The project brought about a first-time, holistic and comprehensive consideration of the topic of learning analytics at Austrian universities and makes an important contribution to the development of functioning learning analytics methods in the university context. The development of appropriate tools in an interdisciplinary team ensures the innovation potential.
The uniqueness of the project results primarily from the fact that the students themselves are at the center and benefit directly from the results.

Aims of the Project

The project goal was to structure and process the data generated by the students in ways that help them optimise their learning behaviour. By providing a way to directly feedback the data generated, students are enabled to better manage their studies. As a consequence, their ability to study can be increased (in the sense of achieving personal goals), and the university can be perceived more strongly as a supportive place of learning.
The focus was directed towards offering evidence-based learning support and intervention, so that the learning content and pathways could be adapted to meet the needs of the students. For this purpose, the project developed an online dashboard, applied tutoring and mentoring measures, and developed freely available didactic models and guidelines that the tutors could then use to support students.

Measures

As addressed under the objectives, the project provides for integrated measures:

• LA measures at the course level: developing LA tools (student and teacher dashboards) based on open source technologies for the learning management systems used at the participating universities and making these tools available to other universities.
• LA measures during and after students begin their studies: Targeted measures are taken in this critical study phase to reduce dropouts and to introduce first-year students as well as possible to the challenges they will face when studying at the university level.
• Ethical and legal measures related to LA measures: A particular challenge associated with the data use is related to data protection and ethical issues. In this project, a catalog of criteria was developed to ensure compliance with ethical and legal principles. In addition, recommendations for the use of the criteria catalog were developed.
• Since the students can interpret the results and visualise the data in online dashboards without psychological support, it is especially important to design the feedback elements in ways that support the students' learning process and encourage behavior conducive to learning (e.g. efficacy, experience of autonomy and competence). In addition to directing students' attention towards international reference models, these models were validated at the universities in focus groups.
• The process of jointly interpreting the processed data was incorporated into tutoring and mentoring programs and student consultations.
• A review of the impact of the measures taken was carried out and adapted accordingly so that the information could be applied at other Austrian universities.

Project Results:

At the participating universities, the project should lead to the establishment of pilot learning analytics activities and support their further development.
At the Austrian level, the developed measures were refined, and Moodle-based "Learners' Corner" tools based on open source technologies were made available.
Analytics of study success at the degree programme level were conducted to understand the level of success and enable statistical forecasting.
Learning analytics was applied at the degree programme level through the peer advising process. The concept connects the use of data visualisations of progress in the degree programme on a dashboard with peer advising.
An interdisciplinary criteria catalog was developed to clarify the ethical and data protection framework conditions. This will be available as OER from the end of 2023 and on.

Learning Analytics for Higher Education Teaching

https://imoox.at/course/lahe

This course explores the topic of learning by taking a particular perspective on higher education teaching. Not only is the topic fundamentally introduced, but current examples from the Austria-wide project "Learning Analytics - Students in Focus" are also shown, the media education recommendations are presented, and the use of a necessary peer advising process is described. Detailed results from work carried out in the field of data protection and ethics are also shown, and ideas for sustainably anchoring learning analytics measures are given.

The course has been primarily developed for stakeholders at higher education institutions, but also for teachers or those interested in this topic.

Teaching with Learning Analytics

https://imoox.at/course/LALehren

This course is a cross-faculty qualification programme for teachers that has been developed as part of the project "Learning Analytics - Students in Focus".
The MOOC addresses how learning analytics can be used in higher education teaching and provides support for student-centered teaching development. The possibilities and limits of the technology in the context of university didactics and the use of methods and tools in learning analytics are considered from several perspectives. This includes how to analyse learning activities, identify learning needs and problems, as well as how to visualise learning activities. Participants will learn how to collect and process data from various sources and how to integrate learning analytics into their teaching methods and strategies so they can improve the quality of their teaching. This should allow them to interpret the data comprehensively and draw educationally relevant conclusions. Data privacy and ethical considerations are central to the use of learning analytics in higher education teaching, and these aspects are also addressed in this course.
On the one hand, this MOOC has been designed for university lecturers who would like to understand their students' learning processes more thoroughly by using learning analytics and to improve their teaching based on these. On the other hand, it has been designed for educational specialists in higher education and continuing education instructors who help teachers learn how to use learning analytics in teaching.

The Learners' Corner, a dashboard for the Moodle learning management system, supports the use of learner data to promote self-regulated learning. It offers three key tools - the Planner, the Activity Tool, and the Learning Diary - all of which are designed to give students a deeper understanding of their behaviour and help them gain more control over their learning behaviour.

The Planner is the heart of the dashboard and has proven particularly popular with students. It provides a complete overview of course and personal milestones, enabling the students to easily and clearly monitor their progress. In response to concerns about a potential flood of reminder emails, we have adjusted the settings to allow students to customise the reminders. Currently, we are exploring the possibility of offering an integrated view of all milestones from different courses.

The Activity tool allows students to track their activities and the time they spend on them on institutional learning platforms. Although students appreciated this overview, they also raised concerns about the accuracy of the time estimates. Therefore, we added an option to allow students to compare their data to those of their classmates or not.

The Learning Diary is a tool that allows students to reflect on their learning experiences and make plans for future learning activities. It is used for both organisation and reflection purposes. Based on students' suggestions, we have added several features, such as the ability to link diary entries to Planner milestones and greater flexibility to respond to questions.

Thanks to valuable feedback from students and other stakeholders, we have been able to continuously improve the dashboard. This underscores the importance of ensuring transparency and taking a user-centered approach towards development. We are confident that these experiences will help us to further optimise the Learners Corner and make it even more responsive to student needs.

Github

• github.com/llttugraz/moodle-local_lytix
• github.com/llttugraz/moodle-lytix_activity
• github.com/llttugraz/moodle-lytix_config
• github.com/llttugraz/moodle-lytix_diary
• github.com/llttugraz/moodle-lytix_grademonitor
• github.com/llttugraz/moodle-lytix_helper
• github.com/llttugraz/moodle-lytix_logs
• github.com/llttugraz/moodle-lytix_planner
• github.com/llttugraz/moodle-lytix_timeoverview

The Learning Analytics Cluster combined two projects funded by the Federal Ministry of Education, Science and Research 2020:

    "Learning Analytics – Studierende im Fokus"
        Lead: TU Graz
        Project partners: University of Vienna and University of Graz

    "PASSt – Predictive Analytics Services für Studienerfolgsmanagement"
        Lead: TU Wien
        Project partners: University of Linz, Vienna University of Economics and Business

The aim of both projects was to be able to make statements about the progress in degree programmes at higher education institutions by appropriately aggregating and analysing data. This would allow the further optimisation of learning behavior, on the one hand, and operations at higher education institutions, on the other. What both projects have in common is that they access a similar database and then analyse it in different contexts.
Both projects see the synergies primarily in the fact that it is imperative to ensure that these data are carefully processed in ethical ways that comply with data protection regulations. In the medium to long term, the aim is also to standardise the data and make the evaluation procedures transparent so that the results can be traced.
The Learning Analytics Cluster served as an exchange platform between the projects but also between other Austrian universities, enabling the project findings and results to be transferred within the Austrian higher education landscape accordingly.