including by personalising learning support and experiences, streamlining data capture and analyses, and providing teachers with new, efficient teaching approaches. However, reports of these impacts, or widespread adoption of learning analytics, or even examples of cross-institutional collaboration are sparse. We argue that this may be because of a lack of educator-driven learning analytics tools that meet their felt needs, and present case studies from three Australian universities that have collaborated to implement such a tool. This tool, the Student Relationship Engagement System (SRES), empowers educators to collect, collate, analyse, and use student engagement and success data that they consider meaningful for their particular contexts. Developed by unfunded educators and widely adopted through collegiate recommendations, the SRES enables personalisation and targeting of student learning and support using relevant data, fostering positive student-teacher relationships and enhancing student engagement. Using the three case studies as a backdrop, we present a revised learning analytics adoption framework focussing on strategy, structure, support, and impact, and use this framework to systematically evaluate the implementation of the SRES at the three institutions to derive 'recipes' for adopting an educator-focussed learning analytics platform. We also discuss three core themes emerging from the case studies, around the needs of academics, the role of academic and educational developers, and flexible and agile information technology practices.

Moodle is used as a learning management system around the world. However, integrated learning analytics solutions for Moodle that provide actionable information and allow teachers to efficiently use it to connect with their students are lacking. The enhanced Moodle Engagement Analytics Plugin (MEAP), presented at ASCILITE2015, enabled teachers to identify and contact students at-risk of not completing their units. Here, we discuss a pilot using MEAP in 36 units at Macquarie University, a metropolitan Australian university. We use existing models for developing organisational capacity in learning analytics and to embed learning analytics into the practice of teaching and learning to discuss a range of issues arising from the pilot. We outline the interaction and interdependency of five stages during the pilot: technology infrastructure, analytics tools and applications; policies, processes, practices and workflows; values and skills; culture and behaviour; and leadership. We conclude that one of the most significant stages is to develop a culture and behaviour around learning analytics.

Descriptions of cross-institutional, educational technology development initiatives that emphasise what actually works in real-world classrooms are rare. In this paper, we describe a multi-institution collaboration that grew from grassroots classroom needs and proved resilient in the face of institutional change. We explain how the initiative came about, how it survived unanticipated change, and how it led to the development of a new open source learning analytics tool for student engagement. We provide some reflections on the first pilot study of the tool and describe future plans. The authors welcome new collaborators and invite interested readers to evaluate and extend the tool for themselves.

How can we best align learning analytics practices with disciplinary knowledge practices in order to support student learning? Although learning analytics itself is an interdisciplinary field, it tends to take a 'one-size-fits-all' approach to the collection, measurement, and reporting of data, overlooking disciplinary knowledge practices. In line with a recent trend in higher education research, this paper considers the contribution of a realist sociology of education to the field of learning analytics, drawing on findings from recent student focus groups at an Australian university. It examines what learners say about their data needs with reference to organizing principles underlying knowledge practices within their disciplines. The key contribution of this paper is a framework that could be used as the basis for aligning the provision and/or use of data in relation to curriculum, pedagogy, and assessment with disciplinary knowledge practices. The framework extends recent research in Legitimation Code Theory, which understands disciplinary differences in terms of the principles that underpin knowledge-building. The preliminary analysis presented here both provides a tool for ensuring a fit between learning analytics practices and disciplinary practices and standards for achievement, and signals disciplinarity as an important consideration in learning analytics practices.

The use of analytics to support learning has been increasing over the last few years. However, there is still a significant disconnect between what algorithms and technology offer and what everyday instructors need to integrate actionable items from these tools into their learning environments. In this paper we present the evolution of the Student Relationship Engagement System, a platform to support instructors to select, collect, and analyze student data. The approach provides instructors the ultimate control over the decision process to deploy various actions. The approach has two objectives: to increase instructor data literacies and competencies, and to provide a low adoption barrier to promote a data-driven pedagogical improvement culture in educational institutions. The system is currently being used in 58 courses and 14 disciplines, and reaches over 20,000 students.

Moodle, an open source Learning Management System (LMS), collects a large amount of data on student interactions within it, including content, assessments, and communication. Some of these data can be used as proxy indicators of student engagement, as well as predictors for performance. However, these data are difficult to interrogate and even more difficult to action from within Moodle. We therefore describe a design-based research narrative to develop an enhanced version of an open source Moodle Engagement Analytics Plugin (MEAP). Working with the needs of unit convenors and student support staff, we sought to improve the available information, the way it is represented, and create affordances for action based on this. The enhanced MEAP (MEAP+) allows analyses of gradebook data, assessment submissions, login metrics, and forum interactions, as well as direct action through personalised emails to students based on these analyses.

Given the focus on boosting retention rates and the potential benefits of pro-active and early identification of students who may require support, higher education institutions are looking at the data already captured in university systems to determine if they can be used to identify such students. This paper uses historical student data to validate an existing learning analytics tool, the Moodle Engagement Analytics Plugin (MEAP). We present data on the utility of the MEAP to identify students ‘at risk’ based on proxy measurements of online activity for three courses/units in three different disciplines. Our results suggest that there are real differences in the predictive power of the MEAP between different courses due to differences in the extent and structure of the learning activities captured in the learning management system.

The challenges facing educators of introductory science subjects include instilling in students a sense of discovery and inquiry instead of just transmitting content knowledge, and integrating assessments that are authentic and worthwhile. In addition, implementation of technology into the curriculum must both engage students and support effective teaching in the context of ever-increasing class sizes. The abstract, and sometimes counterintuitive, nature of biology, for example at a cellular scale, necessitates innovative pedagogical strategies that integrate varied avenues for inquiry-based experimentation and research-led teaching. In this paper, we present a revised curriculum for introductory biology that provides a scaffolded environment where students are encouraged to explore and develop their scientific reasoning skills in authentic theory and practical sessions. We describe and evaluate the design of this scaffolded curriculum, with reference to the integration of theory and practice, a productive failure-based structure of engaging with experimental design, and authentic research-contextualised assessment grounded in critical analyses and application of the primary literature. We also describe the use of technology-enhanced teaching strategies that promote collaborative and active learning, timely feedback for formative and summative assessments, and the integration of online and multimedia resources that support student-centred pedagogy. Our integrative curriculum emphasises developing independence and critical thinking so that students are better equipped for future study in an ever-changing world.

Student response systems are an efficient, inclusive and engaging strategy to increase student participation in large-enrolment classes. Combined with effectively designed questions, they can stimulate and probe deeper conceptual understanding and enhance pedagogical outcomes. Hardware ‘clickers’ have been used and reported extensively but are limited in the variety of possible responses that can be gathered; new web-based student response systems that leverage the increasingly ubiquitous mobile devices that students bring to lectures offer a flexible and stimulating way for students to be emotionally and intellectually invested in knowledge building and conceptual understanding. We describe our experiences with hardware and web-based student response systems, highlighting both well-reported and novel applications of these systems to transform lectures from passive information delivery environments to active learning spaces for both students as well as lecturers.